Molecular insights in cervical carcinogenesis with emphasis on hTERT

Jillian de Wilde The work described in this thesis was performed at the Departement of Pathology (head prof.dr. C.J.L.M. Meijer), section Molecular Pathology (head prof.dr. P.J.F. Snijders), VU University Medical Center, Amsterdam, The Netherlands.

Printed by Ipskamp Drukkers, Enschede, The Netherlands

ISBN 9789086594290

© Copyright 2010, J. de Wilde

All rights reserved. No parts of this publication may be reproduced, stored in a retrieval system or transmitted in any form or means without the prior permission in writing of the author. VRIJE UNIVERSITEIT

Molecular insights in cervical carcinogenesis with emphasis on hTERT

ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad Doctor aan de Vrije Universiteit Amsterdam, op gezag van de rector magnificus prof.dr. L.M. Bouter, in het openbaar te verdedigen ten overstaan van de promotiecommissie van de faculteit der Geneeskunde op donderdag 25 februari 2010 om 11.45 uur in de aula van de universiteit, De Boelelaan 1105

door

Jillian de Wilde

geboren te Heemstede

promotoren: prof.dr. P.J.F. Snijders prof.dr. C.J.L.M. Meijer copromotor: dr. R.D.M. Steenbergen

Table of Contents

Table of Contents

Chapter 1 page 9-38 General introduction Adapted from: HPV-mediated transformation of the anogenital tract J Clin Virol (2005); suppl 1: S25-S33

Chapter 2 page 39-64 hTERT promoter activity and CpG methylation in HPV-induced carcinogenesis Submitted for publication

Chapter 3 page 65-80 Alterations in AP-1 and AP-1 regulatory during HPV-induced carcinogenesis Cellular oncology (2008); 30(1): 77-87

Chapter 4 page 81-110 expression profiling to identify markers associated with deregulated hTERT in HPV-transformed keratinocytes and cervical Int J. Cancer (2008); 122(4): 877-888

Chapter 5 page 111-140 Integrated genomic and transcriptional profiling identifies chromosomal loci with altered in cervical cancer Genes, , Cancer (2008); 47(10): 890-905

Chapter 6 page 141-152 Summary & Discussion

Chapter 7 page 153-160 Nederlandse samenvatting

Chapter 8 page 161-168 Figures in color

Chapter 9 page 169-171 Curriculum Vitae & Publications

Chapter 10 page 173-176 Dankwoord

Chapter 1

General introduction

Adapted from: HPV-mediated transformation of the anogenital tract J Clin Virol 2005;suppl 1:S25-S33

General Introduction

1 Human papillomavirus (HPV) in anogenital Different areas of the lower anogenital tract share common risk factors for cancer development, such as sexual behavior, exposure to human papillomavirus (HPV) and smoking. For cervical cancer infection with high-risk (hr)HPV has been recognized as a necessary cause. The causal relationship between hrHPV infection and cervical cancer has become evident from epidemiological and functional studies 1,2, and hrHPV has been detected in up to 99.7% of cervical squamous cell carcinomas (SCCs) 3,4 and 94% to 100% of cervical adeno- and adenosquamous carcinomas 5,6. A causative role of hrHPV is also suggested for the majority of anal cancers as well as for a subset of vulvar, vaginal and penile cancers. Besides anogenital cancers, a subset of head and neck cancers has also been associated with hrHPV infection (reviewed in 7). In anal cancer the hrHPV detection rates range from 70% to 100%, dependent on gender, localization, sexual orientation and HIV positivity 8-10. Although the overall hrHPV frequency is markedly lower in vulvar carcinomas, specific histological subtypes of vulvar carcinomas, i.e. basaloid and warty carcinomas, display relatively high hrHPV prevalence rates of 75-100%. In contrast, hrHPV is only detected in less than 23% of keratinizing carcinomas of the vulva 11-13. In vaginal carcinomas the hrHPV prevalence is about 60% 14,15, whereas 30-55% of penile carcinomas are hrHPV positive 16-18. As in vulvar carcinomas, penile carcinomas with basaloid features and those of the warty subtype display the strongest association with hrHPV 18-20. The detection of hrHPV in only a subset of vulvar, vaginal and penile cancers points to alternative pathways of carcinogenesis for these sites. A heterogeneous etiology of vulvar cancers is supported by the observation of distinct genetic alterations in tumors that are likely caused by hrHPV versus those that are not 21. Evidence for penile carcinomas being etiologically heterogeneous is supported by a study of Ferreux et al 16 showing at least three alternative carcinogenic routes based on different mechanisms of interference with the p16INK4a/cyclin D/Rb pathway, one of which could be attributed to hrHPV E7 oncoprotein activity. Although hrHPV infections at different sites of the anogenital tract are common in the general population, the cancer frequency varies largely between the different locations. Cervical cancer is the second most common cancer amongst women world wide, with a mean age standardized incidence rate varying from 11.3 per 100,000 women in more developed countries to 18.7 per 100,000

10 Chapter 1 women in less developed countries, and a peak incidence of 44.3 per 100,000 women in Middle Africa 1. The incidence of anal cancer among men having sex with men is on average 35 per 100,000, but higher in HIV infected men 22. On the contrary, vaginal, vulvar and penile cancers are very rare, with incidence rates of about one per 100,000 per year. This suggests that there exist site-dependent differences in susceptibility to viral persistence, virus-mediated transformation or a combination thereof. A possible explanation for the relatively high incidence of cervical and anal cancer could be the presence of a transformation or transition zone, in respectively the cervix and the anus. Particularly the transformation zone, where squamous epithelium transforms into glandular epithelium, is suggested to be more susceptible to HPV-mediated transformation. Next to the strong epidemiological and functional data that led to the universally accepted concept that hrHPV is etiologically involved in cervical carcinogenesis, data on hrHPV involvement in carcinomas at other sites is accumulating and starts to become more convincing. Besides multiple epidemiological studies also functional proof is being provided. For instance, a recent in vitro study showed that also hrHPV-containing oropharyngeal cancer cells depend on viral oncogene E6 and E7 activity for the maintenance of their transformed state 23.

2 HPV and cervical cancer development Cervical cancer evolves from preexisting noninvasive premalignant lesions, referred to as cervical intraepithelial neoplasias (CINs) or squamous intraepithelial lesions (SILs). These premalignant lesions are classified histologically on the basis of progressive atypia of epithelial cells: CIN1 corresponds to mild dysplasia, CIN2 to moderate dysplasia and CIN3 to both severe dysplasia and carcinoma in situ. Related to their risk of progression to invasive cancer CIN1 is also classified as low-grade CIN and CIN2 and CIN3 as high-grade CIN (CIN2/3). It is still a matter of debate whether cervical cancer generally develops from infected normal cervical epithelium via a sequence of well recognizable CIN1-CIN2-CIN3 lesions, or directly via a rapidly induced CIN2/3 lesion (reviewed in 24,25). It is of note that low-grade CIN lesions often display a viral oncoprotein expression pattern suggestive of a productive viral infection (see below), whereas high grade CIN lesions exhibit an expression pattern indicative of HPV-induced transformation, referred to as a transforming infection.

11 General Introduction

Although high-grade CIN lesions may develop rather fast, within 2 to 4 years following infection, it takes generally another 10 to 30 years for development of an invasive cervical carcinoma 26-29. This is supported by retrospective analysis of an unethical medical study conducted in New Zealand between 1965 and 1974, in which CIN3 lesions were left untreated. In women with persistent disease after 24 months 31.1% had developed an invasive carcinoma after 10 years and 50.3% after 30 years 30. This suggests that CIN2/3 represents a heterogeneous disease of which only the advanced stages are likely to have invasive potential, which is supported by studies on molecular markers 31-36. HrHPV infections are very common in young women and frequently resolve spontaneously. The life-time risk to ever contract hrHPV is estimated to be 80% 37. Despite relatively high hrHPV prevalence, the ultimate development of cervical cancer is a rare event occurring after a long period of viral persistence 38. The majority of infected women appear to clear the virus, apparently by an effective immune response. Clearance of an hrHPV infection has been linked to cytological regression 39-41. On the other hand, a persistent hrHPV infection appears a prerequisite for clinical progression and the development of CIN2/3 and cervical cancer 30,41-43

3 HPV 3.1 Classification HPVs are double stranded DNA viruses and belong to the family of Papillomaviridae 44. To date over a hundred different HPV types have been identified which have been grouped into species, and species into genera according to DNA (Figure 1) 44. HPVs are strictly epitheliotrophic and can be subdivided in mucosal and cutaneous types, which infect mucosal and cutaneous epithelium, respectively. The mucosal types are divided in low-risk (lr)HPV types that can cause wart-type and low-grade premalignant lesions and high-risk (hr)HPV types that can cause cancer and its high-grade precursor lesions. Almost all mucosal or genital HPV types are members of the α papillomavirus (A) genus and the majority of hrHPV types belong to A9 and A7 species, of which HPV16 and HPV18, respectively, are the most common representatives. The HPV genome, which is approximately 7,9 kb in size, contains a non-coding long control region (LCR) and at least 8 open reading frames (ORFs) that represent the early genes involved in the viral reproduction cycle (E1, E2, E4,

12 Chapter 1

E5, E6, and E7) and the late genes, encoding the major and minor viral capsid ( and L2, respectively) (reviewed by 45).

Figure 1: Phylogenetic tree based on the L1 ORF sequences of 118 papillomavirus types. The numbers at the ends of each of the branches identify an HPV type; c-numbers refer to candidate HPV types. All other abbreviations refer to animal papillomavirus types. The outermost semicircular symbols identify papillomavirus genera, e.g. the genus alpha- papillomavirus. The number at the inner semicircular symbol refers to papillomavirus species (taken from 44)

3.2 Viral genes E1 and E2 are involved in replication of the viral DNA. E2 hereby acts as a DNA binding and recruits E1, a DNA helicase, to the viral origin of replication 46,47. E2 is additionally ensuring proper segregation of the replicating viral genome in HPV infected cells 48 as well as functioning as a transcriptional regulator for both viral and host cell genes 49-51. E4 exerts several functions on its own or in fusion with part of E1, such as enabling the release of new viral particles, causing cell cycle arrest in G2, and antagonizing E7-mediated cell proliferation 52-56. E5 is a trans-membrane protein that resides predominantly in the endoplasmic reticulum 57. Here it is thought to indirectly influence recycling of growth factors on the cell surface, thereby affecting cell signaling that most likely facilitates malignant transformation 58. The E6 and E7 genes are needed to drive the otherwise non-dividing HPV-infected cells into S-phase in order to

13 General Introduction allow replication of the viral episomes. Both exert their function by directly or indirectly interacting with cellular proteins thereby interfering with cell and cell cycle control. The most well known binding partners of E6 and E7 are tumor suppressors p53 and pRB, respectively. The consequences of these interactions will be discussed in further detail in the next paragraphs.

4 HPV-mediated transformation The long time period between hrHPV infection and cervical cancer appearance as well as the low frequency of progression of hrHPV associated premalignant lesions to invasive cancer reflect the multi-step nature of hrHPV-induced cervical cancer. For the latter, additional genetic and epigenetic events are required. Recent in vivo and in vitro data have provided more insight into the steps that may contribute to malignant transformation following hrHPV infection. These steps include deregulated expression of the viral oncogenes E6 and E7, leading to genetic instability, and alterations in specific regulatory host cell genes by which hrHPV-transformed cells gain an immortal phenotype and subsequent invasive growth properties.

4.1 Deregulation of E6 and E7 transcription Active viral replication and virion production is typically seen in low-grade CIN lesions and benign wart-like lesions, such as condyloma acuminata. In these lesions the viral genome is maintained as monomeric episome(s) in basal cell nuclei, and vegetative DNA amplification occurs only in squamous epithelial cells undergoing terminal differentiation. Usually, low levels of viral mRNA can be detected in the infected basal cells, but viral transcription, including that of the E6 and E7 genes, is markedly increased in the differentiated layers 59,60. Other than providing the E1 and E2 proteins necessary for viral DNA replication, HPVs rely entirely on the host cell DNA replication machinery for viral DNA synthesis (reviewed by 61). By retrovirus-mediated gene transfer it has been demonstrated that HPV E7 alone is necessary and sufficient to induce cellular DNA replication in a differentiation-dependent manner in organotypic raft cultures of primary human keratinocytes 62. Reactivation of cellular DNA replication has also been shown in the differentiating spinous cells of condylo- mata and low grade CIN lesions 63. The fact that differentiated cells have already lost the ability to divide explains why expression of E6 and E7 in differentiated layers does not result in mitosis and cell division. However, when oncogenes become abnormally active in the dividing basal cells, as seen in

14 Chapter 1 high-grade lesions, interference of hrHPV E6 and E7 with cell cycle regulators can result in transformation. An increase in E6/E7 expression in proliferating basal-like cells might be due to integration of the viral DNA in the host cell genome, which is observed in most invasive cancers and a subset of high-grade lesions 64. Conversely, viral integration may also be the result of a genetically unstable environment created by deregulated E6/E7 expression in (para)basal cells, as recent data implies 65. Integration of hrHPV types has been suggested to promote carcinogenesis by a targeted deregulation of critical cellular genes by means of insertional mutagenesis. Although this is not supported by the finding that hrHPV integration sites are randomly distributed over the whole genome with a preference for fragile sites 66, a recent study by Klaus et al. demonstrated the presence of viral-cellular fusion transcripts in a subset of cervical carcinomas and high grade CIN lesions indicating that integration may influence expression of host cell genes 67. Interestingly, the frequency of integration was shown to be HPV-type dependent since hrHPV type 16, 18 and 45 integrate significantly more often than hrHPV types 31 and 33 in CIN3 lesions and carcinomas 65. Epigenetic alterations in the HPV genome, such as histone deacetylation and methylation of E2 binding sites, have been suggested to contribute to E6/E7 deregulation as well 68,69. In summary, it appears that uncontrolled E6/E7 expression in proliferating basal and parabasal epithelial cells is a phenomenon that distinguishes the process of cell transformation from productive viral infection.

4.2 E6 and E7: the viral oncogenes Both viral genes E6 and E7 are needed for induction as well as maintenance of a transformed phenotype, particularly by interference with cell cycle control and apoptosis. HrHPV E6 complexes via a cellular protein, E6-associating protein (E6-AP), with the tumor suppressor gene product p53, resulting in rapid ubiquitin- dependent proteolytic degradation of p53 70. E6-mediated interference with both p53 function and that of the pro-apoptotic protein Bak 71 may prevent cells from undergoing apoptosis. Over the past years a growing list of other proteins has been identified which may contribute to the transforming activity (reviewed by 72,73). Another interesting p53-independent target of E6 is telomerase, which will be discussed in further detail in Paragraph 5.2.1.

15 General Introduction

The E7 gene product of hrHPV is the second major transforming protein. HrHPV E7 interacts with the retinoblastoma tumor suppressor gene product, pRb 74, and its family members, p107 and p130 75, thereby interfering with their control on the G1/S transition of the cell cycle. Inactivation of Rb by hrHPV E7 in proliferating cells can be identified by an upregulation of its upstream inhibitor p16INK4A. Since p16INK4A expression is regulated by an Rb-dependent negative feed-back loop, continuous inactivation of Rb by hrHPV E7 results in strongly increased p16INK4A levels as can be detected in high-grade CIN lesions and cervical carcinomas 76. Hence, increased p16INK4A expression can be considered a marker for lesions harboring a transforming hrHPV infection 77. In addition to the Rb-family members, E7 has been shown to interact with other host cell factors (reviewed by 72,73). It still remains to be determined if and how these interactions relate to E7-mediated transformation. Conclusively, the uncontrolled proliferation and interference in apoptosis exerted by E6 and E7 combined is likely to result in a state of genetic instability, enhancing the risk of malignant transformation.

4.3 HPV-mediated immortalization The transforming properties of hrHPV types, particularly HPV16 and HPV18, were established many years ago by their capacity to induce immortalization of primary human keratinocytes 78-81. Further in vitro models of HPV-mediated carcinogenesis have shown that a fully tumorigenic phenotype can be obtained via sequential induction of transformed phenotypes like immortalization and anchorage independent growth 82,83. Analysis of the genetic basis for this stepwise progression revealed that each phenotype was under control of a recessive regulatory process, arguing that inactivation of tumor suppressor genes is pivotal. Normal human diploid cells in culture have a finite proliferative lifespan and enter senescence after 50 to 100 population doublings 84. However, cells infected with hrHPV can bypass this senescence barrier through inactivation of p53 and Rb by E6 and E7, respectively, resulting in an extended lifespan. The expression of E6 and E7 in proliferating cells has been shown to disturb the mechanisms of duplication and segregation during mitosis and induces severe chromosomal instability (reviewed by 85). In this way hrHPV provides an endogenous carcinogen, driving the additional genetic changes required for malignant transformation. Eventually, E6/E7 expressing cells enter a period of crisis, at which most cells die and from which at low frequency

16 Chapter 1 immortal subclones may arise. The bypass of this second barrier has been associated with activation of the telomere lengthening enzyme telomerase and concomitant arrest of telomere shortening 86,87. Telomere erosion is considered to provide an intrinsic division count system that determines the lifespan of normal somatic cells. The acquisition of an immortal phenotype is suggested to represent the first phenotypical alteration requiring recessive alterations in the host cell genome. Immortalization of hrHPV transfected primary keratinocytes has been associated with specific genetic alterations, such as clonal losses at chromosomes 3p, 6q, 10p, 11p, 11q, 13q and 18q, non-random gains at chromosomes 3q, 5q, 7q, 8q, 9q, 14q, 16, 20 and 22q and structural alterations at chromosomes 10, 18 and 20 (summarized in 35,88-90). These data suggest that particularly the inactivation of putative tumor suppressor genes at chromosomes 3p, 6q, 10p, 11, 13q and/or 18q may play an important role in the acquisition of an immortal phenotype. Moreover, HPV-mediated immortalization appeared to be associated with a strong reactivation of telomerase 86,91.

5. Telomerase 5.1 General characteristics Telomerase is a ribonucleoprotein complex that can add six repeats to telomere ends, thereby compensating for telomere shortening during cell division and allowing cells to bypass the mortality stage barriers. Telomerase activity has been detected in human germ cells, immortal cell lines and most human tumors, but not in a variety of normal somatic tissues, indicating that the reactivation of telomerase is an important step in carcinogenesis 92. The telomerase complex consists of two major subunits: a structural RNA component (hTR) and a catalytic subunit (hTERT) that has reverse transcriptase activity. While hTR is expressed in telomerase negative cells, hTERT is not 93. hTERT mRNA expression has been recognized as the rate limiting step of telomerase activity and altered regulation of hTERT mRNA expression is therefore crucial to the activation of telomerase in cancer cells.

5.2 Regulation of hTERT expression 5.2.1 Transcription factors: The hTERT gene has a CG rich, TATA-less promoter, within which a proximal region of 200 base pairs has been identified as the core promoter, being indispensable for transcription activation 94,95. However, sequences upstream

17 General Introduction and downstream this core promoter are involved in hTERT regulation as well 94,96-99 (Figure 2). Known direct activators of hTERT are SP1 97,99, c-MYC 100, AP2 and AP4 95,97, IK2 97, c-ETS 94, MYOD 97, NF1 97, c-MYB 97, HSP90 101 that binds at SP1 sites and HIF1A 102 that binds the c-Myc binding site. Overexpression of transcription factor BMI1 upregulates hTERT transcription, resulting in immortalization of human mammary epithelial cells 103. It is however yet unknown whether BMI1 binds and transactivates hTERT directly. Indirect activation of hTERT was recently reported for CSF1, which was found to induce both hTERT protein translocation to the nucleus and hTERT transactivation by c-Myc 104. Known repressors that bind hTERT directly are WT1 105, MEN1 106, CTCF 107, SMAD3 108, USF1 and 2 109, COUPTFII 110, p27KIP1 111 and MAD1 100,112, of which the latter four, like HIF1A, compete with c-Myc for its binding site. The transcription factor complex AP-1 can suppress hTERT transcription by binding to two proximal promoter regions, i.e. at -1655 and -718 113. TGF beta indirectly represses hTERT via induction of CIP1 106 and SMAD3 108. Recently, next to SMAD3, E2F binding on the hTERT promoter was shown to be involved in TGFbeta mediated hTERT repression 114. Ectopic expression of hrHPV E6 can induce hTERT expression and telomerase activity 91. Transcription of hTERT can be induced by E6 both directly and indirectly. E6 is able to bind and transactivate the hTERT promoter in complex with c-Myc 115,116. Additionally, E6 associates with E6AP ubiquitin ligase and degrades hTERT repressor NFX1-91, which normally interacts with co- repressor complex mSin3A/histone deacetylase (HDAC) at the hTERT promoter 117,118. By degrading NFX1-91, E6/E6AP changes the chromatin structure at the hTERT promoter which results in increased hTERT expression 119. More recently, NFX123, which is like NFX1-91 a splice variant of NFX1, has been demonstrated to increase hTERT expression posttranscriptionally in HPV E6 containing keratinocytes 120. Also hrHPV E7 was reported to contribute to telomerase activity. Although E7 alone was insufficient to increase endogenous hTERT mRNA, it significantly augmented E6-induced hTERT transcription. Mutation of the E2F site in the hTERT promoter abrogated this ability of E7 121. Microcell-mediated chromosome transfer studies have shown that in addition to E6 and E7 functions the induction of hTERT and telomerase activity in epithelial cells immortalized by full-length hrHPV and cervical cancer cells depends on a recessive event involving chromosomes 4q, 6q and/or 10p,

18 Chapter 1 suggesting that yet unknown tumor suppressor genes that either directly or indirectly regulate hTERT transcription reside on these locations 35,122-124. Interestingly, most recently a noncoding RNA gene, RGM249, located at chromosome 10p15.3 has been identified as a negative regulator of hTERT expression in hepatoma cell lines 125.

Figure 2: Schematic representation of hTERT regulatory sequences and the transcriptional regulators that can bind to it. The 200 bp core promoter is marked by a black bold line, flanking sequences by a dotted line. Transcriptional activators are shown in the upper panel and transcriptional repressors are shown in the lower panel. Arrows point to the (often multiple) binding sites of the individual transcription factors. Note that some transcriptional regulators described above are not shown since these bind outside the indicated region (-600 bp to +450 bp relative to the ATG).

5.2.2 Epigenetic regulation: In order for transcriptional factors to transactivate the hTERT promoter its chromatin needs to be in a specific conformation, which can be accomplished by a combination of epigenetic mechanisms, such as histone modification (acetylation and methylation) and DNA methylation. Pharmacological inhibition of several histone modifying proteins, such as histone deacetylases (HDACs) or Lysine-specific demethylase 1 (LSD1) in normal cells results in an upregulation of hTERT expression 126,127. Furthermore knocking down SET and MYND domain-containing protein 3 (SMYD3), which is required for maintenance of histone H3-K4 trimethylation in tumor cells, abolished trimethylation of H3-K4 and led to diminished histone H3 acetylation in the hTERT promoter region, a phenomenon that coincided with down-regulation of hTERT mRNA and telomerase activity 128.

19 General Introduction

Moreover, as described in section 5.2.1 above, during cervical carcinogenesis hrHPV E6 induces hTERT transcription by indirect inhibition of the co- repressor complex mSin3A/HDAC 119. The most studied mechanism of epigenetic regulation of hTERT is DNA methylation. The 5’ region of the hTERT gene consists of a large ~4kb CpG island (-1800 to +2200, numbered relative to the ATG), suggestive of regulation by DNA methylation 97. In contrast to the general idea that promoter hypermethylation causes chromatin alterations, resulting in silencing of genes, hypermethylation of the hTERT promoter has been correlated with increased expression in some studies 107,129,130. Additionally, it has been demonstrated that the proximal exonic region (exon 1 and 2) can be involved in suppression of hTERT transcription due to binding of transcriptional repressor CTCF, an 11-zinc finger DNA-binding factor. CTCF is methylation sensitive and can only inhibit transcription by binding to unmethylated DNA 107. Recent studies found that methylation of the hTERT promoter in hTERT expressing cells is a dynamic process and that some CpGs flanking the transcription start site remain unmethylated 131,132. This so-called unmethylated core is suggested to ensure an open state of the hTERT chromatin allowing transcription in at least a subset of cells. The tight regulation of hTERT in cancer cells and the presence of suppressive elements are in line with the fact that although hTERT is expressed in cancer cells, its expression is relatively low, i.e. 0.2 to 6 mRNA copies per cell 133,134. Further support for the hTERT regulation being subjected to negative regulators even in cancer cells comes from the recent finding that the hTERT promoter is bound by the methyl binding domain protein MBD2, which mediates silencing of hypermethylated genes in cancer cells, including HeLa cells, and that depletion of MBD2 leads to an upregulation of TERT 135.

5.2.3 DNA copy numbers Increased hTERT expression as seen in tumors may also be related to the fact that copy number gains at 5p15, the hTERT , are frequently detected in various human cancers 136. In cervical carcinomas increased hTERT copy numbers as determined by FISH analysis have been detected in 24% (21/88) of cases 137.

20 Chapter 1

5.3 Telomerase activity as a progression marker In cervical cancer telomerase activity and elevated hTERT expression has been shown in 96% of squamous cell carcinomas and in 40% of CIN3 lesions, while normal cervix, CIN1 and CIN2 lesions had no detectable telomerase activity 32. These findings indicate that elevated levels of hTERT mRNA are related to the progression of a high-grade CIN lesion to invasive cancer. It can be speculated that telomerase positive CIN lesions have gained an immortal phenotype and have reached a point of no return in terms of malignant potential. However, the detection of telomerase activity and hTERT expression in cervical scrape specimens did not reflect the status of these markers in the underlying lesions and as such these markers are not sensitive or specific enough to predict cervical cancer 138-140. Hence, there is a need for novel, more reliable markers for deregulated hTERT activity.

6 Chromosomal alterations As discussed in section 4 specific chromosomal alterations have been related to HPV-mediated transformation in vitro, including losses as 3p, 6q, 10p and 11q, and gains at 3q. The existence of one or more tumor suppressor genes at chromosome 3p that may be involved in cervical carcinogenesis is supported by the frequent detection of (allelic) loss in high-grade CIN lesions and cervical carcinomas. Using both loss of heterozygosity (LOH) analysis and array CGH analysis deletion at chromosome 3p has been found in approximately 30-35% of CIN3 lesions without synchronous cervical carcinomas and in up to 83% of CIN3 lesions adjacent to cervical carcinomas and cervical carcinomas 141-147. No direct association has been detected between allelic imbalance at 3p and telomerase activation in CIN3 lesions and cervical carcinomas 35.

6.1 Gain at 3q A gain at 3q appeared one of the most consistent chromosomal aberrations detected in invasive cervical carcinomas and has been associated with the transition of a CIN3 lesion to invasive cancer 36,90,145,148. This region is of particular interest as it harbors the hTR coding region, of which increased copy numbers appear frequently in cervical carcinomas 149. The detection of increased hTR copy numbers in cervical scrapings has been linked to underlying high grade CIN lesions 150. A second well known candidate

21 General Introduction oncogene at this region is PI3KCA, a member of the PI3K signaling pathway, copy numbers of which are recurrently gained in cervical carcinomas 151.

6.2 Loss at 6q In addition, alterations at chromosome 6 have frequently been detected in both high-grade lesions and cervical carcinomas. LOH at 6p21.3 is found in 75-85% of cervical carcinomas and in 57-75% of CIN lesions 152-154. The 6p21.3 locus harbors the HLA class I antigen genes, and attenuation of HLA class I gene expression allows the hrHPV-infected cells to evade the immune system 155. Both by functional studies, showing a suppression of telomerase by chromosome 6, and by associative studies, showing a significant correlation between allelic imbalance at 6q14-22 and telomerase activation in CIN3 lesions and cervical carcinomas, evidence has been collected for the presence of a telomerase repressor on chromosome 6q 35,124. These data suggest that loss of genes at chromosome 6 is involved in at least two steps during cervical carcinogenesis, one of which is linked to immune evasion and another to telomerase activation.

6.3 Loss at 10p The frequent detection of chromosomal alterations at 10p in HPV-immortalized cell lines 86,89 and the telomerase suppressive effect of 10p14-15 in HPV- immortalized cell lines 123 suggest a functional involvement of gene inactivation at 10p in HPV-mediated immortalization as well. A potential candidate gene is the transcription factor GATA-3, which showed a markedly reduced expression in HPV-immortalized keratinocytes, cervical cancer cell lines, a small subset of CIN3 lesions and the majority of cervical carcinomas 33.

6.4 Loss at 11q Loss of tumor suppressor gene(s) at chromosome 11 has been implicated in the progression from an immortal to a tumorigenic phenotype 156. Allelotyping studies on cervical carcinomas identified common LOH at two loci, i.e. 11q13 157 and 11q22-23 158. One candidate tumor suppressor gene on chromosome 11q13 encodes a member of the Fos gene family, Fos Related Antigen 1 (Fra-1). In addition to Fra-1, the Fos gene family consists of c-Fos, FosB, and Fra-2, which can form heterodimers with members of the Jun family (c-Jun, JunB or JunD), resulting in a so-called AP-1 transcription factor 159. Depending on its composition this

22 Chapter 1 complex is involved in the positive and/or negative regulation of several different genes 159 including hrHPV genes in hrHPV transfected cells 160-164, and hTERT 113. Alterations in AP-1 complex composition have been associated with the tumorigenic phenotype of the cervical carcinoma cell line HeLa that displays high c-Fos expression, while Fra-1 expression is almost undetectable 165. An up regulation of c-Fos and down regulation of Fra-1 was also shown in other tumorigenic cervical cancer cell lines, such as SiHa and SW756, as well as in cervical carcinomas 166,167. The other locus with frequent allelic loss, 11q23, harbors the tumor suppressor gene CADM1 (formally known as TSLC1; tumor suppressor in lung cancer 1), which was found to be silenced by LOH and/or promoter methylation in the majority of cervical cancer cell lines and also shown to be functionally involved in HPV-mediated transformation 34.

6.5 Other alterations Next to the alterations described above, losses of 2q, 4q, and 13q and gains of 1q, and 20q are common to cervical carcinomas 90,145-147,168-173. A recent array CGH study on premalignant cervical lesions has demonstrated that two subsets of high grade CIN lesions can be distinguished, one having little chromosomal alterations and a second set sharing chromosomal alterations, such as a gain on 1, 3q and 20q, with SCC. The suggestion that the latter lesions are more advanced, is supported by the fact that promoter methylation of the tumor suppressor gene CADM1, which was previously associated with the acquisition of an invasive phenotype, is significantly more frequent in this subset of high-grade CIN lesions 36.

7 DNA methylation of tumor suppressor genes in cervical cancer A number of studies have described aberrant methylation of tumor suppressor genes in cervical cancer biopsies and precursor lesions. Tumor suppressor genes showing frequent promoter hypermethylation in cervical carcinomas include CDH1, DAPK, FHIT, HIC-1, p16, RAR-beta, RASSF1A, TIMP-2, CADM1 and MAL 174,175. Although promoter methylation of these genes is common in cervical cancers the biological relevance of most of them awaits further study. So far, methylation-mediated silencing of the tumor suppressor genes CADM1 and MAL was found to be functionally involved in HPV-mediated transformation 31,34,174.

23 General Introduction

The list of methylated gene promoters in cervical cancer is growing rapidly and a number of recent studies have found promoter methylation of (candidate) tumor suppressor genes in cervical scrapings to be predictive for underlying cervical disease (reviewed by 175). Although the ideal marker panel for detecting all clinically relevant cervical lesions has not been established yet, present data suggest that methylation markers are promising triage tools for distinction of women with clinically meaningful cervical disease amongst those that are hrHPV positive.

8 Concept of multistep process of HPV-mediated carcinogenesis and future perspectives Based on the present data a model of HPV-mediated carcinogenesis can be proposed as shown in Figure 3. The different steps within the HPV-mediated carcinogenesis process can be summarized as follows: 1. Persistence of high-risk HPV: Many women acquire hrHPV infections in their adolescence by sexual transmission. Approximately 80% of these women harbor a transient hrHPV infection without epithelial abnormalities. In the remaining 20% of these women, hrHPV infection leads to CIN lesions and a persistent infection, a prerequisite for malignant transformation. It is noteworthy that clearance of the virus parallels the regression of cervical lesions. 2. Deregulation of E6 and E7 expression: An altered transcriptional regulation of the viral oncogenes E6 and E7 results in a topographical shift of E6/E7 expression from the differentiated layers to the proliferating (para)basal cell layers. When overexpressed in proliferating cells E6 and E7 interfere with the cell cycle control and apoptosis regulated by p53 and Rb, respectively, leading to the induction of genetic instability. Whether this is a result of viral integration is presently unknown. 3. (Epi)genetic alterations involving oncogenes and tumor suppressor genes: E6 and E7 induced genetic instability leads to the activation of oncogenes and inactivation of tumor suppressor genes. 3a Immortalization and telomerase activation: Some of these alterations, particularly those involving tumor suppressor genes, can give rise to an immortal phenotype associated with activation of telomerase. 3b. Malignant transformation and invasion: Progression from an immortal to an overt malignant and invasive phenotype results from additional (epi)genetic alterations.

24 Chapter 1

Figure 3: Schematic representation of the multistep process of HPV-mediated carcinogenesis (see also text). Cervical cancer results from a persistent infection with hrHPV. Deregulated expression of E6 and E7 in (para)basal cells induces genetic instability and drives the selective outgrowth of telomerase positive immortal cells that may subsequently gain additional (epi)genetic alterations providing invasive growth properties.

9 Outline of this thesis Although sensitive molecular tests are available for HPV testing, it is clear that further insight in the molecular pathology of cervical carcinogenesis will not only provide novel biomarkers to better predict the risk of invasive cervical cancer, but will also be helpful for the design of novel treatment strategies. In vitro model systems have proven excellent tools to investigate carcinogenic processes. In this thesis an in vitro model system for HPV-mediated transformation, consisting of four HPV-immortalized cell lines 86, is analyzed to gain further insight in the molecular mechanisms underlying HPV-induced carcinogenesis. Particular attention is paid to immortalization and the activation of telomerase by hTERT deregulation.

In Chapter 2 we questioned the following: How does hTERT become deregulated during HPV-induced carcinogenesis? Using luciferase reporter assays containing various hTERT promoter and proximal exonic/intronic regions we showed the existence and location of specific repressive sequences in the hTERT promoter. By subsequent bisulfite

25 General Introduction sequencing of these regions we showed that methylation of these sequences is associated with deregulated hTERT transcription in HPV-transformed cells. Upon analysis of cervical biopsies we observed a gradual increase in methylation of the hTERT regulatory regions with progression towards malignancy indicating that DNA methylation at these regions may provide an attractive biomarker for the early detection of cervical cancer.

Since the transcription factor AP-1 interacts with sequences 5’of the hTERT core promoter, found to be suppressive in chapter 2, and changes in AP-1 complex composition have previously been linked to tumorigenicity of cervical cancer cells, we questioned in Chapter 3: How does expression of AP-1 complex members and their regulatory genes change during HPV-induced transformation in vitro? Expression of AP-1 complex members and their regulatory genes was investigated in primary keratinocytes, early and late passages of non- tumorigenic HPV-immortalized keratinocytes and in tumorigenic cervical cancer cell lines. RT-PCR and Western blot analysis showed an upregulation of c-Fos, Fra-2 and JunB towards tumorigenicity whereas Fra-1 and c-Jun became down regulated, as well as the regulatory and target genes Notch1, Net and CADM1. Although the onset of deregulated expression varied between genes, with early passage immortal cells already showing some increase in c-Fos expression and a reduction in Fra-1 expression, a functional shift in AP-1 complex composition from Fra-1/c-Jun to c-Fos/c-Jun was only observed in tumorigenic cells.

To obtain a genome wide impression of genes regulated during HPV-induced immortalization we asked ourselves in Chapter 4: Which genes are differentially expressed upon telomerase activation in HPV-transfected keratinocytes and may ultimately serve as a surrogate marker for telomerase activation and hTERT deregulation? A model of chromosome 6-mediated telomerase repression was used to analyze expression profiles associated with hTERT deregulation in HPV-transformed cells eventually resulting in the identification of 32 differentially expressed genes in hTERT positive cells. These surrogate markers for deregulated hTERT mRNA expression, two of which (AQ3 and MGP) were confirmed in cervical tissue specimens, may enable the identification of those cervical premalignant lesions that are at highest risk to progress to invasive cancer.

26 Chapter 1

Finally, we extended our genome wide expression analysis studies to cervical carcinomas in Chapter 5. To preclude the identification of responsive changes in interspersed stromal and invading immune cells we focused on genes with altered expression related to chromosomal alterations by integration of genome- wide chromosomal and transcriptional profiles of squamous cell carcinomas and adenocarcinomas . Chromosomal gains of the long arms of chromosome 1, 3, and 20 resulted in increased expression of genes located at 1q32.1-32.2, 3q13.32-23, 3q26.32-27.3, and 20q11.21-13.33, whereas a chromosomal loss of 11q22.3-25 was related to decreased expression of genes located in this region. Differential expression of a subset of these genes was confirmed in an independent validation sample set. These genes may therefore represent valuable prognostic markers.

In Chapter 6 an overview is given of all studies included in this thesis, the combination of which has provided more insight in the mechanisms underlying hTERT and AP-1 deregulation as well as several potential biomarkers that will enable a better risk stratification of hrHPV-positive women.

References

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39. Nobbenhuis, M. A., Helmerhorst, T. J., van den Brule, A. J., Rozendaal, L., Voorhorst, F. J., Bezemer, P. D., Verheijen, R. H., and Meijer, C. J. Cytological regression and clearance of high-risk human papillomavirus in women with an abnormal cervical smear. Lancet, 358: 1782-1783, 2001. 40. Schiffman, M., Wheeler, C. M., and Castle, P. E. Human papillomavirus DNA remains detectable longer than related cervical cytologic abnormalities. J.Infect.Dis., 186: 1169- 1172, 2002. 41. Zielinski G.D., Snijders, P. J., Rozendaal, L., Voorhorst, F. J., Runsink, A. P., de Schipper, F. A., and Meijer, C. J. High-risk HPV testing in women with borderline and mild dyskaryosis: long-term follow-up data and clinical relevance. J.Pathol., 195: 300- 306, 2001. 42. Ho, G. Y., Bierman, R., Beardsley, L., Chang, C. J., and Burk, R. D. Natural history of cervicovaginal papillomavirus infection in young women. N.Engl.J.Med., 338: 423-428, 1998. 43. Nobbenhuis, M. A., Walboomers, J. M., Helmerhorst, T. J., Rozendaal, L., Remmink, A. J., Risse, E. K., van der Linden, H. C., Voorhorst, F. J., Kenemans, P., and Meijer, C. J. Relation of human papillomavirus status to cervical lesions and consequences for cervical-cancer screening: a prospective study. Lancet, 354: 20-25, 1999. 44. de Villiers, E. M., Fauquet, C., Broker, T. R., Bernard, H. U., and zur, H. H. Classification of papillomaviruses. Virology, 324: 17-27, 2004. 45. Doorbar, J. Molecular biology of human papillomavirus infection and cervical cancer. Clin.Sci.(Lond), 110: 525-541, 2006. 46. Frattini, M. G. and Laimins, L. A. Binding of the human papillomavirus E1 origin- recognition protein is regulated through complex formation with the E2 enhancer- binding protein. Proc.Natl.Acad.Sci.U.S.A, 91: 12398-12402, 1994. 47. Liu, J. S., Kuo, S. R., Broker, T. R., and Chow, L. T. The functions of human papillomavirus type 11 E1, E2, and E2C proteins in cell-free DNA replication. J.Biol.Chem., 270: 27283-27291, 1995. 48. Dao, L. D., Duffy, A., Van Tine, B. A., Wu, S. Y., Chiang, C. M., Broker, T. R., and Chow, L. T. Dynamic localization of the human papillomavirus type 11 origin binding protein E2 through mitosis while in association with the spindle apparatus. J.Virol., 80: 4792-4800, 2006. 49. Bouvard, V., Storey, A., Pim, D., and Banks, L. Characterization of the human papillomavirus E2 protein: evidence of trans-activation and trans-repression in cervical keratinocytes. EMBO J., 13: 5451-5459, 1994. 50. Steger, G. and Corbach, S. Dose-dependent regulation of the early promoter of human papillomavirus type 18 by the viral E2 protein. J.Virol., 71: 50-58, 1997. 51. Lee, D., Kim, H. Z., Jeong, K. W., Shim, Y. S., Horikawa, I., Barrett, J. C., and Choe, J. Human papillomavirus E2 down-regulates the human telomerase reverse transcriptase promoter. J.Biol.Chem., 277: 27748-27756, 2002. 52. Doorbar, J., Ely, S., Sterling, J., McLean, C., and Crawford, L. Specific interaction between HPV-16 E1-E4 and cytokeratins results in collapse of the epithelial cell intermediate filament network. Nature, 352: 824-827, 1991. 53. Davy, C. E., Jackson, D. J., Wang, Q., Raj, K., Masterson, P. J., Fenner, N. F., Southern, S., Cuthill, S., Millar, J. B., and Doorbar, J. Identification of a G(2) arrest domain in the E1 wedge E4 protein of human papillomavirus type 16. J.Virol., 76: 9806-9818, 2002. 54. Davy, C. E., Jackson, D. J., Raj, K., Peh, W. L., Southern, S. A., Das, P., Sorathia, R., Laskey, P., Middleton, K., Nakahara, T., Wang, Q., Masterson, P. J., Lambert, P. F., Cuthill, S., Millar, J. B., and Doorbar, J. Human papillomavirus type 16 E1 E4-induced G2 arrest is associated with cytoplasmic retention of active Cdk1/cyclin B1 complexes. J.Virol., 79: 3998-4011, 2005.

