Candidate Biomarkers of Resistance to Retinoids in Cell Lines Derived from Neuroblastoma

FACULTY OF SCIENCE

Candidate biomarkers of resistance to retinoids in cell lines derived from neuroblastoma

Ph.D. Dissertation

VIERA DOBROTKOVÁ

Supervisor: RNDr. Petr Chlapek, DiS., Ph.D.

Department of Experimental Biology

Brno 2019

Bibliographic Entry

Author: Mgr. Viera Dobrotková Faculty of Science, Masaryk University Department of Experimental Biology

Title of Thesis: Candidate biomarkers of resistance to retinoids in cell lines derived from neuroblastoma

Degree Programme: Biology

Field of Study: Molecular and Cellular Biology

Supervisor: RNDr. Petr Chlapek, DiS., Ph.D.

Academic Year: 2018/2019

Number of Pages: 115+0

Keywords: Neuroblastoma; Retinoids; Candidate biomarkers; Resistance; Sensitivity; Differentiation therapy

Bibliografický záznam

Autorka: Mgr. Viera Dobrotková Přírodovědecká fakulta, Masarykova univerzita Ústav experimentální biologie

Název práce: Kandidátní biomarkery rezistence k retinoidům u buněčných linií derivovaných z neuroblastomu

Studijní program: Biologie

Studijní obor: Molekulární a buněčná biologie

Vedoucí práce: RNDr. Petr Chlapek, DiS., Ph.D.

Akademický rok: 2018/2019

Počet stran: 115+0 Klíčová slova: Neuroblastom; Retinoidy; Kandidátní biomarkery; Rezistence; Senzitivita; Diferenciační terapie

Abstract

Retinoids are key compounds in differentiation therapy, mainly in acute promyelocytic leukemia and high-risk neuroblastoma. Despite their proven effectiveness in preventing tumor relapse and improving patient survival, resistance to this treatment represents the most limiting factor in achieving an adequate clinical response. The aim of this study was to analyze the expression of five candidate biomarkers of responsiveness to retinoids that were recently discussed as promising in neuroblastoma. Analysis was performed in neuroblastoma cell lines, and the results were compared with data obtained from immunohistochemistry analysis of corresponding formalin-fixed paraffin-embedded samples. HOXC9 negativity was found to correlate with poor response to retinoids, and HOXC9 and PBX1 upregulation after retinoid treatment could predict sensitivity to retinoids in investigated cell lines. At the protein level, PBX1 downregulation was observed in retinoid-sensitive cell lines, and subsequent immunohistochemical analysis revealed that higher expression of PBX1 was significantly associated with a poorer response to chemotherapy and worse clinical outcome, supporting the usefulness of this biomarker in clinical practice.

Abstrakt

Retinoidy jsou klíčovou složkou diferenciační terapie, zejména u akutní promyelocytární leukémie a u vysoce rizikového neuroblastomu. Navzdory prokázané účinnosti při prevenci relapsu nádorů a zlepšování přežití pacientů představuje rezistence na tuto léčbu faktor, který nejvíce limituje dosahování adekvátní klinické odpovědi. Cílem této práce bylo analyzovat expresi pěti kandidátních biomarkerů senzitivity nebo rezistence k retinoidům, které byly u neuroblastomu v posledních letech popsány. Analýza byla prováděna na neuroblastomových buněčných liniích, výsledky byly porovnány s daty získanými z imunohistochemické analýzy odpovídajících formalínem fixovaných parafínových vzorků. Bylo zjištěno, že HOXC9 negativita koreluje s rezistencí k retinoidům a zvýšení exprese HOXC9 a PBX1 po podání retinoidů byl spojen se senzitivitou k těmto látkám. Na úrovni proteinů byla u senzitivních buněčných linií jako odpověď na působení retinoidů pozorována snížená exprese PBX1. Podle výsledků imunohistochemické analýzy byla vyšší exprese PBX1 spojena s horší odpovědí pacientů na chemoterapii a závažnějším průběhem onemocnění, což podporuje potenciální význam tohoto biomarkeru také v klinické praxi.

Acknowledgements

I would like to express my sincere gratitude to my supervisor RNDr. Petr Chlapek, DiS., Ph.D. for his support, patience, and motivation during my studies. My sincere thanks also go to prof. Renata Veselská, Ph.D., M.Sc. for her professional suggestions and kind encouragements, especially during the most difficult season of my study. I would also like to thank to my amazing colleagues from the Laboratory of Tumor Biology, who taught me to “keep calm and smile”. I would also like to express my gratitude to MUDr. Marta Ježová, Ph.D. for immunohistochemical analysis of tumor samples and to prof. MUDr. Jaroslav Štěrba, Ph.D. and MUDr. Pavel Mazánek for providing us with the clinical data and tumor samples. Last but not least, I would like to warmly thank to my husband, parents, sisters and all beloved ones for their great support, patience and love throughout my studies. Thank you!

This research was supported by the project No. 15-34621A from the Ministry of Healthcare of the Czech Republic, by the project Translation Medicine No. LQ1605 from the National Program of Sustainability II (MEYS CR) and by the project “Podpora výzkumné činnosti studentů molekulární biologie a genetiky” No. 5 (MUNI/A/0877/2016), 6 (MUNI/A/0824/2017), and 7 (MUNI/A/0958/2018).

Declaration

Hereby I declare that I worked on this Ph.D. dissertation on my own under the supervision of RNDr. Petr Chlapek, DiS., Ph.D., and I used only primary and secondary literature, which is properly cited and listed in the References.

Brno 16.7.2019 …………………. Viera Dobrotková

Publications related to thesis and author´s contribution disclosure

Ph.D. thesis is based on 4 manuscripts on which the author has a share (Viera Dobrotková, VD; maiden name Sláviková).

Manuscript 1

Dobrotkova, V., Chlapek, P., Jezova, M., Adamkova, K., Mazanek, P., Sterba, J., Veselska, R., 2019. Prediction of neuroblastoma cell response to treatment with natural or synthetic retinoids using selected protein biomarkers. PLOS ONE 14, e0218269.

VD realized most of the experiments, prepared the original draft and finalized the text after coauthorsʼ comments.

Manuscript 2

Dobrotkova, V., Chlapek, P., Mazanek, P., Sterba, J., Veselska, R., 2018. Traffic lights for retinoids in oncology: molecular markers of retinoid resistance and sensitivity and their use in the management of cancer differentiation therapy. BMC Cancer 18, 1059.

