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Oncogene (2002) 21, 7749 – 7763

2002 Nature Publishing Group All rights reserved 0950 – 9232/02 $25.00

ª

www.nature.com/onc

Expression profiling of primary non-small cell lung cancer for target identification

Jim Heighway*,1, Teresa Knapp1, Lenetta Boyce1, Shelley Brennand1, John K Field1, Daniel C Betticher2, Daniel Ratschiller2, Mathias Gugger2, Michael Donovan3, Amy Lasek3 and Paula Rickert*,3

1Target Identification Group, Roy Castle International Centre for Lung Cancer Research, University of Liverpool, 200 London

  • 2
  • 3

Road, Liverpool L3 9TA, UK; Institute of Medical Oncology, University of Bern, 3010 Bern, Switzerland; Incyte Genomics Inc., 3160 Porter Drive, Palo Alto, California, CA 94304, USA

Using a panel of cDNA microarrays comprising 47 650 transcript elements, we have carried out a dual-channel analysis of gene expression in 39 resected primary human non-small cell lung tumours versus normal lung tissue. Whilst *11 000 elements were scored as differentially expressed at least twofold in at least one sample, 96 transcripts were scored as over-represented fourfold or more in at least seven out of 39 tumours and 30 sequences 16-fold in at least two out of 39 tumours, including 24 transcripts in common. Transcripts (178) were found under-represented fourfold in at least seven out of 39 tumours, 31 of which are underrepresented 16-fold in at least two out of 39 lesions. The relative expression levels of representative genes from these lists were analysed by comparative multiplex RT – PCR and found to be broadly consistent with the microarray data. Two dramatically over-represented genes, previously designated as potential tumour suppressors in breast (maspin) and lung and breast (S100A2) cancers, were analysed more extensively and demonstrate the effectiveness of this approach in identifying potential lung cancer diagnostic or therapeutic targets. Whilst it has been reported that S100A2 is downregulated in NSCLC at an early stage, our microarray, cmRT – PCR, Western and immunohistochemistry data indicate that it is strongly expressed in the majority of tumours.
Introduction

The lack of generally effective therapies for lung cancer leads to the high mortality rate associated with this common disease. Recorded 5-year survival figures vary, to some extent perhaps reflecting differences in ascertainment methods, but across Europe are approximately 10% (Bray et al., 2002). Whilst surgery is an effective strategy for the treatment of localized lesions, most patients present with overtly or covertly disseminated disease. Unfortunately, despite the many advances in chemotherapeutic regimes, for most lung cancer patients, metastatic disease present at diagnosis will be fatal. We have chosen to use microarray transcript profiling to illuminate potential targets with application in the detection or treatment of this disease.
Microarray analysis allows a reversal of the standard cancer genetics paradigm. Instead of attempting to identify areas of the genome which are perturbed in disease and then looking for key cancer-associated genes within these regions, the technology allows us to first identify genes that are differentially expressed in a condition and then to look at the genomic context of that abnormal expression. Perhaps the most powerful prioritization tool in the search for disease significance will be the coupling of gene expression changes to genomic damage events in the tumour DNA.
Lung cancer is commonly divided into small cell
(SCLC) and non-small cell (NSCLC) disease. SCLC, approximately 20% of cases, is invariably metastatic at presentation and is therefore treated primarily through the use of chemotherapeutic agents. In contrast, NSCLC may appear to be localised or only locally metastatic and therefore amenable to surgical resection. NSCLC is further subdivided into three main classes, squamous cell carcinoma, adenocarcinoma and large cell carcinoma. However, many if not most tumours are composed of multiple histological types (Thurlbeck and Churg, 1995; Fraire et al., 1987). Such variation in a presumably clonal lesion has led to the suggestion that lung cancers arise from a multipotential stem cell component of the normal tissue, a hypothesis supported by the analysis of model systems
Oncogene (2002) 21, 7749 – 7763. doi:10.1038/ sj.onc.1205979

Keywords: lung; cancer; microarray; expression; target identification

*Correspondence: J Heighway, Gene Function, Roy Castle International Centre for Lung Cancer Research, 200 London Road, Liverpool L3 9TA, UK; E-mail: [email protected] or Paula Rickert, Incyte Genomics, 3160 Porter Drive, Palo Alto, California, CA 94304, USA; E-mail: [email protected] Received 27 May 2002; revised 8 August 2002; accepted 13 August 2002