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137. Zhang, A., Zheng, C., Hou, M., Lindvall, C., Wallin, K. L., Angstrom, T., Yang, X., Hellstrom, A. C., Blennow, E., Bjorkholm, M., Zetterberg, A., Gruber, A., and Xu, D. Amplification of the telomerase reverse transcriptase (hTERT) gene in cervical carcinomas. Genes Chromosomes.Cancer, 34: 269-275, 2002. 138. Ngan, H. Y., Cheung, A. N., Liu, S. S., Liu, K. L., and Tsao, S. W. Telomerase assay and HPV 16/18 typing as adjunct to conventional cytological cervical cancer screening. Tumour.Biol., 23: 87-92, 2002. 139. Reesink-Peters, N., Helder, M. N., Wisman, G. B., Knol, A. J., Koopmans, S., Boezen, H. M., Schuuring, E., Hollema, H., de Vries, E. G., de Jong, S., and van der Zee, A. G. Detection of telomerase, its components, and human papillomavirus in cervical scrapings as a tool for triage in women with cervical dysplasia. J.Clin.Pathol., 56: 31- 35, 2003. 140. Cheung, A. N., Chiu, P. M., Tsun, K. L., Khoo, U. S., Leung, B. S., and Ngan, H. Y. Chromosome in situ hybridisation, Ki-67, and telomerase immunocytochemistry in liquid based cervical cytology. J.Clin.Pathol., 57: 721-727, 2004. 141. Wistuba, I. I., Montellano, F. D., Milchgrub, S., Virmani, A. K., Behrens, C., Chen, H., Ahmadian, M., Nowak, J. A., Muller, C., Minna, J. D., and Gazdar, A. F. Deletions of chromosome 3p are frequent and early events in the pathogenesis of uterine cervical carcinoma. Cancer Res., 57: 3154-3158, 1997. 142. Rader, J. S., Gerhard, D. S., O'Sullivan, M. J., Li, Y., Li, L., Liapis, H., and Huettner, P. C. Cervical intraepithelial neoplasia III shows frequent allelic loss in 3p and 6p. Genes Chromosomes.Cancer, 22: 57-65, 1998. 143. Guo, Z., Hu, X., Afink, G., Ponten, F., Wilander, E., and Ponten, J. Comparison of chromosome 3p deletions between cervical precancers synchronous with and without invasive cancer. Int.J.Cancer, 86: 518-523, 2000. 144. Allen, D. G., White, D. J., Hutchins, A. M., Scurry, J. P., Tabrizi, S. N., Garland, S. M., and Armes, J. E. Progressive genetic aberrations detected by comparative genomic hybridization in squamous cell cervical cancer. Br.J.Cancer, 83: 1659-1663, 2000. 145. Heselmeyer, K., Macville, M., Schrock, E., Blegen, H., Hellstrom, A. C., Shah, K., Auer, G., and Ried, T. Advanced-stage cervical carcinomas are defined by a recurrent pattern of chromosomal aberrations revealing high genetic instability and a consistent gain of chromosome arm 3q. Genes Chromosomes.Cancer, 19: 233-240, 1997. 146. Hidalgo, A., Schewe, C., Petersen, S., Salcedo, M., Gariglio, P., Schluns, K., Dietel, M., and Petersen, I. Human papilloma virus status and chromosomal imbalances in primary cervical carcinomas and tumour cell lines. Eur.J.Cancer, 36: 542-548, 2000. 147. Kirchhoff, M., Rose, H., Petersen, B. L., Maahr, J., Gerdes, T., Lundsteen, C., Bryndorf, T., Kryger-Baggesen, N., Christensen, L., Engelholm, S. A., and Philip, J. Comparative genomic hybridization reveals a recurrent pattern of chromosomal aberrations in severe dysplasia/carcinoma in situ of the cervix and in advanced-stage cervical carcinoma. Genes Chromosomes.Cancer, 24: 144-150, 1999. 148. Rao, P. H., Arias-Pulido, H., Lu, X. Y., Harris, C. P., Vargas, H., Zhang, F. F., Narayan, G., Schneider, A., Terry, M. B., and Murty, V. V. Chromosomal amplifications, 3q gain and deletions of 2q33-q37 are the frequent genetic changes in cervical carcinoma. BMC.Cancer, 4: 5, 2004. 149. Soder, A. I., Hoare, S. F., Muir, S., Going, J. J., Parkinson, E. K., and Keith, W. N. Amplification, increased dosage and in situ expression of the telomerase RNA gene in human cancer. Oncogene, 14: 1013-1021, 1997. 150. Heselmeyer-Haddad, K., Janz, V., Castle, P. E., Chaudhri, N., White, N., Wilber, K., Morrison, L. E., Auer, G., Burroughs, F. H., Sherman, M. E., and Ried, T. Detection of genomic amplification of the human telomerase gene (TERC) in cytologic specimens as a genetic test for the diagnosis of cervical dysplasia. Am.J.Pathol., 163: 1405-1416, 2003.

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151. Ma, Y. Y., Wei, S. J., Lin, Y. C., Lung, J. C., Chang, T. C., Whang-Peng, J., Liu, J. M., Yang, D. M., Yang, W. K., and Shen, C. Y. PIK3CA as an oncogene in cervical cancer. Oncogene, 19: 2739-2744, 2000. 152. Kersemaekers, A. M., van de Vijver, M. J., Kenter, G. G., and Fleuren, G. J. Genetic alterations during the progression of squamous cell carcinomas of the uterine cervix. Genes Chromosomes.Cancer, 26: 346-354, 1999. 153. Chatterjee, A., Pulido, H. A., Koul, S., Beleno, N., Perilla, A., Posso, H., Manusukhani, M., and Murty, V. V. Mapping the sites of putative tumor suppressor genes at 6p25 and 6p21.3 in cervical carcinoma: occurrence of allelic deletions in precancerous lesions. Cancer Res., 61: 2119-2123, 2001. 154. Arias-Pulido, H., Joste, N., and Wheeler, C. M. Loss of heterozygosity on chromosome 6 in HPV-16 positive cervical carcinomas carrying the DRB1*1501-DQB1*0602 haplotype. Genes Chromosomes.Cancer, 40: 277-284, 2004. 155. Koopman, L. A., Der Slik, A. R., Giphart, M. J., and Fleuren, G. J. Human leukocyte antigen class I gene mutations in cervical cancer. J.Natl.Cancer Inst., 91: 1669-1677, 1999. 156. Koi, M., Morita, H., Yamada, H., Satoh, H., Barrett, J. C., and Oshimura, M. Normal human chromosome 11 suppresses tumorigenicity of human cervical tumor cell line SiHa. Mol.Carcinog., 2: 12-21, 1989. 157. Jesudasan, R. A., Rahman, R. A., Chandrashekharappa, S., Evans, G. A., and Srivatsan, E. S. Deletion and translocation of chromosome 11q13 sequences in cervical carcinoma cell lines. Am.J.Hum.Genet., 56: 705-715, 1995. 158. Hampton, G. M., Penny, L. A., Baergen, R. N., Larson, A., Brewer, C., Liao, S., Busby- Earle, R. M., Williams, A. W., Steel, C. M., Bird, C. C., and . Loss of heterozygosity in cervical carcinoma: subchromosomal localization of a putative tumor-suppressor gene to chromosome 11q22-q24. Proc.Natl.Acad.Sci.U.S.A, 91: 6953-6957, 1994. 159. Eferl, R. and Wagner, E. F. AP-1: a double-edged sword in tumorigenesis. Nat.Rev.Cancer, 3: 859-868, 2003. 160. Kyo, S., Klumpp, D. J., Inoue, M., Kanaya, T., and Laimins, L. A. Expression of AP1 during cellular differentiation determines human papillomavirus E6/E7 expression in stratified epithelial cells. J.Gen.Virol., 78 ( Pt 2): 401-411, 1997. 161. Butz, K. and Hoppe-Seyler, F. Transcriptional control of human papillomavirus (HPV) oncogene expression: composition of the HPV type 18 upstream regulatory region. J.Virol., 67: 6476-6486, 1993. 162. Buchwalter, G., Gross, C., and Wasylyk, B. Ets ternary complex transcription factors. Gene, 324: 1-14, 2004. 163. Kyo, S., Tam, A., and Laimins, L. A. Transcriptional activity of human papillomavirus type 31b enhancer is regulated through synergistic interaction of AP1 with two novel cellular factors. Virology, 211: 184-197, 1995. 164. Rosl, F., Das, B. C., Lengert, M., Geletneky, K., and zur, H. H. Antioxidant-induced changes of the AP-1 transcription complex are paralleled by a selective suppression of human papillomavirus transcription. J.Virol., 71: 362-370, 1997. 165. Soto, U., Das, B. C., Lengert, M., Finzer, P., zur, H. H., and Rosl, F. Conversion of HPV 18 positive non-tumorigenic HeLa-fibroblast hybrids to invasive growth involves loss of TNF-alpha mediated repression of viral transcription and modification of the AP-1 transcription complex. Oncogene, 18: 3187-3198, 1999. 166. Soto, U., Denk, C., Finzer, P., Hutter, K. J., zur, H. H., and Rosl, F. Genetic complementation to non-tumorigenicity in cervical-carcinoma cells correlates with alterations in AP-1 composition. Int.J.Cancer, 86: 811-817, 2000. 167. Prusty, B. K. and Das, B. C. Constitutive activation of transcription factor AP-1 in cervical cancer and suppression of human papillomavirus (HPV) transcription and AP-1 activity in HeLa cells by curcumin. Int.J.Cancer, 113: 951-960, 2005. 168. Alazawi, W., Pett, M., Strauss, S., Moseley, R., Gray, J., Stanley, M., and Coleman, N. Genomic imbalances in 70 snap-frozen cervical squamous intraepithelial lesions:

37 General Introduction

associations with lesion grade, state of the HPV16 E2 gene and clinical outcome. Br.J.Cancer, 91: 2063-2070, 2004. 169. Dellas, A., Torhorst, J., Jiang, F., Proffitt, J., Schultheiss, E., Holzgreve, W., Sauter, G., Mihatsch, M. J., and Moch, H. Prognostic value of genomic alterations in invasive cervical squamous cell carcinoma of clinical stage IB detected by comparative genomic hybridization. Cancer Res., 59: 3475-3479, 1999. 170. Heselmeyer, K., Schrock, E., du, M. S., Blegen, H., Shah, K., Steinbeck, R., Auer, G., and Ried, T. Gain of chromosome 3q defines the transition from severe dysplasia to invasive carcinoma of the uterine cervix. Proc.Natl.Acad.Sci.U.S.A, 93: 479-484, 1996. 171. Matthews, C. P., Shera, K. A., and McDougall, J. K. Genomic changes and HPV type in cervical carcinoma. Proc.Soc.Exp.Biol.Med., 223: 316-321, 2000. 172. Narayan, G., Pulido, H. A., Koul, S., Lu, X. Y., Harris, C. P., Yeh, Y. A., Vargas, H., Posso, H., Terry, M. B., Gissmann, L., Schneider, A., Mansukhani, M., Rao, P. H., and Murty, V. V. Genetic analysis identifies putative tumor suppressor sites at 2q35-q36.1 and 2q36.3-q37.1 involved in cervical cancer progression. Oncogene, 22: 3489-3499, 2003. 173. Scotto, L., Narayan, G., Nandula, S. V., Arias-Pulido, H., Subramaniyam, S., Schneider, A., Kaufmann, A. M., Wright, J. D., Pothuri, B., Mansukhani, M., and Murty, V. V. Identification of copy number gain and overexpressed genes on chromosome arm 20q by an integrative genomic approach in cervical cancer: potential role in progression. Genes Chromosomes.Cancer, 47: 755-765, 2008. 174. Overmeer, R. M., Henken, F. E., Bierkens, M., Wilting, S. M., Timmerman, I., Meijer, C. J., Snijders, P. J., and Steenbergen, R. D. Repression of MAL tumour suppressor activity by promoter methylation during cervical carcinogenesis. J.Pathol., 219: 327- 336, 2009. 175. Wentzensen, N., Sherman, M. E., Schiffman, M., and Wang, S. S. Utility of methylation markers in cervical cancer early detection: appraisal of the state-of-the- science. Gynecol.Oncol., 112: 293-299, 2009.

38 Chapter 2

hTERT promoter activity and CpG methylation in HPV-induced carcinogenesis

Jillian de Wilde Jan M. Kooter Renée M. Overmeer Debbie Claassen-Kramer Chris J.L.M. Meijer Peter J.F. Snijders Renske D.M. Steenbergen

Submitted for publication hTERT methylation during HPV-mediated transformation

Abstract Activation of telomerase resulting from deregulated hTERT expression is a key event during high-risk human papillomavirus (hrHPV)-induced cervical carcinogenesis. In the present study we examined hTERT promoter activity and its relation to DNA methylation as one of the potential mechanisms underlying deregulated hTERT transcription in hrHPV-transformed cells. Included in the analyses were primary keratinocytes, HPV16- and HPV18- immortalized keratinocytes, representing an intermediate state in the carcinogenic process, hrHPV-containing cervical cancer cells and cervical tissue specimens. Using luciferase reporter assays we found that in most telomerase positive cells increased hTERT core promoter activity coincided with increased hTERT mRNA expression. On the other hand basal hTERT promoter activity was also detected in telomerase negative cells with no or strongly reduced hTERT mRNA expression levels. In both telomerase positive and negative cells regulatory sequences flanking both ends of the core promoter markedly repressed exogenous promoter activity. Apparently, repression of these sequences is blocked in the endogenous promoter in telomerase positive cells. By extensive bisulfite sequencing analysis of the region spanning nucleotide -442 to +566 (relative to the ATG) a strong increase in methylated CpGs was detected in hTERT positive cells compared to cells with no or strongly reduced hTERT expression. Subsequent analysis of cervical tissue specimens by methylation-specific PCR (MSP) at two regions flanking the core promoter revealed methylation of both regions in 100% of cervical carcinomas and 38% of the high-grade precursor lesions, compared to 9% of low grade precursor lesions and 5% of normal controls. Taken together, methylation of transcriptional repressive sequences in the hTERT promoter and proximal exonic sequences is associated with deregulated hTERT transcription in HPV-immortalized cells and cervical cancer cells. The detection of DNA methylation at these repressive regions may provide an attractive biomarker for early detection of cervical cancer.

40 Chapter 2

Introduction Telomerase is a ribonucleoprotein with reverse transcriptase activity that adds hexameric TTAGGG repeats onto the telomeric ends of chromosomes. Thereby it compensates for telomere shortening that is inherent to DNA replication, the so-called end replication problem 1. Telomerase activation is a key feature of human cancers. The telomerase complex consists of several subunits, including a structural RNA component (hTR) that serves as a template during telomere elongation 2 and a catalytic subunit (hTERT) 3. hTR is ubiquitously expressed and frequently elevated in cancer cells 4. Expression of hTERT is restricted to telomerase positive cells 3, indicating that hTERT expression controls telomerase activity. Indeed, ectopic expression of hTERT is sufficient for the activation of telomerase in telomerase negative cells 5. The hTERT gene has a CG-rich, TATA-less promoter, within which a proximal region of 200 base pairs has been identified as the core promoter, being indispensable for transcription activation 6,7. This core sequence contains numerous binding sites for both transcriptional activators and repressors 6,8-10. The fact that the 5’ region of the hTERT gene and its promoter are part of a large ~4kb CpG island (-1800 to +2200, numbered relative to the ATG) implies that hTERT expression may be responsive to CpG methylation 8. To evaluate this possible regulatory mechanism, several groups have assessed the methylation status of the hTERT CpG island in a variety of primary cells as well as immortal and cancer cell lines 11-15. In line with the general idea that promoter hypermethylation inhibits transcription, hTERT promoter methylation was found to be correlated with repressed transcription in differentiated cells 15,16. However, other studies did not find a clear correlation between hTERT methylation and hTERT expression 12,13. Interestingly, more recent studies demonstrate the reverse situation, as hypermethylation of the hTERT promoter was found to be associated with increased expression 11,14. These seemingly conflicting results may at least in part be explained by different regions and cells that have been examined, and the different methods used. However, the methylation status of the core-promoter region between - 150 - +150 bp around the start site of transcription was shown to be important for hTERT expression 17. hTERT expressing cells contain alleles in which this core-promoter is predominantly hypomethylated despite hypermethylation of other promoter regions. The chromatin of a hypometylated core-promoter region carries transcription active marks (H3K9Ac and H3K4me2) whereas a methylated core-promoter carries inactive marks (H3K9me3 and H3K27me3).

41 hTERT methylation during HPV-mediated transformation

Although these results suggest that epigenetic events at the core-promoter region are crucial, other parts of the promoter may be important as well. It was demonstrated that the 5’ end of the gene has the capacity to suppress hTERT transcription due to binding of the methylation sensitive transcriptional repressor CTCF to exon 1. In cancer cells CTCF repression was shown to be relieved by methylation of its binding site. A second CTCF binding site has been identified in exon 2 18. Thus, aberrant methylation of the 5’ end of gene, including CTCF sites, can affect hTERT expression. Despite the fact that deregulated hTERT expression is implicated in human papillomavirus (HPV)-mediated pathogenesis of cervical cancer, little is known about the potential relationship between transcriptional activity of hTERT and the methylation status of both the hTERT promoter and proximal exonic sequences in this process. Infection with high-risk human papillomavirus (hrHPV) has been recognized as the main risk factor for the development of cervical cancer, which is supported by the detection of hrHPV in virtually all cervical carcinomas 19,20. HrHPV activities together with host cell factors are required for the progression of hrHPV-induced precancerous lesions to invasive cancer. Our previous studies showed elevated hTERT mRNA levels and increased telomerase activity in over 90% of cervical carcinomas and less than half of high-grade precursor lesions, so-called cervical intraepithelial neoplasias (CINs). Most normal cervical tissues and low-grade CIN lesions were devoid of detectable hTERT mRNA and telomerase activity 21. These findings indicate that elevated levels of hTERT mRNA reflect a late step in the CIN to carcinoma sequence following hrHPV infection. It can be speculated that telomerase- positive CIN lesions have gained an immortal phenotype and have reached a point of no return in terms of malignant potential. Ectopic expression of HPV16 E6, along with E6AP can, (in part) mediated by c-Myc, induce hTERT transcription and telomerase activity directly 22-24. Additionally, E6 associated with E6AP can degrade the hTERT repressor NFX1-91, which normally interacts with the co-repressor complex mSin3A/histone deacetylase (HDAC) at the hTERT promoter 25. By degrading NFX1-91, E6/E6AP changes the chromatin structure at the hTERT promoter which results in increased hTERT expression 26. More recently, NFX1-123, which like NFX1-91 is a splice variant of NFX1, has been demonstrated to increase hTERT expression posttranscriptionally in HPV E6 containing keratinocytes 27.

42 Chapter 2

However, several other studies have shown that in the context of the whole HPV genome, E6 activity alone is insufficient for increasing hTERT expression and concomitant telomerase activation in human keratinocytes 28,29. Microcell- mediated chromosome transfer studies have shown that the increased hTERT mRNA expression and telomerase activity in HPV-immortalized cells and cervical cancer cells may depend on a recessive event, suggesting inactivating alterations of host cell genes being involved in this process as well 29-31. We previously demonstrated that potential hTERT regulatory genes reside on chromosome 6q, which may either directly or indirectly regulate hTERT transcription 5,32. In the present study we aimed to directly assess the activity of the regulatory hTERT sequences in HPV-transformed cells and the potential role of hTERT methylation in cervical carcinogenesis. To this end, we first analyzed the activity of various hTERT promoter and proximal exonic/intronic sequences by transient luciferase reporter assays in four human keratinocyte cell lines, immortalized by full-length HPV16 and HPV18 DNA and three cervical cancer cell lines. Secondly, we used extensive bisulfite sequencing and quantitative methylation-specific PCR (qMSP) to examine hTERT DNA methylation in all cell lines as well as cervical tissue specimens representing the complete spectrum of (pre-)malignant disease.

Methods Cells and cell lines Primary keratinocytes (EK94-2 and EK04-3) were isolated from human foreskins, as described before 29. The cell lines FK16A, FK16B, and FK18A and FK18B were established by transfection of primary foreskin keratinocytes with the entire HPV16 and HPV18 genomes, respectively 29. The cervical carcinoma cell lines SiHa (HPV16), HeLa (HPV18) and CaSki (HPV16), were obtained from the American Type Culture Collection (Manassas, VA). Culture conditions for these cells and cell lines were described previously 29,33. The hTERT-negative osteosarcoma cell line Saos-2 was obtained from American Type Culture Collection (Manassas, VA) and cultured in Dulbecco’s modified Eagle medium (DMEM) supplemented with 10% foetal bovine serum (FBS), penicillin (100 U/mL), streptomycin (100 μg/mL), and L-glutamine (2 mM) (all from Life Technologies, Inc., Breda, The Netherlands).

43 hTERT methylation during HPV-mediated transformation

Clinical samples Formalin fixed, paraffin-embedded biopsies of normal cervix (n=22), CIN1 lesions (n=26), CIN3 lesions (n=29) and cervical squamous cell carcinomas (SCCs) (n=21) were collected during routine clinical practice and stored at the Department of Pathology of the VU University Medical Center. Cervical scrapings analyzed by bisulfite sequencing analysis were collected from women taking part in a population-based cervical screening trial 34. We included three scrapings of women without CIN disease (Pap1 n=2, BMD n=1) and one scrape (Pap3a2) of a woman with CIN disease. HPV DNA presence was determined using GP5+/6+-PCR, followed by an enzyme immunoassay (EIA) with cocktail probes representing pools of high- and low-risk HPV types, respectively 35. Subsequently, HPV typing was performed on PCR products of EIA-positive cases using reverse line blot (RLB) analysis, as described previously 36. EIA-positive samples that failed to reveal an RLB signal, were considered to contain HPV (sub)types or variants that do not react with the specific RLB probes and these HPVs were referred to as HPV X (X). All cervical scrapings, 7 CIN 1 lesions, all except one CIN3 lesion, and all SCCs were hrHPV-positive by GP5+/6+-PCR. None of the normal biopsies was hrHPV-positive. This study followed the ethical guidelines of the Institutional Review Board of the VU University Medical Center.

RNA isolation and quantitative RT-PCR Total RNA was isolated using RNA Bee (Tel-test, Friendswood, TX) following the manufacturer’s instructions. hTERT mRNA was quantified by real time RT- PCR using the TeloTAGGG hTERT (Roche, Woerden, The Netherlands) according to the manufacturer’s manual. Relative hTERT levels were determined by dividing hTERT expression levels by expression levels of the housekeeping gene Porphobilinogen Deaminase (PBGD). hTERT levels were considered to be low when the ratio between hTERT and PBGD expression was <1. All PCR reactions were performed in duplicate and mean values including the standard deviation were calculated. hTERT promoter constructs The pGL3-control vector (Promega Benelux BV, Leiden, The Netherlands) contains the Firefly luciferase gene under the control of a CMV promoter. The pGL3-basic vector (Promega Benelux BV) is a promoterless vector containing the Firefly luciferase gene. The hTERT reporter constructs contain DNA

44 Chapter 2 fragments of the hTERT promoter inserted upstream of the Firefly luciferase gene in the pGL3 basic vector. hTERT-1821/-23, hTERT-499/-23, hTERT-297/-23, hTERT-297/+81, and hTERT-297/+357, which contain hTERT promoter sequences from –1821 bp to -23 bp, -499 to –23 bp, -297 to –23 bp, -297 to +81 bp, and –297 to +357 bp, respectively, relative to the ATG start site (see Figure 2) have previously been referred to as pTERT-1821, pTERT-499, pTERT-297, pTERT-297/ex1 mini, and pTERT-297/ex1 18,37 and were kindly provided by Dr. J. Benhattar (Institute of Pathology, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland).

Transfection and luciferase assay Cells were seeded on 48 wells plates at a concentration of 10,000 cells/well (SiHa, HeLa and CaSki) or 20.000 cells/well (EK04-3, FK16A, FK16B, FK18A, and FK18B) and cultured overnight. Transient transfection of luciferase reporter plasmids was performed using TransPEI (Eurogentec, Seraing, Belgium) according to the manufacturer’s protocol. The Renilla luciferase reporter vector (Promega Benelux BV) was co-transfected as an internal control for transfection efficiency. Briefly, cells were exposed to a transfection mixture containing 500 ng of reporter plasmid and 25 ng of internal control for 4 hours at 37°C. Cells were harvested 24 hours after transfection. Luciferase assays were performed using the Dual Luciferase Reporter Assay System (Promega Benelux BV) and a Lumat LB 9507 luminometer (EG&G Berthold, Bad Wildbad, Germany). For calculations the mean values of relative luciferase activity, i.e. Firefly luciferase divided by Renilla luciferase activity, were used, in which the mean relative luciferase activity of the pGL3 control vector was set at 100%. All experiments were performed (at least) in duplicate and mean values including standard deviation are calculated.

DNA isolation and bisulfite modification Genomic DNA from cultured cells was isolated using DNA STAT-60 (Tel- Test). Genomic DNA from paraffin-embedded tissue specimens and cervical scrapings was isolated as described previously 38. Sodium bisulfite modification was performed with the EZ DNA Methylation Kit, according to the manufacturer’s guidelines (Zymo Research, Orange, CA).

45 hTERT methylation during HPV-mediated transformation

Bisulfite sequencing The hTERT promoter and first exon were amplified using 4 primer sets spanning the hTERT promoter and coding sequence from -442 to +566 bp, relative to the ATG start site (Table 1). All primers have been previously described by Guilleret et al. 39, but were in some cases used in a different combination.

Sequence primers Sequences Location F 5’ GGGTTATTTTATAGTTTAGGT 3’ hTERT/-442 to -219 R 5’ AATCCCCAATCCCTC 3’ F 5’ GTTTTGTTTTTTTATTTTTTAGTTT 3’ hTERT/-208 to +104 R 5’ CCAACCCTAAAACCCCAAA 3’ F 5’- TTTGGGGTTTTAGGGTTGG -3’ hTERT/+88 to +348 R 5’- AACCACCAACTCCTTCAAA -3’ F 5’- GTAGGTGTTTTGTTTGAAGGA -3’ hTERT/+319 to +566 R 5’-TACCAACAAATAAACCAAC-3’ MSP primers Sequences Location F 5’ TAGATTTTCGGGTTCGTTCG 3’ hTERT/-317 to -262 R 5’ TCTATACCCGCGAATCCACT 3’ P 5’ CGACCTAACCCCGACAACGCAACTA 3’ F 5’ GAGTAGCGTAGGCGATTTAGGGCGT 3’ hTERT/+288 to +419 R 5’ GTCCAACAACGCGAAACCGAA 3’ P 5’ CGCACAACCTCTACAACACTCGAACCACCAACTC F3’ 5’ TGGTGATGGAGGAGGTTTAGTAAGT 3’ β actin 5’ AACCAATAAAACCTACTCCTCCCTTAA 3’ P 5’ ACCACCACCCAACACACAATAACAAACACA 3’ Table 1: Primers and probes used for bisulfite sequencing and MSP analysis

The PCR mixtures contained 50 ng of modified DNA, 0.5 μM primers, 200 μM dNTPs, 1.5 mM MgCl2 and 1 U of FastStart Taq DNA polymerase (Roche). Amplification conditions were: denaturation at 95°C for 4 minutes; 40 cycles of 95°C for 1 minute, 60°C for 1 minute and 72°C for 1 minute; and a final elongation step of 72°C for 4 minutes. Subsequently, PCR products were purified using a QIAgen PCR purification kit (Westburg, Leusden, The Netherlands) and cloned in pGEM-T using the pGEM-T Easy Cloning kit (Promega). For most regions, between 10 and 20 cloned PCR fragments were

46 Chapter 2 sequenced using the BigDye Terminator v1.1 Cycle Sequencing Kit on an ABI Prism Avant Genetic Analyzer (Applied Biosystems, Nieuwerkerk a/d IJssel, The Netherlands) and sequences were analyzed using Vector NTI (Invitrogen, Breda, The Netherlands).

Quantitative methylation-specific PCR (qMSP) qMSP was performed using two primer/probe sets, one of which was located in the promoter (region 1) and the other in the first intron and exon 2 (region 2) (Table 1). A standard curve of bisulfite-treated DNA of SiHa was included in each qMSP. The house keeping gene β-actin was included as a quality control (Table 1) 40. qMSP analysis and quantification of results was performed, as described previously 41. All samples were tested in duplicate and in case of discrepancy in quadruplicate. Samples scored positive if at least two test results (quantity ratios) were above zero.

Results hTERT mRNA expression and hTERT promoter activity are partially correlated We determined hTERT mRNA expression by real time RT-PCR in primary keratinocytes (EK cells), HPV-immortalized cell lines and cervical carcinoma cell lines SiHa, HeLa, and CaSki. The cell line Saos-2 was included as an hTERT negative control. The HPV-immortalized cell lines comprised two HPV16-transfected keratinocyte cell lines (FK16A and FK16B) and two HPV18-transfected keratinocyte cell lines (FK18A and FK18B). Either or not following a crisis period, all cell lines became immortal and gained strong telomerase activity, but were not yet tumorigenic in nude mice 29,33. As shown in Figure 1A, hTERT mRNA was undetectable in Saos-2 cells and present at very low levels in primary keratinocytes (0.2). Relatively high hTERT mRNA levels were detected in all HPV-immortalized cell lines and cervical carcinoma cell lines, with hTERT mRNA levels ranging from 1.2 to 9.1, relative to the housekeeping gene PBGD. To investigate hTERT promoter activity in these cells, we measured luciferase expression of construct hTERT-297/-23, containing hTERT promoter sequences from -297 to -23, relative to the ATG. hTERT promoter activities were related to the CMV-promoter activity in the pGL3 control vector, which was set at 100%. The relative hTERT promoter activity was 3% in Saos-2 cells and 5% in EK cells (Figure 1B). Relative levels of hTERT promoter activity in in vitro immortalized cells and cancer cells ranged from 5% in HeLa cells to 37% in

47 hTERT methylation during HPV-mediated transformation

FK16A cells (Figure 1B). However, relative levels of promoter activity did not always correlate with relative hTERT mRNA levels. Of note, promoter activity in EK and Saos-2 cells was comparable to that in HeLa cells (Figure 1B), despite the fact that hTERT mRNA levels were markedly higher in HeLa cells (Figure 1A).

Figure 1: hTERT mRNA expression and core promoter activity in all cell cultures. (A) hTERT mRNA levels relative to the housekeeping gene PBGD and (B) hTERT core promoter activity as assessed by the hTERT-297/-23 reporter construct. Given values are percentages of luciferase activity relative to pGL3 control that was set at 100%.

Repression of hTERT promoter activity by sequences flanking the hTERT core promoter To examine the contribution of sequences located 5’ and 3’ to the hTERT core promoter to hTERT promoter activity, we tested the reporter constructs hTERT-1821/-23, hTERT-499/-23, hTERT-297/+81, and hTERT-297/+357

48 Chapter 2

(schematically represented in Figure 2A) next to the core promoter construct in the various cell lines. Insertion of 5’ sequences, i.e. –499 to –23 (hTERT –499/-23) resulted in a strong reduction in luciferase activity, varying from 45% in HeLa cells to 82% in FK16B and FK18A cells. Also in primary keratinocytes and telomerase negative Saos-2 cells, luciferase activity was strongly repressed, indicating that the repression is cell type-independent. Insertion of additional upstream promoter sequences starting at -1821 (hTERT-1821/-23) did generally not further suppress the promoter activity (Figure 2B), indicating that the suppressive effect can mainly be attributed to sequence -499 to -297, relative to ATG .

Figure 2: hTERT promoter activity analysis, using hTERT reporter constructs carrying different promoter and proximal exonic sequences. (A) Schematic representation of different reporter constructs used. (B) Luciferase activity in Saos-2, EK04-3, FK16A, FK16B, FK18A, FK18B, SiHa, HeLa and CaSki cells following transfection of hTERT-1821/-23 and hTERT-499/-23, relative to hTERT-297/-23 that was set at 100%. (C) Luciferase activity in Saos-2, EK04-3, FK16A, FK16B, FK18A, FK18B, SiHa, HeLa and CaSki following transfection of hTERT-297/+81 and hTERT-297/+357, relative to hTERT-297/-23 that was set at 100%.

Inclusion of 3’ genomic sequences, encoding part of the first exon up to nucleotide +81 (hTERT-297/+81), also repressed the basal luciferase activity which varied from an 18% reduction in FK18B cells to a 67% decrease in SiHa cells (Figure 2C). A further, very strong repression of promoter activity was

49 hTERT methylation during HPV-mediated transformation seen upon addition of sequences up to +357, spanning the first exon, first intron and part of exon 2 (hTERT-297/+357). The resulting reduction in promoter activity ranged from 85% in Saos-2 cells to 96% in FK16B, SiHa and CaSki cells (Figure 2C). Conclusively, our findings indicate that both the -499 to -297 region and core promoter downstream exonic/intronic sequences up to +357 contain putative repressive regulatory sequences. hTERT bisulfite sequencing analysis in cultured cells Since in telomerase positive cells the suppressive effect of sequences flanking the core promoter seems to be released, we reasoned that this might be due to epigenetic differences. This view is supported by studies that show a correlation between hTERT promoter methylation and hTERT transcription 14,39. We therefore determined the methylation status of the putative hTERT regulatory sequences identified in the transient expression assays. By bisulfite sequencing we analyzed CpG methylation of the region spanning nucleotides -442 to +566, relative to the ATG in primary keratinocytes (EK), FK16A and SiHa cells. Using overlapping PCR products the following 4 regions were analyzed: -442 to -219 bp (region S1), -108 to +104 bp (region S2), +88 to +348 bp (region S3), and +319 to +566 bp (region S4), all relative to the ATG site (Figure 3A). Throughout the promoter, except for region S2, few methylated CpGs were detected in EK cells. Compared to these primary cells, methylation was increased in the HPV16-immortalized cell line FK16A at all four regions. An even higher methylation level was found in S1, S3 and S4 from SiHa cells. An overview of the distribution and frequency of methylated CpGs in individual alleles in EK, FK16A and SiHa is shown in Figure 3B. To determine whether methylation occurs at specific transcription factor binding sites, the known CpG overlapping binding sites were plotted at the top of Figure 3A. A rather random distribution of methylated CpGs relative to these sites was evident within region S1 and S2 (Figure 3B, top panels). Interestingly, the presence of a so-called unmethylated core, including the CpGs -19 to -12, which has been described to contribute to hTERT expression by others 17,42, was not observed in the hTERT expressing cells. Within region S3 methylation of FK16A and SiHa cells was mainly concentrated at the 3’ end. The 3’ sub-region preferentially affected by methylation in these cell lines, contains putative binding sites for the transcription factors AP2, AP4 and MYOD 10) (Figure 3B, lower left panel).

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A

B

51 hTERT methylation during HPV-mediated transformation

C

Figure 3: Bisulfite sequencing results of hTERT regulatory regions. (A) Schematic overview of the four regions analyzed: S1: -442 to -219, S2:-208 to -104, S3: +88 to +348, and S4:+319 to +566. Numbers refer to the respective CpG dinucleotides and their position relative to the ATG. The positions of transcription factor binding sites, if containing CpG dinucleotides, are shown at the top by the black lines (or grey lines when located directly next to each other). Regions analyzed by MSP (M1 and M2) are indicated by dotted lines. (B) CpG methylation results of individual cloned PCR products of cultured cells (EK cells, FK16A cells, and SiHa cells). (C) CpG methylation results of individual cloned PCR products of clinical specimens (cervical scraping classified as normal (Pap1), borderline mild dyskaryosis (BMD, Pap2/3a1), moderate dyskaryosis (Pap3a2), and a cervical squamous cell carcinoma (SCC)). Of all samples ten representative clones are given. Unmethylated CpGs are indicated by grey squares and methylated CpGs are indicated by black squares.

Methylation at region S4 was most extensive in SiHa cells, followed by FK16A cells (Figure 3B, lower right panel). Interestingly, within this region the lowest methylation was seen at the second CTCF binding site (CpG 54-56) in all cells analyzed. However, at the first CTCF binding site located within region S2, methylation was slightly increased (Figure 3B, lower right panel). Next to these three cell cultures, the remaining three HPV-immortalized cell lines (FK16B, FK18A and FK18B) as well as the cervical cancer cell lines HeLa and CaSki were subjected to bisulfite sequencing analysis of the S3 and S4 region. Similar to FK16A and SiHa cells, it was found that all remaining three HPV-immortalized cell lines and the two cervical cancer cell lines showed a high density of methylated CpGs in these two regions compared to primary keratinocytes. Moreover, similar to the FK16A and SiHa cells methylation

52 Chapter 2 within the S3 region was particularly increased at the 3’end in FK16B cells, but not in the other cell lines. A summary of CpG methylation frequencies in regions S1 to S4 regions is shown in Table 2.

Cell culture %methylation (total number of clones analyzed) S1 S2 S3 S4

(-442/-219) (-208/+104) (+88/+348) (+319/+566) EK 9 (20) 29 (20) 0 (15) 6 (22) FK16A 27(20) 53 (20) 26 (13) 47 (18) SiHa 51(20) 53 (20) 45 (15) 83 (22) FK16B 27 (16) 40 (16) FK18A 40 (16) 38 (24) FK18B 21 (13) 41 (20) HeLa 18 (12) 29 (21) CaSki 65 (6) 93 (20) Table 2: Percentage of methylation in cultured primary keratinocytes, HPV-immortalized cell lines and cervical carcinoma cell lines hTERT bisulfite sequencing analysis in clinical specimens In addition to the cell lines, DNA from four hrHPV-positive cervical scrapings, classified as normal cytology (n=2), borderline or mild dyskaryosis and moderate dyskaryosis, respectively, as well as a cervical carcinoma biopsy were analyzed by bisulfite sequencing at regions S3 and S4. An overview of methylation of individual CpGs and locations of transcription factor binding sites is shown in Figure 3C. Methylation frequencies in region S3 and S4 are summarized in Table 3.