VD conceived and composed the review and finalized the text after coauthorsʼ comments.

Manuscript 3

Chlapek, P., Slavikova, V., Mazanek, P., Sterba, J., Veselska, R., 2018. Why Differentiation Therapy Sometimes Fails: Molecular Mechanisms of Resistance to Retinoids. Int J Mol Sci 19.

VD citically edited and commented the draft version of this manuscript.

Manuscript 4 (In review)

Veselska, R., Jezova, M., Kyr, M., Mazanek, P., Chlapek, P., Dobrotkova, V., Sterba, J., 2019. Comparative analysis of putative prognostic and predictive markers in neuroblastomas: High expression of PBX1 is associated with a poor response to induction therapy. Manuscript in review.

VD participated in data analyses and manuscript preparation.

Contents

List of abbreviations ...... 10

1 Introduction ...... 13

2 Background ...... 14

2.1 Neuroblastoma ...... 14

2.1.1 Diagnosis ...... 17

2.1.2 Etiology and genetic predispositions ...... 17

2.1.3 Staging and risk stratification ...... 20

2.1.4 Treatment ...... 24

2.2 Differentiation therapy ...... 27

2.2.1 Retinoids ...... 28

2.2.2 Mechanisms of resistance to retinoids ...... 33

2.2.3 Downstream protein markers of retinoid resistance ...... 37

3 Objectives ...... 41

4 Materials and methods ...... 42

4.1 Tumor samples and derivation of cell lines ...... 42

4.2 Chemicals ...... 45

4.3 MTT assay ...... 45

4.4 RT-PCR ...... 46

4.5 Immunoblotting ...... 48

4.6 Retinoid treatment ...... 49

5 Results ...... 51

5.1 Effect of retinoids on cell proliferation ...... 51

5.2 Endogenous gene expression of candidate biomarkers ...... 53

5.3 Endogenous protein expression of candidate biomarkers ...... 59

5.4 Changes in candidate biomarkers gene expression as a response to retinoid treatment ...... 65

5.5 Changes in candidate biomarkers protein expression as a response to retinoid treatment ...... 75

6 Discussion ...... 84

6.1 Predictive value of examined biomarkers according to their endogenous gene expression ...... Chyba! Záložka není definována.

6.2 Predictive value of examined biomarkers according to their endogenous protein expression ...... Chyba! Záložka není definována.

6.3 Changes of candidate biomarkers gene expression in response to retinoid treatment ...... Chyba! Záložka není definována.

6.4 Changes of candidate biomarkers protein expression in response to retinoid treatment ...... Chyba! Záložka není definována.

6.5 Comparison of obtained results with the results of IHC analysis performed on the corresponding tumor samples ...... Chyba! Záložka není definována.

7 Conclusion ...... 96

8 References...... 98

List of abbreviations

13-cis-RA 13-cis retinoic acid 4-HPR fenretinide 9-cis-RA 9-cis retinoic acid ABC ATP-binding cassette ABCA4 ATP-binding cassette transporter ACR acyclic retinoid ALDH1 aldehyde dehydrogenase 1 ALDH1A2 aldehyde dehydrogenase 1 family member A2 ALK anaplastic lymphoma kinase Amp amplified APL acute promyelocytic leukemia ATRA all-trans retinoic acid BCRP breast cancer resistance protein BDNF brain-derived neurotrophic factor BEX bexarotene BMP bone morphogenetic protein bp base pair CAR chimeric antigen receptor CRABP I cellular retinoic acid binding protein I CRABP II cellular retinoic acid binding protein II CT computed tomography CYP26 cytochrome P450 26 DCs dendritic cells DDX39A ATP-dependent RNA helicase DDX39A DMEM Dulbecco´s modified Eagle´s medium DMSO dimethylsulfoxide ECACC European Collection of Cell Cultures ECL enhanced chemiluminescence EMA European Medicines Agency EMT epithelial-mesenchymal transition

ERK extracellular signal-regulated kinase Fc fragment crystallizable FDA Food and Drug Administration FFPE formalin-fixed paraffin-embedded GAPDH glyceraldehyde-3-phosphate dehydrogenase GD2 disialoganglioside GN ganglioneuroma GNB ganglioneuroblastoma HAT histone acetyltransferase HCC hepatocellular carcinoma HDAC histone deacetylase HMGA1 high mobility group protein A1 HMGA2 high mobility group protein A2 HOXC9 homeobox C9 protein HRP horseradish peroxidase HSP90AB1 heat shock protein 90 alpha family class B member 1 IC50 half maximal inhibitory concentration IHC immunohistochemistry INRG International Risk Group INRGSS International Neuroblastoma Risk Group Staging System INSS International Neuroblastoma Staging System kDa kilodalton LRAT lecithin retinol acyltransferase MEM minimum essential media MRI magnetic resonance imaging MRP1 multidrug resistance protein 1 MTT 3-[4,5-dimethylthiazole-2-yl]-2,5-diphenyltetrazolium bromide MYCN MYCN proto-oncogene NAmp not amplified NAD(P)H nicotinamide adenine dinucleotide phosphate NBL neuroblastoma NC neural crest PBX1 pre-B-cell leukemia transcription factor 1

Pgp P-glycoprotein PHOX2B paired like homeobox 2B PI3K phosphoinositide 3-kinases PML promyelocytic leukemia PVDF polyvinylidene difluoride RA retinoic acid RAMBA retinoic acid metabolism-blocking agent RARE retinoic acid response element RARα retinoic acid receptor α RARβ retinoic acid receptor β RBP retinol binding protein RIPA radioimmunoprecipitation assay ROS reactive oxygen species RT-PCR reverse transcription polymerase chain reaction RXR retinoid X receptor SDS sodium dodecyl sulfate SNP single nucleotide polymorphism STRA6 stimulated by retinoic acid 6 TALE three-amino-acid loop extension TAMs tumor-associated macrophages TBS tris-buffered saline TF transcription factor TGF-β transforming growth factor beta TME tumor microenvironment TrkA tropomyosin receptor kinase A TrkB tropomyosin receptor kinase B XAB2 xeroderma pigmentosum group A-binding protein 2 ZNF423 zinc finger protein 423