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(Sunday et al., 1999). It is very likely that transcript profiling will lead to further subdivisions within these overall classes of disease, some which mirror preexisting pathological classes and some which are novel (Garber et al., 2001; Bhattacharjee et al., 2001). Whilst such classification regimes may be very important in understanding disease biology and may become critical in the future with respect to assessing lung cancer prognosis and directing subsequent therapeutic practice, such uses are perhaps currently secondary to the need for improved diagnostic and therapeutic agents.
Given that it is generally easier pharmacologically to inhibit rather than to replace function and given that a lung cancer diagnostic is likely to be most effective where it measures an excess of rather than the lack of a gene product, our attention has been directed primarily towards genes that are over-represented in disease tissue. However, it is likely that the study of underrepresented sequences will considerably enhance our understanding of the biology of the disease process and may lead to the discovery of linked and more conventional targets. We have therefore generated and validated gene lists of both tumour over and under-represented sequences.
As additional verification, we independently assayed expression profiles of two of these genes, osteopontin and PRAME, using multiplex quantitative real-time RT – PCR (TaqManTM, Applied Biosystems) with the housekeeping gene b2-microglobulin as an internal reference (Figure 1). Osteopontin was found to be over-represented at least fourfold in 14 out of 14 tumours assayed, with an average CT (cycle threshold of detectable logarithmic phase amplification) of 22 in lung tumours and 32 in normal tissue. PRAME was measured as over-represented in 13 out of 14 tumours, with an average CT of 28 in tumours and 36 in normal tissue. Our microarray approach for identifying overrepresented genes in lung tumours was thus confirmed by two distinct methods using independent control genes. Having validated the basic experimental protocol, a wider analysis was undertaken.

Microarray data analysis

RNA was extracted from resectable NSCLC tumours from 33 additional patients giving 39 in total, including 13 who had undergone neo-adjuvant chemotherapy (Table 1). A further series of dual channel microarray

Results

Method validation

Dual channel microarray hybridizations were carried out in duplicate for six patients comprising tumour against matched normal tissue across five cDNA microarrays: Human Drug Target (formerly known as Human Genome GEMTM 1) and Human Foundation 1 – 4 (formerly known as Human Genome GEM 2 – 5) (Incyte Genomics, Inc.). Clones representing 14 distinct genes (http://www.roycastle.org/research/) with a differential expression (DE) value greater than two in at least five of the six patients were selected. The validity of these predictions was tested by an independent gene expression analysis, comparative multiplex RT – PCR (cmRT – PCR). As many of the standard control genes are known to be variable in expression between different human tissues and states (Lee et al., 2002) we selected new control genes from within the array data; sequences that showed DE values below two in the tumour versus normal hybridizations from the first six patients. Control primer sets were validated against each other in reactions with paired cDNA samples. The most robust of the tested control loci in terms of ease of amplification and wide reaction compatibility was the KIAA0228 (228) gene (Acc: D86981), located on 17q23.2. We used cmRT – PCR and at least one control gene to test the 14 genes identified as differentially expressed (83 individual hybridised elements). The cmRT – PCR data was consistent with the hybridization data predicting a gene expression difference between the tumour and normal tissue, in each case, in the same direction.

Figure 1 Illustrates TaqManTM quantitative real-time PCR data for matched normal lung and tumour pairs for osteopontin (a) and PRAME (c), confirming the over-representation of these genes in a majority of non-small cell lung tumours. The housekeeping gene b2-microglobulin was used as an internal reference for normalization of sample concentrations. Relative expression values (y-axis) were determined using normal lung tissue from patient 185 (detectably expressing both genes) as the calibrator. (b and d) show cmRT – PCR (b) and RT – PCR (d) analyses of osteopontin and PRAME in matched samples

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Table 1 Lists the patient details and tumour histology

  • Patient
  • Diagnosis
  • Sex
  • Age at surgery
  • T
  • N
  • M
  • Stage

57 61 64 65 67 69 70 74 78 80 83 86 87 89 91 111 122 123 125 128 130 132 134 138 141 142 B1 B2 B3 B4 B5 B6 B7 B8 B9 B10 B11 B12 B14