Cervical specimen % methylation (number of clones analyzed) S3 S4 Normal cytology, hrHPV+ 1 (23) 10 (24) Normal cytology, hrHPV+ 1(25) 11(25) Borderline mild dyskaryosis, 3 (20) 8 (20 Moderate dyskaryosis, hrHPV+ 13 (20) 8 (20) Cervical carcinoma, HPV16+ 17 (20) 7 (20) Table 3: Percentage of methylation in hrHPV-positive cervical scrapings and a cervical carcinoma

Methylation levels in clinical specimens were generally lower than in cell cultures. Only at S3 an increase in methylation was detected proportional to increased severity of the abnormality (Figure 3C, lower left panel). If present, methylation within region S3 tended to be highest at both the 5’and 3’ ends,

53 hTERT methylation during HPV-mediated transformation which together cover putative AP2, AP4 and MYOD binding sites, as mentioned above 10. Although methylation of the S4 region was not increased in the cancer specimen compared to the normal specimens, it was, when present, concentrated at the 3’ end of the region (Figure 3C, lower right panel). Thus, increased methylation of particularly the S3 region, spanning +88 to +348, was associated with malignant transformation both in vitro and in vivo. This particular region resides in the fragment that displayed the strongest repressive effect on the core promoter activity in the transient expression assays. qMSP analysis of the hTERT promoter and first exon To further assess the hTERT methylation status in cervical tissue specimens, we designed two quantitative methylation-specific PCRs (qMSPs). With primer design restrictions taken into account these MSPs encompassed sequences that showed increased methylation in immortalized cell lines and/or severe cervical disease, as found by bisulfite sequencing; i.e. one within the proximal promoter region (M1: -317 to -262) and a second within the gene (M2: +288 to +419) (Figure 3A).

Figure 4: Quantitative methylation-specific PCR (qMSP) results for two regions of the hTERT gene. Results of both cell cultures and cervical tissue biopsies are shown. Region M1 spans nts -317 to -262 bp, relative to the ATG and region M2 spans nt +288 to +219 bp, relative to the ATG. Black boxes indicate methylation positive, gray boxes indicate no methylation and white boxes remain undetermined. HPV status of specimens is depicted as specific HPV type present or negative (-).

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Figure 5: Association between methylation and disease stage. Scatter plots with on the x- axes levels of methylated DNA, on the y-axes the samples grouped for each disease stage (Note that only positive samples are given). (A) Region M1: -317 to -262 bp, relative to the ATG. (B) Region M2: +288 to +219 bp, relative to the ATG.

For validation we tested primary keratinocytes (EK94-2), having a very low hTERT mRNA expression and little methylation as assessed by bisulfite sequencing, and HPV-immortalized and cervical cancer cell lines with elevated hTERT mRNA levels and methylation of the hTERT CpG island, i.e. FK16A, FK16B, FK18A, FK18B, SiHa, HeLa and CaSki. In line with the bisulfite sequencing results, primary keratinocytes were negative by qMSP at both regions, while all hTERT-positive cell lines, except CaSki, were qMSP-positive at both regions. CaSki tested negative at region M1 (Figure 4). In clinical specimens, methylation at M1 was detected in 14% (3/22) of normal controls, 17% (4/23) of CIN1 lesions, 48% (13/27) of CIN3 lesions, and in all (20/20) SCCs (Figure 4). M2 methylation was found in 27% (6/22) of normal controls, 42% (11/26) of CIN1 lesions, 69% (20/29) of CIN3 lesions, and all (20/20)

55 hTERT methylation during HPV-mediated transformation

SCCs (Figure 4). Methylation at both regions was found in 5% (1/22) of normal controls, 9% (2/23) of CIN1 lesions, 38% (11/27) of CIN3 lesions, and 100% (20/20) of SCCs (Figure 4). At both regions the level of methylation increased with the severity of cervical disease (Figure 5). Thus, not only the number of samples positive for methylation increased, but also the degree of methylation per sample increased with stage of disease.

Discussion Deregulated hTERT expression, resulting in the activation of telomerase, is a critical event during hrHPV-induced transformation, and is likely to mark a so- called point of no return during cervical carcinogenesis. To further elucidate the mechanisms underlying hTERT deregulation in HPV-transformed cells, both hTERT promoter activity and DNA methylation alterations were assessed in HPV-immortalized cells and cervical cancer cell lines as well as cervical (pre)cancerous lesions. Using reporter constructs, we found that hTERT core promoter activity in some, but clearly not all, cells analyzed correlated to endogenous mRNA expression in most, though not all, cell lines. If hTERT expression is regulated exclusively by transcription factor binding to the core promoter, reporter activity would be entirely correlated with endogenous hTERT expression. Our findings therefore point to regulatory events that are independent of the core promoter region. Indeed, sequences flanking the core promoter, particularly those spanning -499 to -297 and +88 to +348 (all relative to the ATG), inhibited basal hTERT promoter activity in HPV-immortalized cells and cervical carcinoma cell lines. Transcriptional repression by 5’ sequences is in accordance with previous studies with cancer cell lines 6,7,37. Transcriptional repressors that can bind these sites include WT1 (-358) 43, SP1 (-358, -323, +254) 44, EGR1 (-358) 45, and CTCF (+4) 18, the latter two of which have been described to bind the hTERT promoter in cervical cancer cells 18,45. Although transcriptional repression by 3’ sequences confirms previous results, it cannot be completely ruled out that the reduced promoter activity of the hTERT-297/+357 construct is in part due to alternative splicing of the luciferase gene 37. The partial disparity between endogenous hTERT mRNA levels and exogenous hTERT promoter activity prompted us to assess whether differences in epigenetic factors, particularly DNA methylation, may regulate hTERT expression in HPV-transformed cell lines, as was observed in other cell lines 11-

56 Chapter 2

18,39,42,46-48. Most, though not all, studies found a positive correlation between hTERT methylation and hTERT expression. By extensive bisulfite sequencing of HPV-transfected keratinocyte cell lines, a gradual increase in DNA methylation with progression from a mortal phenotype (represented by primary keratinocytes), via an immortal phenotype (represented by the HPV-immortalized cells) to a tumorigenic phenotype (represented by cervical cancer cells) was observed. Also in HPV-positive cervical samples representing (pre)malignant disease, an increase in methylation with progression of disease was detected at 2 of the 3 regions analyzed. Overall, methylation was less extensive in clinical specimens than in cell lines, which may be explained either by selection of cells containing methylated hTERT during culturing and/or the presence of normal cells in clinical specimens. Remarkably, within region S3, containing exon 1, methylation was more abundant at putative binding sites for AP2, AP4 and MYOD 10). As binding of AP2 can be inhibited by methylation 49, it is well possible that binding of AP4 and MYOD is also methylation-sensitive. Although the beta isoform of AP2 has been demonstrated to activate hTERT transcription via the AP2 binding sites in the core promoter 50, the hTERT regulatory sequences contain multiple AP2 binding sites, some of which may also be repressive and/or bound by the other AP2 family-members (AP2α, γ, δ, ε). Renaud et al. demonstrated that the methylation-sensitive repressor CTCF has two binding sites in the hTERT genomic sequence, located at +4 to +39 and +422 to +440 (both relative to the ATG) 18. In accordance with the described methylation of the first CTCF binding site in different human cancer cell lines and human tumors, including HeLa cells and a cervical carcinoma 42, we also observed increased methylation of this site in HPV-transformed cell lines and a cervical SCC. However, the second CTCF site appeared to be relatively unmethylated compared to the surrounding CpGs. Therefore, inhibition of CTCF binding to the first binding site may be involved in activation of hTERT transcription during HPV-mediated transformation. Co-transfection of CTCF cDNA with hTERT reporter constructs did, however, not affect luciferase activity (data not shown). The latter finding may indicate that either CTCF binds to the hTERT gene but does not inhibit hTERT transcription in these HPV-transformed cells or that CTCF binding is inhibited by a different mechanism. We have no evidence for competitive binding by the CTCF-like transcription factor Boris 51, because Boris expression could not be detected in our cell lines, except for CaSki cells (data not shown).

57 hTERT methylation during HPV-mediated transformation

The high levels of methylation at both CTCF binding sites as detected in HeLa cells by Guilleret et al. 39, could not be confirmed in our studies, a feature that may result from the use of different HeLa subclones 52. Similar to CTCF the transcriptional repressor Egr-1 binds to a CpG containing sequence located at -358 in the hTERT promoter. Interestingly, Egr-1 expression was found to be increased in hTERT positive cervical carcinomas, whereas it acted as a transcriptional repressor using hTERT promoter driven reporter constructs in cervical cancer cell lines. 45. Consequently, also Egr-1 repressive activity may be inhibited by DNA methylation in cervical cancer cells. Indeed in the presnt study the EGR1 binding site was found to be methylated in the HPV-immortalized cell lines as well as cervical cancer cell lines. Recent studies have reported that although the hTERT promoter and coding sequence are frequently methylated in human tumors a(n) (partially) unmethylated region around the transcription start site is required to allow transcription 17,42. Specific CpGs that were found to remain unmethylated in these studies are CpG -20 to CpG -12 42 and CpG -19 to +14 17. Although we also observed only partial methylation around the transcription start site (at -58 bp from the ATG, between CpG -7 and -8), methylation was not decreased compared to the surrounding regions analyzed. In fact, in the SCCs we observed more methylation at region S2, spanning CpG -24 to +15, than at the two downstream regions. However, since the methylation patterns we observed are heterogeneous and dynamic, unmethylated or partially unmethylated alleles may be responsible for hTERT expression, as was also suggested by Zinn et al. 17. Support for this comes from the finding that active histone marks were particularly associated with unmethylated DNA and inactive histone marks generally, though less pronounced, with methylated DNA 17. In line with the highly heterogeneous methylation patterns observed in the individual alleles analyzed, it has been demonstrated that on average hTERT expression is very low and that cancer cells contain less than one copy of hTERT mRNA per cell 53,54. To assess the potential diagnostic value of hTERT methylation we performed qMSP analysis on a region in the hTERT promoter (-330 to –260 bp) and a second region in the first intron and second exon (+290 to +420 bp). With progression to cervical cancer a gradual increase in methylation was observed. Methylation at either the first or the second region was found in a relatively high percentage of normal controls (14% and 27%, respectively) and CIN1

58 Chapter 2 lesions (17% and 37%, respectively). Together with the fact that hTERT mRNA expression is only rarely elevated in normal cervical cells and low grade cervical lesions 21,55, these findings may indicate that generally, methylation on both regions rather than either region is associated with deregulated hTERT expression. Although to the best of our knowledge there are no reports on hTERT methylation in the complete spectrum of cervical squamous lesions, hTERT promoter methylation as detected by qMSP analysis using primers spanning -280 to -160 bp, relative to the ATG, has been detected in almost 60% of cervical carcinomas and none of normal cervical tissues 56. The fact that we observed increased methylation of both regions analyzed in a marked subset of precursor lesions and in all cervical carcinomas indicates that hTERT methylation analysis may be of diagnostic value for the triage of hrHPV- positive women. Since past studies have shown that both telomerase activity and hTERT mRNA and protein levels in cervical scrapings only poorly reflect the status of these markers in the underlying lesions 57-60, hTERT methylation may be an attractive alternative marker. In conclusion we demonstrated that CpG methylation of transcriptionally repressive sequences in the hTERT promoter and proximal exonic sequences is associated with deregulated hTERT transcription in HPV-immortalized cells and cervical cancer cells. Analysis of cervical biopsies representing the full spectrum of cervical disease revealed that the detection of DNA methylation at these repressive regions may provide an attractive biomarker for early detection of cervical cancer.

Acknowledgements We thank Inès Beumer, Désirée de Cooker, Weng Yee Leong, Sabrina de Munnik, Mohammed Asim Uddin, and Rosanne Tamis for excellent technical assistance.

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20. Walboomers, J. M., Jacobs, M. V., Manos, M. M., Bosch, F. X., Kummer, J. A., Shah, K. V., Snijders, P. J., Peto, J., Meijer, C. J., and Munoz, N. Human papillomavirus is a necessary cause of invasive cervical cancer worldwide. J.Pathol., 189: 12-19, 1999. 21. Snijders, P. J., van Duin, M., Walboomers, J. M., Steenbergen, R. D., Risse, E. K., Helmerhorst, T. J., Verheijen, R. H., and Meijer, C. J. Telomerase activity exclusively in cervical carcinomas and a subset of cervical intraepithelial neoplasia grade III lesions: strong association with elevated messenger RNA levels of its catalytic subunit and high-risk human papillomavirus DNA. Cancer Res., 58: 3812-3818, 1998. 22. Klingelhutz, A. J., Foster, S. A., and McDougall, J. K. Telomerase activation by the E6 gene product of human papillomavirus type 16. Nature, 380: 79-82, 1996. 23. Liu, X., Yuan, H., Fu, B., Disbrow, G. L., Apolinario, T., Tomaic, V., Kelley, M. L., Baker, C. C., Huibregtse, J., and Schlegel, R. The E6AP ubiquitin ligase is required for transactivation of the hTERT promoter by the human papillomavirus E6 oncoprotein. J.Biol.Chem., 280: 10807-10816, 2005. 24. Veldman, T., Liu, X., Yuan, H., and Schlegel, R. Human papillomavirus E6 and Myc proteins associate in vivo and bind to and cooperatively activate the telomerase reverse transcriptase promoter. Proc.Natl.Acad.Sci.U.S.A, 100: 8211-8216, 2003. 25. Gewin, L., Myers, H., Kiyono, T., and Galloway, D. A. Identification of a novel telomerase repressor that interacts with the human papillomavirus type-16 E6/E6-AP complex. Genes Dev., 18: 2269-2282, 2004. 26. Xu, M., Luo, W., Elzi, D. J., Grandori, C., and Galloway, D. A. NFX1 interacts with mSin3A/histone deacetylase to repress hTERT transcription in keratinocytes. Mol.Cell Biol., 28: 4819-4828, 2008. 27. Katzenellenbogen, R. A., Vliet-Gregg, P., Xu, M., and Galloway, D. A. NFX1-123 increases hTERT expression and telomerase activity posttranscriptionally in human papillomavirus type 16 E6 keratinocytes. J.Virol., 83: 6446-6456, 2009. 28. Sprague, D. L., Phillips, S. L., Mitchell, C. J., Berger, K. L., Lace, M., Turek, L. P., and Klingelhutz, A. J. Telomerase activation in cervical keratinocytes containing stably replicating human papillomavirus type 16 episomes. Virology, 301: 247-254, 2002. 29. Steenbergen, R. D., Walboomers, J. M., Meijer, C. J., van der Raaij-Helmer EM, Parker, J. N., Chow, L. T., Broker, T. R., and Snijders, P. J. Transition of human papillomavirus type 16 and 18 transfected human foreskin keratinocytes towards immortality: activation of telomerase and allele losses at 3p, 10p, 11q and/or 18q. Oncogene, 13: 1249-1257, 1996. 30. Backsch, C., Wagenbach, N., Nonn, M., Leistritz, S., Stanbridge, E., Schneider, A., and Durst, M. Microcell-mediated transfer of chromosome 4 into HeLa cells suppresses telomerase activity. Genes Chromosomes.Cancer, 31: 196-198, 2001. 31. Poignee, M., Backsch, C., Beer, K., Jansen, L., Wagenbach, N., Stanbridge, E. J., Kirchmayr, R., Schneider, A., and Durst, M. Evidence for a putative senescence gene locus within the chromosomal region 10p14-p15. Cancer Res., 61: 7118-7121, 2001. 32. van Duin, M., Steenbergen, R. D., de Wilde, J., Helmerhorst, T. J., Verheijen, R. H., Risse, E. K., Meijer, C. J., and Snijders, P. J. Telomerase activity in high-grade cervical lesions is associated with allelic imbalance at 6Q14-22. Int.J.Cancer, 105: 577-582, 2003. 33. Steenbergen, R. D., Kramer, D., Braakhuis, B. J., Stern, P. L., Verheijen, R. H., Meijer, C. J., and Snijders, P. J. TSLC1 gene silencing in cervical cancer cell lines and cervical neoplasia. J.Natl.Cancer Inst., 96: 294-305, 2004. 34. Bulkmans, N. W., Rozendaal, L., Snijders, P. J., Voorhorst, F. J., Boeke, A. J., Zandwijken, G. R., van Kemenade, F. J., Verheijen, R. H., Groningen, K., Boon, M. E., Keuning, H. J., van Ballegooijen, M., van den Brule, A. J., and Meijer, C. J. POBASCAM, a population-based randomized controlled trial for implementation of high-risk HPV testing in cervical screening: design, methods and baseline data of 44,102 women. Int.J.Cancer, 110: 94-101, 2004.

61 hTERT methylation during HPV-mediated transformation

35. Jacobs, M. V., Snijders, P. J., van den Brule, A. J., Helmerhorst, T. J., Meijer, C. J., and Walboomers, J. M. A general primer GP5+/GP6(+)-mediated PCR-enzyme immunoassay method for rapid detection of 14 high-risk and 6 low-risk human papillomavirus genotypes in cervical scrapings. J.Clin.Microbiol., 35: 791-795, 1997. 36. van den Brule, A. J., Pol, R., Fransen-Daalmeijer, N., Schouls, L. M., Meijer, C. J., and Snijders, P. J. GP5+/6+ PCR followed by reverse line blot analysis enables rapid and high-throughput identification of human papillomavirus genotypes. J.Clin.Microbiol., 40: 779-787, 2002. 37. Renaud, S., Bosman, F. T., and Benhattar, J. Implication of the exon region in the regulation of the human telomerase reverse transcriptase gene promoter. Biochem.Biophys.Res.Commun., 300: 47-54, 2003. 38. Overmeer, R. M., Henken, F. E., Snijders, P. J., Claassen-Kramer, D., Berkhof, J., Helmerhorst, T. J., Heideman, D. A., Wilting, S. M., Murakami, Y., Ito, A., Meijer, C. J., and Steenbergen, R. D. Association between dense CADM1 promoter methylation and reduced protein expression in high-grade CIN and cervical SCC. J.Pathol., 215: 388-397, 2008. 39. Guilleret, I. and Benhattar, J. Unusual distribution of DNA methylation within the hTERT CpG island in tissues and cell lines. Biochem.Biophys.Res.Commun., 325: 1037-1043, 2004. 40. Fackler, M. J., McVeigh, M., Mehrotra, J., Blum, M. A., Lange, J., Lapides, A., Garrett, E., Argani, P., and Sukumar, S. Quantitative multiplex methylation-specific PCR assay for the detection of promoter hypermethylation in multiple genes in breast cancer. Cancer Res., 64: 4442-4452, 2004. 41. Overmeer, R. M., Henken, F. E., Bierkens, M., Wilting, S. M., Timmerman, I., Meijer, C. J., Snijders, P. J., and Steenbergen, R. D. Repression of MAL tumour suppressor activity by promoter methylation during cervical carcinogenesis. J.Pathol., 219: 327- 336, 2009. 42. Renaud, S., Loukinov, D., Abdullaev, Z., Guilleret, I., Bosman, F. T., Lobanenkov, V., and Benhattar, J. Dual role of DNA methylation inside and outside of CTCF-binding regions in the transcriptional regulation of the telomerase hTERT gene. Nucleic Acids Res., 35: 1245-1256, 2007. 43. Oh, S., Song, Y., Yim, J., and Kim, T. K. The Wilms' tumor 1 tumor suppressor gene represses transcription of the human telomerase reverse transcriptase gene. J.Biol.Chem., 274: 37473-37478, 1999. 44. Won, J., Yim, J., and Kim, T. K. Sp1 and Sp3 recruit histone deacetylase to repress transcription of human telomerase reverse transcriptase (hTERT) promoter in normal human somatic cells. J.Biol.Chem., 277: 38230-38238, 2002. 45. Akutagawa, O., Nishi, H., Kyo, S., Terauchi, F., Yamazawa, K., Higuma, C., Inoue, M., and Isaka, K. Early growth response-1 mediates downregulation of telomerase in cervical cancer. Cancer Sci., 99: 1401-1406, 2008. 46. Licchesi, J. D., Westra, W. H., Hooker, C. M., and Herman, J. G. Promoter hypermethylation of hallmark cancer genes in atypical adenomatous hyperplasia of the lung. Clin.Cancer Res., 14: 2570-2578, 2008. 47. Liu, L., Zhang, J., Bates, S., Li, J. J., Peehl, D. M., Rhim, J. S., and Pfeifer, G. P. A methylation profile of in vitro immortalized human cell lines. Int.J.Oncol., 26: 275-285, 2005. 48. Nomoto, K., Maekawa, M., Sugano, K., Ushiama, M., Fukayama, N., Fujita, S., and Kakizoe, T. Methylation status and expression of human telomerase reverse transcriptase mRNA in relation to hypermethylation of the p16 gene in colorectal cancers as analyzed by bisulfite PCR-SSCP. Jpn.J.Clin.Oncol., 32: 3-8, 2002. 49. Comb, M. and Goodman, H. M. CpG methylation inhibits proenkephalin gene expression and binding of the transcription factor AP-2. Nucleic Acids Res., 18: 3975- 3982, 1990.

62 Chapter 2

50. Deng, W. G., Jayachandran, G., Wu, G., Xu, K., Roth, J. A., and Ji, L. Tumor-specific activation of human telomerase reverses transcriptase promoter activity by activating enhancer-binding protein-2beta in human lung cancer cells. J.Biol.Chem., 282: 26460- 26470, 2007. 51. Loukinov, D. I., Pugacheva, E., Vatolin, S., Pack, S. D., Moon, H., Chernukhin, I., Mannan, P., Larsson, E., Kanduri, C., Vostrov, A. A., Cui, H., Niemitz, E. L., Rasko, J. E., Docquier, F. M., Kistler, M., Breen, J. J., Zhuang, Z., Quitschke, W. W., Renkawitz, R., Klenova, E. M., Feinberg, A. P., Ohlsson, R., Morse, H. C., III, and Lobanenkov, V. V. BORIS, a novel male germ-line-specific protein associated with epigenetic reprogramming events, shares the same 11-zinc-finger domain with CTCF, the insulator protein involved in reading imprinting marks in the soma. Proc.Natl.Acad.Sci.U.S.A, 99: 6806-6811, 2002. 52. Lucey, B. P., Nelson-Rees, W. A., and Hutchins, G. M. Henrietta Lacks, HeLa cells, and cell culture contamination. Arch.Pathol.Lab Med., 133: 1463-1467, 2009. 53. Ducrest, A. L., Amacker, M., Mathieu, Y. D., Cuthbert, A. P., Trott, D. A., Newbold, R. F., Nabholz, M., and Lingner, J. Regulation of human telomerase activity: repression by normal chromosome 3 abolishes nuclear telomerase reverse transcriptase transcripts but does not affect c-Myc activity. Cancer Res., 61: 7594-7602, 2001. 54. Yi, X., Shay, J. W., and Wright, W. E. Quantitation of telomerase components and hTERT mRNA splicing patterns in immortal human cells. Nucleic Acids Res., 29: 4818-4825, 2001. 55. Wisman, G. B., De Jong, S., Meersma, G. J., Helder, M. N., Hollema, H., De Vries, E. G., Keith, W. N., and Van der Zee, A. G. Telomerase in (pre)neoplastic cervical disease. Hum.Pathol., 31: 1304-1312, 2000. 56. Widschwendter, A., Muller, H. M., Hubalek, M. M., Wiedemair, A., Fiegl, H., Goebel, G., Mueller-Holzner, E., Marth, C., and Widschwendter, M. Methylation status and expression of human telomerase reverse transcriptase in ovarian and cervical cancer. Gynecol.Oncol., 93: 407-416, 2004. 57. Cheung, A. N., Chiu, P. M., Tsun, K. L., Khoo, U. S., Leung, B. S., and Ngan, H. Y. Chromosome in situ hybridisation, Ki-67, and telomerase immunocytochemistry in liquid based cervical cytology. J.Clin.Pathol., 57: 721-727, 2004. 58. Ngan, H. Y., Cheung, A. N., Liu, S. S., Liu, K. L., and Tsao, S. W. Telomerase assay and HPV 16/18 typing as adjunct to conventional cytological cervical cancer screening. Tumour.Biol., 23: 87-92, 2002. 59. Reesink-Peters, N., Helder, M. N., Wisman, G. B., Knol, A. J., Koopmans, S., Boezen, H. M., Schuuring, E., Hollema, H., De Vries, E. G., De Jong, S., and Van der Zee, A. G. Detection of telomerase, its components, and human papillomavirus in cervical scrapings as a tool for triage in women with cervical dysplasia. J.Clin.Pathol., 56: 31- 35, 2003. 60. Wisman, G. B., Hollema, H., De Jong, S., ter Schegget, J., Tjong, A. H. S., Ruiters, M. H., Krans, M., De Vries, E. G., and Van der Zee, A. G. Telomerase activity as a biomarker for (pre)neoplastic cervical disease in scrapings and frozen sections from patients with abnormal cervical smear. J.Clin.Oncol., 16: 2238-2245, 1998.

63 hTERT methylation during HPV-mediated transformation

64 Chapter 3

Alterations in AP-1 and AP-1 regulatory genes during HPV-induced carcinogenesis

Jillian de Wilde Johanna De-Castro Arce Peter J.F. Snijders Chris J.L.M. Meijer Frank Rösl Renske D.M. Steenbergen

Cellular Oncology (2008); 30(1), p77-87 AP-1 alterations during HPV-mediated transformation

Abstract Previous studies demonstrated a functional involvement of the AP-1 transcription factor in HPV-induced cervical carcinogenesis. Here, we aimed to obtain further insight in expression alterations of AP-1 family members during HPV-mediated transformation and their relationship to potential regulatory (Notch1, Net) and target (CADM1) genes. mRNA expression levels of c-Jun, JunB, junD, c-Fos, FosB, Fra-1, Fra-2, Notch1, Net and CADM1 were determined by quantitative RT-PCR in primary keratinocytes (n=5), early (n=4) and late (n=4) passages of non-tumorigenic HPV-immortalized keratinocytes and in tumorigenic cervical cancer cell lines (n=7). In a subset of cell lines protein expression and AP-1 complex composition was determined. Starting in immortal stages c-Fos, Fra-2 and JunB expression became up regulated towards tumorigenicity, whereas Fra-1, c-Jun, Notch1, Net and CADM1 became down regulated. The onset of deregulated expression varied amongst the AP-1 members and was not directly related to altered Notch1, Net or CADM1 expression. Nevertheless, a shift in AP-1 complex composition from Fra-1/c-Jun to c-Fos/c-Jun heterodimers was only observed in tumorigenic cells. In conclusion HPV-mediated transformation is associated with altered AP-1, Notch1, Net and CADM1 transcription. Whereas the onset of deregulated expression of various AP-1 family members became already manifest during the immortal state, a shift in AP-1 complex composition appeared a rather late event associated with tumorigenicity.

Key words: cervical cancer, HPV, AP-1, Fra-1, c-Fos, Net, Notch1, CADM1

66 Chapter 3

Introduction Cervical carcinogenesis is initiated by infection with high-risk human papillomavirus (hrHPV) types, in particular HPV types 16 and 18 1,2. However, infection with hrHPV alone is not sufficient for the progression to cervical cancer. In fact, in vitro studies have shown that HPV-induced carcinogenesis is characterized by consecutive stages of transformation reflected by altered phenotypes such as immortalization, anchorage independent growth and tumorigenicity, which necessitate (epi)genetic alterations within the host cell genome 3,4. Somatic cell fusion studies have shown that progression through each of above mentioned stages is particularly dependent on recessive processes, indicating that deficiencies in tumor suppressor gene activity are key events 3. As an example, fusion of tumorigenic cervical carcinoma cells with normal fibroblasts led to a reversion to a non-tumorigenic phenotype 5. In order to define the chromosomes involved, microcell mediated chromosome transfer studies have been performed on HPV transformed cells representing various phenotypes 6-8 It appeared that human chromosome 11 reduced cell growth in soft agar and/or tumorigenicity of cervical carcinoma cell lines SiHa and HeLa without affecting the immortal phenotype 9-11. Allelotyping studies on cervical carcinomas have identified a high frequency of loss of heterozygosity (LOH) at two loci on chromosome 11, i.e. 11q13 12,13 and 11q22-23 14-17. In recent studies we found that the tumor suppressor gene Tumor Suppressor in Lung Cancer 1 (TSLC1), recently renamed as CADM1 (cell adhesion molecule 1), which is localized at 11q23.2, is functionally involved in HPV-induced transformation. We showed that restoration of CADM1 expression in SiHa cells resulted in a suppression of anchorage independent growth and tumorigenicity 11. However, given previous cell fusion experiments it is unlikely that CADM1 silencing alone is sufficient to drive the progression from an immortal to a tumorigenic phenotype. One other gene that might be involved in this process encodes a member of the Fos gene family, Fos Related Antigen 1 (Fra-1), which is located on chromosome 11q13. In addition to Fra-1, the Fos gene family consists of c-Fos, FosB, and Fra-2. These Fos family members encode proteins that form heterodimers with proteins encoded by the Jun family (c-Jun, JunB or JunD), resulting in a so-called AP-1 transcription factor 18. This complex is involved in the positive and/or negative regulation of several different genes, including CADM1, depending on its composition 18. Various studies have shown that changes in AP-1 complex composition are involved in transcriptional regulation of HPV during cervical carcinogenesis 19-

67 AP-1 alterations during HPV-mediated transformation

22. Additionally, alterations in AP-1 complex composition have been associated with the tumorigenic phenotype of the cervical carcinoma cell line HeLa that displayed high c-Fos expression, while Fra-1 expression was almost undetectable 22. Whereas in HeLa cells and tumorigenic segregants of HeLa- fibroblast hybrids (CGL3 cells) the AP-1 complex consisted of c-Fos/c-Jun heterodimers, non-tumorigenic HeLa-fibroblast hybrids (444 cells) displayed Fra-1/c-Jun heterodimers 23,24. A functional involvement of AP-1 in tumorigenicity of cervical cancer cells is supported by the finding that ectopic expression of c-Fos in 444 cells resulted in a tumorigenic phenotype, which was accompanied with changes in AP-1 composition 23. An up regulation of c-Fos and down regulation of Fra-1 was also shown in other tumorigenic cervical cancer cell lines such as SiHa and SW756, as well as in cervical carcinomas 24,25. Recently, increased c-Fos expression in cervical carcinoma cell lines SiHa, HeLa and SW756 was shown to result from the loss of expression of the TCF transcription factor Net 26. In addition, down regulation of Fra-1 in tumorigenic cervical carcinoma cells has been suggested to result from deregulated Notch1 expression 27,28. All the above described findings suggest that both CADM1 silencing and an altered composition of the AP-1 complex represent key events in the progression from an immortal to a tumorigenic phenotype, the latter representing the in vitro counterpart of tumor invasion in vivo. However, present data on alterations in AP-1 complex composition during HPV-induced carcinogenesis are mainly derived from primary human cells, a limited number of cervical carcinoma cell lines and somatic cell hybrids of carcinoma cells and fibroblasts. At present neither it is known at what stage and in which order during HPV-induced carcinogenesis these changes occur nor how they relate to CADM1 silencing. We have previously transfected primary human keratinocytes with full-length HPV types 16 and 18, resulting in the establishment of four immortal keratinocyte cell lines, i.e. FK16A and FK16B containing HPV16, and FK18A and FK18B containing HPV18 29. These cell lines resemble high-grade cervical precursor lesions in organotypic cultures 30 and their genetic profiles closely overlap with those found in cervical (pre)malignant lesions 29,31. Consequently, these cell lines represent a good model system for cervical carcinogenesis, allowing a longitudinal analysis of alterations involved in HPV-mediated transformation. In this study we used this model to investigate when and in what order expression of AP-1 complex encoding and regulatory genes may

68 Chapter 3 change during transformation, and how these expression changes relate to CADM1 silencing.

Materials and methods Cell lines and cell culture Primary human keratinocytes were isolated from foreskins of 6 donors as described before 29. The establishment of the HPV 16 and HPV 18 immortalized cell lines (FK16A, FK16B, FK18A and FK18B) has been described previously 29. The cervical carcinoma cell lines SiHa, HeLa and CaSki, were obtained from the American Type Culture Collection (Manassas, VA, USA). HeLa hybrids 444 and CGL3 were kindly provided by Prof. Dr. E.J. Stanbridge (University of Irvine, Irvine, CA, USA). The cervical carcinoma cell lines 778, 808 (both containing HPV18), 866, and 879 (both containing HPV16) were kindly provided by Prof. Dr. P.L. Stern (Paterson Institute for Cancer Research. Manchester, UK). All cells and cell lines were cultured as described previously 11,26,29,32.

RNA isolation and Real-time RT-PCR RNA was isolated using either the RNeasy kit (Qiagen, Hilden, Germany) or RNA Bee (Tel-Test Inc., Friendswood, Texas, USA) according to the manufacturer’s manual. To exclude amplification of residual DNA, RNA isolates were treated with RQ1 DNAse (Promega, Leiden, The Netherlands) according to the manufacturer’s directions. Real-time RT-PCR for CADM1 was performed on the LightCycler (Roche Diagnostics, Woerden, The Netherlands) as described previously 11. To correct for differences in RNA quality and input, we performed RT-PCR for housekeeping gene porphobilinogen deaminase (PBGD) as described before 33. For real-time RT-PCR of the remaining genes cDNA was prepared using an oligodT primer (Invitrogen, Breda, The Netherlands) and AMV Reverse Transcriptase (Promega). Quantitative PCR for c-Fos, Fra-1, Fra-2, c-Jun, JunB, Notch1, Net and the house keeping gene snRNP was performed on the ABI/Prism 7700 Sequence Detector System (Taqman-PCR; Perkin Elmer/Applied Biosytems, Warrington, United Kingdom). All the primers and probes were selected using Primer Express 2.0 (Applied Biosystems, Warrington, United Kingdom) or taken from the RT-primer database of the University of Gent in Belgium (http://medgen.ugent.be/rtprimerdb). The following primers were used: c-Fos 5’ AAA AGG AGA ATC CGA AGG GAA

69 AP-1 alterations during HPV-mediated transformation

A 3’ and 5’ GTC TGT CTC CGC TTG GAG TGT AT 3’, FosB 5’ TCC AGG CGG AGA CAG ATC A 3’ and 5’ ACT CCA GAC GTT CCT TCT CCT TT 3’, Fra-1 5’ CAG CTC ATC GCA AGA GTA GCA 3’ and 5’ CAA AGC GAG GAG GGT TGG A 3’, Fra-2 5’ TAG ATA TGC CTG GCT CAG GCA G 3’ and 5’ GGT TGG ACA TGG AGG TGA TCA C 3’, c-Jun 5’ TCG ACA TGG AGT CCC AGG A 3’ and 5’ GGC GAT TCT CTC CAG CTT CC 3’, JunB 5’ TGG TGG CCT CTC TCT ACA CGA 3’ and 5’ GGG TCG GCC AGG TTG AC 3’, JunD 5’ CCC CTC CCC TTT TTT TGT TCT GT 3’ and 5’ CCG GGC GAA CCA AGG AT 3’, Notch1 5’ TGA CGA CGT TGC CGG GTA CA 3’ and 5’ ACC ACC TCA CAC GTG GCA C 3’, Net 5’ GCC CGG GTC CTC CTA GAA A 3’ and 5’ GAT TGC ACT CTC CAT ACC CAG ATG 3’ and snRNP 5’ TCC TCA CCA ACC TGC CAG A 3’ and 5’ TGA AGC CAG GGA ACT GAT TGA 3’. Primers for CADM1, PBGD, c-Fos, FosB, Fra-2, Notch1 and snRNP were all intron flanking. No intron flanking primers could however be selected for Jun family members, all of which lack intron sequences, and Fra-1. For all targets potential amplification of residual DNA was controlled for by both treatment of RNA isolates with RQ1 DNAse and inclusion of cDNA reactions without the addition of reverse transcriptase. These latter control reactions were always negative. All reaction mixtures contained 12.5 μl 2x Sybr Green master mix (Perkin Elmer/Applied Biosytems), primers at 0.5 μM and cDNA prepared from 30 ng RNA in a total volume of 25 μl. The following reaction conditions were used : 95°C for 10 minutes and 40 cycles of 95°C for 15 seconds and 60°C for 1 minute. In each amplification round a dilution series of RNA derived from primary keratinocytes ranging from 12.5 pg to 1.25 pg was included to generate a standard curve. For each sample the Ct was determined, i.e. the cycle number at which the amount of amplified target crossed a fixed threshold. The amount of mRNA of a specific gene in each sample was intrapolated from the standard curve using the Ct value. The relative expression of a gene of interest was calculated by dividing the amount of mRNA of that specific gene by the amount of snRNP U1A mRNA. Relative expression levels in primary keratinocytes were set to 100% by the following formula: (GENE/snRNP) HPV containing cells/(GENE/snRNP) primary keratinocytes x 100%. Each run contained two reactions per specimen per gene. Mean expression values were used for

70 Chapter 3 calculations. Additionally, we confirmed reproducibility by performing additional runs for each gene of interest on a subset of the specimens.

Nuclear extracts and Western blot analysis Nuclear extracts for Western blot analysis and EMSA were prepared as described previously 34. Protein concentration was determined by the Bradford method using bovine serum albumin as a standard. Nuclear extracts were separated on a 10% SDS-polyacrylamide gel, and electrotransferred to polyvinylidene difluoride membranes (Immobilon-P, Millipore, Bedford, MA, USA) and probed with the following antibodies: c-Fos (06-341, Upstate Biotechnology, Charlottesville, VA, USA), Fra-1 (sc-605 X, Santa Cruz Biotechnology, Santa Cruz, CA, USA), and polyclonal Net antisera number 2005 35. Bands were visualized with horseradish peroxidase-conjugated anti- Rabbit IgG or anti-mouse IgG using the ECL+ detection system (PerkinElmer Life Sciences Inc., Wellesly, MA, USA)

Electrophoretic mobility shift assays (EMSAs) AP-1 consensus oligonucleotide 5’-CGCTTGATGACTCAGCCGGAA-3’ 36 was generated in an Applied Biosystems synthesizer using phosphoramitide chemistry and further purified by HPLC. The annealed oligonucleotide was labelled with 32P-γ-ATP (Amersham, 3000 Ci/mmol) with T4 polynucleotidokinase and purified from a 15% polyacrylamide gel. The binding reaction was performed as described before 37. After 30 min incubation at room temperature, 2 μg of specific antibody were added and incubated at 4°C for 1 hour. Antibodies used were: c-Jun (sc-822X), Fra-1 (sc-183X) and c-Fos (sc- 52X) all from Santa Cruz. The complexes were resolved on 5.5% non-denaturing polyacrylamide gels, by running 30 min at 280V followed by 75 min at 350V. Gels were dried and exposed to x-ray films.

Results Altered expression of AP-1 complex genes during HPV-mediated carcinogenesis To investigate how expression of AP-1 complex encoding genes changes during HPV-induced carcinogenesis, we analyzed their mRNA expression levels in five isolates of primary keratinocytes (EK), early and late passages of four HPV-immortalized keratinocyte cell lines (FK16A, FK16B, FK18A, FK18B), and seven cervical carcinoma cell lines. Whereas all HPV-immortalized cells

71 AP-1 alterations during HPV-mediated transformation were previously found to be non-tumorigenic, all carcinoma cell lines induce tumor formation in nude mice 11. mRNA expression of the Fos family members c-Fos, Fra-1 and Fra-2, and the Jun family members c-Jun, and JunB was analyzed by real time RT-PCR. Expression of JunD and FosB could not be analyzed, due to undetectable mRNA levels. Compared with primary keratinocytes, c-Fos mRNA levels were increased in early passages of the HPV-immortalized cells and in cervical carcinomas cell lines, but not in late passages of the HPV-immortalized cells (Figure 1A). Fra-2 mRNA levels gradually increased from primary cells to the tumorigenic cells (Figure 1B), whereas Fra-1 mRNA expression was found to gradually decrease during transformation (Figure 1C). Also for c-Jun, a gradual down regulation of mRNA expression was observed, which was though less pronounced and became apparent from the late passage HPV-immortalized cells onwards (Figure 1D). For JunB, an increase in mRNA expression is seen in both HPV- immortalized cell lines and in cervical carcinoma cell lines (Figure 1E).