1 Introduction

Neuroblastoma (NBL) is a complex disease with several factors determining the clinical outcome. The administration of retinoids represents an important part of the treatment for patients suffering from high-risk NBL because of the ability of retinoids to prevent tumor relapse after myeloablative therapy. However, toxicity and intrinsic or acquired resistance to retinoids limit their use in clinical practice, and seeking for biomarkers predicting patient response to retinoids is therefore a key strategy for further improvement of differentiation therapy. Several putative biomarkers, including DDX39A, HMGA1, HMGA2, HOXC9, and PBX1, indicating the sensitivity or resistance of NBL cells to retinoids have been reported in recent studies. The aim of this thesis was to analyze the expression of these candidate biomarkers that were reported to be associated with the responsiveness of NBL cell lines to retinoids to analyze their usefulness in predicting NBL patient responses to such a treatment. For this purpose, the expression of candidate biomarkers was analyzed in NBL cell lines at both mRNA and protein levels, and the obtained results were compared with the results of immunohistochemistry analysis performed on corresponding formalin-fixed paraffin- -embedded (FFPE) samples.

2 Background

2.1 Neuroblastoma

NBL is an early childhood solid tumor derived from neuroepithelial cells that migrate from the neural crest to form the sympathetic nervous system. The neural crest (NC), sometimes defined as the fourth germ layer, is a transient tissue derived from neuroectoderm in vertebrates. This embryonic population was identified in 1868 as a group of cells localized between the neural tube and the epidermis in the vertebrate embryo (Figure 1). After a phase of epithelial-mesenchymal transition (EMT), cells delaminate and migrate from the NC area and settle down in different parts of the body to become a part of either epithelial, mesenchymal, or endothelial components of the face, trunk, or heart, as well as the peripheral sympathetic ganglia and neuroendocrine adrenal medulla (Shakhova and Sommer, 2008; Strobl-Mazzulla and Bronner, 2012; Pegoraro and Monsoro-Burq, 2013; Shtukmaster et al., 2013).

Fig. 1 - Neural crest migration after neural tube closure with illustration of several cell lineages formed from NC cells. (Adapted from Kaltschmidt et al., 2012)

The history of NBL goes back to 1910, when James Homer Wright first recognized it as a tumor originating from primitive neural cells and called it neuroblastoma. He was also the first to describe rosettes - the circular clumps of cells typically occurring in NBL bone marrow, which are today known as “Homer Wright rosettes” (Wright, 1910). This study refers to two prior papers that described two patterns of NBL spreading to the liver and bones. NBL is the second most common solid tumor in children, accounting for 8-10% of childhood cancer in the USA and Europe (Cheung and Dyer, 2013) with an incidence of 10.5 per million children, slightly more affecting males (1.2/1.0) (Irwin and Park, 2015). NBL is known for its heterogeneity with clinical appearance varying from spontaneous regression to aggressive metastatic disease with dissemination mainly to the liver, bones, brain, and skin (Moreno et al., 2013). This heterogeneity is, among others, significantly related to the age at diagnosis - infants younger than 18 months are usually diagnosed with tumors that regress spontaneously, and surgical management is sufficient as a curable treatment (Stage 4S). Unfortunately, older patients diagnosed with NBL most frequently suffer from life-threatening tumors refractory to multimodal treatment (Newman and Nuchtern, 2016). Adrenal glands are the most frequent location of the primary tumor, but NBL can also develop anywhere along the sympathetic nervous system from the neck to the pelvis (Figure 2) (Friedman and Castleberry, 2007). Localization of primary NBL tumors represents another key factor affecting the variability in clinical presentation and patient outcomes. Spontaneous regression of the tumor is defined as an unexpected shrinkage or disappearance of the tumor mass without therapeutic intervention. Although this phenomenon has been observed in several cancer types (Challis and Stam, 1990; Papac, 1998), the vast majority of it is ascribed to NBL, even though its prevalence is hard to determine precisely. A specific pattern of metastatic spread, called stage 4S, was identified many years ago in 1971 (D’Angio et al., 1971) in infants younger than 1 year. These patients had typical small abdominal primary tumors with limited dissemination and very good prognoses. Despite the fact that spontaneous regression is usually associated with this particular stage of NBL, it is not clearly restricted only to stage 4S disease but more accurately to infants with any stage of disease if the tumor has biologically favorable characteristics (Kushner et al., 1996; Cozzi et al., 2013). Although the mechanism behind spontaneous regression is still unclear, much research has been

conducted in this field. According to previous studies, tropomyosin receptor kinase A (TrkA)-mediated apoptosis (Brodeur et al., 2009), telomere shortening (Hiyama et al., 1995; Matthay et al., 2016), immune-mediated destruction (Antunes et al., 2000), and epigenetic modification (Decock et al., 2011) might be involved in this process. All of the studies stress the importance of further research, since a better understanding of the processes leading to spontaneous regression might help to identify possible targets for more successful therapy and to identify patients whose tumors have the capacity to undergo regression.

Fig. 2 - Primary sites of neuroblastoma. (Davidoff, 2012)

2.1.1 Diagnosis

NBL is the most common malignancy diagnosed in the first year of life (Matthay et al., 2016) with a median age at diagnosis of 18 months (London et al., 2005). After this period, the incidence of patients diagnosed with NBL decreases over time (Nakagawara et al., 2018). Fatigue, loss of appetite, fever, and joint pain are the most common symptoms of NBL, making this disease difficult to diagnose properly. Depending on the primary tumor location, a swollen belly (abdomen), breathing problem (chest), or inability to stand or walk (tumor pressing on the spinal cord) may occur among patients. To confirm NBL diagnosis, a combination of laboratory tests, radiographic imaging and immunohistochemistry is performed. Finding that elevated levels of catecholamines and their metabolites are detectable in the urine of most NBL patients even before any symptoms are noticeable led to massive infant screening in many countries, including Japan, Canada, Austria and Germany, in the early 1980s (Woods et al., 2002). For several years, this screening program was considered to be the only one successful for childhood malignancies, resulting in a 2-fold increase in NBL diagnosis. However, studies from Canada and Germany showed no reduction in mortality of these patients, indicating that many of cases detected in this screening would probably have disappeared without treatment (Woods et al., 1996; Schilling et al., 2003). Considering these findings together with the fact that many of the diagnosed infants would have been subjected to unnecessary treatment, the screening program was halted in 2004 (Tsubono and Hisamichi, 2004).