  • Squamous
  • M

MMF
67 73 79 70 68 73 75 71 66 70 73 67 72 68 62 61 66 54 78 50 43 54 60 75 71 53 71 71 50 54 39 57 58 62 53 54 62 54 62
221121212322222122222222212223122222322
010001000110020012001010002222222222222
XXXXXXXXXXXXXXXXXXXXXXXXXX0000000000000
IB IIB IA IA IB IIA IB IA IB IIB IIB IB IB IIIA IB
Large cell endocrine Pulmonary carcinoid Adenocarcinoma

  • Squamous
  • F

  • Squamous
  • M

MFMMMMMFMMFMMF
Adenocarcinoma Adenocarcinoma Squamous Squamous Squamous Adenocarcinoma Adenocarcinoma Squamous Adenocarcinoma Atypical carcinoid Adenocarcinoma Adenocarcinoma Adenocarcinoma Squamous
IA IIB IIIA IB IB IIB IB IIB IB IB IA IIIA IIIA IIIA IIIA IIIA IIIA IIIA IIIA IIIA IIIA IIIA IIIA IIIA

  • Squamous
  • M

FF
Large cell endocrine Squamous

  • Squamous
  • F

  • Squamous
  • M

MMMMF
Neuroendocrine ca. Adenocarcinoma Adenocarcinoma Adenocarcinoma Adenocarcinoma Adenocarcinoma Adenocarcinoma Squamous Adenocarcinoma Adenocarcinoma Large cell Squamous Adenocarcinoma Adenocarcinoma
FFMMFMMMM

T, N and M refer to the tumour, node and metastasis status according to WHO guidelines

hybridizations was carried out for all patients comparing tumour against matched normal tissue (27 patients) or tumour against a pooled normal sample (six patients). For the majority of patient samples, duplicate hybridizations were performed across all five cDNA microarrays. The data presented in this study was obtained from 298 individual array analyses that passed hybridization QC, screening 34 – 37 different patient samples across each of 47 650 clones representing 39 176 unique gene/EST clusters.
Approximately 11 000 clones were scored as signifi- cantly differentially expressed (4twofold: Yue et al., 2001) in at least one sample. We were primarily interested in identifying sequences dramatically differentially expressed in a wide range of disease samples, or else sequences that were very dramatically differentially expressed in a smaller number of tumours. Gene lists were constructed of (a) genes that were differentially expressed fourfold or more in seven or more (approximately 20%) tumours and (b) genes that were differentially expressed 16-fold or more in two or more tumours (Tables 2 and 3). Approximately 50% of the elements highlighted in the fourfold tumour overrepresented list were various immunoglobulin transcripts, the relative expression levels of which correlated with each other closely across the tumour series (data not shown). Removing these sequences left a list of 96 genes with Genbank annotation, some of which were represented in the primary list by multiple array elements. These remaining 96 were ranked in order of number of tumours in which the element passed the restriction criteria. Following removal of Igrelated genes, 30 elements were scored as overrepresented 16-fold or more in at least two tumours and of those, 24 were common to both lists. One hundred and seventy-eight non-Ig genes with Genbank annotation were scored as under-represented fourfold or more in seven or more tumours with 30 of these under-represented 16-fold in two or more lesions. One element, representing the calcium binding protein S100A8 (MRP8), was present in both the over and under-represented lists. The expression profile of this gene did not correlate closely with those of immunoglobulin related elements.

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Table 2 Lists in ranked order four- and 16-fold tumour over-represented elements that passed the restriction criteria

Genbank Acc Chr. loc. 46up in: 166up in: 26up in: Gene description (closest PD match to element sequence)