Changes in Net, Notch1, and CADM1 mRNA expression during HPV-mediated transformation An up regulation of c-Fos mRNA expression in cervical carcinoma cells has been shown to result from reduced expression of Net 26. Moreover, down regulation of Fra-1 has been suggested to result from deregulated Notch1 expression 27. Since both c-Fos and Fra-1 expression changed substantially with progression towards tumorigenicity, we next investigated Net and Notch1 mRNA levels in the same RNA isolates of all cell lines. As depicted in Figure 1F Net mRNA levels were yet reduced in late passages of HPV-immortalized cells, which became even more prominent in cervical carcinoma cell lines. For Notch1, a different expression pattern was observed. In HPV-immortalized cell lines, especially at late passages, an increase of Notch1 mRNA levels was found. In cervical carcinoma cell lines, however, Notch1 mRNA levels decreased again, not only compared to HPV immortalized cell lines but also compared to primary keratinocytes (Figure 1G). For CADM1 we previously reported a strongly reduced mRNA expression in cervical carcinoma cell lines compared to early passages of HPV-immortalized cells and primary keratinocytes 11. To relate CADM1 mRNA levels to expression of AP-1 family members, we quantified CADM1 mRNA levels as well. Figure 1H shows that CADM1 mRNA levels decreased in late passages of

72 Chapter 3 the HPV-immortalized cell lines and became virtually undetectable in the cervical carcinoma cell lines.

Figure 1: Real-time RT-PCR results for c-Fos (A), Fra-2 (B), Fra-1 (C), c-Jun (D), JunB (E), Net (F), Notch1 (G), and CADM1 (H) in primary keratinocytes (EK) [N=5], early passages of HPV-immortalized cell lines [immortal early N=4], late passages of HPV-immortalized cell lines [immortal late N=4], and cervical carcinoma cell lines [tumor N=7]. For cell populations representing the different stages of transformation boxplots of the mRNA levels relative to the housekeeping gene snRNP are shown, in which the relative mRNA expression in primary keratinocytes are set to 100%. Grey boxes represent the middle 50% of the data: the 25th percentile to the 75th percentile. The white lines in these grey boxes represent the median. The whiskers represent the highest and the lowest values, asterixes represent any outlyers.

Changes in AP-1 composition are associated with tumorigenicity and not immortality To determine how altered mRNA expression levels correlated to protein levels, Western blot analysis for c-Fos and Fra-1 was performed on a subset of cell lines. Non-tumorigenic HeLa-fibroblast hybrids (444), and tumorigenic

73 AP-1 alterations during HPV-mediated transformation segregants of these 444 cells (CGL3), were included as a control 38. As shown in Figure 2A c-Fos was expressed in all cells analyzed, with increased expression seen in cervical carcinoma cell line SiHa, whereas Fra-1 protein expression was evident in both primary keratinocytes and HPV-immortalized cell lines but not in SiHa cells. These data are in line with the RT-PCR results indicating that mRNA levels and protein levels correlate well. Additionally, we detected Fra-1 expression but not c-Fos expression in 444 cells and c-Fos expression but not Fra-1 expression in CGL3 cells, which is in agreement with previous findings 24. Previous studies have demonstrated a direct correlation between changes in AP-1 composition and tumorigenicity of HeLa cells. In tumorigenic HeLa cells showing hardly any Fra-1 protein expression the AP-1 complex consisted of c-Fos/c-Jun heterodimers. In 444 cells on the other hand Fra-1 protein expression was increased and the AP-1 complex was found to contain Fra-1/c-Jun heterodimers. CGL3 cells displayed reduced Fra-1 protein expression and a reversal of the AP-1 complex into c-Fos/c-Jun heterodimers 23,24. To examine whether the observed changes in c-Fos and Fra-1 expression in our model reflected an altered composition of the AP-1 complex we performed Electrophoretic Mobility Shift Assays (EMSAs) in combination with antibodies specific for c-Jun, Fra-1 and c-Fos on primary keratinocytes, late passages of HPV immortalized cell lines, SiHa, 444, and CGL3 cells (Figure 2B). In both primary keratinocytes and HPV immortalized cell lines (upper panels), a ‘supershift’ was seen upon addition of c-Jun and Fra-1 specific antibodies, indicating that the AP-1 complex mainly exists as Fra-1/c-Jun heterodimers. Notably, although c-Fos was expressed to a certain extent as detected by Western blot in these cells (Figure 2A), no incorporation of c-Fos in the AP-1 complex could be detected by EMSA. In SiHa cells on the other hand application of c-Fos and c-Jun resulted in a ’supershift’ pointing to an AP-1 complex consisting of c-Fos/c-Jun heterodimers (lower left panel on the left) as was previously also shown for HeLa cells 24. In the lower middle and right panels it is shown that in 444 cells a ‘supershift’ was observed upon addition of c-Jun and Fra-1 specific antibodies and in CGL3 cells upon addition of c-Jun and c-Fos specific antibodies. These data indicate that the AP-1 complex consisted of Fra-1/c-Jun heterodimers in 444 cells and c-Fos/c-Jun heterodimers in CGL3 cells, as was also found previously 24.

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Figure 2: Primary keratinocytes (EK), late passages of the HPV-immortalized cell lines FK16A, FK16B, FK18A, FK18B, SiHa, 444, and CGL3 cells were harvested at confluency. (A) Western blot of nuclear extracts 15 µg/lane) using 10% SDS-PAGE gels and antibodies against Fra-1, c-Fos and actin as a loading control. Molecular masses are indicated in kDa. (B) EMSAs using 32P-labeled AP-1 consensus oligonucelotides and 2 µg of c-Jun, Fra-1 or c-Fos antibody for the ‘supershifts’. The AP-1 and retarded complexes are marked by arrows.

Discussion Previous reports have demonstrated that both alterations in the composition of AP-1 transcription factor and CADM1 gene silencing are associated with the tumorigenic phenotype of HPV-transformed cells 11,23,24. However, it was unknown at what stage during HPV-induced malignant transformation alterations in AP-1 occur and how they relate to potential AP-1 regulatory genes, such as Net and Notch1. In the present study we have shown that mRNA expression levels of the AP-1 family members c-Fos, Fra-1, Fra-2, c-Jun and JunB change at different stages during malignant transformation of primary keratinocytes by hrHPV. mRNA expression of c-Fos, Fra-2 and JunB increased during HPV-mediated transformation, whereas Fra-1 and c-Jun expression levels dropped with progression towards malignancy. The onset of the altered expression levels

75 AP-1 alterations during HPV-mediated transformation varied among the different genes. Whereas Fra-1 and JunB changed early on following immortalization, alterations in Fra-2 and c-Jun expression occurred in late immortal cells. Interestingly, a biphasic change in c-Fos expression was seen, that ultimately resulted in high c-Fos levels in cervical carcinoma cells. The cause of this phenomenon is still unclear and awaits further elucidation. Most prominent changes in the expression levels of the AP-1 complex encoding genes were observed in the tumorigenic cells and were reflected by an altered composition of the AP-1 complex. Whereas in primary cells and HPV- immortalized cells c-Jun/Fra-1 heterodimers were found, in tumorigenic cells heterodimers consist primarily of a c-Jun/c-Fos composition. Our findings support the data from previous studies describing an inverse correlation between Fra-1 and c-Fos expression in cervical carcinoma cells resulting in an AP-1 complex consisting of c-Jun/ Fra-1 heterodimers in non- tumorigenic hybrid cells and a shift to c-Jun/ c-Fos heterodimers in tumorigenic segregants 24,26. Interestingly we did observe elevated c-Fos levels in a subset of the non-tumorigenic HPV-immortalized cells, indicating that the presence of c- Fos does not necessarily result in the formation of c-Jun/c-Fos heterodimers, as has also been demonstrated before by Rösl et al. 22. Decreased Fra-1 mRNA levels on the other hand were exclusively found in the tumorigenic cells, indicating that composition of the AP-1 complex is more likely to be dependent on Fra-1 expression levels, rather than on c-Fos expression levels. Using RNA interference mediated knockdown of Fra-1 expression in the immortal cells it would be interesting to determine whether changes in Fra-1 expression are indeed sufficient for a shift in AP-1 complex composition from Fra-1/ c-Jun to c-Fos/ c-Jun heterodimers and an induction of tumorigenicity. We showed that an inverse correlation between c-Fos and Net expression was restricted to tumorigenic cells, as demonstrated previously in tumorigenic versus non-tumorigenic HeLa-hybrids 26. The present finding that a down regulation of Net was yet evident in late immortal cells, can be explained by the fact that Net can act both as a repressor and as an activator of c-Fos transcription depending on its phosphorylation status. Phosphorylated Net activates c-Fos transcription and unphosphorylated Net represses c-Fos transcription 39. Further studies will reveal whether the phosphorylation status of Net differs between late passage immortal cells and carcinoma cells.mRNA levels of Notch1, a potential regulator of Fra-1 expression 27, were found to only partially correlate with Fra- 1 mRNA levels, suggesting other regulators to be involved as well. Moreover, the finding that a peak in Notch1 mRNA expression was seen in late passages

76 Chapter 3 of HPV-immortalized cells, which dropped again in cervical carcinoma cell lines, may in part explain the discrepancies between studies describing Notch1 having transforming capacity 40,41 and acting as a tumor suppressor gene 27,28. The report by Weijzen et al. 41 showing oncogenic activities of Notch1 concerned CaSki cells. In the present study the AP-1 and Notch1 expression levels in CaSki were found to be opposite to all other cervical carcinoma cell lines analyzed, i.e. elevated Fra-1, reduced c-Fos and elevated Notch1 mRNA levels. In a second study involving other carcinoma cell lines Notch1 over expression inhibited proliferation, suggestive of Notch1 having tumor suppressive activities in late stages of transformation 40. This latter finding matches with the observed down regulation of Notch1 in all carcinoma cell lines, except from CaSki in the present study. On the other hand, the up regulation of Notch1 in the HPV immortalized cell lines suggests that Notch1 may be involved in early stages of cellular transformation, as was also demonstrated by Lathion et al., showing that low expression of Notch1 in primary keratinocytes induced transformation 40. Finally, we aimed to relate changes in CADM1 mRNA levels to changes in AP-1 dimer composition. Similar to the alterations in AP-1 family members and regulators, particularly c-Jun, Fra-2 and Net and to a lesser extent Fra-1, CADM1 down regulation became apparent in late passage immortal cells and was further decreased in the cervical carcinoma cell lines. A possible interconnection is supported by a recent publication in which CADM1 has been identified as a target of the AP-1 transcriptional complex 42. Our recent studies have shown that promoter methylation also contributes to CADM1 silencing in cervical cancer cells 11. It will be of interest to determine whether and how an altered AP-1 complex composition affects CADM1 transcription in HPV transformed cells and how this is related to promoter methylation at the different stages of transformation. Since CADM1 has not only been shown to suppress tumorigenicity but also anchorage independent growth this also raises the question whether an altered AP-1 complex composition also affects anchorage independent growth. With respect to the latter it is of note that the viral protein E2 has recently been demonstrated to regulate MMP-9 expression, a well known regulator of tumor invasion, via an induction of AP-1 activity 43. Moreover, next to E2 also HPV16 E6 has been demonstrated to modulate AP-1 activity 44. Consequently, it will be interesting to examine whether the shift in AP-1 composition as observed in tumorigenic cells is related to altered expression levels of the viral proteins.

77 AP-1 alterations during HPV-mediated transformation

Up until now AP-1 complex proteins have primarily been studied in cervical carcinoma cell lines and their derivates. The present study has provided more insight in the status of these genes in immortal, not yet tumorigenic cells, which have previously been demonstrated to closely resemble premalignant cervical lesions 30. We showed that for a subset of AP-1 members as well as for Net and Notch1 the onset of deregulated expression AP-1 expression occurred in these immortal cells. These cells therefore provide a valuable tool for further functional studies to elucidate the mechanism underlying the altered expression regulation of AP-1 during HPV-mediated transformation. In conclusion, we demonstrated that HPV-mediated transformation is associated with altered AP-1 transcription. Whereas the onset of deregulated expression varied amongst the AP-1 members, a shift in AP-1 complex composition was restricted to tumorigenic cells.

Acknowledgments We thank Prof. Dr. Eric Stanbridge (Department of Microbiology and Molecular Genetics, University of Irvine, Irvine, CA, USA) for the hybrid cell lines. Prof. Dr. P.L. Stern (Paterson Institute for Cancer Research. Manchester, UK) is highly acknowledged for the cervical carcinoma cell line.

References

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10. Saxon, P. J., Srivatsan, E. S., and Stanbridge, E. J. Introduction of human chromosome 11 via microcell transfer controls tumorigenic expression of HeLa cells. EMBO J., 5: 3461-3466, 1986. 11. Steenbergen, R. D., Kramer, D., Braakhuis, B. J., Stern, P. L., Verheijen, R. H., Meijer, C. J., and Snijders, P. J. TSLC1 gene silencing in cervical cancer cell lines and cervical neoplasia. J.Natl.Cancer Inst., 96: 294-305, 2004. 12. Jesudasan, R. A., Rahman, R. A., Chandrashekharappa, S., Evans, G. A., and Srivatsan, E. S. Deletion and translocation of chromosome 11q13 sequences in cervical carcinoma cell lines. Am.J.Hum.Genet., 56: 705-715, 1995. 13. Srivatsan, E. S., Misra, B. C., Venugopalan, M., and Wilczynski, S. P. Loss of heterozygosity for alleles on chromosome II in cervical carcinoma. Am.J.Hum.Genet., 49: 868-877, 1991. 14. Bethwaite, P. B., Koreth, J., Herrington, C. S., and McGee, J. O. Loss of heterozygosity occurs at the D11S29 locus on chromosome 11q23 in invasive cervical carcinoma. Br.J.Cancer, 71: 814-818, 1995. 15. Hampton, G. M., Penny, L. A., Baergen, R. N., Larson, A., Brewer, C., Liao, S., Busby-Earle, R. M., Williams, A. W., Steel, C. M., Bird, C. C., and . Loss of heterozygosity in cervical carcinoma: subchromosomal localization of a putative tumor-suppressor gene to chromosome 11q22-q24. Proc.Natl.Acad.Sci.U.S.A, 91: 6953-6957, 1994. 16. Mugica-Van Herckenrode, C., Rodriguez, J. A., Iriarte-Campo, V., Carracedo, A., and Barros, F. Definition of a region of loss of heterozygosity at chromosome 11q in cervical carcinoma. Diagn.Mol.Pathol., 8: 92-96, 1999. 17. O'sullivan, M. J., Rader, J. S., Gerhard, D. S., Li, Y., Trinkaus, K. M., Gersell, D. J., and Huettner, P. C. Loss of heterozygosity at 11q23.3 in vasculoinvasive and metastatic squamous cell carcinoma of the cervix. Hum.Pathol., 32: 475-478, 2001. 18. Eferl, R. and Wagner, E. F. AP-1: a double-edged sword in tumorigenesis. Nat.Rev.Cancer, 3: 859- 868, 2003. 19. Butz, K. and Hoppe-Seyler, F. Transcriptional control of human papillomavirus (HPV) oncogene expression: composition of the HPV type 18 upstream regulatory region. J.Virol., 67: 6476-6486, 1993. 20. Kyo, S., Tam, A., and Laimins, L. A. Transcriptional activity of human papillomavirus type 31b enhancer is regulated through synergistic interaction of AP1 with two novel cellular factors. Virology, 211: 184-197, 1995. 21. Kyo, S., Klumpp, D. J., Inoue, M., Kanaya, T., and Laimins, L. A. Expression of AP1 during cellular differentiation determines human papillomavirus E6/E7 expression in stratified epithelial cells. J.Gen.Virol., 78 ( Pt 2): 401-411, 1997. 22. Rosl, F., Das, B. C., Lengert, M., Geletneky, K., and zur, H. H. Antioxidant-induced changes of the AP-1 transcription complex are paralleled by a selective suppression of human papillomavirus transcription. J.Virol., 71: 362-370, 1997. 23. Soto, U., Das, B. C., Lengert, M., Finzer, P., zur, H. H., and Rosl, F. Conversion of HPV 18 positive non-tumorigenic HeLa-fibroblast hybrids to invasive growth involves loss of TNF-alpha mediated repression of viral transcription and modification of the AP-1 transcription complex. Oncogene, 18: 3187-3198, 1999. 24. Soto, U., Denk, C., Finzer, P., Hutter, K. J., zur, H. H., and Rosl, F. Genetic complementation to non- tumorigenicity in cervical-carcinoma cells correlates with alterations in AP-1 composition. Int.J.Cancer, 86: 811-817, 2000. 25. Prusty, B. K. and Das, B. C. Constitutive activation of transcription factor AP-1 in cervical cancer and suppression of human papillomavirus (HPV) transcription and AP-1 activity in HeLa cells by curcumin. Int.J.Cancer, 113: 951-960, 2005. 26. van Riggelen, J., Buchwalter, G., Soto, U., De Castro, A. J., Hausen, H. Z., Wasylyk, B., and Rosl, F. Loss of net as repressor leads to constitutive increased c-fos transcription in cervical cancer cells. J.Biol.Chem., 280: 3286-3294, 2005. 27. Talora, C., Sgroi, D. C., Crum, C. P., and Dotto, G. P. Specific down-modulation of Notch1 signaling in cervical cancer cells is required for sustained HPV-E6/E7 expression and late steps of malignant transformation. Genes Dev., 16: 2252-2263, 2002. 28. Talora, C., Cialfi, S., Segatto, O., Morrone, S., Kim, C. J., Frati, L., Paolo, D. G., Gulino, A., and Screpanti, I. Constitutively active Notch1 induces growth arrest of HPV-positive cervical cancer cells via separate signaling pathways. Exp.Cell Res., 305: 343-354, 2005. 29. Steenbergen, R. D., Walboomers, J. M., Meijer, C. J., van der Raaij-Helmer EM, Parker, J. N., Chow, L. T., Broker, T. R., and Snijders, P. J. Transition of human papillomavirus type 16 and 18 transfected human foreskin keratinocytes towards immortality: activation of telomerase and allele losses at 3p, 10p, 11q and/or 18q. Oncogene, 13: 1249-1257, 1996. 30. Steenbergen, R. D., Parker, J. N., Isern, S., Snijders, P. J., Walboomers, J. M., Meijer, C. J., Broker, T. R., and Chow, L. T. Viral E6-E7 transcription in the basal layer of organotypic cultures without

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apparent p21cip1 protein precedes immortalization of human papillomavirus type 16- and 18- transfected human keratinocytes. J.Virol., 72: 749-757, 1998. 31. Wilting, S. M., Snijders, P. J., Meijer, G. A., Ylstra, B., van den Ijssel, P. R., Snijders, A. M., Albertson, D. G., Coffa, J., Schouten, J. P., van de Wiel, M. A., Meijer, C. J., and Steenbergen, R. D. Increased gene copy numbers at chromosome 20q are frequent in both squamous cell carcinomas and adenocarcinomas of the cervix. J.Pathol., 209: 220-230, 2006. 32. Brady, C. S., Bartholomew, J. S., Burt, D. J., Duggan-Keen, M. F., Glenville, S., Telford, N., Little, A. M., Davidson, J. A., Jimenez, P., Ruiz-Cabello, F., Garrido, F., and Stern, P. L. Multiple mechanisms underlie HLA dysregulation in cervical cancer. Tissue Antigens, 55: 401-411, 2000. 33. Westerman, B. A., Neijenhuis, S., Poutsma, A., Steenbergen, R. D., Breuer, R. H., Egging, M., van Wijk, I. J., and Oudejans, C. B. Quantitative reverse transcription-polymerase chain reaction measurement of HASH1 (ASCL1), a marker for small cell lung carcinomas with neuroendocrine features. Clin.Cancer Res., 8: 1082-1086, 2002. 34. Bachmann, A., Hanke, B., Zawatzky, R., Soto, U., van Riggelen, J., zur, H. H., and Rosl, F. Disturbance of tumor necrosis factor alpha-mediated beta interferon signaling in cervical carcinoma cells. J.Virol., 76: 280-291, 2002. 35. Giovane, A., Sobieszczuk, P., Ayadi, A., Maira, S. M., and Wasylyk, B. Net-b, a Ras-insensitive factor that forms ternary complexes with serum response factor on the serum response element of the fos promoter. Mol.Cell Biol., 17: 5667-5678, 1997. 36. Lee, W., Mitchell, P., and Tjian, R. Purified transcription factor AP-1 interacts with TPA-inducible enhancer elements. Cell, 49: 741-752, 1987. 37. De-Castro Arce, J., Soto, U., van Riggelen, J., Schwarz, E., Hausen, H. Z., and Rosl, F. Ectopic expression of nonliganded retinoic acid receptor beta abrogates AP-1 activity by selective degradation of c-Jun in cervical carcinoma cells. J.Biol.Chem., 279: 45408-45416, 2004. 38. Stanbridge, E. J. Genetic analysis of tumorigenicity in human cell hybrids. Cancer Surv., 3: 335-350, 1984. 39. Buchwalter, G., Gross, C., and Wasylyk, B. Ets ternary complex transcription factors. Gene, 324: 1- 14, 2004. 40. Lathion, S., Schaper, J., Beard, P., and Raj, K. Notch1 can contribute to viral-induced transformation of primary human keratinocytes. Cancer Res., 63: 8687-8694, 2003. 41. Weijzen, S., Zlobin, A., Braid, M., Miele, L., and Kast, W. M. HPV16 E6 and E7 oncoproteins regulate Notch-1 expression and cooperate to induce transformation. J.Cell Physiol, 194: 356-362, 2003. 42. Bahassi, e. M., Karyala, S., Tomlinson, C. R., Sartor, M. A., Medvedovic, M., and Hennigan, R. F. Critical regulation of genes for tumor cell migration by AP-1. Clin.Exp.Metastasis, 21: 293-304, 2004. 43. Behren, A., Simon, C., Schwab, R. M., Loetzsch, E., Brodbeck, S., Huber, E., Stubenrauch, F., Zenner, H. P., and Iftner, T. Papillomavirus E2 protein induces expression of the matrix metalloproteinase-9 via the extracellular signal-regulated kinase/activator protein-1 signaling pathway. Cancer Res., 65: 11613-11621, 2005. 44. Nees, M., Geoghegan, J. M., Hyman, T., Frank, S., Miller, L., and Woodworth, C. D. Papillomavirus type 16 oncogenes downregulate expression of interferon-responsive genes and upregulate proliferation-associated and NF-kappaB-responsive genes in cervical keratinocytes. J.Virol., 75: 4283-4296, 2001.

80 Chapter 4

Gene expression profiling to identify markers associated with deregulated hTERT in HPV-transformed keratinocytes and cervical cancer

Jillian de Wilde Saskia M. Wilting Chris J.L.M. Meijer Mark A. v.d. Wiel Bauke Ylstra Peter J.F. Snijders Renske D.M. Steenbergen

International Journal of Cancer (2008); 122(4). p877-88.

Surrogate markers for hTERT deregulation

Abstract Although high-risk human papillomavirus (HPV) infection plays a major role in the development of cervical cancer, additive oncogenic events are involved as well. One key event involves increased activity of telomerase resulting from a deregulated expression of its catalytic subunit hTERT. Our previous microcell- mediated chromosome transfer studies revealed that introduction of human chromosome 6 in the HPV16 immortalized keratinocyte cell line FK16A and in the HPV16 containing cervical cancer cell line SiHa induced growth arrest, resulting from a repression of hTERT mRNA expression and telomerase activity. Here, this model was used to analyze expression profiles associated with hTERT deregulation in HPV transformed cells. Microarray expression analysis of 12 FK16A/chromosome 6 hybrids, four of which were negative for endogenous hTERT and 8 of which were positive for endogenous hTERT, resulted in the identification of 164 differentially expressed genes. Differential expression of a selection of 5 genes was verified by real-time RT-PCR. Of these 164 genes, 32 were also differentially expressed in other HPV transformed cells with deregulated hTERT. For 2 of these genes, encoding AQP3 and MGP, altered expression in hTERT positive cervical carcinomas was confirmed by real-time RT-PCR and immunohistochemistry, respectively. Moreover, increased MGP protein expression was significantly more frequent in high- grade cervical premalignant lesions with elevated hTERT mRNA expression compared with those without. In summary, we identified 32 candidate biomarkers for deregulated hTERT mRNA expression which may enable the identification of cervical premalignant lesions that are at highest risk to progress to invasive cancer.

Keywords: HPV, hTERT, telomerase, cervical carcinogenesis, microarray expression analysis

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Introduction The main risk factor for the development of cervical cancer is infection with high-risk human papillomavirus (hrHPV) 1, which is supported by the detection of hrHPV in virtually all cervical carcinomas 2. Cervical cancer evolves from pre-existing noninvasive premalignant lesions referred to as cervical intraepithelial neoplasias (CINs), graded CIN1 to CIN3. Progression of an hrHPV infected CIN lesion to invasive cancer is a result of further specific (epi)genetic alterations within the host cell genome 3,4. One of the consequences that is crucial for tumor development is an increased activity of telomerase 5,6. Telomerase is a ribonucleoprotein that can elongate the chromosomal ends or telomeres, thereby compensating for telomere shortening that is inherent to DNA replication7. Whereas most cancer cells display elevated telomerase activity and stabilized telomeres, resulting in an unlimited lifespan, most primary somatic cells exhibit absence of detectable telomerase activity and continuous telomere erosion during cell division. The latter ultimately leads to the induction of senescence 7. Telomerase consists of several subunits, including a structural RNA component (hTR) that serves as a template during telomere elongation 8 and a catalytic subunit (hTERT) that has reverse transcriptase activity9. Increased activity of telomerase in tumor cells invariably results from deregulated hTERT expression 9. Elevated hTERT mRNA levels and concomitant telomerase activity can be detected in a marked subset of CIN3 lesions and more than 90% of cervical carcinomas, whereas normal cervical tissues and low grade precursor lesions only rarely show increased hTERT levels and telomerase activity 5,10. This indicates that elevated hTERT expression and simultaneous telomerase activation is a frequent event during cervical carcinogenesis and may be a valuable marker for progressive CIN lesions. However, both telomerase activity and hTERT mRNA and protein levels in cervical scrapings only poorly reflect the status of these markers in the underlying lesions 11-14. This is likely owing to factors like sampling variability in combination with the presence of physiological telomerase activity in admixed activated lymphocytes and epithelial stem cells. Notably, telomerase activity is more than incidentally detected in normal cervical scrapings and biopsies of normal cervix 14,15. Currently available markers do not allow a distinction between deregulated and physiologically regulated hTERT expression and telomerase activity. Hence, there is a need for markers that are specific for deregulated hTERT expression.

83 Surrogate markers for hTERT deregulation

To identify such markers, in vitro models can be of value. Others and we have previously shown that in vitro immortalization of primary keratinocytes by hrHPV is associated with increased activity of telomerase 16,17. Although ectopic expression of HPV16 E6 can induce hTERT expression and telomerase activity directly 18, several studies have shown that in the context of the whole HPV genome E6 by itself does not necessarily increase hTERT expression and activate telomerase in human keratinocytes 16,19. Instead, microcell-mediated chromosome transfer studies have shown that the induction of hTERT and telomerase activity in HPV-immortalized cells and cervical cancer cells depends on a recessive event, suggesting that inactivation of yet unknown tumor suppressor genes are involved in this process as well 20,21. We have previously shown that introduction of chromosome 6 in an HPV16-immortalized keratinocyte cell line, FK16A, and in the HPV16-containing cervical cancer cell line SiHa resulted in a growth arrest after a lag period, which was associated with a strong reduction of hTERT mRNA expression, repression of telomerase activity, and telomeric attrition 22. Ectopic expression of hTERT could prevent the telomeric shortening-based growth arrest induced by chromosome 6. These data provide functional evidence for the reversal to a mortal phenotype by chromosome 6 as a consequence of interference with hTERT activity. Furthermore, we showed that elevated hTERT mRNA levels and concomitant telomerase activity in both cervical (pre)cancers and HPV16 immortalized epithelial cells were associated with an allelic imbalance at 6q14-22 23. These findings locate candidate hTERT repressive gene(s) to chromosome 6q14-22, the loss of which can apparently mediate HPV-induced immortalization and cervical carcinogenesis. Interestingly, introduction of chromosome 6 in the HPV16 immortalized cell line FK16A yielded not only a number of hybrids in which hTERT was repressed and a growth arrest was induced, but also a number of revertant FK16A-chromosome 6 hybrids in which hTERT expression was restored 22. Since these hybrids were all derived from the same parental cells, they provide a unique model system to identify markers that are associated with deregulated hTERT expression and telomerase activity. In this study we aimed to identify surrogate markers for deregulated hTERT by comparing the RNA expression profiles of FK16A hybrids displaying repression of endogenous hTERT with those of hTERT-positive FK16A revertant hybrids. This resulted in the identification of 164 differentially expressed genes, a subset of which may provide novel markers for the risk stratification of hrHPV infected women.

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Methods

This study followed the ethical guidelines of the Institutional Review Board of the VU University Medical Center.

Cell lines and cell culture Primary keratinocytes (EK2000-12 and EK2000-13) were isolated from human foreskin as described before 16. The following HPV 16-immortalized cell lines were established during previous studies 16,22: Cell line FK16A was established by transfection of primary foreskin keratinocytes with the entire HPV16 genome. Immortalization of these cells was found to be associated with an arrest of telomeric shortening and activation of telomerase 16. FK16A-hTERT was established by transduction of FK16A with a retroviral hTERT construct (LZRS-hTERT-IRES [internal ribosomal entry site]-GFP [green fluorescent protein]) 22. The endogenous hTERT negative FK16A/chromosome 6 (FK16A/#6) hybrids (clones MCF25cl2, MCF26cl4, MCF29cl3, and MCF29cl8) were established by microcell-mediated chromosome transfer of chromosome 6 into FK16A-hTERT 22. The endogenous hTERT-positive FK16A/#6 hybrids (MCF9cl6, MCF9cl6b, MCF9cl19, MCF15cl8, MCF15cl15b, MCF15cl18, MCF15cl20, and MCF15cl21) are revertant clones of FK16A/#6 hybrids 22. The cervical carcinoma cell line SiHa was obtained from the American Type Culture Collection (Manassas, VA). All cells and cell lines were cultured as described before 16,22.

Tissue specimens Formalin fixed, paraffin-embedded biopsies of normal cervix, high grade CIN lesions and cervical squamous cell carcinomas (SCCs), as well as frozen specimens of SCCs were used. CIN lesions and SCC specimens were collected at the Department of Obstetrics and Gynaecology at the VU University Medical Center (Amsterdam) during the course of routine clinical practice from women undergoing colposcopy-directed biopsy or hysterectomy. Normal cervical epithelial cells were obtained by brushing cervices from women undergoing a hysterectomy for other reasons than cervical (pre)neoplastic disease. All frozen SCC specimens contained >70% tumor cells. All SCCs and high-grade CIN (CIN2/3) lesions were hrHPV positive as determined by general primer GP5+/6+ polymerase chain reaction (PCR) 24.

85 Surrogate markers for hTERT deregulation

RNA isolation Cultured cells harvested from subconfluent cultures, series of consecutive cryosections of frozen cervical SCC specimens, and normal brushed cervical cells were homogenized in Trizol reagent (Life Technologies, Inc., Breda, The Netherlands). Total RNA was isolated according to the manufacturer’s manual. RNA quality was checked by analysis on the Bioanalyzer 2100 (Agilent Technologies, Palo Alto, CA, USA). Only RNA isolates having a 28S/18S ratio greater than 1.8 were subjected to microarray analysis.

Microarray slide preparation, probe preparation, hybridization and scanning A collection of 18,861 oligo squences representing 18,664 unique human genes (Sigma-Genosys, Zwijndrecht, The Netherlands) was spotted at a concentration of 10 μM, in 150 mM sodium phosphate (pH 8.5), on CodeLink slides (Amersham BioSciences, Roosendaal, The Netherlands), using a SpotArray Enterprise (Perkin Elmer Life Sciences, Zaventum, Belgium), and processed according to the manufacturer’s protocol. These in house printed oligo arrays have recently been described by Carvalho et al. 25, and Van den IJssel et al. 26. cDNA was prepared from 75 μg of cell line RNA and 75 μg of Universal Human Reference RNA (Stratagene, La Jolla, CA, USA). cDNA synthesis, hybridization and scanning were performed as described previously 27-29. To investigate reproducibility of the hybridizations, technical replicates were included of RNA isolated from primary keratinocytes (EK2000-12), SiHa cells and the FK16A#6 hybrid MCF15cl8. The resulting expression profiles of each of the replicates were highly comparable. These findings underline the reliability of the data obtained, as was also found in previous studies in which validation of the same micro array platform has been described 28-30.

Data analysis Spots were quantified by Imagene 5.5.4 software (Biodiscovery Ltd., Marina de Rey, CA., USA) using the default settings. Of each spot the local median background was subtracted from the median signal intensity in both Cy3 and Cy5 channels. All genes with signal intensity values below 50 in both channels were excluded from further analysis. Signal intensity values below 50 in one of the two channels were replaced by 50. Subsequently, all data were normalized using a Lowess correction. Four endogenous hTERT-negative FK16A/#6 hybrids and 8 endogenous hTERT-positive FK16A/#6 hybrids were compared by microarray ANOVA

86 Chapter 4 analysis (MAANOVA) 31. A false discovery rate (FDR) was calculated for each gene. All genes with a FDR ≤ 0.15 were considered differentially expressed. Additionally, Cy3/Cy5 ratios were calculated from the Lowess corrected values. These ratios were used to calculate a fold change for each gene for endogenous hTERT-positive versus endogenous hTERT-negative cells. The entire dataset described here is available from the Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/projects/geo/) through series accession number GSE8288.

RT-PCR for endogenous and ectopic hTERT RT-PCR primers for endogenous and exogenous hTERT were selected using Vector NTI Suite 7.1 (Invitrogen). For ectopic hTERT a sense primer (5’ AACGCAGGGATGTCGCTG 3’) was selected in the coding sequence of the hTERT mRNA and an antisense primer (5’ AGAGGGGCGAATTTACGTAGC 3’) in the LZRS-hTERT-IRES-GFP vector. For endogenous hTERT a sense primer (5’ GGCTGTGCCACCAAGCATTC 3’) was selected in the coding sequence of the hTERT mRNA and an antisense primer (5’ AGGGCTGCTGGTGTCTGCTC 3’) was selected in the noncoding sequence of the hTERT mRNA, which was not present in the retroviral vector. To assess RNA quality and input, RT-PCR for U1 small nuclear ribonucleoprotein specific A protein (snRNP U1A) was essentially performed as described previously 5. First strand cDNA synthesis was performed as described before5 on 100 ng of total RNA using antisense primers for either ectopic or endogenous hTERT and snRNP U1A in a single reaction. Subsequent PCR reactions for ectopic hTERT, endogenous hTERT and snRNP U1A were performed separately at an annealing temperature of 58°C, 65°C, and 58°C for 35, 40 and 35 cycles, respectively. PCR products were separated on a 1.5% agarose gel.

Real time RT-PCR Intron flanking PCR primers and fluorescent probes were selected using Primer Express 2.0 (Applied Biosystems, Warrington, United Kingdom) or taken from the RT-primer database of the University of Gent in Belgium (http://medgen.ugent.be/rtprimerdb). cDNA synthesis and real time PCR were performed as described before 32 with the exception that an oligo-dT20 primer (Invitrogen) was used for reverse transcription. Total RNA was reverse transcribed and the resulting cDNA was

87 Surrogate markers for hTERT deregulation used for real time PCR on the ABI/Prism 7700 Sequence Detector System (Taqman-PCR; Applied Biosytems). Real time PCR was performed for IMP1 (forward 5’ ATA ACT TTG TAG GGC GTC TCA TT 3’, reverse 5’ TCT TGC AAC GAG GAG ATG GT 3’), RGS5 (forward 5’ GGC GTG ATT CCC TGG ACA 3’, reverse 5’ ACT GAA TTC AGA CTT CAG GAA ACT TTT G 3’), WISP2 (forward 5’ TGA GAG GCA CAC CGA AGA C 3’, reverse 5’ TGG GTA CGC ACC TTT GAG A 3’), AQP3 (forward 5’ CCC ATC GTG TCC CCA CTC 3’, reverse 5’ GCC GAT CAT CAG CTG GTA CA 3’), and SEMP1 (forward 5’ GAT GAG GAT GGC TGT CAT TG 3’, reverse 5’ TAC CAT GCT GTG GCA ACT AAA 3’). In each amplification a dilution series of RNA derived from primary keratinocytes ranging from 1,250 ng to 0.125 ng was included to generate a standard curve.

For each sample the Ct was determined, i.e. the cycle number at which the amount of amplified target crossed a fixed threshold. The amount of mRNA of a specific gene in each sample was intrapolated from the standard curve using the

Ct value. To correct for differences in RNA quality and input, quantitative RT-PCR for the house keeping gene snRNP U1A (forward 5’ TCC TCA CCA ACC TGC CAG A 3’, reverse 5’ TGA AGC CAG GGA ACT GAT TGA 3’) was also performed on each cDNA. The relative expression of a gene of interest was calculated by dividing the amount of mRNA of that specific gene by the amount of snRNP U1A mRNA. Each reaction mixture contained 12.5 μl 2x Sybr Green master mix (Perkin Elmer/Applied Biosytems), primers at 0.5 μM and cDNA prepared from 30 ng RNA in a total volume of 25 μl. All PCR experiments were performed in duplicate and mean values were used for calculations. hTERT mRNA expression in CIN lesions and SCC was determined on the Lightcycler (Roche Diagnostics, Woerden, The Netherlands) using the TeloTAGGGhTERT Quantification Kit (Roche Diagnostics) according to the manufacturer’s instructions.

Immunohistochemistry Immunohistochemical staining was performed on 4 μm sections of 8 paraffin embedded telomerase positive cervical SCC, 22 high-grade CIN lesions, 13 of which showed elevated hTERT mRNA expression, and 3 histologically normal cervical specimens. Endogenous peroxidase was inactivated by incubation with

0.3% H2O2 in methanol for 30 minutes. For antigen retrieval, slides were pretreated with citrate buffer (10 mM, pH 6.0) in a microwave oven and rinsed

88 Chapter 4 with PBS. Slides were incubated with monoclonal antibody for Matrix Gla Protein (52.1C5D, dilution 1:1000, Alexis Biochemicals, Grunberg, Germany) for one hour at room temperature. For antibody detection the EnVision horseradish peroxidase system (Dako, Copenhagen, Denmark) was used. Sections were counterstained with hematoxylin. Slides were judged by two pathologists and MGP staining patterns in CIN lesions and SCCs were compared to those in normal cervical epithelial sections. Increased expression refers to a combination of both a more intense staining of epithelial cells as well as an increased proportion of epithelial cells staining positive.