2.1.2 Etiology and genetic predispositions

NBL is a developmental malignancy arising within the neuronal ganglia of the peripheral sympathetic nervous system. As previously mentioned, these neuronal structures are derived from the ventrolateral neural crest cells. In the process of maturation within the NC, NC precursors gain multipotent differentiation potential and attain a self-renewing phenotype. Subsequent differentiation of these precursors into epithelial, mesenchymal, and endothelial cell lineages including the peripheral sympathetic ganglia and neuroendocrine adrenal medulla is dependent on signaling gradients of bone morphogenetic protein (BMP), Wnt, Notch, and other ligands. Inhibition of any of these

signaling cascades may predispose early multipotent NC precursors to malignant transformation (Louis and Shohet, 2015). The vast majority of NBL cases are sporadic, with only approximately 1-2% of patients having a family history of the disease with an autosomal dominant pattern of inheritance (Mossé et al., 2008). To this day, no environmental factor has been shown to influence the risk of developing NBL, although maternal drug and hair dye use during pregnancy might have a negative impact on disease progression (Bluhm et al., 2006). In addition, neurocristopathies (disorders of neural crest-derived cells), including Hirschsprung disease, Turner syndrome, and neurofibromatosis type 1, have been reported to predispose patients to NBL (Blatt et al., 1997; Nemecek et al., 2003; Shahar and Shinawi, 2003). Despite the fact that MYCN proto-oncogene amplification has been identified as a negative prognostic factor many years ago (Seeger et al., 1985), the genetic basis of NBL remains unclear. Since understanding the genetic background of the disease involved in tumorigenesis represents a key point in developing optimal treatment for patients, many studies have focused on identifying genetic drivers of NBL. The first gene alteration found to predispose patients to NBL is a loss-of-function mutation on the paired like homeobox 2B (PHOX2B) gene (Mosse et al., 2004; Trochet et al., 2004). PHOX2B is responsible for NC precursors differentiation towards sympathetic neurons, and its loss-of-function mutations result in blocking NBL cells differentiation by disrupting calcium regulation, as was described recently (Pei et al., 2013; Wang et al., 2014). Later, a genome-wide linkage study of 6000 single nucleotide polymorphisms (SNPs) was performed in 20 families with NBL. As a result, 2p23-p24 chromosome bands containing 104 genes were identified as a hereditary factor in these familial NBL cases (Mossé et al., 2008). In addition to the MYCN gene, the anaplastic lymphoma kinase gene (ALK) is located in this region, and activating mutations in its tyrosine kinase domain were previously reported as a potential oncogenic event in NBL, as this gene has been identified to be involved in nervous system development (Hakomori et al., 2005; George et al., 2007; Osajima- Pontual et al., 2011). Indeed, ALK mutations were found to be present in approximately 80% of families with NBL and somatically acquired in 10% of all NBL patients (Chen et al., 2008; George et al., 2008; Janoueix-Lerosey et al., 2008; Mossé et al., 2008). Interestingly, ALK mutations were the first oncogenic mutations suggested to cause familial pediatric cancer - susceptibility genes are tumor suppressor genes in most cases. Moreover, ALK seems to cooperate with MYCN in promoting

tumorigenesis (Schulte et al., 2013). This description of the genetic landscape of NBL has already been applied in clinics - children from families with identified ALK or PHOX2B mutations are recommended to undergo ultrasonography and urinary catecholamine analysis until a minimum of age 5 to catch the very first signs of tumorigenesis. In general, two mechanisms of genomic instability may contribute to NBL progression: numerical and segmental chromosomal imbalances. Interestingly, patient prognosis was also reported to be highly correlated with these two types of genetic alterations. Patients carrying numerical chromosomal abnormalities with chromosome gains/losses have very good outcomes, even if they are older with advanced stages of disease, whereas segmental chromosome imbalances (gains/losses of smaller fragments) might be a strong predictor of poor outcomes in patients with metastatic tumors (Janoueix- Lerosey et al., 2009; Schleiermacher et al., 2012). From the group of segmental alterations, 1p, 3p, and 11q deletions together with 1q, 2p, and 17q gains are the most frequently detected in NBL and were confirmed to be statistically significant prognostic factors and to be associated with an increased risk of relapse (Janoueix-Lerosey et al., 2009). Moreover, loss of heterozygosity in chromosome segment 1p predicts poor outcomes and has been proven to correlate with MYCN amplifications (Caron et al., 1996; Riley et al., 2004). In addition to these tumor-specific genetic rearrangements, mutations in genes responsible for cell growth, cycle, and immunity typically contribute to final phenotypic changes in NBL patients. The MYCN oncogene, considered to be the hallmark of NBL, has a key role during nervous system development and is found to be overexpressed in approximately 25% of primary NBL tumors (Muñoz et al., 2006). The N-Myc protein functions as a transcription factor, both activating and repressing genetic targets and is a critical determinant of the capacity of NBL cells to terminally differentiate in response to retinoids. It is well described that the aberrant expression of N-Myc during developmental processes is associated with birth defects (Charron et al., 1992; Farina et al., 2002). Moreover, transgenic mouse models confirm that deregulated MYCN in the NC itself is sufficient to drive tumorigenesis (Hansford et al., 2004). Several studies demonstrated that retinoic acid-mediated differentiation of NBL cells depends on the downregulation of N-myc protein and that overexpression of exogenous N-myc promotes a differentiation-resistant phenotype (Thiele et al., 1985; Farina et al., 2002; Nguyen et al., 2003). While the fact that amplified MYCN prevents neuronal differentiation

is well known (Negroni et al., 1991; Nara et al., 2007), the molecular mechanism underlying this observation has remained unexplained for many years. A recent study profiling the retinoid signaling response of NBL cell lines revealed opposing regulation of retinoic acid (RA) and N-Myc on a number of differentiation-relevant genes and determined the pathways involved in N-Myc-mediated retinoid resistance, with transforming growth factor beta (TGF-β) signaling being a key regulator. TGF-β1 was previously shown to be induced by RA in RA-responsive NBL cell lines (Cohen et al., 1995), and its effect as a transcriptional regulator was strongly altered by N-Myc not only by the transcriptional regulation of TGFB1 mRNA but also through protein-protein interactions with a number of TGF-β signaling-associated proteins. This finding suggests several possibilities of combination treatment of retinoids with TGF-β activators to reduce MYCN-amplified RA-resistant neuroblastoma cell viability (Duffy et al., 2017).