12224892 30057 3413861 14250681 35147 416114 2088550 790537 6688166 544761 2065174 3150034 393318 35569 31894 13516384 12653176 14043321 14198020 1903383 452483 4481752 13111934 292829
8q23.3 2q32.2 1p36.33 12q13.13
4q22.1 Xq28 6q22.2 11q22.3 2q24.1 10p15.1 1q23.1
7q33
13q14.11
8q22.2 14q23.3 8q22.1
4q26
20q13.12 17p11.2 22q11.22 10p15.1 13q12.11 15q26.1 17q21.2 11p11.2
4p13
6q24.1 11q22.2 4p16.1 6q22.1 Xp11.23 Xq28
10q21.2 17q21.33 17q21.33
1q32.1 19q13.2 17q25.3 12q23.3 2q36.1 15q15.3 3p25.2
3q24
17q21.2
15q14 2q35
22q11.23
2q37.1
20q11.21 11q23.3
5q34
26 22 22 18 18 18 18 18 17 17 17 17 17 16 16 16 16 15 15 15 15 14 14 14 13 13 13 13 13 12 12 12 12 12 12 11 11 11 11 11 11 11 11 10 10 10 10 10 10 10 10 10 10
9
65
33 30 31 20 28 21 26 25 23 20 19 18 24 24 19 28 27 24 23 20 20 18 24 23 23 20 24 22 17 19 21 16 25 30 23 25 14 22 18 22 20 17 23 16 24 15 25 13 21 17 23 27 19 19 17 19 18 10 14 16 13 16 19 18 23 18 15 21 16
Homo sapiens mRNA; cDNA DKFZp667P184. Human mRNA for pro-alpha-1 type 3 collagen. Homo sapiens mRNA for KIAA0450 protein. Homo sapiens, keratin 6A. Human mRNA for osteopontin. Human antigen (MAGE-1) gene. Human hereditary haemochromatosis region, histone 2A-like gene. Human glutamate receptor (GluR4). Homo sapiens partial mRNA for GalNAc-T5 (GALNT5 gene). Chlordecone reductase {clone HAKRa} [human, liver, mRNA]. Homo sapiens S100A2 gene, exon 1-3. Homo sapiens aldose reductase-like peptide. OSF-2p1 Human mRNA for polyA binding protein. Human mRNA for glutathione peroxidase-like protein. Homo sapiens genomic DNA, chromosome 8q23, clone: KB1241F12. Homo sapiens, MAD2 (mitotic arrest deficient, yeast, homolog)-like 1. Homo sapiens, ubiquitin carrier protein E2-C.
11
24322875

33

  • 5
  • H.sapiens gene for cytokeratin 17.

Human preferentially expressed antigen of melanoma (PRAME). Human dihydrodiol dehydrogenase Human connexin 26. Human, protein regulator of cytokinesis 1. DNA topoisomerase II (EC 5.99.1.3) Human midkine gene, complete cds Homo sapiens, similar to ubiquitin carboxy-terminal hydrolase L1. Homo sapiens mRNA for transmembrane protein (THW gene). Human mRNA for type I interstitial collagenase (MMP1) Homo sapiens, S100 calcium-binding protein P. H.sapiens COL10A1 gene for collagen (alpha-1 type X). Homo sapiens prostate associated PAGE-1.
219928 12653130 11558106 10437218 13905069 30094 3300091 15079897 29840 8919392 1418927 7677071 5834583 339708 3483454 394340 13676499 2367444 5419854 34070
334

4

52
Homo sapiens, melanoma antigen, family A, 3. Human cell cycle control gene CDC2. Homo sapiens mRNA full length insert cDNA clone EUROIMAGE 781354. H.sapiens mRNA for prepro-alpha1(I) collagen. Homo sapiens ubiquitin-conjugating enzyme E2. Human mRNA encoding rat C4.4-like protein Human thymidine kinase mRNA, complete cds Homo sapiens full length insert cDNA clone ZA02A01. H. sapiens (D2S351) DNA segment containing (CA) repeat; AFM294yf5. Macaca fascicularis brain cDNA clone:QflA-13282. Myoblast city Homo sapiens mRNA; cDNA DKFZp566N043. Human mRNA for cytokeratin 15 Human thrombospondin 2 (THBS2). Human, insulin-like growth factor binding protein 2 (36kD). Homo sapiens genomic DNA, chromosome 22q11.2, clone KB1125A3. Human bilirubin UDP-glucuronosyltransferase isozyme 1. Homo sapiens mRNA for fls353. Homo sapiens tripartite motif protein TRIM29 alpha. Homo sapiens pituitary tumor-transforming 1 (PTTG1) gene, exon 4. Human PNG pseudogene, complete sequence Human ARF-activated phosphatidylcholine-specific phospholipase D1a (hPLD1). Homo sapiens pro-alpha 2(I) collagen (COL1A2) gene, complete cds. Homo sapiens:Probable G-protein coupled receptor (GPR87). Homo sapiens, keratin 14.
307505 13279202 5103013 184472 4589928 12275863 6318669 2911809 1185462 179595 14042718 12803708 14602472 14279429 7328949 533527 13516845 12052859 14042497 10440167 914203
22q12.2 3q26.31 7q21.3 3q25.1 17q21.2 1q32.1 Xq28
999999999999888
Human ladinin (LAD) mRNA. Human chondrosarcoma CSAG2b mRNA sequence Human 20-alpha HSD gene for 20 alph-hydroxysteroid dehydrogenase. Homo sapiens, melanoma antigen, family A, 9, mRNA, complete cds. Human hxCT mRNA for cystine/glutamate exchanger, complete cds Human mRNA; cDNA DKFZp564O2071 (from clone DKFZp564O2071); complete cds Human cDNA FLJ14751 fis, similar to R. norvegicus potassium channel regulator 1 Human cDNA: FLJ23468 fis, clone HSI11603 blk=protein tyrosine kinase [Human, B lymphocytes, mRNA, 2608 nt]. Homo sapiens keratin 19 (KRT19) gene.
10p15.1 Xq28 4q28.3
10q24.33 12p11.1 4q35.1 8q23.1 17q21.2 NP
6729680 15012098 340159
Human, similar to small inducible cytokine subfamily B (Cys-X-Cys), member 10 Source: Human pro-urokinase. Human gremlin mRNA
10q22.2