Results Cell cultures and hTERT expression analysis To identify markers reflecting deregulated hTERT expression, we selected 12 previously established cell hybrids, all carrying the same genetic background, for microarray expression analysis. These hybrids were generated by the introduction of chromosome 6 in the HPV16 immortalized cell line FK16A, which resulted in a suppression of hTERT expression and telomerase activity 22. In the majority of hybrids, the so-called non-revertants, this led to a growth arrest after a delay period. In a subset of hybrids, however, telomerase was reactivated and cells resumed proliferation. The latter hybrids are referred to as revertant hybrids. From these revertants, 8 hybrids (i.e. MCF9cl6, MCF9cl6b, MCF9cl19, MCF15cl8, MCF15cl15b, MCF15cl18, MCF15cl20, and MCF15cl21, hereafter referred to as FK16A[+] hybrids) were selected for microarray expression analysis. The growth arrest that became manifest in the non-revertants did, however, hamper the isolation of sufficient RNA required for microarray analysis. Moreover, the process of growth arrest in these cells is likely to be accompanied with altered gene expression profiles specific for senescing cells that may interfere with the study outcome. To avoid this complication we made use of FK16A cells in which prior to the introduction of chromosome 6 a retroviral hTERT expression vector was introduced. Notwithstanding the fact that endogenous hTERT was repressed in these hybrids, the expression of ectopic hTERT resulted in a maintenance of their proliferative capacity. In the present study we used 4 of these hybrids (i.e. MCF25cl2, MCF26cl4, MCF29cl3, and MCF29cl8), hereafter referred to as FK16A [-] hybrids, in which endogenous hTERT expression was repressed 22.

89 Surrogate markers for hTERT deregulation

To verify presence or absence of endogenous and/or ectopic hTERT mRNA in the different cell lines, RT-PCR was performed first, using primers that can distinguish between endogenous and ectopic hTERT (Figure 1). As a control for RNA quality and input, simultaneous RT-PCR was performed for the housekeeping gene snRNP U1A, which was detectable in all cell lines. Similar to parental FK16A cells, FK16A cells transduced with hTERT (FK16A-hTERT) and cervical cancer cells (SiHa), which served as positive controls, all FK16A[+] hybrids displayed endogenous hTERT mRNA expression. No endogenous hTERT mRNA could be demonstrated in FK16A[-] hybrids and primary keratinocytes (EK), the latter serving as negative control. On the other hand, ectopic hTERT transcripts were only detected in FK16A[-] hybrids and FK16A-hTERT cells. These results confirm both the absence of endogenous hTERT mRNA and presence of ectopic hTERT mRNA in the FK16A[-] hybrids.

Figure 1: Ectopic and endogenous hTERT mRNA levels. RT-PCR for ectopic hTERT (A), endogenous hTERT (B), and snRNP U1A (C).

Identification of differentially expressed genes in FK16A[-] versus FK16A[+] The 4 FK16A[-] and 8 FK16A[+] hybrids were subsequently subjected to microarray expression analysis for 18,664 genes using in-house printed oligo arrays. Of the 18,664 genes represented on the array, 8,995 yielded sufficient signal intensities to be analyzed. Expression signatures of FK16A[-] and FK16A[+] hybrids were compared by microarray-ANOVA (MAANOVA) and further analysis was performed as summarized in Figure 2.

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After correcting for multiple testing, and by using a false discovery rate (FDR) cutoff value of ≤ 0.15, 86 and 87 genes were identified that were most significantly up- and down regulated, respectively, in the FK16A[+] hybrids (Figure 2A). Since the 60-mer oligo for hTERT spotted on the array corresponded to the 3’ untranslated region, which was not represented in the hTERT cDNA vector, we could specifically evaluate endogenous hTERT expression levels, excluding interference by ectopic hTERT in the FK16A[-] hybrids. Although the microarray data of hTERT expression did not meet the selection criteria (FDR ≤ 0.15), a 3.0 fold (range 0.8-4.6) increase (FDR=0.28) in expression of endogenous hTERT was seen in the FK16A[+] hybrids compared with the FK16A[-] hybrids, which is in line with the hTERT RT-PCR results.

Figure 2: Identification of upregulated and downregulated genes in hTERT positive cells. MAANOVA analysis of FK16A[-] vs. FK16A[+] (A). Exclusion of genes associated with ectopic hTERT expression (B). Fc = Fold change

To exclude interference by genes that are differentially expressed due to ectopic hTERT expression in the FK16A[-] hybrids, we performed expression analysis on FK16A-hTERT and parental FK16A cells as well. Amongst the genes showing altered expression in the FK16A[+] hybrids 7 and 2 showed more than 2 fold up regulation and down regulation, respectively, in FK16A compared with FK16A-hTERT (Table 1) and were excluded from further analysis (Figure 2B). The remaining 164 genes (79 upregulated and 85 downregulated) are listed

91 Surrogate markers for hTERT deregulation in Table 2 and 3. Using Expression Array Systemic Explorer (EASE) software (http://david.niaid.nih.gov/david/ease1.htm) we were able to link many of these genes to specific cellular processes such as signal transduction (25), development (20), cell proliferation (12), apoptosis (6), DNA repair (5), ossification (3) and inflammation (3). A schematic overview of these genes and corresponding cellular processes is shown in Figure 3.

Up/ Fc FK16A vs Genbank ID Gene down Chr FK16A hTERT NM_014221 Mature T-cell proliferation 1 (MTCP1) ↓ X 3.3 Helix-loop-helix protein 1R21, 5'UTR (sequence from the D28449 ↓ 1 2.5 5'cap to the start codon) AF019225 Apolipoprotein L ↑ 22 6.9 NM_006102 Plasma glutamate carboxypeptidase (PGCP) ↑ 8 5.6 AK025615 cDNA: FLJ21962 fis, clone HEP05564 ↑ 12 3.0 Solute carrier family 12 (potassium/chloride transporters), NM_006598 ↑ 5 2.9 member 7 (SLC12A7) X56196 XIST, coding sequence 'd' mRNA (locus DXS399E) ↑ X 2.5 Uncharacterized hematopoietic stem/progenitor cells protein NM_018467 ↑ 19 2.4 MDS032 (MDS032) NM_000791 Dihydrofolate reductase (DHFR) ↑ 5 2.3 Table 1: Genes differentially expressed in FK16A versus FK16A hTERT and in FK16A[+] hybrids versus FK16A[-] hybrids

Genbank ID Gene Location FDR NM_194071 cAMP responsive element binding protein 3-like (CREB3L2) 7q33 0.000 NM_001145 angiogenin, ribonuclease, RNase A family, 5 precursor (ANG) 14q11.2 0.010 insulin-like growth factor 2 mRNA binding protein (IGF2BP1) NM_006546 17q21.32 0.047 (IMP1) NM_001202 bone morphogenetic protein 4 (BMP4) 14q22.2 0.070 NM_003929 RAB7, member RAS oncogene family-like 1 (RAB7L1) 1q32.1 0.097 NM_177453 progestin and adipoQ receptor family member III (PAQR3) 4q21.21 0.100 NM_030918 sorting nexin family member 27 (SNX27) 1q21.3 0.100 NM_015150 raft-linking protein (Raftlin) 3p25.1 0.113 NM_014333 immunoglobulin superfamily, member 4 (IGSF4) 11q23.3 0.113 NM_053056 cyclin D1 (CCND1) 11q13.3 0.113 NM_013253 dickkopf (Xenopus laevis) homolog 3 (DKK3) 11p15.3 0.113 NM_001928 D component of complement (adipsin) (DF) 19p13.3 0.113 AK000958 cDNA FLJ10096 fis, clone HEMBA1002439 16q24.1 0.113 M30818 interferon-induced cellular resistance mediator protein (MxB) 21q22.3 0.117 NM_003012 secreted frizzled-related protein 1 (SFRP1) 8p11.21 0.126 AL137382 cDNA DKFZp434L1226 (from clone DKFZp434L1226) 16q24.3 0.126 NM_003617 regulator of G-protein signalling 5 (RGS5) 1q23.3 0.126 NM_001553 insulin-like growth factor binding protein 7 (IGFBP7) 4q12 0.126 NM_024944 chondrolectin precursor (CHODL) 21p21.1 0.126 AK026368 cDNA: FLJ22715 fis, clone HSI13726 1q12 0.126 NM_018195 hypothetical protein FLJ10726 (FLJ10726) 11q23.1 0.126 AF088053 full length insert cDNA clone ZD64D01 16p12.1 0.126

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NM_015150 raft-linking protein (Raftlin) 3p24.3 0.126 (Gerbich blood group) (GYPC), transcript NM_002101 2q14.3 0.128 variant 1 NM_006851 glioma pathogenesis-related protein (GLIPR1) 12q21.1 0.128 NM_001850 collagen, type VIII, alpha 1 (COL8A1) 3q12.1 0.128 NM_007283 monoglyceride lipase (MGLL) 3q21.3 0.128 NM_000483 apolipoprotein C-II (APOC2) 19q13.31 0.128 NM_006528 pathway inhibitor 2 (TFPI2) 7q21.3 0.128 NM_002430 meningioma (disrupted in balanced translocation) 1 (MN1) 22q12.1 0.128 NM_003254 tissue inhibitor of metalloproteinase 1 (TIMP1) Xp11.3 0.128 NM_015544 DKFZP564K1964 protein (DKFZP564K1964) 17q11.2 0.128 NM_006404 protein C receptor, endothelial (EPCR) (PROCR) 20q11.22 0.128 insulin-like growth factor 2 mRNA binding protein (IGF2BP1) NM_006546 17q21.32 0.128 (IMP1) NM_000358 transforming growth factor, beta-induced, 68kD (TGFBI) 5q31.1 0.128 NM_000962 prostaglandin-endoperoxide synthase 1 isoform 1 (PTGS1) 9q33.2 0.128 AK025344 cDNA: FLJ21691 fis, clone COL09555 3p21.1 0.128 NM_021127 phorbol-12-myristate-13-acetate-induced protein (PMAIP1) 18q21.32 0.128 NM_005803 flotillin 1 (FLOT1) 6p21.33 0.128 NM_002240 potassium inwardly-rectifying channel J6 21q22.13 0.128 NM_016626 ring finger and KH domain containing 2 (RKHD2) 18q21.1 0.128 NM_006468 polymerase (RNA) III (DNA directed) (62kD) (RPC62) 1q21.1 0.128 AL049447 cDNA DKFZp586A0722 (from clone DKFZp586A0722) 2p23.3 0.128 AL110139 cDNA DKFZp564O1763 (from clone DKFZp564O1763) 15q26.1 0.128 NM_004467 fibrinogen-like 1 (FGL1) 8p22 0.129 NM_003881 WNT1 inducible signaling pathway protein 2 (WISP2) 20q13.12 0.133 NM_007173 serine protease 23 (PRSS23) 11q14.2 0.133 NM_003999 oncostatin M receptor (OSMR) 5p13.1 0.134 NM_000900 matrix Gla protein (MGP) 12p13.3 0.134 NM_014905 glutaminase C (GLS) 2q32.2 0.134 NM_001155 annexin A6 (ANXA6), splice variant 1 5q33 0.136 NM_022154 solute carrier family 39 (zinc transporter) (SLC39A8) 4q24 0.136 NM_025195 G-protein-coupled receptor induced protein (TRIB1) 8q24.13 0.136 NM_005909 microtubule-associated protein 1B (MAP1B) 5q13.2 0.136 NM_019079 hypothetical protein (FLJ10884) 1p31.3 0.136 NM_025227 bactericidal/permeability-increasing protein (BPIL1) 20q11.21 0.136 tumor necrosis factor receptor superfamily, member 11b NM_002546 8q24.12 0.136 (TNFRSF11B) NM_002310 leukemia inhibitory factor receptor (LIFR) 5p13.1 0.136 NM_006010 arginine-rich protein (ARP) 3p21.31 0.136 SET and MYND domain containing 3 NM_022743 1q44 0.136 (Histonmethyltranferase) (SMYD3) X97261 metallothionein isoform 1R 16q12.2 0.136 NM_014042 DKFZP564M082 protein (DKFZP564M082) 11q13.4 0.136 NM_020158 exosome component 5 (Rrp46) (EXOSC5) 19q13.2 0.136 NM_025191 ER degradation enhancer mannosidase alpha-like (EDEM3) 1q25.3 0.136 AK025365 cDNA: FLJ21712 fis, clone COL10231 20p12.3 0.136 NM_017586 chromosome 9 open reading frame 7 (C9ORF7) 9q34.2 0.136 NM_013247 HtrA-like serine protease (OMI) 2p13.1 0.136 AF086471 full length insert cDNA clone ZD88A01 11p15.1 0.136 NM_012071 BUP protein (BUP) 10p12.2 0.142

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NM_152707 solute carrier family 25, member 16 (SLC25A16) 10q21.3 0.145 NM_013286 RNA binding motif protein 15B (RBM15B) 3p21.2 0.145 NM_005625 syndecan binding protein (syntenin) (SDCBP) 8q12.1 0.145 NM_024640 ischemia/reperfusion inducible protein (YRDC) 1p34.3 0.145 NM_001622 alpha-2-HS-glycoprotein (AHSG) 3q27.3 0.147 NM_000267 neurofibromin, eurofibromatosis-related protein (NF-1) 17q11.2 0.147 NM_003536 H3 histone family, member K (H3FK) 6p22.1 0.147 potassium calcium-activated channel, subfamily M, beta NM_014505 12q15 0.147 member 4 (KCNMB4) NM_004040 ras homolog gene family, member B (RHOB) 2p24.1 0.148 NM_018413 chondroitin-4-sulfotransferase (C4ST gene) (HSA269537) 12q23.3 0.148 Table 2: Upregulated genes in FK16A[+] hybrids

Genbank ID Gene Location FDR NM_017818 WD repeat domain 8 (WDR8) 1p36.32 0.076 NM_004925 aquaporin 3 (AQP3) 9p13.3 0.076 NM_016627 archaemetzincins-2 isoform 1 (AMZ2) 17q24.2 0.100 NM_006020 alkylation repair; alkB homolog (ABH) 14q24.3 0.100 NM_016576 guanosine monophosphate reductase 2 (GMPR2) 14q11.2 0.100 NM_020196 XPA binding protein 2 (XAB2) 19p13.2 0.100 U92989 clone DT1P1E11 , CAG repeat region 17q25.1 0.100 NM_003843 sciellin (SCEL) 13q22.3 0.100 NM_001915 cytochrome b-561 isoform 1 (CYB561) 17q23.3 0.113 NM_153450 mediator of RNA polymerase II transcription (MED19) 11q12.1 0.113 NM_018442 IQ motif and WD repeats 1 (IQWD1) 1q24.2 0.113 NM_016230 NADPH cytochrome B5 oxidoreductase (NCB5OR) 6q14.2 0.113 AK023814 cDNA FLJ13752 fis, clone PLACE3000352 5q32 0.113 senescence-associated epithelial membrane protein NM_021101 3q28 0.113 (SEMP1) NM_018301 hypothetical protein FLJ11016 (FLJ11016) Xq22.3 0.126 NM_001498 glutamate-cysteine ligase, catalytic (72.8kD) (GLCLC) 6p12.1 0.126 NM_207400 FLJ39739 1q21.1 0.126 NM_004145 myosin IXB (MYO9B) 19p13.11 0.126 NM_004050 BCL2-like 2 (BCL2L2) 14q11.2 0.126 NM_005802 topoisomerase I binding, arginine/serine-rich (TOPORS) 9p21.1 0.126 NM_006402 hepatitis B virus x-interacting protein (9.6kD) (XIP) 1p13.3 0.126 melanoma-associated antigen p97 (melanotransferrin), 3' K03200 3q29 0.128 flank NM_017544 NF-kappa B repressing factor (NKRF) Xq24 0.128 NM_024857 hypothetical protein LOC79915 17q11.2 0.128 NM_016243 NAD(P)H:quinone oxidoreductase type 3 (NQO3A2) 1q32.1 0.128 NM_002394 solute carrier family 3, member 2 (SLC3A2) 11q12.3 0.128 NM_020761 Regulatory associated protein of mTOR (Raptor) 17q25.3 0.128 NM_022740 homeodomain interacting protein kinase 2 (HIPK2) 7q34 0.128 phosphoinositide-3-kinase, catalytic, beta polypeptide NM_006219 3q22.3 0.128 (PIK3CB) NM_000484 amyloid beta A4 protein precursor, isoform a (APP) 21q21.3 0.128 NM_020927 hypothetical protein LOC57687 16q23.1 0.128 Rho guanine nucleotide exchange factor (GEF) 19 NM_153213 1p36.13 0.128 (ARHGEF19)

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NM_017434 dual oxidase 1 (DUOX1) 15q21.1 0.128 AK024506 FLJ00116 protein, partial cds 14q32.33 0.128 NM_014553 transcription factor CP2-like 1 (TFCP2L1) 2q14.2 0.128 NM_138452 dehydrogenase/reductase (SDR family) member 1 (DHRS1) 14q11.2 0.134 mitogen-activated protein kinase kinase kinase kinase 5 NM_006575 14q21.3 0.134 (MAP4K5) MADS box transcription enhancer factor 2, polypeptide A NM_005587 15q26.3 0.136 (MEF2A) cytochrome P450, subfamily IIB (phenobarbital-inducible) NM_000767 19q13.2 0.136 (CYP2B) phosphoribosyl pyrophosphate synthetase-associated protein NM_002767 17p11.2 0.136 2 (PRPSAP2) AL133017 cDNA DKFZp434E0727 (from clone DKFZp434E0727) - 0.136 NM_025082 C16Orf56 16q22.1 0.136 NM_000293 phosphorylase kinase, beta (PHKB) 16q12.1 0.136 NM_018022 transmembrane protein 51 (TMEM51) 1p26.21 0.136 NM_021188 ZNF410 14q24.3 0.136 NM_194278 C14orf117 14q24.3 0.136 RAD51 (S. cerevisiae) homolog (E coli RecA homolog) NM_002875 15q15.1 0.136 (RAD51) glycine-, glutamate-, thienylcyclohexylpiperidine-binding NM_014704 1p36.32 0.136 protein (KIAA0562) NM_006700 FLN29 gene product (FLN29) 12q24.13 0.136 NM_005781 activated p21cdc42Hs kinase (ACK1) 3q29 0.136 ATP synthase, H+ transporting, mitochondrial F0 complex, NM_015684 14q21.3 0.136 subunit s (ATP5S) NM_001707 B-cell CLL/lymphoma 7b (BCL7B) 7q11.23 0.136 NM_005799 PDZ domain protein (Drosophila inaD-like) (INADL) 1p31.3 0.136 NM_005232 EPH receptor A1 (EPHA1) 7q34 0.136 NM_015888 hook homolog 1 (HOOK1) 1p32.1 0.136 NM_005547 involucrin (IVL) 1q21.3 0.136 NM_017918 hypothetical protein FLJ20647 (FLJ20647) 4q25 0.136 NM_003976 artemin (ARTN) 1p34.1 0.136 NM_001305 claudin 4 (CLDN4) 7q11.23 0.136 NM_033394 ankyrin repeat and coiled-coil containing 1 (TANC1) 2q24.2 0.137 NM_007109 transcription factor 19 (SC1) (TCF19) 6p21.33 0.138 NM_147128 zinc finger/RING finger 2 (ZNRF2) 7p15.1 0.142 protein tyrosine phosphatase, non-receptor type 18 (brain- NM_014369 2q21.1 0.142 derived) (PTPN18) NM_002272 keratin 4 (KRT4 12q13.13 0.142 NM_003686 exonuclease 1 (EXO1) 1q43 0.145 HSV-1 stimulation-related gene 1 (HSRG1), MON1 NM_014940 16q23.1 0.145 homolog B (MON1B) NM_002633 phosphoglucomutase 1 (PGM1) 1p31.3 0.147 NM_004496 forkhead box A1 (FOXA1) 14q21.1 0.147 NM_001007 ribosomal protein S4, X-linked (RPS4X) Xq13.1 0.147 NM_005068 single-minded (Drosophila) homolog 1 (SIM1) 6q16.3 0.147 NM_006925 splicing factor, arginine/serine-rich 5 (SFRS5) 14q24.2 0.147 NM_002863 phosphorylase, glycogen; liver (PYGL) 14q22.1 0.147 NM_139275 A-kinase anchor protein 1 isoform 2 precursor (AKAP1) 17q23.2 0.147 NM_004737 like-glycosyltransferase (LARGE) 22q12.3 0.147

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NM_173834 Yip1 domain family member 6 (YIPF6) Xq13.1 0.147 AK024156 cDNA FLJ14094 fis, clone MAMMA1000372 10q11.22 0.147 NM_053005 HCCA2 , complete cds 11p15.5 0.147 NM_006297 X-ray repair cross complementing protein 1 (XRCC1) 19q13.31 0.147 NM_001540 heat shock 27kD protein 1 (HSPB1) 7q11.23 0.147 NM_021167 ocular development-associated gene (GATAD1) 7q21.2 0.147 NM_004272 homer homolog 1 (Drosophila) (HOMER1) 5q14.1 0.147 NM_003204 NRF1 protein (NRF1) 17q21.32 0.147 NM_022104 phosphorylated CTD interacting factor 1 (PCIF1) 20q13.12 0.148 AF116682 PRO2013 , complete cds (HSPC280) 6q24.1 0.148 NM_002018 flightless I (Drosophila) homolog (FLII) 17p11.2 0.148 Table 3: Downregulated genes in FK16A[+] hybrids

Figure 3: Classification of differentially expressed genes to several cellular processes using Ease software (please note that not all differentially expressed genes have been classified).

No significant differential expression of known telomerase regulators A number of genes has previously been described to be involved in the regulation of hTERT. hTERT activating genes include c-Myc 33, Bmi1 34 and HIF-1α 35. On the other hand p53 36, TGF β 37, Menin 38, Rak 38, BRIT1 38, SIP1 38, BRCA1 39, NMI 39, WT1 40, and MAD1 41 have been identified as hTERT repressors. E2F-1 42, Sp1 43,44, USF1, USF2 45,46 and NFX1 47 have been

96 Chapter 4 implicated in both activation of hTERT in tumor cells and repression of hTERT in normal cells. None of these genes were found to be differentially expressed (FDR ≤ 0.15) between FK16A/#6[+] and FK16A/#6[-] hybrids, although Sp1 and NMI were more than twofold downregulated in FK16A/#6[+] hybrids. The FDR values of these latter two genes were, however, greater than 0.15 (FDR=0.18 and FDR=0.22 respectively). For another two genes, i.e. USF1 and BRIT1, no oligos were present on the array.

Confirmation of microarray data by real time RT-PCR To further verify our microarray expression data we performed real time RT-PCR for a selection of 3 upregulated genes (IMP1, RGS5 and WISP2) and 2 down regulated genes (AQP3 and SEMP1). The same RNA isolates as originally used for microarray expression analysis were subjected to RT-PCR. Compared with the median mRNA expression levels in the four FK16A[-] hybrids IMP1 was 2 to 3 fold and WISP2 2 to 4 fold up regulated in 4 out of 8 FK16A[+] hybrids (Figure 4A, C). RGS5 mRNA expression was about 2 fold increased in 3 of the FK16A[+] hybrids (Figure 4B). For AQP3 a 2 to 12 fold down regulation of mRNA expression was observed in 6 FK16A[+] hybrids (Figure 4D) and SEMP1 was 2 to 5 fold down regulated in 5 FK16A[+] hybrids (Figure 4E). These findings confirm differential expression of these genes in FK16A[+] hybrids compared with FK16A[-] hybrids.

Differential expression of a subset of identified genes in primary cells, HPV- immortalized cells and cervical cancer cells. We next aimed to acquire a further notion on the expression of the 164 identified genes in normal epithelial cells, cervical cancer cells, and HPV16 immortalized parental FK16A cells without an added chromosome 6. Therefore, we included the expression profiles of primary keratinocytes (EK), FK16A and the cervical carcinoma cell line SiHa and calculated the fold change (Fc) of the 164 genes listed above in FK16A and SiHa versus FK16A [-] hybrids and in FK16A and SiHa versus EK. Subsequent selection of genes that were at least 2 fold up- or down regulated in FK16A/SiHa versus FK16A[-] and in FK16A/SiHa versus EK ultimately resulted in 17 up regulated and 15 down regulated genes in endogenous hTERT positive cells (Figure 5; Tables 4 and 5). The up regulated genes include genes involved in signaling, such as RGS5, WISP2, LIFR and AHSG, and genes originally associated with bone

97 Surrogate markers for hTERT deregulation morphogenesis, including TNFRSF11B, MGP and WISP2. The down regulated genes comprise genes coding for membrane proteins, like SEMP1, EPHA1, AQP3 and SCEL, an anti-apoptotic protein, i.e. BCL2L2, and a protein involved in DNA repair, i.e. XRCC1.

Figure 4: Real time RT-PCR for IMP1 (A), RGS5 (B), WISP2 (D), AQP3 (E), and SEMP1 (F) on FK16A[+](MCF9cl6, MCF9cl6b, MCF9cl19, MCF15cl8, MCF15cl15b, MCF15cl18, MCF15cl20, MCF15cl21) and [-] (MCF25cl2, MCF26cl4, MCF29cl3, MCF29cl8) hybrids

Figure 5: Selection of genes that are at least 2 fold upregulated or downregulated in FK16A and SiHa compared with both primary keratinocytes and FK16A[-] hybrids

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Genbank ID Gene Location FDR Insulin-like growth factor 2 mRNA binding protein NM_006546 17q21 0.0467 (IGF2BP1) (IMP1) NM_001928 D component of complement (adipsin) (DF) 19p13 0.1125 AL137382 DKFZp434L1226 (from clone DKFZp434L1226) 16q24 0.1255 NM_003617 Regulator of G-protein signalling 5 (RGS5) 1q23 0.1255 NM_002101 Glycophorin C (Gerbich blood group) (GYPC) 2q14 0.1285 NM_006851 Glioma pathogenesis-related protein (RTVP1) 12q21 0.1285 NM_000483 Apolipoprotein C-II (APOC2) 19q13 0.1285 NM_004467 Fibrinogen-like 1 (FGL1) 8p22 0.1287 NM_003881 WNT1 inducible signaling pathway protein 2 (WISP2) 20q13 0.1329 NM_000900 Matrix Gla protein (MGP) 12p12 0.1345 Tumor necrosis factor receptor superfamily, member NM_002546 8q24 0.1363 11b (TNFRSF11B) NM_025227 Bactericidal/permeability-increasing protein (BPIL1) 20q11 0.1363 NM_002310 Leukemia inhibitory factor receptor (LIFR) 5p13 0.1363 NM_022154 solute carrier family 39 (zinc transporter) (SLC39A8) 4q24 0.1363 NM_001622 Alpha-2-HS-glycoprotein (AHSG) 3q27 0.1473 NM_014210 Ecotropic viral integration site 2A (EVI2A) 17q11 0.1473 NM_003536 H3 histone family, member K (H3FK) 6p22 0.1473 Table 4: Genes upregulated in both FK16A[+] hybrids and in hTERT positive non-hybrid cells, i.e. FK16A and SiHa

Genbank ID Gene Location FDR NM_004925 Aquaporin 3 (AQP3) 9p33 0.0760 NM_003843 Sciellin (SCEL) 13q22 0.1000 Senescence-associated epithelial membrane protein NM_021101 3q28 0.1125 (SEMP1) AK023814 cDNA FLJ13752 fis, clone PLACE3000352 5q32 0.1125 NM_016230 Flavohemoprotein b5+b5R (LOC51167) 6q14 0.1125 NM_004050 BCL2-like 2 (BCL2L2) 14q11 0.1255 NM_017434 Dual oxidase 1 (DUOX1) 15q21 0.1285 Dehydrogenase/reductase (SDR family) member 1 NM_138452 14q11 0.1345 (DHRS1) NM_003976 Artemin (ARTN) mRNA 1p34 0.1363 NM_017918 FLJ20647 (FLJ20647) 4q25 0.1363 NM_005232 EphA1 (EPHA1) 7q34 0.1363 NM_014704 KIAA0562 gene product (KIAA0562) 1p36 0.1363 NM_001540 Heat shock 27kD protein 1 (HSPB1) 7q11 0.1473 X-ray repair complementing defective repair in NM_006297 19q33 0.1473 Chinese hamster cells 1 (XRCC1) NM_053005 HCCA2 (HCCA2) 11p15 0.1473 Table 5: Genes downregulated genes in both FK16A[+] hybrids and in hTERT positive non- hybrids, i.e. FK16A and SiHa

99 Surrogate markers for hTERT deregulation

Analysis of AQP3 mRNA levels in normal cervical epithelium and cervical carcinomas Of the 15 down regulated genes identified, AQP3 revealed the most significant down regulation. As mentioned before, down regulation of this gene could be confirmed in the hTERT positive FK16A[+] hybrids (Figure 4D). In order to investigate whether AQP3 mRNA levels were also down regulated in hTERT positive clinical samples, real time RT-PCR was performed on 8 cervical SCCs and normal cervical epithelial cells. All SCCs showed elevated hTERT mRNA levels compared with normal cervical cells as determined by quantitative RT- PCR (data not shown). AQP3 real time RT-PCR revealed a 15 to 120 fold down-regulation of AQP3 mRNA in all SCCs (Figure 6). This indicates that AQP3 mRNA expression is not only reduced in HPV transformed cell lines with elevated hTERT but also in cervical carcinomas.

Figure 6: Real time RT-PCR for AQP3 on normal cervical keratinocytes and cervical carcinomas

Analysis of MGP protein levels in normal cervical epithelium, high grade cervical lesions and cervical carcinomas We subsequently selected the up regulated gene encoding Matrix Gla Protein (MGP) for further analysis of protein over expression by means of immunohistochemistry. MGP has previously been shown to be differentially expressed in carcinomas, including those of the cervix 48-51. MGP immunohistochemical analysis was performed on previously established organotypic cultures of primary keratinocytes, FK16A and SiHa cells 52, 3

100 Chapter 4 specimens containing normal cervical epithelium, 22 CIN2/3 lesions and 8 cervical SCCs. In addition to the SCCs, all CIN2/3 biopsies were hrHPV positive. All SCCs and 13 of the 22 high-grade CIN lesions showed elevated hTERT mRNA expression as determined by quantitative RT-PCR (results not shown). Whereas no or weak MGP immunostaining was seen in the primary keratinocytes (Figure 7A), increased MGP protein expression was observed in FK16A (Figure 7B) and SiHa cells (data not shown). In samples with normal cervical epithelium weak cytoplasmic staining of MGP could be detected in the (para)basal cells up to the spinous layer (Figure 7C). In 7 out of 8 cervical SCCs, clear cytoplasmic MGP staining was seen in the tumor cells, including the basal cells (Figure 7D). In a subset of them an even more intense staining was seen at the borders of the tumor fields. Moreover, a strong staining of individual tumor cells was occasionally observed. Macrophages, part of the infiltrating lymphocytes, plasma cells and capillaries were found to be positive for MGP as well, whereas no staining was evident in the surrounding stromal cells (Figure 7E). In cervical epithelium with normal histology adjacent to SCC in the tumor tissues, only weak cytoplasmic staining was observed in the parabasal to spinous layer (Figure 7F), comparable to the staining observed in the epithelium of normal cervical tissue specimens. On the other hand, in dysplastic epithelium adjacent to SCC an increased cytosolic staining could be observed, which was also evident in the basal cells (Figure 7G). In 68% of high grade CIN lesions elevated MGP expression was seen in the lower two-third of the epithelium up to the full thickness of the epithelium. Chi-squared statistical testing revealed that a significantly higher percentage of high-grade lesions with elevated hTERT mRNA expression showed increased MGP protein expression compared to those without (p=0.047). Examples of high-grade CIN lesions with and without elevated hTERT mRNA showing respectively high and low MGP expression are shown in Figure 7H and I. The presence of a high grade CIN lesion in the latter section was confirmed by p16 positive staining (data not shown). These findings indicate that MGP mRNA and protein levels are not only up regulated in cell lines with elevated hTERT, but that MGP protein expression is also increased in high grade CIN lesions with elevated hTERT mRNA expression.

101 Surrogate markers for hTERT deregulation

Figure 7: Immunohistochemistry for MGP. MGP staining in a raft culture of primary keratinocytes (A) a raft culture of FK16A cells (B), normal cervical epithelium (C), cervical carcinoma (D), infiltrating lymphocytes (E), normal cervical epithelium adjacent to carcinoma (F), dysplastic cervical epithelium adjacent to carcinoma (G), a high-grade CIN lesions with elevated hTERT mRNA (H) and a high-grade CIN lesions without elevated hTERT mRNA (I).

Discussion Elevated hTERT mRNA expression and concomitant activation of telomerase constitute a key event during cervical carcinogenesis. However, the detection of elevated hTERT mRNA levels and telomerase activation in cervical smears does not provide a reliable marker for deregulated hTERT expression in the underlying lesions14. In this study we aimed to identify differentially expressed genes reflecting conditions of deregulated hTERT expression by comparing the expression profiles of a unique panel of hTERT-repressed and hTERT-positive cell hybrids. Microarray ANOVA analysis of the gene expression signatures of hTERT negative and hTERT positive FK16A hybrids resulted in the identification of 79 upregulated and 85 downregulated genes in the hTERT positive cells. Differentially expressed genes comprise genes involved in a wide variety of cellular processes such as signal transduction, development, cell proliferation, apoptosis, DNA repair, ossification and inflammation.

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The reliability of our data analysis was confirmed by the detection of a 3 fold increase of hTERT expression in the endogenous hTERT-positive hybrids compared with the endogenous hTERT negative hybrids, and by corresponding real time RT-PCR results obtained from 3 up regulated genes (i.e. IMP1, RGS5, and WISP2), and 2 down regulated genes (i.e AQP3 and SEMP1). Differential expression of these genes could be verified in a subset of the FK16A[+] hybrids. The fact that not all revertant hybrids showed the same expression profile for these genes corresponds to the likelihood that not all FK16A[+] hybrids have regained immortality by the same mechanism. Cell complementation studies, not only on cervical cancer cell lines but also on genetically related HPV-immortalized cell lines including FK16A cells, have shown that there are several routes by which cells can be immortalized and reactivate telomerase during HPV mediated transformation (reviewed by Steenbergen et al. 3 and R.D.M. Steenbergen unpublished observations). The 17 upregulated and 15 downregulated genes that were also differentially expressed in hTERT positive and negative non-hybrid cells are most likely associated with deregulated hTERT expression in vivo. Of these genes AQP3 was most significantly down regulated, which was confirmed by real time RT PCR in both hTERT positive hybrid cells and cervical SCC. AQP3 is an integral membrane protein that, in addition to water, also transports nonionic small molecules such as urea and glycerol 53 and of which expression has been reported in various normal human tissues 54. To our knowledge this is the first study showing a down regulation of AQP3 expression in cervical carcinomas. Over expression of other AQP family members has been described in several human cancers such as colorectal cancer (AQP 1 and 5) 55 and brain cancer (AQP1) 56. It should, however, be noted that the homology between AQP3 and other AQP family members is low 53, and it is still questionable whether altered expression of these genes reflects a cause or merely a consequence of the carcinogenic process. One of the up regulated genes, MGP, has previously been shown to be up regulated in cervical carcinomas 49. Moreover, up regulation of MGP has been shown in breast cancer, ovarian cancer, renal cancer and testicular tumors 48,50,51. MGP is an 84-residue vitamin K-dependent extracellular matrix protein, which is expressed at high levels in heart, kidney, and lung and is up-regulated by vitamin D in bone cells 57. MGP acts as a calcification inhibitor by repressing bone morphogenetic protein 2 (BMP2) in cartilage and vasculature 58. The role of MGP in carcinogenesis still remains to be determined. Interestingly,

103 Surrogate markers for hTERT deregulation silencing of the MGP repressed protein BMP2 has recently been described in cervical carcinomas 59. In the present study we demonstrated an upregulation of MGP expression in not only 86% of cervical carcinomas with elevated hTERT expression, but also in a significantly higher proportion of high-grade CIN lesions with elevated hTERT expression compared with their counterparts without elevated hTERT mRNA (p=0.047). Although this correlation just reached significance, the relevance is underlined by the fact that in a dataset with relatively few samples, statistically significant results can only occur when the effect sizes are large. The fact that we could confirm AQP3 down regulation and MGP up regulation in clinical samples does not only validate our data analysis, but also supports that our in vitro model system for HPV-mediated transformation to a certain extent mirrors HPV mediated transformation in vivo. Of the other up regulated genes 4 encode proteins involved in signalling, i.e. RGS5, a negative regulator of G-protein signalling, WISP2, a downstream target of Wnt signalling, LIFR, a signal transducing molecule and AHSG, an inhibitor of tyrosine kinase. Another 3 up regulated genes have originally been associated with bone morphogenesis, but appeared to be differentially expressed in other human cancers as well 48,49,60-63. These include TNFRSF11B, involved in osteoclastogenesis, MGP, as discussed above, and WISP2, involved in modulating bone turnover. In addition to AQP3, also other down regulated genes encode membrane proteins, like SEMP1, a tight junction protein, EPHA1, a tyrosine kinase receptor, and SCEL, a protein involved in homotypic and heterotypic associations. The remaining down regulated genes include BCL2L2, an anti- apoptotic protein and XRCC1 involved in DNA repair. The finding that none of the known telomerase regulators were found to be associated with deregulated hTERT expression may at least in part be due to the fact that in order to avoid false positives the limit for selection of differentially expressed genes was rather high (FDR < 0.15). The transcription factor SP1 for example had an FDR of 0.18 and was therefore not considered to be differentially expressed. Secondly, part of the known regulators may not be identified as they function in a highly cell type specific manner, or their activity may be regulated at the post-transcriptional level. An example of a gene regulated at the translational level is NFX1, which was shown to be involved in telomerase regulation in HPV transformed cells 47.

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Recent studies have provided evidence for a multifunctional role of hTERT in tumorigenesis, as besides its telomerase activating function it also was found to be involved in the regulation of the chromatin state and DNA damage responses 64. Moreover, in mouse models Tert appeared a critical determinant in the mobilization and proliferation of epidermal stem cells 65. Consequently, the genes identified in the present study may have broader implications and not only provide candidate surrogate markers for telomerase activation itself, but may also be related to the telomere-length independent functions of hTERT. Future studies are warranted to investigate whether expression of these genes in cervical smears reflects their status and hTERT deregulation in the underlying tissue. In summary, we have identified 32 genes which were commonly found to be differentially expressed in HPV transformed cells with deregulated hTERT. These genes, particularly exemplified by AQP3 and MGP, may provide novel biomarkers for deregulated hTERT and allow the identification of those cervical cancer precursor lesions that have a high likelihood of progression to invasive carcinoma.

Acknowledgements We thank Paul Eijk and Paul van den Ijssel for excellent technical assistance with microarray experiments. Jaqueline Cloos and Soemini Kasanmoentalib are highly acknowledged for their contribution to the data analysis. We thank Rob Dee for excellent assistance with primer selection for real time PCR experiments. SM Wilting was supported by a grant of the Consortium of Medical Biology Systems in the Netherlands (CMSB-137). RDM Steenbergen was supported by a fellowship of the Royal Netherlands Academy of Arts and Sciences.