2.1.3 Staging and risk stratification

Histopathological characterization of the tumor represents a key step in determining patient risk and choosing the most appropriate treatment strategy in each case. For this purpose, the International Neuroblastoma Staging System (INSS) was developed, enabling physicians to distinguish favorable and unfavorable groups based on the surgeon’s definition of resectability (Brodeur et al., 1993; Newman and Nuchtern, 2016). According to this system, patients with early-stage tumors (stages 1 and 2) have a better prognosis than patients with advanced-stage tumors (stages 3 and 4). An overview of the criteria for each NBL stage according to INSS is given in Table 1. Although the INSS is utilized worldwide, a new International Neuroblastoma Risk Group Staging System (INRGSS) for pretreatment risk classification is replacing the current system in many groups. Unlike the INRGSS, the INSS can change depending on the skill of the surgeon and cannot be used for assigning a risk group before some treatment has started, since it defines a postsurgical staging of NBL. In contrast, the INRGSS is based on clinical assessment and biological characteristics of tumors obtained from imaging tests - computed tomography (CT) or magnetic resonance imaging (MRI). Localized tumors are defined as stage L1 or L2, and metastatic tumors as stage M and MS (Monclair et al., 2009). A detailed overview of the stages in the INRGSS is given in Table 2.

Tab. 1 - International Neuroblastoma Staging System. (Adapted from Brodeur et al., 1993)

Stage Criteria

Localized tumor, complete resection with/without microscopic margins, 1 ipsilateral nodes negative.

2A Localized tumor, incomplete gross resection, ipsilateral nodes negative.

Localized tumor, with/without gross resection, ipsilateral nodes positive, 2B contralateral nodes negative.

Unresectable unilateral tumor that infiltrates the midline, with/without ipsilateral lymph 3 nodes, or localized tumor with contralateral positive nodes, or midline tumor with bilateral extension.

Any primary tumor with dissemination to distant lymph nodes, bone, bone marrow, 4 liver, skin (except as defined by 4S).

Localized primary tumor in infants < 12 months, with metastases limited to skin, liver, 4S bone marrow.

Tab. 2 - International Neuroblastoma Risk Group Staging System. (Adapted from Monclair et al., 2009)

Stage Criteria

L1 Localized tumor without image-defined risk factors.

L2 Localized tumor with presence of one or more image-defined risk factors.

M Distant metastatic disease (except stage MS).

MS Metastatic disease “special”, equivalent to stage 4S (INSS).

As mentioned above, pretreatment risk classification of NBL patients represents a key step in choosing the optimal treatment strategy for each patient, since the staging system alone is insufficient for predicting disease progression. The International Risk Group (INRG) classification system, which is currently widely adopted around the world, was proposed after comprehensive regression tree analyses of 8800 NBL patients all over the world based on several prognostic variables: INRGSS stage, age at diagnosis, histology category, tumor differentiation, MYCN oncogene amplification, chromosome segment 11q status, and DNA ploidy (Cohn et al., 2009). In this classification system, NBL patients are stratified into very-low-risk (5-year event-free survival (EFS) >85%), low-risk (EFS >75– ≤85%), intermediate-risk (EFS ≥50–≤75%), and high-risk (EFS <50%) groups. In general, MYCN gene amplification (more than 10 copies per cell) is considered to be the most important risk factor indicating poor prognosis in NBL patients (Seeger et al., 1985; Schmidt et al., 2000). In contrast, younger age at diagnosis (less than 18 months), higher degree of cell differentiation, stroma rich in Schwann cells and DNA hyperdiploidy are correlated with good prognosis (Fredlund et al., 2008; Cohn et al., 2009). A detailed INRG pretreatment risk group classification scheme is given in Table 3. In addition to the prognostic factors mentioned above, the tumor microenvironment (TME) plays a critical role in patient prognosis and clinical staging. Many NBL tumors that regress spontaneously or differentiate typically have stroma rich in Schwann cells, which are an abundant source of neurotrophins. These growth factors stimulate immature NBL cells to differentiate into benign ganglioneuroblastoma and ganglioneuroma (Ambros et al., 1996; Kwiatkowski et al., 1998). As a result, clinical trials testing agents targeting the TME have been initiated with main strategies including direct targeting of TME cells, targeting signaling pathways activated by the TME and immunotherapy (Borriello et al., 2016).

Tab. 3 - International Neuroblastoma Risk Group system. (Adapted from Cohn et al., 2009) Blank field = “any”; GN, ganglioneuroma; GNB, ganglioneuroblastoma; NBL, neuroblastoma; Amp, amplified; NAmp, not amplified.

INRG Age MYCN 11q Risk group Histology Ploidy Stage (months) status aberration

GN maturing/ L1/L2 GNB intermixed Any, except GN Very low-risk L1 maturing or NAmp GNB intermixed

MS < 18 NAmp No

Any, except GN L2 < 18 maturing or NAmp No GNB intermixed Low-risk GNB nodular; L2 ≥ 18 NAmp No NBL M < 18 NAmp Hyperdiploid

Any, except GN < 18 maturing or NAmp Yes L2 GNB intermixed Intermediate- GNB nodular; risk ≥ 18 NAmp Yes NBL

< 12 NAmp Diploid M 12 to < 18 NAmp Diploid

Any, except GN L1 maturing or Amp GNB intermixed

GNB nodular; L2 ≥ 18 Amp NBL High-risk < 18 Amp M ≥ 18

NAmp Yes MS < 18 Amp

2.1.4 Treatment

As previously mentioned, NBL is a heterogeneous disease requiring a multidisciplinary approach for treatment. Moreover, choosing the right therapy for each patient depends on correct patient stratification into one of the risk categories. While children with favorable nonmetastatic NBL usually require little or no cytotoxic therapy, outcomes for patients with high-risk NBL are still poor, although many new therapeutic strategies, such as biological therapy and immunotherapy have shown promising preclinical results (Park et al., 2013). Treatment for low-risk patients consists of surgical resection alone, and infants with stage 4S NBL without substantial symptoms may undergo observation only in the presence of tumor with favorable biological characteristics. Intermediate-risk NBL patients usually undergo chemotherapy and tumor resection. Moreover, radiation therapy is administered in cases with the risk of organ impairment when the tumor does not respond to initial chemotherapy (Davidoff, 2012). In contrast, patients with high-risk NBL (typically carriers of MYCN amplification and older than 18 months of age) receive an intensive multimodal therapy subdivided into three phases: induction, consolidation, and postconsolidation (maintenance) therapy (Figure 3). In the induction phase, the administration of chemotherapy and surgery are aimed at minimizing the tumor mass and removing as much of it as possible. The following consolidation phase has a goal to eliminate remaining minimal disease, and maintenance therapy is developed to treat residual disease that remains despite induction and consolidation treatment regimens (Smith and Foster, 2018).