  • 15q13.3
  • 6274527

Continued

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Table 2 (Continued )

Genbank Acc Chr. loc. 46up in: 166up in: 26up in: Gene description (closest PD match to element sequence)

2306914 188691 2546963 30374 14286293 12803652 14043731 929656 10439469 14603393 35322
17p12 1q22
888888888777777777777777777
22 10 16 13 19 19 12 12 22 14 19
9
17 19 21 13 18 21 19 11 10 10 16 17 22 23 17 13
9
Homo sapiens protein kinase mRNA. Human migration inhibitory factor-related protein 8 (MRP8) gene. Human mRNA for diubiquitin Human radiated keratinocyte mRNA for cysteine protease inhibitor. Homo sapiens, similar to RIKEN cDNA 1200008O12 gene. Source: Homo sapiens, keratin 13. Homo sapiens, clone MGC:14128 IMAGE:3610547. H.sapiens mRNA for neutrophil gelatinase associated lipocalin. FLJ22932 fis, highly similar to Human carcinoma-associated antigen GA733-2. Human, CK2 interacting protein 1; HQ0024c protein. H.sapiens mRNA for p cadherin.
6p21.31 3q21.1
10q23.33 17q21.2 8q24.13 9q34.13 2q16.3 1q21.3 16q22.1 19q13.11
5q13.2 17p11.2 14q22.2 17p11.2 18q21.33 11q12.3 17p11.2 18q21.33
1q22
23

  • 897916
  • Human 11kd protein mRNA.

1737211 12653220 414584 14286195 453368 12653112 181915 1172085 338424 6688152 4929718 14286301 5689824 36154
Human basic transcription factor 2 p44 (btf2p44) gene. Human, ubiquitin B, clone MGC:8385 IMAGE:2820408. Human protein tyrosine phosphatase (CIP2). Human, aldehyde dehydrogenase 3 family, member A1. Human maspin mRNA, complete cds. Homo sapiens, flap structure-specific endonuclease 1. Human ubiquitin carrier protein (E2-EPF) mRNA, complete cds. Human squamous cell carcinoma antigen (SCCA1) gene, exon 8. Human small proline rich protein (sprII) mRNA, clone 174N. Homo sapiens mRNA for small proline-rich protein 3 (SPRR3 gene). Human CGI-125 protein.
3

  • 4
  • 1q22

17q13.1 1q25.1 15q13.1 Xp11.3 3p21.31
1q22 1q22 1q22
12q23.2 18q21.32 10q11.23
Homo sapiens, lactate dehydrogenase B. Homo sapiens mRNA full length insert cDNA clone EUROIMAGE 295344. H.sapiens RR2 mRNA for small subunit ribonucleotide reductase.

  • Human lactoferrin (HLF1).
  • 187121

  • 338433
  • 5

43322
Human small proline-rich protein gene.
3327379 14599490 12804462 13325357 338414
Source: Homo sapiens small proline-rich protein 1 (SPRR1A) gene. Human small proline-rich protein 2F (SPRR2F) gene. Human, similar to achaete-scute complex (Drosophila) homolog-like 1. Homo sapiens, gastrin-releasing peptide.
10
42

  • 7
  • Human prostate secreted seminal plasma protein.

Listed is the closest Genbank match to the Incyte cDNA element sequence, the most likely genomic position of the sequence (BLAT similarity), the number of times the element score exceeded the filter threshold, the number of times it was scored as differentially expressed (DE42) and the abbreviated Genbank annotation for the matched sequence

Table 3 Lists in ranked order four- and 16-fold tumour under-represented elements that passed the restriction criteria

46

down in: down in: down in: Gene description (closest PD match to element sequence)
166

26

  • Genbank Acc
  • Chrom. Loc.