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human papillomavirus type 16- and 18-transfected human keratinocytes. J.Virol., 72: 749-757, 1998. 53. Ishibashi, K., Sasaki, S., Fushimi, K., Uchida, S., Kuwahara, M., Saito, H., Furukawa, T., Nakajima, K., Yamaguchi, Y., Gojobori, T., and . Molecular cloning and expression of a member of the aquaporin family with permeability to glycerol and urea in addition to water expressed at the basolateral membrane of kidney collecting duct cells. Proc.Natl.Acad.Sci.U.S.A, 91: 6269-6273, 1994. 54. Inase, N., Fushimi, K., Ishibashi, K., Uchida, S., Ichioka, M., Sasaki, S., and Marumo, F. Isolation of human aquaporin 3 gene. J.Biol.Chem., 270: 17913-17916, 1995. 55. Moon, C., Soria, J. C., Jang, S. J., Lee, J., Obaidul, H. M., Sibony, M., Trink, B., Chang, Y. S., Sidransky, D., and Mao, L. Involvement of aquaporins in colorectal carcinogenesis. Oncogene, 22: 6699-6703, 2003. 56. Saadoun, S., Papadopoulos, M. C., Davies, D. C., Bell, B. A., and Krishna, S. Increased aquaporin 1 water channel expression in human brain tumours. Br.J.Cancer, 87: 621- 623, 2002. 57. Cancela, L., Hsieh, C. L., Francke, U., and Price, P. A. Molecular structure, chromosome assignment, and promoter organization of the human matrix Gla protein gene. J.Biol.Chem., 265: 15040-15048, 1990. 58. Zebboudj, A. F., Imura, M., and Bostrom, K. Matrix GLA protein, a regulatory protein for bone morphogenetic protein-2. J.Biol.Chem., 277: 4388-4394, 2002. 59. Sova, P., Feng, Q., Geiss, G., Wood, T., Strauss, R., Rudolf, V., Lieber, A., and Kiviat, N. Discovery of novel methylation biomarkers in cervical carcinoma by global demethylation and microarray analysis. Cancer Epidemiol.Biomarkers Prev., 15: 114- 123, 2006. 60. Banerjee, S., Saxena, N., Sengupta, K., Tawfik, O., Mayo, M. S., and Banerjee, S. K. WISP-2 gene in human breast cancer: estrogen and progesterone inducible expression and regulation of tumor cell proliferation. Neoplasia., 5: 63-73, 2003. 61. Saxena, N., Banerjee, S., Sengupta, K., Zoubine, M. N., and Banerjee, S. K. Differential expression of WISP-1 and WISP-2 genes in normal and transformed human breast cell lines. Mol.Cell Biochem., 228: 99-104, 2001. 62. Holen, I., Croucher, P. I., Hamdy, F. C., and Eaton, C. L. Osteoprotegerin (OPG) is a survival factor for human prostate cancer cells. Cancer Res., 62: 1619-1623, 2002. 63. Holen, I., Cross, S. S., Neville-Webbe, H. L., Cross, N. A., Balasubramanian, S. P., Croucher, P. I., Evans, C. A., Lippitt, J. M., Coleman, R. E., and Eaton, C. L. Osteoprotegerin (OPG) expression by breast cancer cells in vitro and breast tumours in vivo--a role in tumour cell survival? Breast Cancer Res.Treat., 92: 207-215, 2005. 64. Masutomi, K., Possemato, R., Wong, J. M., Currier, J. L., Tothova, Z., Manola, J. B., Ganesan, S., Lansdorp, P. M., Collins, K., and Hahn, W. C. The telomerase reverse transcriptase regulates chromatin state and DNA damage responses. Proc.Natl.Acad.Sci.U.S.A, 102: 8222-8227, 2005. 65. Flores, I., Cayuela, M. L., and Blasco, M. A. Effects of telomerase and telomere length on epidermal stem cell behavior. Science, 309: 1253-1256, 2005.

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Integrated genomic and transcriptional profiling identifies chromosomal loci with altered gene expression in cervical cancer

Saskia M Wilting Jillian de Wilde Chris JLM Meijer Johannes Berkhof Yajun Yi Wessel N van Wieringen Boudewijn JM Braakhuis Gerrit A Meijer Bauke Ylstra Peter JF Snijders Renske DM Steenbergen

Genes, Chromosomes & Cancer (2008); 47, p890-905

Integrated chromosomal and transcriptional profiling

Abstract For a better understanding of the consequences of recurrent chromosomal alterations in cervical carcinomas, we integrated genome-wide chromosomal and transcriptional profiles of 10 squamous cell carcinomas (SCCs), 5 adenocarcinomas (AdCAs) and 6 normal controls. Previous genomic profiling showed that gains at chromosome arms 1q, 3q, and 20q as well as losses at 8q, 10q, 11q, and 13q were common in cervical carcinomas. Altered regions spanned multiple megabases, and the extent to which expression of genes located there is affected remains unclear. Expression analysis of these previously chromosomally profiled carcinomas yielded 83 genes with significantly differential expression between carcinomas and normal epithelium. Application of differential gene locus mapping (DIGMAP) analysis and the array CGH expression integration tool (ACE-it) identified hotspots within large chromosomal alterations in which gene expression was altered as well. Chromosomal gains of the long arms of chromosome 1, 3, and 20 resulted in increased expression of genes located at 1q32.1-32.2, 3q13.32-23, 3q26.32- 27.3, and 20q11.21-13.33, whereas a chromosomal loss of 11q22.3-25 was related to decreased expression of genes located in this region. Overexpression of DTX3L, PIK3R4, ATP2C1, and SLC25A36, all located at 3q21.1-23 and identified by DIGMAP, ACE-it or both, was confirmed in an independent validation sample set consisting of 12 SCCs and 13 normal ectocervical samples. In conclusion, integrated chromosomal and transcriptional profiling identified chromosomal hotspots at 1q, 3q, 11q, and 20q with altered gene expression within large commonly altered chromosomal regions in cervical cancer.

Key words: squamous cell carcinoma, adenocarcinoma, microarray, array CGH, HPV

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Introduction Although the implementation of cervical screening programs has resulted in a decrease in the incidence of cervical cancer in developed countries, it still remains the second most common cancer in women worldwide. Histologically, cervical carcinomas can be classified into multiple types, including squamous cell carcinomas (SCCs) in 70-80% and adenocarcinomas (AdCAs) in 5-10% of cases 1,2. Persistent infection with high-risk (i.e., oncogenic) human papillomavirus (hr- HPV) is causally involved in cervical carcinogenesis. Deregulated expression of the viral oncoproteins E6 and E7 interferes with cell cycle control due to their ability to induce degradation of the tumour suppressor proteins TP53 and RB1, respectively. This results in uncontrolled cell proliferation and accumulation of specific (epi) genetic changes in the host cell genome, driving progression to a malignant phenotype 3,4. Only a minority of all women infected with hr-HPV will ultimately develop cervical cancer, emphasizing the multi-step nature of cervical carcinogenesis. More insight into the (epi) genetic alterations that occur during cervical carcinogenesis is essential for the discovery of genes that are biologically relevant in cervical cancer development and progression. Microarray-based technology enables high-resolution genome-wide screening for altered chromosomal regions (array-based comparative genomic hybridization (array CGH)) as well as altered gene expression. Recurrent chromosomal alterations found by (array) CGH involved many losses (chromosome arms 2q, 3p, 4p, 5q, 6q, 8q, 10q, 11q, 13q, 18q) and gains (1, 3q, 5p, 8q, 20q, and Xq) 5-14. Even when using high-resolution array CGH, affected regions are still multiple megabases in size and contain substantial amounts of genes 13. The extent to which these recurrent chromosomal alterations have functional relevance by resulting in abnormal expression of the involved genes is still largely unknown. Similarly, several studies have been conducted to determine transcriptional profiles of cervical carcinomas, yielding large numbers of genes with altered expression 15-21. Identification of tumor cell specific and functionally relevant genes from expression array analysis is hampered by the large number of secondary or responsive changes in gene expression not only in tumour cells, but in interspersed stromal and invading immune cells as well. Indeed, previous studies using microdissection or in situ hybridization approaches showed that a substantial subset of differentially expressed genes in cervical carcinomas was specific for stromal cells 16,21.

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To identify genes with altered expression related to chromosomal alterations we integrated genome-wide mRNA expression profiles and previously generated high-resolution chromosomal signatures of cervical carcinomas, for which RNA and DNA were isolated from the same frozen sections 13. For this purpose two innovative statistical approaches were used, namely differential gene locus mapping (DIGMAP) and the array CGH and expression integration tool (ACE- it). Whereas DIGMAP compares expression of windows of genes located next to each other between carcinomas and normal epithelium, ACE-it determines the association between chromosomal alterations and gene expression by comparing the expression of a particular gene between carcinomas that show an alteration at the locus of that gene and carcinomas without a chromosomal alteration 22,23. Although only a limited number of samples were included in this study, the statistical analyses used do correct for this small sample size. Integration resulted in the identification of five chromosomal hotspots where common chromosomal alterations were associated with changes in gene expression. Differential expression of a subset of genes identified by this integrated approach was confirmed in an independent validation sample set using real-time RT-PCR.

Methods Tissue Specimens We used frozen specimens of SCCs and AdCAs, all of which were collected during the course of routine clinical practice at the Department of Obstetrics and Gynaecology at the VU University Medical Center (Amsterdam) (Table 1). Normal epithelial control samples were obtained from histologically normal frozen biopsies or smears of non-cancer patients undergoing hysterectomy (Table 2). Tissue biopsies were quick-frozen and stored in liquid nitrogen immediately after completion of the surgical procedure. Cervical smears were collected directly after hysterectomy using brushes. Brushes were stored in TRIzol Reagent (Life Technologies, Inc. Breda, The Netherlands), which stabilizes RNA molecules, immediately after a cytological specimen was made for microscopical examination. For microarray analysis 10 SCCs, 5 AdCAs and 6 samples of normal epithelium were used. Normal controls included five samples of normal squamous epithelium (NSE) and one sample of RNA from normal endocervical columnar epithelium (NCE), which are further specified in Table 2. RNA isolated from two different biopsies of the same SCC was hybridized as a biological replicate. One of the normal ectocervical epithelial

114 Chapter 5 control samples was hybridised twice as a technical replicate to determine technical variation. Real-time RT-PCR was performed on all carcinomas included in microarray analysis as well as an independent set of 12 SCCs and 13 histologically normal squamous epithelial samples of the ectocervix (Table 1 and 2). This study followed the ethical guidelines of the Institutional Review Board of the VU University Medical Center.

Sample Differentiation grade Tumour stage HPV type Age (yrs) Technique SCC 2 PD IB 16 39 MA/qRT-PCR SCC 3 Unknown IIA 16 78 qRT-PCR SCC 4 MD IIA 67 62 MA/qRT-PCR SCC 11 PD IIB 16 75 qRT-PCR SCC 12 PD IB 16 44 MA/qRT-PCR SCC 15 PD IB 16 47 MA/qRT-PCR SCC 20 PD IIB 45 34 qRT-PCR SCC 27 MD IB2 69 49 MA/qRT-PCR SCC 28 MD IB2 35 48 MA/qRT-PCR SCC 29 MD IB1/IIB 16 48 qRT-PCR SCC 32 MD IIA 16 37 MA/qRT-PCR SCC 36 MD IIA 16 72 MA/qRT-PCR SCC 38 MD IB1/IIA 16 51 MA/qRT-PCR SCC 39 PD IB1 33 40 MA/qRT-PCR SCC 40 PD IB1 45 57 qRT-PCR SCC 42 PD IB1 16 79 qRT-PCR SCC 44 PD Unknown 16 51 qRT-PCR SCC 45 PD G3 45 52 qRT-PCR SCC 46 PD G2 31 65 qRT-PCR SCC 49 PD G2 16 32 qRT-PCR SCC 51 PD Unknown 16 25 qRT-PCR SCC 54 PD IB1 33 60 qRT-PCR AdCA 1 WD IB 16 34 MA/qRT-PCR AdCA 2 WD IB 16 35 qRT-PCR AdCA 7 MD IB 16 31 MA/qRT-PCR AdCA 10 MD IB2 16 39 MA/qRT-PCR AdCA 11 MD IB1 18 64 MA/qRT-PCR AdCA 12 MD IB2 18 41 MA/qRT-PCR AdCA 14 Unknown IIB 18 42 qRT-PCR AdCA 15 PD IB1 18 39 qRT-PCR Table 1: Summary of clinical data and HPV typing of carcinomas analyzed. SCC, squamous cell carcinoma; AdCA, adenocarinoca; WD, well differentiated; MD, moderately differentiated; PD, poorly differentiated; MA, microarray; qRT-PCR, real-time RT-PCR

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Sample Origin HPV type Age (yrs) Technique Type of material NCE (endo)cervix -;-;-;-;58/70 43;75;59;43;28 MA pool of 5 smears NSE1A/B (ecto)cervix -;-;-;- 59;47;48;52 MA pool of 4 smears NSE2 (ecto)cervix -;58;- 40;56;52 MA pool of 3 frozen tissues NSE3 uvula - 43 MA frozen tissue NSE4 uvula - 52 MA frozen tissue NSE5 uvula - 48 MA frozen tissue NSE6 (ecto)cervix 35 36 qRT-PCR frozen tissue NSE7 (ecto)cervix - 45 qRT-PCR frozen tissue NSE8 (ecto)cervix - 36 qRT-PCR frozen tissue NSE9 (ecto)cervix - 39 qRT-PCR frozen tissue NSE10 (ecto)cervix 16 30 qRT-PCR frozen tissue NSE11 (ecto)cervix - 29 qRT-PCR frozen tissue NSE12 (ecto)cervix 16 33 qRT-PCR frozen tissue NSE13 (ecto)cervix 16 30 qRT-PCR frozen tissue NSE14 (ecto)cervix - 34 qRT-PCR frozen tissue NSE15 (ecto)cervix 70 31 qRT-PCR frozen tissue NSE16 (ecto)cervix 16 31 qRT-PCR frozen tissue NSE17 (ecto)cervix - 47 qRT-PCR frozen tissue NSE18 (ecto)cervix 42 33 qRT-PCR frozen tissue Table 2: Summary of Clinical Data and HPV Typing of Normal Samples Analyzed NCE, normal columnar epithelium; NSE, normal squamous epithelium; MA, microarray; qRT- PCR, real-time RT-PCR.

RNA Isolation Total RNA was isolated from all samples using TRIzol Reagent according to the manufacturers’ instructions. Frozen tissue specimens were mounted using Tissue-Tek O.C.T. (Sakura Finetek Europe B.V., Zoeterwoude, The Netherlands) and were serially sectioned at -20°C according to the sandwich method in which the outer sections were H&E stained for histological assessment by an experienced pathologist and sequential series of in-between cryo-sections were used for RNA extraction. Only tumor specimens containing ≥70% tumour cells were included. If necessary (<70% epithelial cells) frozen biopsies of normal samples were first enriched for epithelial cells by means of laser capture microdissection using a Leica ASLMD microscope (Leica, Heidelberg, Germany). Of these samples 10 μm thick cryosections were cut and mounted on PEN foil coated slides (Leica). Sections were stained with Mayers’ hematoxylin for 1 min and completely dehydrated by rinsing the slides in 50, 70 and 100% ethanol followed by an 8 min incubation in xylene. Slides were stored in closed 50 ml tubes at -80ºC to avoid rehydration of the tissue and subsequent RNA degradation until microdissection was performed. In a pilot experiment using this protocol RNA integrity was assessed using RNA Nano Chips on an Agilent

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2100 Bioanalyzer (Agilent Technologies, Waldbronn, Germany). RNA quality of non-microdissected samples was checked by agarose gel electrophoresis.

HPV Typing DNA was isolated after RNA extraction with TRIzol following the manufacturers’ recommendations 13. HPV typing was performed using the general primer GP5+/6+ polymerase chain reaction (PCR) followed by reverse line blot, as described previously 24. Results are shown in Table 1.

Expression Microarray Analysis We used oligo arrays containing the 19K Human Release 1.0 oligonucleotide library, designed by Compugen (San Jose, CA) and obtained from Sigma- Genosys (Zwijndrecht, The Netherlands). In total 18,861 60-mer oligos representing 17,260 unique genes were spotted on the array. Arrays were produced at the VUmc Microarray facility 25,26. In short, cDNA was prepared from 15 μg of total sample RNA and 15 μg of Universal Human Reference

RNA (Stratagene, La Jolla, California, USA) using oligo-dT20-VN primer (Invitrogen, Breda, The Netherlands) and coupled to Cy3 (test sample) or Cy5 (reference). Slides were pre-hybridized for 45 min at 37°C with a pre- hybridization solution containing 30 μg salmon sperm DNA (Gibco, Breda, The Netherlands), 12 μg poly(A) (Pharmacia), 60 μg yeast tRNA (Sigma) and 24 μg Cot-1 DNA (Invitrogen) dissolved in 127 μl hybridization mix (0.2% SDS, 8% glycerol, 50% formamide, and 0.1% dextrane sulphate in 2x SSC). Pre- hybridization was followed by probe hybridization for 14 hours at 37°C. Both pre-hybridization and hybridization were performed in HybStation 12 (Perkin- Elmer Life Sciences). Hybridized arrays were then scanned using ScanArray Express (Perkin-Elmer Life Sciences, Zaventum, Belgium) and quantified in ImaGene 5.6.1 software (BioDiscovery Ltd, Marina del Rey, CA) using default settings. Flagged spots were excluded from further analysis. The entire dataset described here (including previously described array CGH data 13) is available from the Gene Expression Omnibus (GEO, http://www.ncbi.nlm.nih.gov/projects/geo/) through series accession number GSE6473.

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Microarray Data Analysis Data Pre-processing Microarray data were normalized using Lowess regression. When both intensities were below 50, hybridization was assumed inefficient and the ratio value was considered ‘missing’. The cut-off “50” is based on technical reproducibility experiments on our platform. To obtain more stable ratios, intensity values below 50 were substituted by 50 when the other channel was above 50. Genes with missing ratio values in more than 20% of arrays were excluded from analysis. Remaining missings were imputed using K-nearest neighbour imputation.

Cluster Analysis Unsupervised hierarchical clustering was performed on all genes that met our quality criteria in Spotfire DecisionSite 7.3 (Spotfire Inc., Göteborg, Sweden) using the Euclidean distance measure and complete linkage.

LIMMA Differential Gene Expression Analysis Differentially expressed genes were determined using the Linear Models for MicroArray data (LIMMA) statistical package from BioConductor (www.bioconductor.org) 27. Genes with False Discovery Rate (FDR) below 0.05 were considered statistically significant. Since we included three normal squamous epithelial controls of non-cervical origin, we applied an additional conservative selection criterion in which only significant genes that showed a fold change (FC) of at least two to the normal cervical controls were considered truly differentially expressed.

DIGMAP Analysis Differential gene locus mapping (DIGMAP) analysis was carried out to investigate aberrant expression patterns of groups of genes based on their chromosomal location as described by 23. Statistically significant loci were identified using the TTest, which generated confidence (“T”) scores by log- transformation of the reciprocal P value. An automated scanning method employing sliding window analysis was used to find so-called differential flag regions (DFRs). In this study, regions with a T score greater than 2 SDs from the mean of total T scores for all sliding windows and consisting of at least five consecutive significant sliding windows were considered a DFR if at least 70% of genes located in this region showed concordant differential expression

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(log2(FC) > 0 indicates increased expression; log2(FC) < 0 indicates decreased expression).

ACE-it In the carcinomas mRNA expression levels of genes were directly linked to gene copy numbers as measured by array CGH using the Array CGH Expression integration tool (ACE-it) 22. This tool identifies genes with differential expression between carcinomas that showed either a gain or a loss and carcinomas without a chromosomal alteration. The relation between gene expression and gene dosage is tested for all genes present on the oligo-array which fulfil the grouping criteria, using the one-sided Wilcoxon- test followed by Benjamini-Hochbergs’ multiplicity correction for FDR control. We allowed for five contaminating samples within the groupings and considered gene dosage and gene expression linked for genes with an FDR below 0.2.

Real-time RT-PCR Intron-flanking primers were selected for nine genes (i.e. DEK, SEMP1, ITGAV, SYCP2, MAL, ATP2C1, SLC25A36, PIK3R4 and DTX3L) using Primer Express 2.0 (Applied Biosystems, Warrington, United Kingdom) or taken from the RT- primer database of the University of Gent in Belgium (http://medgen.ugent.be/rtprimerdb) (Table 3).

Size Annealing Gene Primers (5’-3’) (bp) (°C) DEK F: AGAGAGGTTGACAATGCAAGTCT 71 56 R: TCTGCCCCTTTCCTTGTG SEMP1 F: GATGAGGATGGCTGTCATTG 75 55 R: TACCATGCTGTGGCAACTAAA ITGAV F: TTGTTGCTACTGGCTGTTTTG 89 60 R: TCCCTTTCTTGTTCTTCTTGAG SYCP2 F: ACAGAAAACTGAAGACTACCTTTGTTA 88 55 R: TCATCAGCTCCATTCAAATTAAA MAL F: GCAAGACGGCTTCACCTACAG 74 59 R: GCAGAGTGGCTATGTAGGAGAACA ATP2C1 F: GGATGTTCAGCAGCTTTCACAA 93 59 R: TCTGTAGCGACTTAATAATTTTCATCTTG SLC25A36 F: CCAGTGTCAACCGAGTAGTGTCT 76 57 R: AGGAACGAGGCCCTTCTTTT PIK3R4 F: GACTGCTACAAAAACCCCATGTT 90 60 R: CGGCACCATAACGTATCCATAA DTX3L F: CAGTGAAAGGGCAGCTAAGG 74 60 R: GCACAGGTTTTTCGTCAACA Table 3: Primer Sequences Used for Real-Time RT-PCR. F, Forward primer; R, Reverse primer; ITGAV primer sequences were retrieved from Rogojina et al 28

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Total RNA was reverse transcribed using oligo-dT20 primer (Invitrogen) and the resulting cDNA was used for real-time PCR on the ABI/Prism 7700 Sequence Detector System (Taqman-PCR; Applied Biosystems). cDNA corresponding to 25 ng of total RNA was amplified in a total reaction volume of 25 μl containing 12.5 μl 2x Sybr Green master mix (Perkin-Elmer/Applied Biosystems) and 0.5 μM primers. Relative expression values for each gene were determined from a standard curve, using primary keratinocytes (EK) or the cervical cancer cell line SiHa. The slopes of all standard curves were between –3.1 and –3.9 with a correlation coefficient of at least 0.98, ensuring sufficient efficiency of all experiments. All PCR experiments were performed in duplicate (delta Ct ≤1.5 between replicates) and mean values were used for calculations.

Statistical Analysis of Real-time RT-PCR Results Linear (Pearson) correlation between microarray results and real-time RT-PCR values was determined. Expression levels as measured by real-time RT-PCR were compared between carcinomas and normal cervical epithelium, using the non-parametric Wilcoxon-rank test. Two-sided P values below 0.1 were considered statistically significant.

Results SCC Expression Profiles Differ from those of AdCAs In this study, expression profiles of 10 SCCs and 5 AdCAs of the cervix were determined. To investigate the similarity between the overall expression profiles of these two histological subtypes of cervical cancer we performed unsupervised hierarchical clustering analysis with the expression values of all genes fulfilling the quality criteria (n = 12,831). This resulted in three clusters, one cluster containing only SCCs and two clusters containing AdCAs (Fig. 1). Within the SCC group, the biological replicates (SCC12A and SCC12B) clustered very closely together, indicating that the dataset is reliable. Interestingly, one of the AdCA groups (including AdCA1 and 12) clustered more closely to the SCC group than to the other AdCA group (including AdCA7, 10 and 11). This result suggests that expression profiles of a subset of the AdCAs included in this study are more similar to SCCs than to the other AdCAs. In concordance with this observation, the chromosomal profile of AdCA12 also showed alterations that are in general more specific for SCCs, including gains of 3q and 20q 13. However, AdCAs still form a separate cluster,

120 Chapter 5 indicating that expression profiles differ between SCCs and AdCAs. Differences in both expression and chromosomal profiles between SCC and AdCA of the cervix have been described previously 13,15,29.

Figure 1: Dendrogram obtained by unsupervised hierarchical clustering of SCCs and AdCAs. SCC12A and B are biological replicates, respectively.

Identification of Differentially Expressed Genes To determine which genes were differentially expressed in cervical carcinomas we compared the expression profiles of all tumours (n = 15) to those of normal epithelium (n = 6) using the LIMMA statistical package. In this way 39 differentially expressed genes were identified (24 upregulated genes and 15 downregulated genes). Since cluster analysis separated SCCs and AdCAs based on their overall expression profiles, we also conducted separate analyses for both tumor types. The comparison of SCCs (n = 10) with normal epithelium identified 55 overexpressed genes and 21 downregulated genes. These 76 genes included all but seven of the genes that were differentially expressed between all tumors and normal epithelium. When we compared only AdCAs (n = 5) to normal epithelium no significant differences in expression were found, which is possibly due to the small number of samples investigated. All genes showing differential expression between carcinomas and normal epithelium in the comparisons described above were combined into one list of 83 genes (58 upregulated and 25 downregulated genes) (Table 4). Significantly differential expression between SCCs and AdCAs was found for 16 genes, 8 of which were higher expressed in SCCs (Table 5).

Validation of Differentially Expressed Genes by Real-time RT-PCR To confirm the results obtained by LIMMA differential gene expression analysis we determined expression values of five selected genes (ITGAV, MAL, SEMP1, DEK, and SYCP2) by real-time RT-PCR in all carcinomas analyzed by microarray. ITGAV and MAL were the most significantly up- and down- regulated gene in carcinomas compared to normal, respectively. SEMP1 showed

121 Integrated chromosomal and transcriptional profiling increased expression in SCCs compared to AdCAs as well as compared to normal epithelium, whereas upregulation of DEK and SYCP2 was previously shown to be associated with hr-HPV infection 30,31. Overall, real-time RT-PCR and microarray values showed a good correlation as was previously shown for the platform used (Fig. 2; Pearson correlation r = 0.77, P < 0.0005) 26.

all carcinomas only SCCs GenBank Acc No Gene symbol Cytoband FDR FC (normal cervix) FDR FC (normal cervix) downregulated genes in cervical carcinomas compared to normal epithelial tissue NM_014658 RAP1GA1 1p36.12 0.1665 2.3 0.0303 3.0 NM_004425 ECM1 1q21.2 0.0497 2.7 0.0590 2.2 NM_002371 MAL 2q11.1 0.0032 34.3 0.0039 33.1 J00129 FGB 4q31.3 0.3926 3.8 0.0486 6.6 AK001007 FLJ10145 5q23.2 0.0878 2.5 0.0363 3.0 NM_002770 PRSS2 7q34 0.0200 10.5 0.0214 10.6 NM_004063 CDH17 8q22.1 0.1067 2.6 0.0363 3.2 AL137555 C9orf88 9q34.11 0.0497 2.2 0.0624 2.0 AK022845 C9orf58 9q34.13 0.0122 2.6 0.0010 3.4 AL122071 SLC16A9 10q21.2 0.1540 3.7 0.0363 5.4 NM_000543 SMPD1 11p15.4 0.1040 2.1 0.0454 2.4 M62402 IGFBP6 12q13.13 0.0243 5.8 0.0255 5.9 X07695 KRT4 12q13.13 0.0271 17.7 0.0363 15.3 NM_016039 CLE7 14q22.1 0.0497 2.4 0.0483 2.5 NM_002435 MPI 15q24.1 0.0123 4.5 0.0133 4.7 NM_001520 GTF3C1 16p12.1 0.0537 2.9 0.0448 3.1 AB045292 M83 16p13.3 0.1714 2.3 0.0043 3.2 NM_017839 AYTL1 16q12.2 0.0580 2.9 0.0363 3.2 NM_006373 VAT1 17q21.31 0.0271 2.4 0.0308 2.4 NM_002476 MYL4 17q21.32 0.0497 2.8 0.0483 2.8 NM_014921 LPHN1 19p13.12 0.0394 1.9 0.0311 2.0 NM_020428 CTL2 19p13.2 0.0521 2.1 0.0354 2.3 NM_001928 DF 19p13.3 0.0464 9.2 0.0363 9.9 NM_006087 TUBB4 19p13.3 0.0497 2.1 0.0624 2.0 NM_006307 SRPX 23p11.4 0.0497 4.8 0.0549 4.8 upregulated genes in cervical carcinomas compared to normal epithelial tissue AB050716 TINAGL1 1p35.2 0.0497 4.6 0.0043 6.3 NM_003579 RAD45L 1p34.1 0.0499 1.9 0.0150 2.2 NM_006417 IFI44 1p31.1 0.0394 4.7 0.0212 5.6 NM_004428 EFNA1 1q22 0.0497 2.6 0.0549 2.4 AK024944 FLJ21291 1q32.1 0.0249 2.6 0.0067 2.9 AL137717 DKFZp434J1630 2p11.2 0.0499 2.7 0.0576 2.7 NM_004688 NMI 2q23.3 0.1365 3.3 0.0486 4.0 NM_002210 ITGAV 2q32.1 0.0090 2.4 0.0106 2.3 NM_007315 STAT1 2q32.2 0.0654 3.3 0.0043 4.5 NM_000090 COL3A1 2q32.2 0.0543 20.5 0.0354 27.8 AK000160 MYO1B 2q32.3 0.0497 2.6 0.0034 3.6 NM_000094 COL7A1 3p21.31 0.2214 2.1 0.0392 3.6 AK025135 DTX3L 3q21.1 0.0563 3.1 0.0303 3.5 AL122079 CCDC14 3q21.1 0.0341 2.5 0.0311 2.6 NM_004526 MCM2 3q21.3 0.0497 2.3 0.0039 3.0 Y08991 PIK3R4 3q21.3 0.2749 1.7 0.0450 2.1 NM_014382 ATP2C1 3q21.3 0.1186 2.0 0.0454 2.4 NM_018155 SLC25A36 3q23 0.1792 1.8 0.0483 2.4

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NM_003071 SMARCA3 3q24 0.0592 1.9 0.0448 2.2 AF086432 GPR87 3q25.1 0.4196 8.6 0.0491 19.5 NM_003875 GMPS 3q25.31 0.0338 1.8 0.0150 2.0 NM_016625 RSRC1 3q25.32 0.0871 2.0 0.0354 2.4 NM_003722 TP73L 3q28 0.4562 7.9 0.0363 21.4 AF101051 SEMP1 3q28 0.7625 4.4 0.0491 13.7 AL049229 DKFZp564O1016 3q29 0.1792 2.0 0.0317 2.6 Z24724 ATP13A3 3q29 0.0090 3.0 0.0043 3.3 AK024639 ATP13A3 3q29 0.1081 2.1 0.0454 2.4 AL050097 DKFZp586B0319 3q29 0.1058 3.6 0.0486 4.4 NM_001553 IGFBP7 4q12 0.0627 2.8 0.0363 3.3 NM_000582 SPP1 4q22.1 0.1311 1.8 0.0483 3.0 NM_003118 SPARC 5q33.1 0.0959 2.4 0.0363 3.1 NM_002932 DKFZp779B1535 5q33.1 0.1242 2.9 0.0465 3.5 NM_002341 LTB 6p21.33 0.2267 2.0 0.0491 2.6 NM_002800 PSMB9 6p21.32 0.1248 3.3 0.0363 4.5 NM_003472 DEK 6p22.3 0.0497 2.4 0.0106 2.9 NM_018950 HLA-F 6p22.1 0.1186 10.1 0.0363 15.5 NM_000416 IFNGR1 6q23.3 0.1540 4.1 0.0311 5.8 NM_002835 PTPN12 7q11.23 0.0497 2.3 0.0635 2.1 NM_014791 MELK 9p13.2 0.0497 1.9 0.0324 2.1 NM_001786 CDC2 10q21.2 0.0497 2.5 0.0180 2.9 NM_005127 CLECSF2 12p13.31 0.3683 2.9 0.0255 5.6 NM_002583 PAWR 12q21.2 0.0960 1.9 0.0354 2.2 NM_002345 LUM 12q21.33 0.0243 3.1 0.0235 3.2 NM_001845 COL4A1 13q34 0.0394 2.2 0.0235 2.6 AF035787 RF-IP4 14q32.33 0.1792 5.8 0.0363 9.5 NM_004048 B2M 15q21.1 0.0537 4.7 0.0454 5.2 NM_004165 RRAD 16q22.1 0.0497 3.6 0.0067 4.6 NM_001793 CDH3 16q22.1 0.1949 3.0 0.0214 4.5 NM_003150 STAT3 17q21.2 0.0959 1.9 0.0483 2.1 NM_002592 PCNA 20p12.3 0.1067 2.4 0.0363 2.9 NM_014258 SYCP2 20q13.33 0.0497 4.8 0.0265 6.1 NM_006806 BTG3 21q21.1 0.0125 2.3 0.0039 2.7 AK023589 FLJ13527 21q22.3 0.0884 1.9 0.0278 2.2 NM_005940 MMP11 22q11.23 0.0090 13.7 0.0043 15.7 AF019225 APOL1 22q12.3 0.1235 4.2 0.0486 6.0 NM_001953 ECGF1 22q13.33 0.2007 7.4 0.0246 14.0 M97168 XIST 23q13.2 0.0394 6.7 0.0149 9.4 X56196 XIST 23q13.2 0.0394 4.5 0.0150 6.5 X56197 XIST 23q13.2 0.0532 2.6 0.0280 3.4 AK001758 RLR1 23q25 0.0537 2.2 0.0432 2.4 NM_004961 GABRE 23q28 0.3781 2.2 0.0265 4.1 Table 4: Differentially Expressed Genes as Determined by LIMMA Statistical Analysis Between Carcinomas and Normal Epithelium. For genes printed in bold, elevated expression was related to increased copy numbers as determined by DIGMAP and/or ACE-it analysis. FDR, False Discovery Rate; FC, Fold change.

123 Integrated chromosomal and transcriptional profiling

GenBank Acc No gene symbol cytoband FDR downregulated genes in SCCs compared to AdCAs X73079 PIGR 1q32.1 0.0143 AK022207 MLPH 2q37.3 0.0219 NM_017862 FHFR 4p16 0.0212 NM_017540 GALNT10 5q33.2 0.0219 NM_001306 CLDN3 7q11.23 0.0212 X74956 MUC5B 11p15.5 0.0197 AB045292 M83 16p13.3 0.0212 NM_003225 TFF1 21q22.3 0.0212 upregulated genes in SCCs compared to AdCAs AF101051 SEMP1 3q28 0.0012 NM_003722 TP73L 3q28 0.0197 NM_006718 PLAGL1 6q24.2 0.0335 NM_002855 PVRL1 11q23.3 0.0213 NM_005127 CLECSF2 12p13.31 0.0197 NM_001941 DSC3 18q12.1 0.0143 NM_004961 GABRE 23q28 0.0197 AK026383 FLJ22730 8 or 14 0.0213 Table 5: Differentially Expressed Genes as Determined by LIMMA Statistical Analysis Between SCCs and AdCAs. FDR, False Discovery Rate.

Figure 2. The overall correlation between microarray and real-time RT-PCR values for DEK, ITGAV, MAL, SEMP1 and SYCP2.

In addition, we verified differential expression of these genes in a separate validation sample set consisting of 13 normal epithelial samples of the ectocervix and 12 SCCs. Expression values of DEK, ITGAV, SEMP1, and SYCP2 showed more variation within the group of SCCs than in the normal samples, indicating various levels of (over)expression within the carcinomas.

124 Chapter 5

Nevertheless, increased expression of DEK and ITGAV as well as decreased expression of MAL in SCCs compared to normal ectocervical epithelium was statistically significant, thereby verifying our microarray results (Figs. 3A-C; P < 0.05). Expression of SYCP2 and SEMP1 was also increased in SCCs, albeit at a lower level of significance (Figs. 3D-E; P < 0.1).

Figure 3. Real-time RT-PCR results for a subset of genes identified by differential expression analysis. Box plots of the log-transformed expression levels of A. DEK, B. ITGAV, C. MAL, D. SEMP1 and E. SYCP2 are shown in the independent validation set consisting of SCCs and normal ectocervical epithelial samples. The upper and lower boundaries of the boxes represent the 75th and 25th percentiles, respectively. The black line within the box represents the median, the whiskers represent the minimum and maximum values that lie within 1.5 inter quartile range from the end of the box. Values outside this range are represented by triangles. ** P<0.05; * P<0.10.

125 Integrated chromosomal and transcriptional profiling

Altered Gene Expression Related to the Chromosomal Location To identify genes with altered expression associated with recurrent genetic alterations, we next aimed for the integration of gene expression and gene copy numbers. Genome-wide chromosomal profiles of the carcinomas transcrip- tionally profiled in this study were previously generated and described 13. Using gene expression data of carcinomas and normal epithelium, differential gene locus mapping analysis (DIGMAP) was performed 23, in which all genes present on the array were grouped based on their chromosomal location. This yielded loci exhibiting differential gene expression between either SCCs or AdCAs and normal epithelium. A number of these loci overlapped with frequently altered chromosomal alterations found by array CGH (Table 6).

DIGMAP analysis array CGH analysis comparison locus % gains/losses in SCC % gains/losses in AdCA 1q32.1 67 57 3q13.32-q22.3 100 14 3q26.32-q27.3 100 29 SCC vs normal 7q22.1 11 14 9q34.11-q34.2 0 0 16p13.3 11 0

1q32.1-q32.2 67 57 AdCA vs normal 9q34.3 0 0 19p13.3 11 0 Table 6: Loci with Differential Gene Expression Determined by DIGMAP Analysis in Relation to Chromosomal Alterations

Genes located at 1q32.1 showed an overall increase in expression in both SCCs and AdCAs compared with normal epithelium. On the long arm of chromosome 3 two loci were identified which showed differential gene expression between SCCs and normal epithelium but not between AdCAs and normal epithelium. In agreement with these findings, gains of chromosome 1q were frequently found in both SCCs and AdCAs, whereas gains of 3q were more specific for SCCs 13. The fact that we also identified loci with downregulated expression at chromosome arms 7q, 9q, 16p, and 19p which do not overlap with common chromosomal losses, suggests that other regulatory mechanisms of gene expression, such as epigenetic alterations, also play a role in cervical cancer. An overview of all genes located within the regions identified by DIGMAP is given in Supplementary Table 1.

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Using gene expression and CGH array data, the Array CGH and Expression integration tool (ACE-it) was applied 22, in which expression and CGH array data were aligned for all carcinomas. Expression of genes was compared between carcinomas that showed either a gain or a loss of the respective gene locus and carcinomas without such chromosomal alteration. As a consequence, this analysis could only be performed on those genes for which sufficient numbers of carcinomas with and without chromosomal alteration were present (n = 654). Genes located at 1p36.23 (1 gene), 3q13.12-13.33 (8 genes), 3q21.1- 23 (22 genes), 20p12.2 (1 gene), and 20q11.21-13.33 (15 genes) showed increased expression in carcinomas with gains at these particular regions, whereas expression of 16 genes located at 11q22.3-25 and 1 gene located at 18q23 was decreased in carcinomas with a loss of the chromosomal region in which they reside (FDR < 0.2) (Supplementary Table 2). Results from array CGH, DIGMAP and ACE-it analysis are combined in Fig. 4. Particularly for chromosomes 1 and 3, integration of expression and chromosomal profiles resulted in the identification of chromosomal hotspots with altered gene expression within larger chromosomally altered regions. Whereas CGH analysis showed frequent gains (>50%) of the complete long arm of both chromosome 1 and 3, altered gene expression was only found at 1q32.1- 32.2, 3q13.32-23, and 3q26.32-27.3

Figure 4. An overview of frequencies of gains and losses on chromosomes A. 1, B. 3, C. 11, and D. 20 as determined by array CGH is depicted in grey. Loci identified by DIGMAP and ACE-it are shown in blue and yellow respectively.

127 Integrated chromosomal and transcriptional profiling

Validation of Integration Results by Real-time RT-PCR To verify the results obtained by integrating transcriptional and chromosomal profiles we selected 4 genes located at chromosome 3q21.1-23, namely DTX3L, PIK3R4, ATP2C1 and SLC25A36. Of these genes DTX3L and ATP2C1 were identified by DIGMAP, SLC25A36 by ACE-it and PIK3R4 was found in both analyses. In addition, significantly differential expression of these four genes was found between carcinomas and normal epithelium by LIMMA analysis. Real-time RT-PCR confirmed increased expression of all four genes in the independent validation sample set consisting of 12 SCCs and 13 normal ectocervical samples (Fig. 5, P < 0.05). The fact that overexpression of genes identified by different methods of integration could be validated in an independent data set underlines the validity of our approach and shows that the use of multiple statistical analyses has additional value.

Figure 5. Real-time RT-PCR results for genes identified by integrated analysis. Box plots of the log-transformed expression levels of A. ATP2C1, B. SLC25A36, C. PIK3R4 and D. DTX3L are shown in the independent validation set consisting of SCCs and normal ectocervical epithelial samples. The upper and lower boundaries of the boxes represent the 75th and 25th percentiles, respectively. The black line within the box represents the median, the whiskers represent the minimum and maximum values that lie within 1.5 inter quartile range from the end of the box. Values outside this range are represented by triangles. ** P<0.05.