Fig. 3 - Current treatment strategy for high-risk NBL.

Although there are slight variations in these regimens depending on where a patient is being treated, this multimodal treatment generally includes chemotherapy, surgical resection, myeloablative consolidation therapy with stem cell rescue, radiation therapy, differentiation therapy and antibody-based immunotherapy (Matthay et al., 1999; Sterba, 2002; Yu et al., 2010). Standard chemotherapy consists of dose-dense or dose-intensive and myeloablative regimens using alkylating agents (cyclophosphamide, temozolomide), platinum compounds, topoisomerase-I inhibitors (topotecan, irinotecan), and topoisomerase-II inhibitors (doxorubicin, etoposide). Unfortunately, a significant number of high-risk NBL patients will still relapse and eventually die of disease.

2.1.4.1 New treatment strategies

Years of intensive research on NBL cell lines and mouse models have resulted in a better understanding of the processes and mechanisms involved in NBL tumorigenesis and progression and have led to the identification of new candidates for more precise and successful therapy. Some of these new agents can be used together with conventional regimens, and some have the potential to be used as independent treatment strategies. Several promising treatment strategies developed recently will be discussed below. Biological therapy that has improved survival outcomes in many malignant diseases appears to be a promising strategy for patients with advanced NBL. The first attempt in this field is targeted immunotherapy based on cell sensitivity to antibody-dependent cell-mediated cytotoxicity (Cheung, 1991) and uses an antiganglioside antibody against disialoganglioside (GD2), the predominant antigen expressed uniformly on the surface of NBL and retinoblastoma, rhabdomyosarcoma, or osteosarcoma cells (Davidoff, 2012). The idea of this strategy is to specifically target tumor cells by monoclonal antibodies that can recognize GD2 antigens localized on the surface of tumor cells. In the next step, the fragment crystallizable (Fc) component of the antibody can bind to the Fc receptor on monocytes, macrophages, or natural killer cells and stimulate tumor cell lysis via antibody-dependent cell-mediated cytotoxicity (Yang and Sondel, 2010). Another option for cancer immunotherapy includes adoptive T-cell therapy with chimeric antigen receptors (CARs) to recognize GD2 antigens. According to the results of a phase 1 study in 19 high-risk NBL patients, this approach can induce a complete tumor response associated with improved survival (Pule et al., 2008; Louis et al., 2011).

The discovery of the activation germline mutation of the ALK kinase gene in a majority of familial NBL that results in worse event-free and overall survival introduced the possibility to develop new targeted therapy for carriers of this mutation (Chen et al., 2008). Not surprisingly, after positive preclinical data and discovery of a growing number of clinically approved ALK inhibitors, a clinical phase 1 trial was initiated aiming to introduce crizotinib for pediatric cancer patients (Mossé et al., 2013). In this study, only 1 of 11 NBL patients carrying ALK mutations showed response to the treatment, suggesting that such an approach alone is probably insufficient and that the combination of ALK inhibitors with other therapeutic strategies might be more effective (Wood et al., 2017). Tyrosine kinase (Trk) receptors for neurotrophins that are important for the development of the sympathetic nervous system have also been studied in NBL pathogenesis. Among this group of receptor-ligand pairs, TrkA expression is associated with favorable outcomes, as it appears to mediate differentiation processes in neurons and its agonists can induce cellular differentiation. Conversely, the tropomyosin receptor kinase B (TrkB) pathway seems to promote NBL survival and is usually expressed in advanced-stage disease. Therefore, blocking the TrkB/brain-derived neurotrophic factor (BDNF) signaling pathway with specific inhibitors can block crucial survival pathways in cells and result in apoptosis (Nakagawara et al., 1994). In the previous decade, miRNAs – small, noncoding single-stranded RNAs – have been extensively studied, since their ability to downregulate expression of targeted mRNA makes them candidates for having a tumor-suppressive role. Indeed, miRNA dysregulation has been observed in a variety of cancer types, including NBL (Wei et al., 2009). In recent studies based on genome-wide microRNA profiling, several miRNA molecules have been indicated to regulate ALK expression (De Mariano et al., 2017), impair the growth of chemoresistant NBL cells (Soriano et al., 2016), or block neuronal differentiation (Samaraweera et al., 2014). Targeting miRNA expression in NBL cells might therefore represent a new treatment strategy for patients with particular miRNA expression profiles (Tivnan et al., 2012). In terms of providing an individual therapeutic approach for each NBL patient, the molecular features of the tumor itself together with the detailed diagnosis need to be precisely considered to facilitate treatment and management of NBL (Zage, 2018). In addition to many other potentially effective treatment strategies, molecular tumor

profiling might be effective in the development of personalized therapy for children with recurrent neuroblastoma. In an initial pilot study, DNA sequencing and RNA expression profiling were performed on tumor biopsies, and individualized patient treatment plans were created considering the results obtained from each analysis (Sholler et al., 2012). Several additional studies have also shown promising results, demonstrating that molecular profiling could guide individualized treatment strategies for NBL patients (Harris et al., 2016; Worst et al., 2016). Differentiation treatment with retinoids, which represents another key step in multimodal therapy for high-risk NBL, will be discussed in detail in the following part of this dissertation.