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    University of Wollongong Research Online University of Wollongong Thesis Collection 1954-2016 University of Wollongong Thesis Collections 2015 Characterisation of SerpinB2 as a stress response modulator Jodi Anne Lee University of Wollongong Follow this and additional works at: https://ro.uow.edu.au/theses University of Wollongong Copyright Warning You may print or download ONE copy of this document for the purpose of your own research or study. The University does not authorise you to copy, communicate or otherwise make available electronically to any other person any copyright material contained on this site. You are reminded of the following: This work is copyright. Apart from any use permitted under the Copyright Act 1968, no part of this work may be reproduced by any process, nor may any other exclusive right be exercised, without the permission of the author. Copyright owners are entitled to take legal action against persons who infringe their copyright. A reproduction of material that is protected by copyright may be a copyright infringement. A court may impose penalties and award damages in relation to offences and infringements relating to copyright material. Higher penalties may apply, and higher damages may be awarded, for offences and infringements involving the conversion of material into digital or electronic form. Unless otherwise indicated, the views expressed in this thesis are those of the author and do not necessarily represent the views of the University of Wollongong. Recommended Citation Lee, Jodi Anne, Characterisation of SerpinB2 as a stress response modulator, Doctor of Philosophy thesis, School of Biological Sciences, University of Wollongong, 2015. https://ro.uow.edu.au/theses/4538 Research Online is the open access institutional repository for the University of Wollongong.
  • An Essential Mediator of Trichostatin A-Induced Tumor-Selective Killing in Human Cancer Cells

    An Essential Mediator of Trichostatin A-Induced Tumor-Selective Killing in Human Cancer Cells

    Cell Death and Differentiation (2010) 17, 109–118 & 2010 Macmillan Publishers Limited All rights reserved 1350-9047/10 $32.00 www.nature.com/cdd Ubiquitin B: an essential mediator of trichostatin A-induced tumor-selective killing in human cancer cells PWu1,2, Y Tian1,2, G Chen1, B Wang1, L Gui1,LXi1,XMa1, Y Fang1, T Zhu1, D Wang1, L Meng1,GXu1, S Wang1, D Ma*,1 and J Zhou*,1 Although histone deacetylase inhibitors (HDACis) are emerging as a new class of anticancer agents, the mechanism of tumor- selective killing by HDACi is not well understood. We used suppression of mortality by antisense rescue technique (SMART) to screen the key genes responsible for the tumor-selective killing by trichostatin A (TSA). Twenty-four genes were identified, the most significant of which was ubiquitin B (UbB). The expression of UbB was selectively upregulated by TSA in tumor cells, but not non-malignant cells. Further observation indicated that TSA induced a substantial dissipation of mitochondrial transmembrane potential, release of cytochrome c into the cytosol, and proteolytic cleavage of caspases-3/9 in HeLa cells, which was apparently mediated by ubiquitylation and the subsequent degradation of mitochondrial membrane proteins including BCL-2 and MCL-1. In contrast, knockdown of UbB expression inhibited the TSA-induced apoptotic cascade by abolishing TSA-induced ubiquitylation and the subsequent degradation of mitochondrial membrane proteins. Furthermore, apicidine, another HDACi, exhibited activity similar to that of TSA. Interestingly, TSA induced UbB-dependent proteasomal degradation of BCR–ABL fusion protein in K562 leukemic cells. Thus, our findings highlight the essential role of UbB and UbB- dependent proteasomal protein degradation in HDACi-induced tumor selectivity.
  • Role of RUNX1 in Aberrant Retinal Angiogenesis Jonathan D