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Discussion In the present study, we integrated transcriptional profiles of cervical carcinomas with their chromosomal profiles to identify genes with altered expression associated with copy number alterations. Others and we previously showed that frequent chromosomal alterations in cervical carcinomas are usually quite large in size. Integration allowed for fine mapping of these large chromosomally altered regions resulting in the identification of loci in which gene expression is altered as well. To the best of our knowledge, this is the first study on cervical carcinomas in which high-resolution transcriptional and chromosomal profiles were generated from the same frozen tissue sections, which prevents possible confounding of the results by tumor heterogeneity. Nevertheless, a recent study by 32, using array CGH and expression array data of two independent sets of cervical carcinomas, revealed concordant regions in which an association between chromosomal alterations and elevated gene expression was found (i.e., 3q27-29 and 20q13.1). 33 identified potential chromosomal alterations important for the development of cervical cancer by alignment of expression microarray data. Comparable with our results altered expression of genes located at 1q, 3q, and 11q was identified in either high-grade premalignant lesions or invasive carcinomas. We chose to compare expression patterns in carcinomas to those of unmatched normal controls instead of tumour-surrounding normal epithelium of the patient to ensure absence of genetically changed cells that otherwise might be present as a possible consequence of field cancerization. A significant proportion of carcinomas are surrounded by a field of cells that are clonally related to the carcinoma and thus show cancer-related genotypic alterations 34,35. 36 already showed a local field effect of genomic instability associated with (pre)malignant cervical lesions. On the other hand, the use of unmatched controls may result in increased variability due to inter-person differences. To reduce this potential inter-patient variability, we hybridized pools of RNA obtained from normal cervical epithelium of various individuals. As we aimed to identify genes that next to hrHPV contribute to cervical cancer development, both HPV positive and negative normal control samples were included to minimize identification of HPV-induced transcriptional changes. Even though we only included a relatively small amount of samples, differential gene expression analysis without integration to chromosomal alterations still

129 Integrated chromosomal and transcriptional profiling identified 83 significantly differentially expressed genes between carcinomas and normal epithelium. Altered expression of a subset of these genes was validated in an independent sample set. A number of genes found to be differentially expressed in this study have been previously reported as modified in cervical cancer, including MAL, KRT4, EFNA1, MCM2, SEMP1, SPP1, PSMB9, CDH3, MMP11 and CLECSF2 15,16,18,20,37-39. In addition, differential expression of a number of genes detected by LIMMA, including ITGAV, STAT1, MCM2, TP73L, SEMP1, SPP1, B2M, CDH3, STAT3 and ECGF1, could be confirmed at the protein level by searching a high throughput immunohistochemistry staining database constructed on a panel of cancers (http//:www.hpr.se). Integration analysis using DIGMAP and ACE-it, showed that gene expression and copy numbers were related at 1q32.1-32.2, 3q13.12-23, 3q26.32-27.3, 11q22.3-25 and 20q11.21-13.33. Especially for chromosomes 1 and 3 integration analysis resulted in the fine mapping of large chromosomally altered regions. Whereas the most frequent area of gain on both chromosomes was about 40 Mb in size, loci identified by integration ranged from 4-20 Mb. DIGMAP and ACE-it use very different approaches for integration of expression and genomics, which explains why partly different loci were identified. Despite these differences three genes located at 3q13.33 and 21 genes located at 3q21.1-22.2 were common in both analyses. Both approaches have their advantages and disadvantages. Because DIGMAP analysis uses gene sets rather than individual genes, this method is likely to detect smaller differences in expression that are persistent within the gene set than LIMMA does for individual genes. DIGMAP analysis detects coordinated changes in expression of genes located next to each other, which only provides indirect evidence of the involvement of a chromosomal alteration in the regulation of gene expression. This is underlined by the fact that DIGMAP also identified a number of loci that do not show frequent chromosomal alterations. On the other hand, altered gene expression does not have to be caused by the same mechanism in all tumor samples. Genes showing altered expression as a consequence of different mechanisms may potentially be the most interesting ones. In addition, DIGMAP enables analysis of all genes present on the array of which the genomic location is known. In contrast to DIGMAP, ACE-it allows determination of a more direct correlation between a chromosomal alteration and changes in expression of the genes located there, provided that no other differences exist between carcinomas with and without an alteration. Therefore,

130 Chapter 5 this approach is quite sensitive for detection of subtle but consistent changes in expression related to chromosomal alterations. A disadvantage of ACE-it, especially when working with small sample sizes, is the fact that a sufficient number of carcinomas with and without a certain chromosomal alteration are needed to perform the analysis. To examine the potential value of both approaches we subsequently validated differential expression of four genes located at 3q21.1-21.3, which were identified either by DIGMAP (DTX3L and ATP2C1), ACE-it (SLC25A36) or both (PIK3R4). Using an independent validation sample set, overexpression of all four genes could be confirmed. This underlines the suggestion that both analyses can yield valuable information and are complementary to each other. Of these genes DTX3L encodes a member of the deltex family of proteins, which function as E3 ligases and modify Notch signaling 40. The Notch signaling pathway has been implicated in cervical cancer before, although results are contradictory as to whether its role is oncogenic or tumor suppressive 41-43. PIK3R4 encodes the regulatory subunit of the class III phosphatidyl- inositol-kinase (PI3K) signaling pathway, which was shown to be involved in amino-acid-induced mTOR activation and may as such be essential for cell growth control 44. Mutations in PIK3R4 have recently been described in breast cancer 45. Whereas relatively little is known about class III PI3K signaling in cervical cancer, deregulated class I PI3K signaling, of which the catalytic subunit PIK3CA is also located at 3q, has been described in cervical cancer 46,47. ATP2C1, encoding a P-type cation transport ATPase, plays an essential role in the epidermis by keeping basal keratinocytes in their undifferentiated state 48. Specific cellular functions of the protein encoded by SLC25A36 are unknown at the moment, but indicates that the protein is located in the mitochondrial membrane and possesses transporter activity. A gain of chromosome 3q is the most frequently found chromosomal alteration in cervical carcinomas and has been described in a number of other solid tumors as well 49. The fact that the frequency of this event gradually increases from low-grade lesions to high-grade lesions, reaching a maximum in invasive carcinomas indicates that a 3q gain is closely tied to malignant progression of cervical lesions 7,11,50-52. Therefore, markers based on this chromosomal alteration are likely to be specific for progressive premalignant lesions and carcinomas. Two promising candidate oncogenes are located within this region, namely hTR and PIK3CA 49,53. Their potential value as marker for cervical cancer is supported by recent studies showing increased gene copy numbers of

131 Integrated chromosomal and transcriptional profiling hTR and increased PIK3CA protein expression in scrapings of women with underlying high-grade premalignant disease compared with scrapings of women with mild or no underlying disease 54-56. In this study expression values of hTR were not available. PIK3CA was included in the 3q26.32-27.3 region identified by DIGMAP, but did not show significantly differential expression independent of chromosomal location (LIMMA analysis). Other interesting genes identified by DIGMAP, but not LIMMA, located within this region include LAMP3, overexpression of which was associated with metastasis in cervical cancer 57, ST6GAL1, enhanced expression of which was shown in cervical squamous cell carcinoma 58, and RCF4, for which an association between gene dosage and gene expression in cervical cancer has been previously described 32. In summary, besides PIK3CA and hTR, other genes located within the 3q gain are overexpressed in cervical carcinomas and may be good candidate marker genes as well. To enable reliable statistical testing we expanded our normal control group, of which we had limited amounts of high-quality RNA available, with normal squamous epithelium from another source. We are aware of the fact that the heterogeneity within our normal control group may have resulted in the identification of lower numbers of significantly differentially expressed genes. Nonetheless, this approach apparently did not result in false positive outcomes of identified differentially expressed genes since we were able to validate their differential expression in a separate set of samples, in which only normal cervical tissue specimens were used as controls. Another limitation of this study is the relatively small sample size. We would like to emphasize that identification of genes showing significant upregulation in tumours associated with increased copy number of the gene locus in such a small sample group indicates that altered structure and activity of these genes are common in cervical carcinomas. This is supported by confirmation of increased expression of a subset of these genes in an independent validation sample set. We do realise that a larger sample size is needed to identify genes that are less strongly affected. In conclusion, this study shows that integrated genome-wide transcriptional and chromosomal profiling of cervical carcinomas appears a promising strategy for fine mapping of large chromosomally altered regions to identify loci with altered gene expression that might be biologically meaningful. Further studies of the genes identified in this study are needed to assess their biological relevance in (cervical) carcinogenesis as well as their potential value as

132 Chapter 5 biomarker for improved detection of high-grade cervical lesions and carcinomas.

Acknowledgements We are thankful to Folkert van Kemenade for histological assessment of all samples included in this study. We thank Muriël Verkuijten and Paul Eijk for excellent technical assistance with microarray experiments. Mark van de Wiel, Marcel van Verk and Paul van den IJssel are highly acknowledged for their contribution to the data analysis.

References

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14. Hidalgo A, Baudis M, Petersen I, Arreola H, Pina P, Vazquez-Ortiz G et al. Microarray comparative genomic hybridization detection of chromosomal imbalances in uterine cervix carcinoma. BMC Cancer 2005;5:77. 15. Chao A, Wang TH, Lee YS, Hsueh S, Chao AS, Chang TC et al. Molecular characterization of adenocarcinoma and squamous carcinoma of the uterine cervix using microarray analysis of gene expression. Int J Cancer 2006;119:91-8. 16. Chen Y, Miller C, Mosher R, Zhao X, Deeds J, Morrissey M et al. Identification of cervical cancer markers by cDNA and tissue microarrays. Cancer Res 2003;63:1927-35. 17. Cheng Q, Lau WM, Tay SK, Chew SH, Ho TH, and Hui KM. Identification and characterization of genes involved in the carcinogenesis of human squamous cell cervical carcinoma. Int J Cancer 2002;98:419-26. 18. Santin AD, Zhan F, Bignotti E, Siegel ER, Cane S, Bellone S et al. Gene expression profiles of primary H. Virology 2005;331:269-91. 19. Sopov I, Sorensen T, Magbagbeolu M, Jansen L, Beer K, Kuhne-Heid R et al. Detection of cancer-related gene expression profiles in severe cervical neoplasia. Int J Cancer 2004;112:33-43. 20. Wong YF, Cheung TH, Tsao GS, Lo KW, Yim SF, Wang VW et al. Genome-wide gene expression profiling of cervical cancer in Hong Kong women by oligonucleotide microarray. Int J Cancer 2006;118:2461-9. 21. Gius D, Funk MC, Chuang EY, Feng S, Huettner PC, Nguyen L et al. Profiling microdissected epithelium and stroma to model genomic signatures for cervical carcinogenesis accommodating for covariates. Cancer Res 2007;67:7113-23. 22. van Wieringen WN, Belien JA, Vosse SJ, Achame EM, and Ylstra B. ACE-it: a tool for genome-wide integration of gene dosage and RNA expression data. Bioinformatics 2006;22:1919-20. 23. Yi Y, Mirosevich J, Shyr Y, Matusik R, and George AL, Jr. Coupled analysis of gene expression and chromosomal location. Genomics 2005;85:401-12. 24. van den Brule AJ, Pol R, Fransen-Daalmeijer N, Schouls LM, Meijer CJ, and Snijders PJ. GP5+/6+ PCR followed by reverse line blot analysis enables rapid and high- throughput identification of human papillomavirus genotypes. J Clin Microbiol 2002;40:779-87. 25. Braakhuis BJ, Senft A, de Bree R, de Vries J, Ylstra B, Cloos J et al. Expression profiling and prediction of distant metastases in head and neck squamous cell carcinoma. J Clin Pathol 2006;59:1254-60. 26. Muris JJ, Ylstra B, Cillessen SA, Ossenkoppele GJ, Kluin-Nelemans JC, Eijk PP et al. Profiling of apoptosis genes allows for clinical stratification of primary nodal diffuse large B-cell lymphomas. Br J Haematol 2007;136:38-47. 27. Smyth GK. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 2004;3:Article3. 28. Rogojina AT, Orr WE, Song BK, and Geisert EE, Jr. Comparing the use of Affymetrix to spotted oligonucleotide microarrays using two retinal pigment epithelium cell lines. Mol Vis 2003;9:482-96. 29. Contag SA, Gostout BS, Clayton AC, Dixon MH, McGovern RM, and Calhoun ES. Comparison of gene expression in squamous cell carcinoma and adenocarcinoma of the uterine cervix. Gynecol Oncol 2004;95:610-7. 30. Slebos RJ, Yi Y, Ely K, Carter J, Evjen A, Zhang X et al. Gene expression differences associated with human papillomavirus status in head and neck squamous cell carcinoma. Clin Cancer Res 2006;12:701-9. 31. Wise-Draper TM, Allen HV, Thobe MN, Jones EE, Habash KB, Munger K et al. The human DEK proto-oncogene is a senescence inhibitor and an upregulated target of high-risk human papillomavirus E7. J Virol 2005;79:14309-17. 32. Narayan G, Bourdon V, Chaganti S, Arias-Pulido H, Nandula SV, Rao PH et al. Gene dosage alterations revealed by cDNA microarray analysis in cervical cancer:

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identification of candidate amplified and overexpressed genes. Genes Chromosomes Cancer 2007;46:373-84. 33. Fitzpatrick MA, Funk MC, Gius D, Huettner PC, Zhang Z, Bidder M et al. Identification of chromosomal alterations important in the development of cervical intraepithelial neoplasia and invasive carcinoma using alignment of DNA microarray data. Gynecol Oncol 2006;103:458-62. 34. Braakhuis BJ, Tabor MP, Kummer JA, Leemans CR, and Brakenhoff RH. A genetic explanation of Slaughter's concept of field cancerization: evidence and clinical implications. Cancer Res 2003;63:1727-30. 35. Braakhuis BJ, Leemans CR, and Brakenhoff RH. Using tissue adjacent to carcinoma as a normal control: an obvious but questionable practice. J Pathol 2004;203:620-1. 36. Chu TY, Shen CY, Lee HS, and Liu HS. Monoclonality and surface lesion-specific microsatellite alterations in premalignant and malignant neoplasia of uterine cervix: a local field effect of genomic instability and clonal evolution. Genes Chromosomes Cancer 1999;24:127-34. 37. Hatta M, Nagai H, Okino K, Onda M, Yoneyama K, Ohta Y et al. Down-regulation of members of glycolipid-enriched membrane raft gene family, MAL and BENE, in cervical squamous cell cancers. J Obstet Gynaecol Res 2004;30:53-8. 38. Vazquez-Ortiz G, Pina-Sanchez P, Vazquez K, Duenas A, Taja L, Mendoza P et al. Overexpression of cathepsin F, matrix metalloproteinases 11 and 12 in cervical cancer. BMC Cancer 2005;5:68. 39. Wu D, Suo Z, Kristensen GB, Li S, Troen G, Holm R et al. Prognostic value of EphA2 and EphrinA-1 in squamous cell cervical carcinoma. Gynecol Oncol 2004;94:312-9. 40. Takeyama K, Aguiar RC, Gu L, He C, Freeman GJ, Kutok JL et al. The BAL-binding protein BBAP and related Deltex family members exhibit ubiquitin-protein isopeptide ligase activity. J Biol Chem 2003;278:21930-7. 41. Radtke F and Raj K. The role of Notch in tumorigenesis: oncogene or tumour suppressor? Nat Rev Cancer 2003;3:756-67. 42. Talora C, Sgroi DC, Crum CP, and Dotto GP. Specific down-modulation of Notch1 signaling in cervical cancer cells is required for sustained HPV-E6/E7 expression and late steps of malignant transformation. Genes Dev 2002;16:2252-63. 43. Zagouras P, Stifani S, Blaumueller CM, Carcangiu ML, and Artavanis-Tsakonas S. Alterations in Notch signaling in neoplastic lesions of the human cervix. Proc Natl Acad Sci U S A 1995;92:6414-8. 44. Nobukuni T, Joaquin M, Roccio M, Dann SG, Kim SY, Gulati P et al. Amino acids mediate mTOR/raptor signaling through activation of class 3 phosphatidylinositol 3OH- kinase. Proc Natl Acad Sci U S A 2005;102:14238-43. 45. Wood LD, Parsons DW, Jones S, Lin J, Sjoblom T, Leary RJ et al. The genomic landscapes of human breast and colorectal cancers. Science 2007;318:1108-13. 46. Bader AG, Kang S, Zhao L, and Vogt PK. Oncogenic PI3K deregulates transcription and translation. Nat Rev Cancer 2005;5:921-9. 47. Bertelsen BI, Steine SJ, Sandvei R, Molven A, and Laerum OD. Molecular analysis of the PI3K-AKT pathway in uterine cervical neoplasia: frequent PIK3CA amplification and AKT phosphorylation. Int J Cancer 2006;118:1877-83. 48. Yoshida M, Yamasaki K, Daiho T, Iizuka H, and Suzuki H. ATP2C1 is specifically localized in the basal layer of normal epidermis and its depletion triggers keratinocyte differentiation. J Dermatol Sci 2006;43:21-33. 49. Sugita M, Tanaka N, Davidson S, Sekiya S, Varella-Garcia M, West J et al. Molecular definition of a small amplification domain within 3q26 in tumors of cervix, ovary, and lung. Cancer Genet Cytogenet 2000;117:9-18. 50. Alazawi W, Pett M, Strauss S, Moseley R, Gray J, Stanley M et al. Genomic imbalances in 70 snap-frozen cervical squamous intraepithelial lesions: associations with lesion grade, state of the HPV16 E2 gene and clinical outcome. Br J Cancer 2004;91:2063-70.

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51. Kirchhoff M, Rose H, Petersen BL, Maahr J, Gerdes T, Lundsteen C et al. Comparative genomic hybridization reveals a recurrent pattern of chromosomal aberrations in severe dysplasia/carcinoma in situ of the cervix and in advanced-stage cervical carcinoma. Genes Chromosomes Cancer 1999;24:144-50. 52. Kirchhoff M, Rose H, Petersen BL, Maahr J, Gerdes T, Philip J et al. Comparative genomic hybridization reveals non-random chromosomal aberrations in early preinvasive cervical lesions. Cancer Genet Cytogenet 2001;129:47-51. 53. Ma YY, Wei SJ, Lin YC, Lung JC, Chang TC, Whang-Peng J et al. PIK3CA as an oncogene in cervical cancer. Oncogene 2000;19:2739-44. 54. Goto T, Takano M, Sasa H, Tsuda H, Yamauchi K, and Kikuchi Y. Clinical significance of immunocytochemistry for PIK3CA as a carcinogenesis-related marker on liquid-based cytology in cervical intraepithelial neoplasia. Oncol Rep 2006;15:387- 91. 55. Heselmeyer-Haddad K, Janz V, Castle PE, Chaudhri N, White N, Wilber K et al. Detection of genomic amplification of the human telomerase gene (TERC) in cytologic specimens as a genetic test for the diagnosis of cervical dysplasia. Am J Pathol 2003;163:1405-16. 56. Heselmeyer-Haddad K, Sommerfeld K, White NM, Chaudhri N, Morrison LE, Palanisamy N et al. Genomic amplification of the human telomerase gene (TERC) in pap smears predicts the development of cervical cancer. Am J Pathol 2005;166:1229- 38. 57. Kanao H, Enomoto T, Kimura T, Fujita M, Nakashima R, Ueda Y et al. Overexpression of LAMP3/TSC403/DC-LAMP promotes metastasis in uterine cervical cancer. Cancer Res 2005;65:8640-5. 58. Wang PH, Lee WL, Lee YR, Juang CM, Chen YJ, Chao HT et al. Enhanced expression of alpha 2,6-sialyltransferase ST6Gal I in cervical squamous cell carcinoma. Gynecol Oncol 2003;89:395-401.

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SUPPLEMENTARY TABLES

locus genes C1orf106; CACNA1S; TMEM9; PKP1; TNNT2; LAD1; NAV1; IPO9; LMOD1; TIMM17A; RNPEP; ELF3; PTPN7; UBE2T; PPP1R12B; JARID1B; RABIF; KLHL12; ADIPOR1; CYB5R1; TMEM183A; PPFIA4; MYBPH; CHI3L1; BTG2; 1q32.1 FMOD; PRELP; OPTC; ATP2B4; ZC3H11A; SNRPE; SOX13; ETNK2; PLEKHA6; PPP1R15B; PIK3C2B; MDM4; LRRN2; RBBP5; RIPK5; KLHDC8A; PCTK3; DKFZp564C1416; FLJ21291; ELK4; NUCKS1; RAB7L1; FLJ13904; AVPR1B; CTSE; IKBKE

B4GALT4; CDGAP; TMEM39A; KTELC1; C3orf1; PLA1A; COX17; C3orf15; NR1I2; GSK3B; FSTL1; NDUFB4; HGD; RABL3; GTF2E1; HCLS1; GOLGB1; EAF2; SLC15A2; CD86; CSTA; WDR5B; KPNA1; DTX3L; PARP14; HSPBAP1; PDIA5; SEC22A; ADCY5; PTPLB; MYLK; CCDC14; KALRN; UMPS; ITGB5; SLC12A8; ZNF148; SNX4; DKFZp564A2116; OSBPL11; SLC41A3; ALDH1L1; 3q13.32-q22.3 KLF15; ZXDC; TXNRD3; GPR175; MCM2; PODXL2; MGLL; RUVBL1; EEFSEC; FLJ21000; RPN1; ACAD9; KIAA1257; GP9; KIAA1160; FLJ13973; CNBP; COPG; H1FX; RPL32P3; MBD4; IFT122; PLXND1; TMCC1; FLJ22198; PIK3R4; ATP2C1; ASTE1; NEK11; NUDT16P; MRPL3; ACPP; DNAJC13; ACAD11; CCRL1; UBA5; CDV3; TOPBP1; SLCO2A1; RYK; AMOTL2; ANAPC13; CEP63; EPHB1; PPP2R3A; PCCB; STAG1

ZMAT3; PIK3CA; FLJ12091; FLJ11448; ZNF639; MFN1; GNB4; ACTL6A; MRPL47; NDUFB5; USP13; PEX5L; CCDC39; FXR1; SOX2OT; ATP11B; DCUN1D1; MCCC1; LAMP3; MCF2L2; KLHL6; KLHL24; YEATS2; PARL; 3q26.32-q27.3 ABCC5; EIF2B5; DVL3; AP2M1; ABCF3; ALG3; EIF4G1; FAM131A; CLCN2; POLR2H; CHRD; EPHB3; MAGEF1; VPS8; EHHADH; MAP3K13; FLJ10189; SFRS10; ETV5; CRYGS; TBCCD1; DNAJB11; AHSG; AHSG; EIF4A2; RFC4; ST6GAL1; RPL39L; MASP1; RTP4; SST; FLJ21428; LPP; DKFZp586A061

TRRAP; ARPC1B; PDAP1; BUD31; PTCD1; CPSF4; ATP5J2; ZNF394; ZKSCAN5; C7orf38; ZNF655; ZNF3; ZNF268; COPS6; MCM7; AP4M1; TAF6; 7q22.1 GAL3ST4; STAG3; PILRA; ZCWPW1; MEPCE; HRBL; LRCH4; PCOLCE; TFR2; GNB2; PERQ1; POP7; EPHB4; SLC12A9; ARS2; ACHE; MUC3A; MUC12; FLJ11958; SERPINE1; AP1S1; PLOD3; ZNHIT1; DKFZp547L144; FIS1

FUBP3; PRDM12; EXOSC2; ABL1; LAMC3; C9orf58; NUP214; FAM78A; POMT1; UCK1; RAPGEF1; MED27; NTNG2; SETX; DDX31; GTF3C4; C9orf9; 9q34.11-q34.2 TSC1; EEF1A1; GTF3C5; ABO; MED22; SURF1; SURF2; SURF4; REXO4; C9orf7; SLC2A6; ADAMTSL2; VAV2; FLJ23227; WDR5

POLR3K; C16orf33; RHBDF1; MPG; C16orf35; HBZ; LUC7L; RGS11; PDIA2; AXIN1; MRPL28; TMEM8; NME4; DECR2; RAB11FIP3; SOLH; PIGQ; 16p13.3 RAB40C; RHOT2; RHBDL1; STUB1; NARFL; MSLN; CHTF18; LMF1; CACNA1H; UBE2I; BAIAP3; GNPTG; UNKL; CLCN7; TELO2; IFT140; TMEM204; HN1L; MAPK8IP3; NME3; NUBP2; HAGH

OPTC; ATP2B4; ZC3H11A; SNRPE; SOX13; ETNK2; PLEKHA6; PPP1R15B; PIK3C2B; MDM4; LRRN2; RBBP5; RIPK5; KLHDC8A; PCTK3; 1q32.1-q32.2 DKFZp564C1416; FLJ21291; ELK4; NUCKS1; RAB7L1; FLJ13904; AVPR1B; CTSE; IKBKE; LGTN; DYRK3; IL20; IL24; FAIM3; PIGR; PFKFB2; C4BPB; C4BPA; CD55; CR2

KIAA0649; MRPS2; PAEP; CAMSAP1; UBAC1; C9orf69; GPSM1; CARD9; 9q34.3 SNAPC4; SDCCAG3; PMPCA; INPP5E; SEC16A; NOTCH1; EGFL7; AGPAT2; C9orf86; EDF1; FBXW5; PTGDS; CLIC3; ABCA2

FZR1; C19orf28; C19orf29; PIP5K1C; TJP3; MATK; KIAA1086; DAPK3; PIAS4; MAP2K2; SIRT6; CCDC94; FSD1; STAP2; SH3GL1; C19orf10; TICAM1; 19p13.3 M6PRBP1; UHRF1; PTPRS; SAFB2; SAFB; RPL36; LONP1; DUS3L; FUT6; NRTN; CAPS; RANBP3; RFX2; ZNF445; MLLT1; CLPP; KHSRP; CRB3; DENND1C Supplementary Table 1: Genes located within the regions identified by DIGMAP. Genes printed in bold also showed significantly differential expression in LIMMA analysis.

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GenBank Acc No Gene symbol Cytoband FDR NM_007262 PARK7* 1p36.23 0.175 NM_020235 BBX* 3q13.12 0.140 AL137663 PHLDB2* 3q12.2 0.175 AK023256 NAT13* 3q13.2 0.180 NM_001690 ATP6V1A* 3q13.2 0.194 AK023022 QTRTD1* 3q13.31 0.176 NM_015642 ZBTB20* 3q13.31 0.194 AL442097 DKFZp547K204* 3q13.31 0.176 NM_018266 TMEM39A* 3q13.33 0.180 NM_016589 C3orf1* 3q13.33 0.14 NM_002093 GSK3B* 3q13.33 0.175 NM_005213 CSTA* 3q21.1 0.180 NM_002264 KPNA1* 3q21.1 0.180 AK026276 HSPBAP1* 3q21.1 0.140 NM_012430 SEC22A* 3q21.1 0.194 NM_000373 UMPS* 3q21.2 0.180 AF039019 ZNF148* 3q21.2 0.194 AL390142 ZXDC* 3q21.2 0.180 NM_004526 MCM2* 3q21.3 0.140 NM_014049 ACAD9* 3q21.3 0.140 AB032986 KIAA1160* 3q21.3 0.194 AK024035 FLJ13973* 3q21.3 0.14 NM_006026 H1FX* 3q21.3 0.149 NM_003925 MBD4* 3q21.3 0.180 Y08991 PIK3R4* 3q21.3 0.140 NM_007208 MRPL3* 3q21.3 0.140 NM_001099 ACPP* 3q22.1 0.180 AK023168 DNAJC13* 3q22.1 0.140 NM_007027 TOPBP1* 3q22.1 0.140 S59184 RYK* 3q22.1 0.140 AK001285 ANAPC13* 3q22.1 0.149 NM_002718 PPP2R3A* 3q22.2 0.176 NM_020191 MRPS22* 3q23 0.140 NM_018155 SLC25A36* 3q23 0.175 NM_001184 ATR* 3q23 0.140 NM_003478 CUL5** 11q22.3 0.181 NM_018195 SDHD** 11q23.1 0.181 NM_012459 TIMM8B** 11q23.1 0.181 NM_000317 PTS** 11q23.1 0.140 NM_015523 REXO2** 11q23.2 0.175 NM_004716 PCSK7** 11q23.3 0.197 NM_004788 UBE4A** 11q23.3 0.181 AF272373 MLL/ELL** 11q23.3 0.197 AF272371 MLL** 11q23.3 0.140 NM_001467 SLC37A4** 11q23.3 0.149 NM_006389 HYOU1** 11q23.3 0.176 NM_015313 ARHGEF12** 11q23.3 0.198 NM_006176 NRGN** 11q24.2 0.180 AK000493 FLJ20486** 11q24.2 0.175 NM_003139 SRPR** 11q24.2 0.181 NM_005238 ETS1** 11q24.3 0.198 NM_014384 ACAD8** 11q25 0.181 AK024825 FLJ21172** 18q23 0.149 NM_018848 MKKS* 20p12.2 0.180

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NM_003098 SNTA1* 20q11.21 0.180 NM_002951 RPN2* 20q11.23 0.176 AB033045 KIAA1219* 20q11.23 0.140 NM_005461 MAFB* 20q12 0.194 NM_016470 C20orf111* 20q13.12 0.149 NM_006811 SERINC3* 20q13.12 0.140 NM_003404 YWHAB* 20q13.12 0.180 AK027088 STK4* 20q13.12 0.198 NM_001316 CSE1L* 20q13.13 0.149 NM_017453 STAU* 20q13.13 0.175 NM_004776 B4GALT5* 20q13.13 0.181 NM_003859 DPM1* 20q13.13 0.176 AK025758 FLJ22105* 20q13.2 0.198 AF091034 RAB22A* 20q13.32 0.140 AK001603 GTPBP5* 20q13.33 0.198 NM_014835 OSBPL2* 20q13.33 0.198 NM_007002 ADRM1* 20q13.33 0.198 NM_017896 C20orf11* 20q13.33 0.18 NM_018257 PCMTD2* 20q13.33 0.176 Supplementary Table 2: Genes that showed direct linkage between expression and copy numbers as determined by ACE-it. *: Genes showing elevated expression in tumours with a chromosomal gain compared to tumours without a chromosomal alteration; **: Genes showing decreased expression in tumours with a chromosomal loss compared to tumours without a chromosomal alteration; Genes printed in bold are identified by DIGMAP analysis as well, whereas the underlined gene showed significantly differential expression in LIMMA analysis.; FDR: False Discovery Rate

139 Integrated chromosomal and transcriptional profiling

140 Chapter 6

Summary & Discussion

Summary and Discussion

Summary & Discussion Cervical cancer develops over a long period of time as a result of a persistent infection with hrHPV. The main 2 histotypes of cervical cancer i.e. squamous cell carcinoma (SCC) and adenocarcinoma (AdCa) are preceded by precursor lesions. Precursor lesions of SCCs are called Cervical Intraepithelial Neoplasia (CIN). Depending on the degree of atypia CIN can be differentiated in 3 grades i.e. CIN1 (minor atypia), CIN2 (moderate atypia) and CIN3 (severe atypia). Progression of an hrHPV-induced premalignant lesion to invasive cancer is driven by the accumulation of genetic and epigenetic alterations in the host cell genome. Identification of these alterations will not only improve our understanding of cancer biology, but may lead to new screening tools and new (immuno)therapeutic strategies. Present screening programs are based on the cytomorphological assessment of abnormal cells in cervical scrapes, the so-called Pap-test. Recent randomized- controlled, prospective trials have shown that testing for hrHPV positivity in cervical screening programs results in earlier detection of clinically relevant cervical precursor lesions, enables better detection of AdCA and its precursor lesions and greatly reduces the number of false-negative smears 1-3. However, hrHPV testing also results in the detection of women with transient hrHPV infections who do not have or will develop cervical cancer precursor lesions and for whom follow-up examinations are redundant. Presently, cytology is recommended for risk stratification of hrHPV-positive women, and women with abnormal cytology (threshold BMD or worse) should be referred for colposcopy. Since, however, hrHPV positive women with normal cytology have an increased risk compared to those without hrHPV, additional reliable disease markers are needed as triage tool. Although prophylactic vaccination against HPV16 and 18 has recently been implemented for pre-pubertal women in many countries 4,5, the current vaccines do not achieve full protection against non-HPV16,-18 associated cervical cancer and its precursor lesions. In addition, the vaccines have no effect on existing infections with HPV 16,-18 and consequently, cervical screening remains necessary in the foreseeable future 6,7. Most studies aiming at the identification of cervical disease markers are based on the molecular analysis of cervical carcinomas and its precursor lesions. However, to obtain functional insight in the biologically relevant events and in order to reduce complexity, the study of in vitro models mimicking the multistep process of HPV-induced carcinogenesis is crucial. Previous work by

142 Chapter 6 others and us has revealed that hrHPV types can induce immortalization of primary human keratinocytes in vitro 8,9. Primary keratinocytes normally have a limited lifespan due to telomere shortening 10. Expression of the viral oncogenes in primary cells induces a state of genetic instability from which immortal clones may emerge. These immortal cells display strong telomerase activity, a necessary event for maintenance of telomeres and consequently the immortal phenotype 11. In this thesis an in vitro model of hrHPV-transfected keratinocytes was studied, aiming at unravelling molecular events underlying HPV-mediated transformation, with a special focus on the phenotype immortalization. In addition, we performed an integrated analysis of chromosome and expression profiles of cervical carcinomas, as an alternative approach to get more insight into cervical carcinogenesis.

Mechanisms underlying hTERT deregulation during HPV-mediated immortalization In chapter 2 we examined what mechanisms may underlie hTERT deregulation in hrHPV transformed cell lines. Using luciferase reporter constructs we analyzed the transcriptional activity of various hTERT promoter regions as well as proximal exonic/intronic sequences and determined the relationship with epigenetic modifications. Although most telomerase positive cells showing elevated hTERT mRNA expression revealed substantial hTERT core promoter activity, hTERT core promoter activity was also detected in telomerase negative cells with no or strongly reduced hTERT mRNA expression levels. Moreover, regulatory sequences flanking both ends of the core promoter markedly repressed promoter activity. Since this phenomenon was observed in both telomerase positive and negative cells we reasoned that epigenetic events might be involved in blocking this repressive effect in telomerase positive cells. Interestingly, by extensive bisulfite sequencing analysis of the region spanning nucleotides -442 to +566 (relative to the ATG) a marked increase in methylated CpGs was detected in hTERT positive cells compared to cells with no or strongly reduced hTERT expression. Subsequent analysis of cervical tissue specimens by methylation specific PCR (MSP) for two suppressive regions flanking the core promoter revealed methylation of both regions in 100% of cervical carcinomas and 38% of the high-grade precursor lesions, compared to 9% of low-grade precursor lesions and 5% of normal controls. Hence, the correlation between DNA methylation at these transcriptional repressive regions

143 Summary and Discussion and hTERT expression suggests that this methylation event is likely to contribute to hTERT deregulation in HPV-transformed cells. Its association with increasing severity of cervical disease suggests that hTERT methylation is also relevant for telomerase reactivation during cervical carcinogenesis.

Altered expression of AP-1 complex members and their regulatory genes during HPV-mediated transformation in vitro The transcription factor AP-1 represents an important mediator in many cancer- specific alterations in different human cancers 12. AP-1 does not only activate HPV transcription, but has also been found to interact with sequences 5’ of the hTERT core promoter, which we found to be suppressive in chapter 2. The AP- 1 transcription factor is a heterodimer consisting of a member of the Fos gene family, i.e. c-Fos, FosB, Fra-1 and Fra-2, and a member of the Jun family, i.e. c-Jun, JunB or JunD. Depending on its composition this complex is involved in the positive and/or negative regulation of several genes (reviewed by 12). Alterations in AP-1 complex composition have been associated with tumorigenicity during cervical carcinogenesis in vitro and in vivo 13-15. In normal cells Fra-1 is expressed and the AP-1 complex consists primarily of Fra- 1/c-Jun heterodimers, while in tumorigenic cells c-Fos is upregulated resulting in a shift to c-Fos/c-Jun heterodimers. In chapter 3 we aimed to obtain further insight in expression alterations of AP-1 family members during HPV-mediated transformation and their relationship to potential regulatory (Notch1, Net) and target (CADM1) genes. mRNA expression levels of all AP-1 complex members (c-Jun, JunB, JunD, c-Fos, FosB, Fra-1, and Fra-2) as well as Notch1, Net and CADM1 were determined by quantitative RT-PCR in primary keratinocytes, early and late passages of non-tumorigenic HPV-immortalized keratinocytes and in tumorigenic cervical cancer cell lines. In a subset of cell lines protein expression and AP-1 complex composition were determined as well. Starting in immortal stages c-Fos, Fra-2 and JunB expression became up regulated towards tumorigenicity, whereas Fra-1, c-Jun, Notch1, Net and CADM1 became down regulated. The onset of deregulated expression varied amongst the AP-1 members and was not directly related to altered Notch1, Net or CADM1 expression. Notwithstanding this, a shift in AP-1 complex composition from Fra-1/c-Jun to c-Fos/c-Jun heterodimers was only observed in tumorigenic cells. Thus, whereas the onset of deregulated expression of various AP-1 family members became already manifest during the immortal state, a shift in AP-1 complex composition appeared a late event associated with tumorigenicity.

144 Chapter 6

Altered gene expression associated with deregulated hTERT in vitro The study in Chapter 4 aimed at getting more insight into the altered gene expression profiles associated with HPV-mediated immortalization, in particular telomerase activation. Our previous microcell-mediated chromosome transfer studies revealed that introduction of human chromosome 6 in the HPV16 immortalized keratinocyte cell line FK16A and in the HPV16 containing cervical cancer cell line SiHa induced growth arrest, resulting from a repression of hTERT mRNA expression and telomerase activity 16. To analyze expression profiles associated with hTERT deregulation in HPV transformed cells we performed microarray expression analysis on 12 FK16A/chromosome 6 hybrids, four of which were negative for endogenous hTERT and 8 of which were positive for endogenous hTERT. This resulted in the identification of 164 differentially expressed genes and differential expression of a selection of 5 genes was verified by quantitative RT-PCR. Of these 164 genes, 32 were also differentially expressed in other HPV transformed cells with deregulated hTERT. For 2 of these genes, encoding AQP3 and MGP, altered expression in hTERT positive cervical carcinomas was confirmed by quantitative RT-PCR and immunohistochemistry, respectively. Moreover, increased MGP protein expression was significantly more frequent in high-grade cervical premalignant lesions with elevated hTERT mRNA expression compared to those without. Thus, we identified 32 candidate surrogate markers for deregulated hTERT mRNA expression, which may enable the identification of cervical premalignant lesions that are at highest risk to progress to invasive cancer.

Altered gene expression and commonly altered chromosomal regions in cervical carcinomas In chapter 5 we used an alternative approach to discover events that are relevant for cervical carcinogenesis. By integrating genome-wide chromosomal and transcriptional profiles of cervical carcinomas we aimed to detect altered expression patterns related to chromosomal alterations. Previous genomic profiling showed that gains at chromosomes 1q, 3q and 20q as well as losses at 8q, 10q, 11q and 13q were common in cervical carcinomas 17. Application of differential gene locus mapping (DIGMAP) analysis and the array CGH expression integration tool (ACE-it) identified hotspots within large chromosomal alterations in which gene expression was altered as well. Chromosomal gains of the long arms of chromosome 1, 3 and 20 resulted in

145 Summary and Discussion increased expression of genes located at 1q32.1-32.2, 3q13.32-23, 3q26.32- 27.3, and 20q11.21-13.33, whereas a chromosomal loss of 11q22.3-25 was related to decreased expression of genes located there. Overexpression of 4 genes located at chromosome 3q, DTX3L, PIK3R4, ATP2C1, and SLC25A36, as identified by DIGMAP, ACE-it or both, was confirmed in an independent validation set of cervical carcinomas and normal cervical tissues.