2.2 Differentiation therapy

Differentiation therapy is a therapeutic strategy that aims at inducing the reactivation of endogenous differentiation programs and the maturation of cancer cells (Cruz and Matushansky, 2012). This idea was first proposed in 1961 by Pierce, after self-differentiation was observed in teratocarcinomas (Pierce and Verney, 1961; Xu et al., 2014). In the following years, several studies suggested the potential of this strategy in the treatment of hematological malignancies (Sachs, 1978; Breitman et al., 1980, 1981). The very first attempts included demonstrations of the differentiating capacity of dimethyl sulfoxide (DMSO) on erythropoiesis (Friend et al., 1971). In addition, several compounds, such as phorbol diesters, teleocidins, polar planar drugs, cytokines, or vitamin D metabolites, have shown potential to induce cell differentiation in vitro (Koeffler, 1983; Nowak et al., 2009). Later in the 1980s, all-trans retinoic acid (ATRA) was used in the treatment of acute promyelocytic leukemia (APL), which radically changed this disease into one of the most curable forms of leukemia (Huang et al., 1989; Xu et al., 2014). As it was realized very soon, ATRA was specifically effective in APL cells carrying a translocation between chromosomes 15 and 17 and not in other leukemias (Breitman et al., 1981). This observation has a simple explanation: this characteristic chromosomal translocation results in the fusion of the retinoic acid receptor α (RARα) and promyelocytic leukemia (PML) genes. The fusion product subsequently recruits corepressors and inhibits the expression of target genes required for granulocytic differentiation (Nowak et al., 2009). Consequently, increased levels of ATRA are

necessary to both disrupt the PML/RARα fusion protein and to promote a therapeutic response to the treatment. Differentiation therapy in solid tumors is undoubtedly much more challenging, since the molecular mechanisms responsible for differentiation blocks may vary among tumor types and are usually more complex. Indeed, no such effect comparable to that of ATRA for treating APL has been reported to date in solid tumors. Nevertheless, the capability of retinoids to induce differentiation of malignant cells was confirmed in several tumor types, including NBL (Sidell et al., 1983), choriocarcinoma (Chou, 1982), or teratocarcinoma (Lehtonen et al., 1983). As previously mentioned, APL is caused by a special fusion gene responsible for tumorigenicity and the reversal of one pathway is sufficient to mediate cell differentiation and therefore to highly improve patient prognosis (Xu et al., 2014). In contrast, solid tumor tissue is a heterogeneous mass containing aberrant cells at various stages of differentiation, and a mono-targeted strategy seems insufficient in this case. For this reason, regimens that include a combination of differentiation-inducing agents with conventional radiation or chemotherapy might have greater efficacy. For example, histone deacetylase (HDAC) inhibitors were reported to increase the expression of retinoid receptors, and their coadministration with retinoids represents a promising strategy to improve the efficacy of retinoid treatment in solid tumors (Yang et al., 2011).

2.2.1 Retinoids

Retinoids are natural and synthetic derivatives of vitamin A and represent the prototype compounds used in differentiation therapy of human malignancies. The therapeutic potential of retinoids is based on their key role in regulation of cell differentiation, growth, and apoptosis, which predetermines them for use in therapy and also in chemoprevention (Chou, 1982; Felsted et al., 1983; Sidell et al., 1983; Sakashita et al., 1993; Van heusden et al., 1998; Dragnev et al., 2000; Reynolds, 2000). In recent years, the mechanism through which retinoids regulate innate and adaptive immunity have been described, which has received great attention and explained the antineoplastic effects of retinoids from another perspective. According to recently published study, retinoids could affect the differentiation, recruitment and polarization of tumor-associated macrophages (TAMs), which participate in the tumorigenesis of many cancers and their

emergence into tumor stroma is associated with a poor prognosis (Liss et al., 2002). Moreover, ATRA treatment was reported to inhibit the differentiation and maturation of dendritic cells (DCs) and to improve the antigen-specific immune response, since DCs in their immature stage are highly efficient in taking up and processing antigens (Jin et al., 2010). Retinoids are lipophilic isoprenoids composed of a highly conjugated terpene chain and a hydrophilic polar group, which can be modified to generate several forms of retinoids. The main source of retinoids for humans is provitamin A, which is acquired from diet by metabolizing carotenoids into retinal in the gut. Retinal is then reduced to retinol, which is the most abundant transport form of retinoids in the human body and is enzymatically activated to retinoic acid by the isoforms of aldehyde dehydrogenase 1 (ALDH1) (Chlapek et al., 2018). There are several stereo isoforms of RA in the organism: all-trans retinoic acid (ATRA), 9-cis retinoic acid (9-cis-RA), and 13-cis retinoic acid (13-cis-RA). Moreover, ATRA can be isomerized to 9-cis or 13-cis-RA and both 9-cis and 13-cis-RA can be isomerized to ATRA (Figure 4). Among these isoforms, ATRA was proved to be the most active isomer in the human body (Lanvers et al., 1998).

Fig. 4 - Chemical structures of RA isomers. (Marchetti et al., 1997)

After retinoids are absorbed in the intestine and metabolically transformed, retinol binding protein (RBP) binds to retinol in the circulation protecting it from chemical modification. Subsequent cellular uptake of retinoids activated by RBP binding to the cell surface RBP receptor stimulated by retinoic acid 6 (STRA6) is facilitated by transporters such as the scavenger receptor class B type 1, or the ATP-binding cassette transporter ABCA4 (Molday and Zhang, 2010; Reboul and Borel, 2011; Sun and Kawaguchi, 2011; Kelly and von Lintig, 2015). Since retinoids show limited stability and low solubility in aqueous solutions, their transport through the cell occurs by transport proteins, which shuttle RA from cytosol to the nucleus to bind retinoid acid receptors. Among these transport proteins, cellular retinoic acid binding protein I and II (CRABPI and CRABPII) deliver retinoids to the retinoic acid receptor (RAR) or retinoid X receptor (RXR), which are nuclear receptors from the steroid hormone receptor superfamily of ligand-activated inducible transcription factors (TFs). When activated by retinoids, receptors form homo- or heterodimers (RXR-RXR/RAR-RAR, RXR-RAR) that subsequently bind to retinoic acid response elements (RAREs) in the promoter regions of target genes or antagonize the enhancer action of other TFs (Figure 5) (Gigueère, 1994; Dobrotkova et al., 2018). Besides directing retinoids to these nuclear receptors, CRAB proteins can also regulate their amount by delivering ATRA to the catabolic pathway to be degraded by cytochrome P450 enzymes (Napoli, 2017). In addition to this well-defined mechanism of regulating genomic transcriptional activity via RA receptors, extranuclear, nongenomic effects of retinoids have been recently described. In several studies, RA was identified to rapidly (within minutes after RA administration) activate kinase signaling pathways. As a result, RA-activated kinases can phosphorylate TFs, which in turn activate the transcription of genes (involved for example in neuronal differentiation) that are not directly regulated by retinoids, expanding the spectrum of their biological activities (Ochoa et al., 2003; Cañón et al., 2004; Iskakova et al., 2015; Waetzig et al., 2019). For example, in neuronal cell lines, retinoid-mediated activation of extracellular signal-regulated kinases (ERKs) via the activation of upstream phosphoinositide 3-kinase (PI3K)/Akt kinases has been described (Pan et al., 2005; Cheung et al., 2009). In fibroblasts, mammary breast tumor cells, and leukemia cells, RA activates the p38 mitogen-activated protein kinase (p38MAPK), suggesting that the activation of particular kinase signaling pathways is cell type-dependent