    Role of RUNX1 in Aberrant Retinal Angiogenesis Jonathan D

    Page 1 of 25 Diabetes Identification of RUNX1 as a mediator of aberrant retinal angiogenesis Short Title: Role of RUNX1 in aberrant retinal angiogenesis Jonathan D. Lam,†1 Daniel J. Oh,†1 Lindsay L. Wong,1 Dhanesh Amarnani,1 Cindy Park- Windhol,1 Angie V. Sanchez,1 Jonathan Cardona-Velez,1,2 Declan McGuone,3 Anat O. Stemmer- Rachamimov,3 Dean Eliott,4 Diane R. Bielenberg,5 Tave van Zyl,4 Lishuang Shen,1 Xiaowu Gai,6 Patricia A. D’Amore*,1,7 Leo A. Kim*,1,4 Joseph F. Arboleda-Velasquez*1 Author affiliations: 1Schepens Eye Research Institute/Massachusetts Eye and Ear, Department of Ophthalmology, Harvard Medical School, 20 Staniford St., Boston, MA 02114 2Universidad Pontificia Bolivariana, Medellin, Colombia, #68- a, Cq. 1 #68305, Medellín, Antioquia, Colombia 3C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, 55 Fruit St., Boston, MA 02114 4Retina Service, Massachusetts Eye and Ear Infirmary, Department of Ophthalmology, Harvard Medical School, 243 Charles St., Boston, MA 02114 5Vascular Biology Program, Boston Children’s Hospital, Department of Surgery, Harvard Medical School, 300 Longwood Ave., Boston, MA 02115 6Center for Personalized Medicine, Children’s Hospital Los Angeles, Los Angeles, 4650 Sunset Blvd, Los Angeles, CA 90027, USA 7Department of Pathology, Harvard Medical School, 25 Shattuck St., Boston, MA 02115 Corresponding authors: Joseph F. Arboleda-Velasquez: [email protected] Ph: (617) 912-2517 Leo Kim: [email protected] Ph: (617) 912-2562 Patricia D’Amore: [email protected] Ph: (617) 912-2559 Fax: (617) 912-0128 20 Staniford St. Boston MA, 02114 † These authors contributed equally to this manuscript Word Count: 1905 Tables and Figures: 4 Diabetes Publish Ahead of Print, published online April 11, 2017 Diabetes Page 2 of 25 Abstract Proliferative diabetic retinopathy (PDR) is a common cause of blindness in the developed world’s working adult population, and affects those with type 1 and type 2 diabetes mellitus.
  • 1A Multiple Sclerosis Treatment

    1A Multiple Sclerosis Treatment

    The Pharmacogenomics Journal (2012) 12, 134–146 & 2012 Macmillan Publishers Limited. All rights reserved 1470-269X/12 www.nature.com/tpj ORIGINAL ARTICLE Network analysis of transcriptional regulation in response to intramuscular interferon-b-1a multiple sclerosis treatment M Hecker1,2, RH Goertsches2,3, Interferon-b (IFN-b) is one of the major drugs for multiple sclerosis (MS) 3 2 treatment. The purpose of this study was to characterize the transcriptional C Fatum , D Koczan , effects induced by intramuscular IFN-b-1a therapy in patients with relapsing– 2 1 H-J Thiesen , R Guthke remitting form of MS. By using Affymetrix DNA microarrays, we obtained and UK Zettl3 genome-wide expression profiles of peripheral blood mononuclear cells of 24 MS patients within the first 4 weeks of IFN-b administration. We identified 1Leibniz Institute for Natural Product Research 121 genes that were significantly up- or downregulated compared with and Infection Biology—Hans-Knoell-Institute, baseline, with stronger changed expression at 1 week after start of therapy. Jena, Germany; 2University of Rostock, Institute of Immunology, Rostock, Germany and Eleven transcription factor-binding sites (TFBS) are overrepresented in the 3University of Rostock, Department of Neurology, regulatory regions of these genes, including those of IFN regulatory factors Rostock, Germany and NF-kB. We then applied TFBS-integrating least angle regression, a novel integrative algorithm for deriving gene regulatory networks from gene Correspondence: M Hecker, Leibniz Institute for Natural Product expression data and TFBS information, to reconstruct the underlying network Research and Infection Biology—Hans-Knoell- of molecular interactions. An NF-kB-centered sub-network of genes was Institute, Beutenbergstr.
  • Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?

    Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?

    Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Science (Cancer Biology) Aneuploidy: Using genetic instability to preserve a haploid genome? Submitted by: Ramona Ramdath In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Science Examination Committee Signature/Date Major Advisor: David Allison, M.D., Ph.D. Academic James Trempe, Ph.D. Advisory Committee: David Giovanucci, Ph.D. Randall Ruch, Ph.D. Ronald Mellgren, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: April 10, 2009 Aneuploidy: Using genetic instability to preserve a haploid genome? Ramona Ramdath University of Toledo, Health Science Campus 2009 Dedication I dedicate this dissertation to my grandfather who died of lung cancer two years ago, but who always instilled in us the value and importance of education. And to my mom and sister, both of whom have been pillars of support and stimulating conversations. To my sister, Rehanna, especially- I hope this inspires you to achieve all that you want to in life, academically and otherwise. ii Acknowledgements As we go through these academic journeys, there are so many along the way that make an impact not only on our work, but on our lives as well, and I would like to say a heartfelt thank you to all of those people: My Committee members- Dr. James Trempe, Dr. David Giovanucchi, Dr. Ronald Mellgren and Dr. Randall Ruch for their guidance, suggestions, support and confidence in me. My major advisor- Dr. David Allison, for his constructive criticism and positive reinforcement.
  • Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant

    Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant

    Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7,
  • Supplementary Methods

    Supplementary Methods

    Supplementary methods Human lung tissues and tissue microarray (TMA) All human tissues were obtained from the Lung Cancer Specialized Program of Research Excellence (SPORE) Tissue Bank at the M.D. Anderson Cancer Center (Houston, TX). A collection of 26 lung adenocarcinomas and 24 non-tumoral paired tissues were snap-frozen and preserved in liquid nitrogen for total RNA extraction. For each tissue sample, the percentage of malignant tissue was calculated and the cellular composition of specimens was determined by histological examination (I.I.W.) following Hematoxylin-Eosin (H&E) staining. All malignant samples retained contained more than 50% tumor cells. Specimens resected from NSCLC stages I-IV patients who had no prior chemotherapy or radiotherapy were used for TMA analysis by immunohistochemistry. Patients who had smoked at least 100 cigarettes in their lifetime were defined as smokers. Samples were fixed in formalin, embedded in paraffin, stained with H&E, and reviewed by an experienced pathologist (I.I.W.). The 413 tissue specimens collected from 283 patients included 62 normal bronchial epithelia, 61 bronchial hyperplasias (Hyp), 15 squamous metaplasias (SqM), 9 squamous dysplasias (Dys), 26 carcinomas in situ (CIS), as well as 98 squamous cell carcinomas (SCC) and 141 adenocarcinomas. Normal bronchial epithelia, hyperplasia, squamous metaplasia, dysplasia, CIS, and SCC were considered to represent different steps in the development of SCCs. All tumors and lesions were classified according to the World Health Organization (WHO) 2004 criteria. The TMAs were prepared with a manual tissue arrayer (Advanced Tissue Arrayer ATA100, Chemicon International, Temecula, CA) using 1-mm-diameter cores in triplicate for tumors and 1.5 to 2-mm cores for normal epithelial and premalignant lesions.
  • Serpins—From Trap to Treatment

    Serpins—From Trap to Treatment

    MINI REVIEW published: 12 February 2019 doi: 10.3389/fmed.2019.00025 SERPINs—From Trap to Treatment Wariya Sanrattana, Coen Maas and Steven de Maat* Department of Clinical Chemistry and Haematology, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands Excessive enzyme activity often has pathological consequences. This for example is the case in thrombosis and hereditary angioedema, where serine proteases of the coagulation system and kallikrein-kinin system are excessively active. Serine proteases are controlled by SERPINs (serine protease inhibitors). We here describe the basic biochemical mechanisms behind SERPIN activity and identify key determinants that influence their function. We explore the clinical phenotypes of several SERPIN deficiencies and review studies where SERPINs are being used beyond replacement therapy. Excitingly, rare human SERPIN mutations have led us and others to believe that it is possible to refine SERPINs toward desired behavior for the treatment of enzyme-driven pathology. Keywords: SERPIN (serine proteinase inhibitor), protein engineering, bradykinin (BK), hemostasis, therapy Edited by: Marvin T. Nieman, Case Western Reserve University, United States INTRODUCTION Reviewed by: Serine proteases are the “workhorses” of the human body. This enzyme family is conserved Daniel A. Lawrence, throughout evolution. There are 1,121 putative proteases in the human body, and about 180 of University of Michigan, United States Thomas Renne, these are serine proteases (1, 2). They are involved in diverse physiological processes, ranging from University Medical Center blood coagulation, fibrinolysis, and inflammation to immunity (Figure 1A). The activity of serine Hamburg-Eppendorf, Germany proteases is amongst others regulated by a dedicated class of inhibitory proteins called SERPINs Paulo Antonio De Souza Mourão, (serine protease inhibitors).