So, by studying both an in vitro model system of HPV16 and HPV18-immortalized cell lines and cervical tissue specimens, we gained more insight in the (epi)genetic processes and expression alterations associated with HPV-induced transformation, in particular hTERT deregulation and immortalization. hTERT transcriptional activity was shown to be regulated by both activating and suppressive promoter elements in HPV-immortalized cell lines. The suppressive elements revealed increasing levels of DNA methylation during HPV-induced transformation in vitro. In concordance with the in vitro results hTERT promoter methylation frequencies also increased with the histopathological grade of disease in cervical tissue samples. Next to the epigenetic modifications, changes in gene expression levels were demonstrated in this thesis. Expression of c-Fos family members, constituting part of the transcription complex AP-1, changed at immortalization of hrHPV-transfected cells, while an altered AP-1 complex composition was restricted to tumorigenic cells. Moreover, based on genome wide expression analysis a number of 32 genes, including MGP and AQ3, was identified that were differentially expressed upon telomerase activation in vitro. mRNA expression of another set of genes, such as DTX3L, PIK3R4, ATP2C1, and SLC25A36, was found to be commonly altered in cervical carcinomas as a result of chromosomal aberrations.

Future perspectives Following these observations it will be of utmost interest to determine biological relevance of the gene alterations identified in this thesis. hTERT regulation hTERT upregulation and concomitant telomerase activation, which are fundamental to immortality, were demonstrated to be correlated to methylation of repressive regulatory hTERT sequences. It remains, however, to be resolved

146 Chapter 6 whether methylation represents one of the most critical events inducing immortalization, or whether other factors, e.g. altered regulation of transcription factors, are the driving force. Moreover, it is not yet clear what determines aberrant hTERT methylation and which methylation sites are most essential. The very heterogeneous methylation patterns seen in individual alleles indicate that hTERT methylation is a very dynamic process. Unravelling the exact regulatory mechanisms will require a more detailed analysis using for example reporter constructs driven by in vitro methylated promoter elements tested in both presence and absence of HPV, as well as the analysis of other chromatin modulators e.g. by ChIP analysis. It will be interesting to determine whether there is any direct or indirect relation between hTERT upregulation (by these methylation events and/or any of the known hTERT transcriptional regulators) and the genes showing altered expression upon hTERT upregulation, as identified in chapter 4. Hereto both cDNA overexpression and RNA interferences studies using the in vitro model system are warranted.

Identifying new tumor suppressor genes Similarly, it also remains to be determined whether there are novel tumor suppressor genes amongst the down regulated genes identified in chapter 5. Functional studies on the HPV-transfected cell lines at different stages of transformation will allow us to pinpoint which phenotype the respective genes may impinge on. In fact, one of the down regulated genes identified in chapter 5, i.e., MAL, was in later studies found to act as a tumor suppressor gene in HPV–transformed cells 18. However, the exact mechanism by which MAL inactivation promotes tumorigenesis still remains to be resolved.

Identifying new oncoproteins from upregulated genes It is additionally of interest to find out whether identified upregulated genes code for oncoproteins that may actively contribute to HPV-induced carcinogenesis. Some of the upregulated genes identified herein are of particular interest, such as PIK3R4 and DTX3L, which are members for the PI3K-AKT and Notch signalling pathways, respectively. hrHPV E7 has been demonstrated to induce phosphorylation of AKT and increased levels of P-AKT have been described in cervical carcinomas and CIN lesions 19,20. Using our in vitro model system we more recently found that the PI3K/AKT pathway becomes activated

147 Summary and Discussion during hrHPV-induced transformation in vitro and future studies may tell us whether this is linked to PIK3R4 overexpression. As shown in chapter 3, Notch expression alters during passaging of our hrHPV transfected cell lines. Potentially the altered Notch expression may be related to altered DTX3L expression, encoding a deltex family protein known to regulate Notch degradation 21. However, present data on the role of Notch signalling in cervical carcinogenesis are inconsistent 22,23, necessitating further research.

Clinical implications As hrHPV testing is now being considered as an alternative for cytology-based cervical cancer screening, there is need for additional triage markers to distinguish hrHPV positive women who are in need of more intensive management because of a high risk for the development of cervical (pre)cancer. As stated above gene alterations associated with HPV-induced transformation as described in this thesis may provide such molecular markers. Recent studies have shown that hypermethylation of gene promoters can be reliably detected in cervical scrapings using quantitative MSP techniques 18,24 Presently ongoing studies are exploiting the diagnostic value of methylation markers in clinical practice by studying methylation frequencies in scrapings using both cross sectional studies as well as prospective population based studies, such as the POBASCAM trial 25. A number of novel methylation markers, such as CADM1 26, are attractive candidate triage markers. Additional methylation markers, to be deduced from the candidate marker genes identified in this thesis, might contribute to the composition of methylation marker panels displaying high sensitivity and specificity for clinically relevant CIN lesions and cervical cancer, one of which may be hTERT We identified the MAL gene as the most significantly downregulated gene in cervical carcinomas (chapter 5). In further studies silencing was found to result from promoter methylation, which was detected in 53% of high-grade CIN lesions and 90% of SCC 18. Similarly, also other down regulated genes identified in this thesis may be located within or near a CpG island, suggesting that decreased expression may result from promoter hypermethylation. As demonstrated for hTERT in chapter 2 we cannot exclude that also part of the upregulated genes may be regulated by DNA methylation. These genes may be either hypermethylated like hTERT, thereby inhibiting binding of methylation sensitive suppressive factors or hypomethylated, as described for several (candidate) oncogenes 27-30.

148 Chapter 6

With respect to the upregulated genes it will also be worthwhile to explore whether protein or mRNA overexpression can be measured in scrapings. It has yet been demonstrated that increased protein expression of p16INK4a and other cell cycle components such as MCM2, TOPIIα, PCNA and Ki-67 can be detected in cervical scrapings 31-33. Recent studies have also described the detection of altered mRNA expression levels in cervical scrapings. For example elevated KIF23 mRNA expression was demonstrated in cervical scrapings of cancer patients 34, and reduced MAL mRNA expression has been detected in cervical scraping of patients with high-grade CIN disease 18. Ultimately, a marker panel consisting of methylation markers, expression markers or a combination thereof is likely to become an attractive triage tool in future screen programs in which HPV testing will play a central role. The urgency of such a molecular marker panel will become reality in case self-collection of cervico-vaginal specimens is more accepted as screening tool, for which cytology is not an attractive option.

References

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9. Pirisi, L., Yasumoto, S., Feller, M., Doniger, J., and DiPaolo, J. A. Transformation of human fibroblasts and keratinocytes with human papillomavirus type 16 DNA. J.Virol., 61: 1061-1066, 1987. 10. Hayflick, L. The limited in vitro lifetime of human diploid cell strains. Exp.Cell Res., 37: 614-636, 1965. 11. Steenbergen, R. D., Walboomers, J. M., Meijer, C. J., van der Raaij-Helmer EM, Parker, J. N., Chow, L. T., Broker, T. R., and Snijders, P. J. Transition of human papillomavirus type 16 and 18 transfected human foreskin keratinocytes towards immortality: activation of telomerase and allele losses at 3p, 10p, 11q and/or 18q. Oncogene, 13: 1249-1257, 1996. 12. Eferl, R. and Wagner, E. F. AP-1: a double-edged sword in tumorigenesis. Nat.Rev.Cancer, 3: 859- 868, 2003. 13. Prusty, B. K. and Das, B. C. Constitutive activation of transcription factor AP-1 in cervical cancer and suppression of human papillomavirus (HPV) transcription and AP-1 activity in HeLa cells by curcumin. Int.J.Cancer, 113: 951-960, 2005. 14. Soto, U., Das, B. C., Lengert, M., Finzer, P., zur, H. H., and Rosl, F. Conversion of HPV 18 positive non-tumorigenic HeLa-fibroblast hybrids to invasive growth involves loss of TNF-alpha mediated repression of viral transcription and modification of the AP-1 transcription complex. Oncogene, 18: 3187-3198, 1999. 15. Soto, U., Denk, C., Finzer, P., Hutter, K. J., zur, H. H., and Rosl, F. Genetic complementation to non- tumorigenicity in cervical-carcinoma cells correlates with alterations in AP-1 composition. Int.J.Cancer, 86: 811-817, 2000. 16. Steenbergen, R. D., Kramer, D., Meijer, C. J., Walboomers, J. M., Trott, D. A., Cuthbert, A. P., Newbold, R. F., Overkamp, W. J., Zdzienicka, M. Z., and Snijders, P. J. Telomerase suppression by chromosome 6 in a human papillomavirus type 16-immortalized keratinocyte cell line and in a cervical cancer cell line. J.Natl.Cancer Inst., 93: 865-872, 2001. 17. Wilting, S. M., Snijders, P. J., Meijer, G. A., Ylstra, B., van den Ijssel, P. R., Snijders, A. M., Albertson, D. G., Coffa, J., Schouten, J. P., van de Wiel, M. A., Meijer, C. J., and Steenbergen, R. D. Increased gene copy numbers at chromosome 20q are frequent in both squamous cell carcinomas and adenocarcinomas of the cervix. J.Pathol., 209: 220-230, 2006. 18. Overmeer, R. M., Henken, F. E., Bierkens, M., Wilting, S. M., Timmerman, I., Meijer, C. J., Snijders, P. J., and Steenbergen, R. D. Repression of MAL tumour suppressor activity by promoter methylation during cervical carcinogenesis. J.Pathol., 219: 327-336, 2009. 19. Bertelsen, B. I., Steine, S. J., Sandvei, R., Molven, A., and Laerum, O. D. Molecular analysis of the PI3K-AKT pathway in uterine cervical neoplasia: frequent PIK3CA amplification and AKT phosphorylation. Int.J.Cancer, 118: 1877-1883, 2006. 20. Menges, C. W., Baglia, L. A., Lapoint, R., and McCance, D. J. Human papillomavirus type 16 E7 up- regulates AKT activity through the retinoblastoma protein. Cancer Res., 66: 5555-5559, 2006. 21. Lai, E. C. Protein degradation: four E3s for the notch pathway. Curr.Biol., 12: R74-R78, 2002. 22. Radtke, F. and Raj, K. The role of Notch in tumorigenesis: oncogene or tumour suppressor? Nat.Rev.Cancer, 3: 756-767, 2003. 23. Maliekal, T. T., Bajaj, J., Giri, V., Subramanyam, D., and Krishna, S. The role of Notch signaling in human cervical cancer: implications for solid tumors. Oncogene, 27: 5110-5114, 2008. 24. Reesink-Peters, N., Wisman, G. B., Jeronimo, C., Tokumaru, C. Y., Cohen, Y., Dong, S. M., Klip, H. G., Buikema, H. J., Suurmeijer, A. J., Hollema, H., Boezen, H. M., Sidransky, D., and van der Zee, A. G. Detecting cervical cancer by quantitative promoter hypermethylation assay on cervical scrapings: a feasibility study. Mol.Cancer Res., 2: 289-295, 2004. 25. Bulkmans, N. W., Rozendaal, L., Snijders, P. J., Voorhorst, F. J., Boeke, A. J., Zandwijken, G. R., van Kemenade, F. J., Verheijen, R. H., Groningen, K., Boon, M. E., Keuning, H. J., van Ballegooijen, M., van den Brule, A. J., and Meijer, C. J. POBASCAM, a population-based randomized controlled trial for implementation of high-risk HPV testing in cervical screening: design, methods and baseline data of 44,102 women. Int.J.Cancer, 110: 94-101, 2004. 26. Overmeer, R. M., Henken, F. E., Snijders, P. J., Claassen-Kramer, D., Berkhof, J., Helmerhorst, T. J., Heideman, D. A., Wilting, S. M., Murakami, Y., Ito, A., Meijer, C. J., and Steenbergen, R. D. Association between dense CADM1 promoter methylation and reduced protein expression in high- grade CIN and cervical SCC. J.Pathol., 215: 388-397, 2008. 27. Goldstein, M., Meller, I., and Orr-Urtreger, A. FGFR1 over-expression in primary rhabdomyosarcoma tumors is associated with hypomethylation of a 5' CpG island and abnormal expression of the AKT1, NOG, and BMP4 genes. Genes Chromosomes.Cancer, 46: 1028-1038, 2007. 28. Honda, T., Tamura, G., Waki, T., Kawata, S., Terashima, M., Nishizuka, S., and Motoyama, T. Demethylation of MAGE promoters during gastric cancer progression. Br.J.Cancer, 90: 838-843, 2004.

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29. Kato, N., Tamura, G., and Motoyama, T. Hypomethylation of hepatocyte nuclear factor-1beta (HNF- 1beta) CpG island in clear cell carcinoma of the ovary. Virchows Arch., 452: 175-180, 2008. 30. Choi, E. K., Uyeno, S., Nishida, N., Okumoto, T., Fujimura, S., Aoki, Y., Nata, M., Sagisaka, K., Fukuda, Y., Nakao, K., Yoshimoto, T., Kim, Y. S., and Ono, T. Alterations of c-fos gene methylation in the processes of aging and tumorigenesis in human liver. Mutat.Res., 354: 123-128, 1996. 31. Goel, M. M., Mehrotra, A., Singh, U., Gupta, H. P., and Misra, J. S. MIB-1 and PCNA immunostaining as a diagnostic adjunct to cervical Pap smear. Diagn.Cytopathol., 33: 15-19, 2005. 32. Shroyer, K. R., Homer, P., Heinz, D., and Singh, M. Validation of a novel immunocytochemical assay for topoisomerase II-alpha and minichromosome maintenance protein 2 expression in cervical cytology. Cancer, 108: 324-330, 2006. 33. Wentzensen, N., Bergeron, C., Cas, F., Eschenbach, D., Vinokurova, S., and von Knebel, D. M. Evaluation of a nuclear score for p16INK4a-stained cervical squamous cells in liquid-based cytology samples. Cancer, 105: 461-467, 2005. 34. Gius, D., Funk, M. C., Chuang, E. Y., Feng, S., Huettner, P. C., Nguyen, L., Bradbury, C. M., Mishra, M., Gao, S., Buttin, B. M., Cohn, D. E., Powell, M. A., Horowitz, N. S., Whitcomb, B. P., and Rader, J. S. Profiling microdissected epithelium and stroma to model genomic signatures for cervical carcinogenesis accommodating for covariates. Cancer Res., 67: 7113-7123, 2007.

151 Summary and Discussion

152 Chapter 7

Nederlandse Samenvatting

Nederlandse samenvatting

Nederlandse samenvatting

Nieuwe inzichten in moleculaire veranderingen die optreden tijdens transformatie door HPV Wereldwijd is baarmoederhalskanker de op een na meest voorkomende vorm van kanker bij vrouwen. Met name door de invoering van een bevolkingsonderzoek is het voorkomen van deze ziekte in ontwikkelde landen de afgelopen decennia sterk gedaald. De ontwikkeling van baarmoederhalskanker is een langdurig proces van vele jaren (12 tot 30 jaar) en is het gevolg van een persisterende infectie met hoog- risico humaan papilloma virussen (hrHPV). Er kunnen twee typen baarmoederhalskanker worden onderscheiden, namelijk plaveiselcelcarcinomen (SCC) en adenocarcinomen (AdCa), welke worden voorafgegaan door voorloperlaesies. De voorloperlaesies van SCC worden ook wel cervicale intraepitheliale neoplasieën (CIN) genoemd. CIN laesies kunnen worden gegradeerd van 1 tot 3 met toenemende ernst van de afwijking. Progressie van een hrHPV bevattende CIN laesie tot een invasief carcinoom is het resultaat van een opeenstapeling van genetische en epigenetische veranderingen in het genoom van de gastvrouwcel. Het identificeren van deze veranderingen zal niet alleen leiden tot een verbeterd inzicht in de biologie van baarmoederhalskanker, maar ook tot nieuwe strategieën voor bevolkingsonderzoek, diagnostiek en (immuno)therapie. Het huidige bevolkingsonderzoek voor baarmoederhalskanker is gebaseerd op de cytologische beoordeling van uitstrijkjes van de baarmoederhals, de zogenaamde Pap-test. Recente studies hebben uitgewezen dat het testen op de aanwezigheid van hrHPV in uitstrijkjes leidt tot een verbetering van het huidige bevolkingsonderzoek, doordat voorloperlaesies en adenocarcinomen eerder ontdekt worden en er nagenoeg geen vals negatieve uitstrijkjes meer worden afgegeven. Ondanks deze zeer goede negatieve voorspellende waarde, resulteert het testen op de aanwezigheid van hrHPV ook in de detectie van relatief onschuldige HPV infecties die niet zullen leiden tot baarmoederhalskanker. Om de specificiteit van een hrHPV test te verbeteren is er behoefte aan een additionele test op zogenaamde ziektemerkers, welke binnen de groep van hrHPV-positieve vrouwen kan voorspellen wie er daadwerkelijk een verhoogd risico op baarmoederhalskanker heeft. Alhoewel er recentelijk twee profylactische vaccins zijn ontwikkeld voor de twee meest voorkomende hrHPV typen 16 en 18, geven deze vaccins geen bescherming tegen infectie met

154 Chapter 7 de andere hrHPV typen die baarmoederhalskanker kunnen veroorzaken. Tevens hebben deze vaccins geen effect op reeds bestaande infecties met HPV type 16 en type 18. Het bevolkingsonderzoek naar baarmoederhalskanker blijft daarom nog steeds nodig in de toekomst. De meeste studies die als doel hebben ziektemerkers voor baarmoederhalskanker te identificeren, zijn gebaseerd op de analyse van (epi)genetische veranderingen in baarmoederhalstumoren en bijbehorende voorloperlaesies. Om echter inzicht te verkrijgen in de veranderingen die biologisch relevant zijn, zijn in vitro modellen die het ontstaan van baarmoederhalskanker nabootsen heel belangrijk. Eerdere onderzoeken, onder andere uitgevoerd op ons lab, hebben uitgewezen dat hrHPV gekweekte primaire humane epitheelcellen, keratinocyten, kan immortaliseren, wat betekent dat deze cellen oneindig vaak kunnen delen. Normaal gesproken hebben primaire cellen een beperkte delingscapaciteit en levensduur, omdat de chromosoomeinden, de telomeren, bij elke celdeling verkorten. Aanwezigheid van een hrHPV type en expressie van de virale oncogenen resulteert in genetische instabiliteit, hetgeen kan leiden tot immortalisatie. In deze immortale cellen is een enzym genaamd telomerase geactiveerd dat de telomeren verlengt.

Om meer inzicht te krijgen in het ontstaan van baarmoederhalskanker is in dit proefschrift een in vitro model voor baarmoederhalskanker bestudeerd. Het onderzoek heeft zich met name gericht op het ontrafelen van de (epi)genetische veranderingen die betrokken zijn bij de transformatie van cellen door hrHPV typen, met speciale aandacht voor het proces van immortalisatie. Tevens zijn genetische veranderingen zowel op chromosoomniveau als op genexpressieniveau in baarmoederhalstumoren in kaart gebracht.

Regulatie van telomerase activiteit in HPV-geïmmortaliseerde cellen Expressie van het katalytische deel van het telomerase complex, hTERT, is grotendeels bepalend voor de activiteit van telomerase. In Hoofdstuk 2 is onderzocht hoe hTERT expressie ontregeld wordt in hrHPV geïmmortaliseerde cellen. Door middel van reporter constructen is de transcriptionele activiteit van verschillende delen van de hTERT promoter en flankerende gebieden bepaald. hTERT promoter activiteit werd niet alleen gevonden in cellen met hTERT expressie maar ook in cellen zonder hTERT expressie. Hiernaast werd in zowel hTERT positieve als negatieve cellen de activiteit van de hTERT kernpromoter

155 Nederlandse samenvatting onderdrukt door flankerende sequenties. Deze bevindingen wijzen erop dat wellicht epigenetische veranderingen, zoals DNA methylering, betrokken zijn bij de ontregeling van hTERT expressie in telomerase positieve cellen. Methylering van het DNA kan bepaald worden door middel van bisulfiet sequentie analyse of methyleringsspecifieke PCR (MSP). Bisulfiet sequentie analyse van de hTERT sequentie van nucleotide -442 tot +526 (ten opzichte van de ATG) toonde aan dat er beduidend meer methylering is in hTERT positieve cellen dan in hTERT negatieve cellen. Vervolgens wees MSP analyse van twee subregio’s in deze hTERT sequentie uit dat beide gebieden gemethyleerd zijn in 100% van baarmoederhalstumoren, 38% van de hooggradige CIN laesies (CIN3), 9% van de laaggradige CIN laesies (CIN1) en 5% van de normale controles. Methylering nam dus toe met de ernst van de laesie. Deze bevindingen suggereren dat methylering van hTERT hoogstwaarschijnlijk bijdraagt aan de ontregeling van hTERT expressie in HPV-getransformeerde cellen in vitro en in vivo.

Expressieveranderingen van AP-1 complex genen tijdens hrHPV- geïnduceerde transformatie De transcriptiefactor AP-1 is betrokken bij het ontstaan van heel veel verschillende tumoren. Daarnaast is AP-1 een activator van HPV transcriptie en kan het ook de expressie van hTERT reguleren door binding aan de regulerende sequenties die beschreven zijn in hoofdstuk 2. AP-1 is een heterodimeer die bestaat uit een lid van de Fos-familie (c-Fos, FosB, Fra-1 of Fra-2) en een lid van de Jun familie (c-Jun, JunB, of JunD). Afhankelijk van de samenstelling is het AP-1 complex betrokken in de positieve of negatieve regulering van expressie van diverse genen. Veranderingen in de samenstelling van het AP-1 complex zijn eerder in verband gebracht met tumorigeniteit tijdens het ontstaan van baarmoederhalskanker in vitro en in vivo. In normale cellen komt Fra-1 tot expressie en bestaat het AP-1 complex voornamelijk uit Fra-1/c-Jun heterodimeren. In tumorigene cellen komt c-Fos verhoogd tot expressie wat leidt tot een verschuiving naar voornamelijk c-Fos/c- Jun heterodimeren. In Hoofdstuk 3 hebben we geprobeerd om meer inzicht te krijgen in de expressieveranderingen van AP-1 complex genen tijdens transformatie door hrHPV. Ook hebben we onderzocht hoe expressie van deze AP-1 complex genen zich verhoudt tot expressie van potentiële regulatoren van deze genen zoals Notch1 en Net en expressie van een AP-1 target gen, namelijk CADM1. Door middel van kwantitatieve RT-PCR is mRNA expressie bepaald

156 Chapter 7 van zowel alle AP-1 complex genen (c-Jun, JunB, JunD, c-Fos, FosB, Fra-1 en Fra-2) als Notch1, Net en CADM1 in primaire keratinocyten, vroege en late passages van niet-tumorigene HPV-geïmmortaliseerde keratinocyten en tumorigene baarmoederhalskanker cellijnen. In een aantal cellijnen is hiernaast ook eiwit expressie en de samenstelling van het AP-1 complex bepaald. Vanaf het vroege immortale stadium tot aan tumorigeniteit bleek de mRNA expressie van c-Fos, Fra-2 en JunB expressie toe te nemen, terwijl Fra-1, c-Jun, Notch1, Net en CADM1 mRNA expressie afnamen. Het stadium vanaf waar de AP-1 complex genen een veranderde expressie begonnen te vertonen verschilde per gen en een verandering in expressie was niet direct gecorreleerd met afwijkende expressie van Notch1, Net of CADM1. Desalniettemin vond een verschuiving van Fra-1/c-Jun naar c-Fos/c-Jun heterodimeren pas plaats in tumorigene cellen. Hieruit kan geconcludeerd worden dat hoewel de expressie van de AP-1 complex genen al verandert in immortale cellen, een verschuiving in AP-1 complex samenstelling pas relatief laat plaatsvindt en alleen waargenomen wordt in tumorigene cellen.

Genexpressieverschillen geassocieerd met ontregelde hTERT expressie In Hoofdstuk 4 zijn de veranderingen in genexpressie die optreden tijdens hrHPV-geïnduceerde immortalisatie en gerelateerd zijn aan hTERT deregulatie in kaart gebracht. Eerdere microcelfusie studies hebben aangetoond dat introductie van het humane chromosoom 6 in de HPV16-bevattende cellijnen, waaronder de geïmmortaliseerde keratinocyt cellijn FK16A, een groeistop veroorzaakt. Deze groeistop werd veroorzaakt door verminderde expressie van hTERT mRNA en afgenomen telomerase activiteit. Om expressie veranderingen te bepalen die specifiek zijn voor ontregelde hTERT expressie hebben we 12 FK16A-chromosoom 6 hybriden geanalyseerd met expressie microarrays. Vier van deze FK16A-chromosoom 6 hybriden waren negatief en 8 positief voor mRNA expressie van endogeen hTERT. Met deze analyse zijn 164 genen geïdentificeerd met afwijkende expressie in hTERT positieve hybriden ten opzichte van hTERT negatieve hybriden. Van 5 genen is deze veranderde expressie bevestigd door middel van kwantitatieve RT-PCR. Van de 164 genen kwamen 32 genen ook veranderd tot expressie in andere hTERT positieve hr-HPV getransformeerde cellen. Afwijkende expressie van twee van deze genen, AQP3 en MGP, is bevestigd in hTERT positieve weefselmonsters van baarmoederhalstumoren met behulp van respectievelijk kwantitatieve RT- PCR en immunokleuringen. Tevens was MGP expressie significant verhoogd in

157 Nederlandse samenvatting hooggradige CIN laesies met hTERT expressie ten opzichte van hooggradige CIN laesies zonder hTERT expressie. Samenvattend zijn er 32 kandidaat surrogaat markers voor ontregelde hTERT expressie geïdentificeerd. Toekomstig onderzoek moet verder uitwijzen of deze markers bij kunnen dragen aan het identificeren van hrHPV-positieve vrouwen die een verhoogd risico hebben op de ontwikkeling van baarmoederhalskanker.

Veranderde genexpressie geassocieerd met vaak voorkomende chromosomale afwijkingen in baarmoederhalstumoren In Hoofdstuk 5 hebben we een andere benadering gebruikt om genveranderingen te ontrafelen die relevant zijn voor het ontstaan van baarmoederhalskanker. Door chromosomale en expressieprofielen van baarmoederhalstumoren te integreren, hebben we onderzocht welke veranderde expressiepatronen gekoppeld zijn aan chromosomale afwijkingen. Eerdere profilering van chromosomale afwijkingen laat zien dat (een) extra kopie(ën) van chromosoom 1q, 3q en 20q en een verlies van chromosoom 8q, 10q, 11q en 13q frequent voorkomen in baarmoederhalstumoren. Middels twee geavanceerde analyse programma’s is aangetoond dat een verhoogde expressie van genen op chromosoom 1q32.1-32.2, 3q13.32-23, 3q26.32-27.3, en 20q11.21-13.33 gecorreleerd is met een toename in DNA op deze gebieden. Anderzijds was een verlies van chromosoom 11q22.3-25 geassocieerd met verlaagde expressie van de genen op dit gebied. Overexpressie van 4 genen op chromosoom 3q, DTX3L, PIK3R4, ATP2C1, en SLC25A36, is vervolgens bevestigd in een onafhankelijke groep baarmoederhalstumoren en normale controles.

Samenvattend hebben wij door onderzoek op zowel een in vitro modelsysteem bestaand uit hrHPV-geimmortaliseerde keratinocyt cellijnen als weefselmonsters meer inzicht gekregen in de (epi)genetische veranderingen die betrokken zijn bij immortalisatie en het ontstaan van baarmoederhalskanker. We hebben laten zien dat transcriptionele activiteit van de hTERT promoter in HPV-geïmmortaliseerde cellijnen gereguleerd wordt door zowel activerende als remmende promoterelementen. Met name de remmende promoterelementen bleken in toenemende mate gemethyleerd te worden gedurende het in vitro transformatie proces. In overeenstemming hiermee werd ook in vivo een toename van hTERT DNA methylering gevonden naarmate de laesies ernstiger werden.

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Naast epigenetische veranderingen hebben wij in dit proefschrift ook genexpressie veranderingen laten zien. Expressie van Fos familieleden, die deel uitmaken van de AP-1 transcriptiefactor, veranderde al tijdens de immortalisatie van hrHPV getransfecteerde cellen, terwijl een veranderde compositie van het AP-1 complex uitsluitend gezien werd in tumorigene cellen. Hiernaast zijn er met behulp van microarray expressie analyse 32 genen, inclusief MGP en AQP3, geïdentificeerd met afwijkende expressie in cellen met hTERT expressie. mRNA expressie van een andere set genen, DTX3L, PIK3R4, ATP2C1, en SLC25A36 is veranderd als gevolg van chromosomale veranderingen in baarmoederhalstumoren.

Toekomstige studies zullen moeten uitwijzen welke van de genen en veranderingen beschreven in dit proefschrift een actieve rol spelen bij het ontstaan van baarmoederhalskanker. Gebruikmakend van modelsystemen zoals beschreven in dit proefschrift zullen we de onderliggende biologie van tumoren veroorzaakt door hrHPV steeds beter begrijpen. Een verbeterd inzicht in de biologie zal uiteindelijk ook leiden tot een betere preventie, diagnostiek en behandeling van baarmoederhalskanker. Zo vormen de bevindingen beschreven in dit proefschrift bijvoorbeeld ook de basis voor nieuwe (moleculaire) testen om hrHPV-positieve vrouwen met een verhoogd risico op baarmoederhalskanker te identificeren.

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Figures in color Figures in color

Chapter 1 – Figure 2

Figure 2: Schematic representation of hTERT regulatory sequences and the transcriptional regulators that can bind to it. The 200 bp core promoter is marked by a black bold line, flanking sequences by a dotted line. Transcriptional activators are shown in the upper panel and transcriptional repressors are shown in the lower panel. Arrows point to the (often multiple) binding sites of the individual transcription factors. Note that some transcriptional regulators described above are not shown since these bind outside the indicated region (-600 bp to +450 bp relative to the ATG).

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Chapter 4 – Figure 3

Figure 3: Classification of differentially expressed genes to several cellular processes using Ease software (please note that not all differentially expressed genes have been classified).

163 Figures in color

Colored figure on the back of this page

164 Chapter 8

Colored figure on the back of this page

165 Figures in color

Chapter 4 – Figure 7

Figure 7: Immunohistochemistry for MGP. MGP staining in a raft culture of primary keratinocytes (A) a raft culture of FK16A cells (B), normal cervical epithelium (C), cervical carcinoma (D), infiltrating lymphocytes (E), normal cervical epithelium adjacent to carcinoma (F), dysplastic cervical epithelium adjacent to carcinoma (G), a high-grade CIN lesions with elevated hTERT mRNA (H) and a high-grade CIN lesions without elevated hTERT mRNA (I).

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Chapter 5 – Figure 4

Figure 4. An overview of frequencies of gains and losses on chromosomes A. 1, B. 3, C. 11, and D. 20 as determined by array CGH is depicted in grey. Loci identified by DIGMAP and ACE-it are shown in blue and yellow respectively.

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168 Chapter 9

Curriculum Vitae & Publications

Curriculum Vitae & Publications

Curriculum Vitae The author of this thesis was born on the 6th of November 1978 in Heemstede. In 1997 she graduated from high school (gymnasium) at the Fioretti College in Lisse. In the same year she started her study Medical Biology at VU University in Amsterdam. During this study two traineeships on different topics were carried out. In the first one at the department of Molecular Pathology of the VU University Medical Center (Dr. RDM Steenbergen), she studied allelic imbalances on chromosome 6 in HPV-immortalized cell lines. During the second traineeship at the department of Medical Oncology of the Leyden University Medical Center (Dr. LTC Peltenburg) she investigated c-Myc mediated apoptosis in melanoma cells. She received her M.Sc. degree in 2003. Her PhD was performed at the departement of Molecular Pathology (Prof. Dr. CJLM Meijer and Prof. Dr. PJF Snijders) of the VU University Medical Center, which resulted in this thesis. From 2008 on she has been working as a Post Doc at the Toxicogenetics departement of the Leyden University Medical Center.

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Publications

1. van Duin M, Steenbergen RD, de Wilde J, Helmerhorst TJ, Verheijen RH, Risse EK, Meijer CJ, Snijders PJ. Telomerase activity in high-grade cervical lesions is associated with allelic imbalance at 6Q14-22. Int.J.Cancer (2003); 105: 577-82.

2. de Bruin EC, Meersma D, de Wilde J, den O, I, Schipper EM, Medema JP, Peltenburg LT. A serine protease is involved in the initiation of DNA damage-induced apoptosis. Cell Death.Differ. (2003); 10: 1204-12.

3. Steenbergen RD, de Wilde J, Wilting SM, Brink AA, Snijders PJ, Meijer CJ. HPV- mediated transformation of the anogenital tract. J.Clin.Virol. 2005; 32 Suppl 1: S25- S33.

4. de Wilde J, Wilting SM, Meijer CJ, van de Wiel MA, Ylstra B, Snijders PJ, Steenbergen RD. Gene expression profiling to identify markers associated with deregulated hTERT in HPV-transformed keratinocytes and cervical cancer. Int.J.Cancer (2008); 122: 877-88.

5. de Wilde J, De Castro AJ, Snijders PJ, Meijer CJ, Rosl F, Steenbergen RD. Alterations in AP-1 and AP-1 regulatory genes during HPV-induced carcinogenesis. Cell Oncol. (2008); 30: 77-87.

6. Wilting SM, de Wilde J, Meijer CJ, Berkhof J, Yi Y, van Wieringen WN Braakhuis BJ, Meijer GA, Ylstra B, Snijders PJ, Steenbergen RD. Integrated genomic and transcriptional profiling identifies chromosomal loci with altered gene expression in cervical cancer. Genes Chromosomes.Cancer (2008); 47: 890-905.

7. de Wilde J, Kooter JM, Overmeer RM, Claassen-Kramer D, Meijer CJ, Snijders PJ, Steenbergen RD. Epigenetic regulation of repressive hTERT regulatory sequences during HPV-induced carcinogenesis. Submitted for publication

8. Pines A, Hameetman L, de Wilde J, Alekseev S, de Gruijl FR, Vrieling H, Mullenders LH. Global genome nucleotide excision repair protects against UVB induced skin cancer in the absence of transcription coupled repair. Submitted for publication

9. Yuan X, de Wilde J, Jonker MJ, Verhoef A, Wittink FR, Bessems JG, Hakkert BC, Kuiper R, van Steeg H, Breit TM, Luijten M. Discriminating reprotoxici and non- reprotoxic phthalates by transcriptomics analysis of rat testis. Submitted for publication

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Dankwoord

Dankwoord

Dankwoord Natuurlijk wil ik een aantal mensen bedanken die hebben bijgedragen aan de totstandkoming van dit boekje. Allereerst Dr. Renske Steenbergen, Renske toen ik mijn studie Medische Biologie bijna had afgerond en op zoek was naar een aio-plaats heb jij je ervoor ingezet dat ik onder jouw supervisie kon gaan promoveren. Wij kenden elkaar natuurlijk al van de stage die ik bij jou gelopen heb en ik kon op deze manier het onderzoek, dat ik toen al deels was begonnen, voortzetten. Jouw onuitputtelijke enthousiasme en energie hebben ervoor gezorgd dat ik, ondanks dat het onderzoek niet altijd even voorspoedig verliep, mij steeds weer heb kunnen motiveren om door te gaan, wat uiteindelijk geleid heeft tot dit resultaat. Daarvoor ben ik jou ontzettend veel dank verschuldigd. Daarnaast wil ik graag mijn beide promotoren Prof. Dr. Peter Snijders en Prof. Dr. Chris Meijer bedanken. Jullie hebben mij de mogelijkheid gegeven om te promoveren op dit onderzoek en jullie enthousiasme en kennis hebben in grote mate bijgedragen aan de totstandkoming van dit boekje. I would like to thank Prof. Dr. Frank Rösl, Dr. Jan Kooter, Dr. Wim van Criekinge, Prof. Dr. Ate van der Zee, Dr. Wolter Mooi, Prof. Dr. Gerrit Meijer and Dr.Gemma Kenter for their willingness to critically read this thesis and for attending the ceremony. De fotografen, Jaap en Ron, wil ik bedanken voor hun hulp bij het klaarmaken van de plaatjes in dit proefschrift. Ook wil ik graag alle mensen bedanken die geholpen hebben met het uitvoeren van de miroarrays en de analyse hiervan. Ik ben één van de eersten geweest die expressiearrays heeft uitgevoerd op de microarray faciliteit van de VU en wist daarom niet altijd goed hoe ik om moest gaan met de enorme hoeveelheden data. Bauke, Paul, Paul, Mark, Soemini en Jaqueline ontzettend bedankt voor jullie hulp. En dan wil ik natuurlijk de mensen van de MPA bedanken. Bart, Wendy, Daniëlle, Antoinette, Nathalie, Muriël, René, Rick, Stephan, Anthonie, Pien, Marjolein, Debby, Fatih, Sonja, Martijn, Sylvia, Duco en Douwe bedankt voor de gezellige pauzes en gezamenlijke uitjes. Verder wil ik ook graag mijn studenten/stagiaires bedanken: Inès en Katarina bedankt voor jullie inzet. Mijn mede aio’s: Renée, Floor, Mariska, Emily, Dorien en Murat bedankt voor alle gezelligheid en support. Ik wens jullie veel succes met je eigen boekje. Floor, jou wil ik ook nog eens extra bedanken voor het zoeken naar keratinocyte foto’s voor de voorkant van dit proefschrift.

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En dan natuurlijk mijn paranimfen Saskia en Debbie. Saskia, vanaf het moment dat wij in 2003 naast elkaar neergezet werden, klikte het enorm goed tussen ons. Samen hebben we de wondere wereld van microarrays ontdekt en zo ontstond een fijne samenwerking. Niet alleen op het werk maar ook daarbuiten zaten we vaak op één lijn, wat leidde tot een hechte vriendschap. Heel erg bedankt voor de gezelligheid en steun de afgelopen jaren en voor je hulp bij de afronding van dit boekje. Ik ben ontzettend blij dat jij mijn paranimf wil zijn. Debbie, toen ik als student begon aan mijn stage op een project van jou en Renske, heb jij mij ontzettend veel geleerd over het moleculaire werk. Nog steeds pluk ik hier de vruchten van. Ook in de jaren die daarop volgden waarin ik aio was, heb ik enorm veel gehad aan jouw uitgebreide kennis en enthousiasme. Jij stond samen met Renske aan de basis van mijn project en ik vind het heel leuk dat jij, als mijn paranimf, ook betrokken bent bij de afronding hiervan. Ook de andere (ex)aio’s bij pathologie: Saskia, Saskia, Rieneke, Inge, Jessica, Hedy, Cindy, Tineke, Linda, Anke en Meike bedankt voor de gezelligheid tijdens en na het werk. Als laatste wil ik mijn familie bedanken. Lieve mama en papa, jullie hebben mij de kans gegeven om te studeren en mij onvoorwaardelijke gesteund de afgelopen jaren. Zonder jullie was ik niet gekomen tot dit resultaat. Hiernaast wil ik jullie, maar ook Wim en vooral Tera, ontzettend bedanken voor het vele oppassen de afgelopen jaren. Doordat ik wist dat de kinderen goed verzorgd werden, kon ik mij volledig richten op het afronden van dit boekje. Lieve Wilbert, jij bent mijn steun en toeverlaat. Bedankt voor al jouw liefde, interesse, geduld en begrip de afgelopen jaren. Ik ben ongelofelijk blij en gelukkig met jou. Lieve Finn en Jens, jullie zijn mijn grote trots en beide ook al onderzoekers in de dop. Ik hou onzettend veel van jullie. Bedankt dat ik jullie mama mag zijn.

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