(Alsayed et al., 2001; Piskunov and Rochette-Egly, 2012). A detailed understanding also to these non-genomic mechanisms of retinoid acid effects undoubtedly opens new therapeutic perspectives for the future use of retinoids in clinical practice.

Fig. 5 - Regulation of gene expression by RA. When RA is present and binds to RAR/RXR complex bound to RARE element, co-repressors that were blocking RAR/RXR heterodimer by default are replaced by several co-activators of the nuclear receptor co-activator (NCOA) family that bind to RAR and recruit activating factors such as Trithorax and histone acetylase (HAT) enabling transcription of particular gene. (Cunningham and Duester, 2015)

2.2.1.1 Synthetic retinoids

Although natural retinoids have been used as differentiation inducers for APL (ATRA) or NBL (13-cis-RA) patients for many years, vitamin A-associated toxicity including liver and lipid alterations, dry skin, teratogenicity, bone and connective tissue damage markedly limits their long-term administration. This is the main reason, why synthetic analogues of retinoids are being produced by modification of several functional groups with the aim to increase chemoprevention efficacy and reduce their toxicity and side effects compared to natural retinoids. To date, many derivatives of natural retinoids have been synthetized and investigated extensively. At least some of them will be mentioned below.

Acyclic retinoid ((2E,4E,6E,10E)-3,7,11,15-tetramethylhexadeca-2,4,6,10,14- pentaenoic acid; ACR) (Figure 6A), a synthetic vitamin A-like compound acting as a ligand for RXRα was found to prevent the development of hepatocellular carcinoma (HCC) and to induce apoptosis and inhibit cell growth of human HCC cells when administered together with PI3K inhibitor (Baba et al., 2013). Bexarotene (4-(1-(3,5,5,8,8- pentamethyl-5,6,7,8-tetrahydro-2-naphthyl)ethenyl) benzoic acid; BEX) (Figure 6B) is a synthetic retinoid approved by the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) for treatment of cutaneous T cell lymphoma as a third-generation retinoid compound (Gniadecki et al., 2007). Moreover, BEX has been indicated to decrease proliferation and promote apoptosis in several other cancer types including thyroid, non-small cell lung cancer or NBL, especially when combined with standard chemotherapy (Klopper et al., 2015; Dheer et al., 2018; Dragnev et al., 2018). Fenretinide (N-(4-hydroxyphenyl) retinamide; 4-HPR) (Figure 6C), another synthetic derivative of ATRA has been shown to exhibit anti-tumor and also chemopreventive effects in several types of cancer including breast, bladder, oral mucosa, ovarian cancer, and NBL (Maurer et al., 2013; Wang et al., 2013a; Han et al., 2015; Puntoni et al., 2016; Anding et al., 2018; Song et al., 2019). In human breast cancer models, orally active retinoid-relate molecule ST1926 ((E)-3-[4-[3-(1-adamantyl)-4-hydroxyphenyl]phenyl] prop-2-enoic acid) (Figure 6D) and its antitumor activity have been investigated. Interestingly, ATRA-resistant cells were sensitive to this synthetic retinoid. Moreover, ST1926 was able to induce apoptosis, caused DNA damage and its ability to inhibit cell growth was independent of the retinoid-receptor signaling pathway, which highlighted the therapeutic potential of this retinoid and stressed the importance of its further clinical evaluation (Aouad et al., 2017). TAC-101 (4-[3,5-bis(trimethylsilyl) benzamide] benzoic acid) (Figure 6E), an oral synthetic retinoid showed to suppress hepatocellular carcinoma cells growth and inhibit angiogenesis both in colon cancer and hepatocellular carcinoma (Murakami et al., 1999; Okusaka et al., 2012). Another compound, WYC-209 (ethyl 2-((4,4-dimethyl-1- oxidothiochroman-6-yl)ethynyl)pyrimidine-5-carboxylate) (Figure 6F) was recently identified as promising compound in treating malignant melanoma thanks to its ability to inhibit proliferation of malignant murine melanoma tumor-repopulating cells which are known to resist conventional chemotherapy (Chen et al., 2018).

As is apparent from these examples, development of new compounds able to minimize negative side effects and even improve therapeutic impact of retinoids represents very promising step in an effort to mediate malignant cells differentiation status as successfully as possible. Several synthetic retinoids are currently being tested and many of them already showed better side-effect profile and anti-angiogenic effects, even in ATRA-resistant cell lines. However, their biggest disadvantage is undoubtedly the lack of information about their long-term effects on human body, especially of the newly-synthetized ones (Dobrotkova et al., 2018).

Fig. 6 - Chemical structures of synthetic retinoids. (A) acyclic retinoid, (B) bexarotene, (C) fenretinide, (D) ST1926, (E) TAC-101, (F) WYC-209.

2.2.2 Mechanisms of resistance to retinoids

In addition to the relative toxicity and several side effects of retinoid treatment that were discussed above, resistance to these compounds represents the most challenging aspect of their future use in the anticancer therapy (Masetti et al., 2012). A detailed understanding to the mechanisms of resistance or sensitivity to retinoids is therefore a key aspect that may help in prediction of patient clinical response to such a treatment and also in developing mechanisms able to sensitize tumor cells to these compounds.

In general, two types of drug resistance may occur - acquired or intrinsic. In the case of acquired or secondary drug resistance, tumor that initially responded to treatment is no longer sensitive to the anti-cancer agent as evidenced by proliferation arrest or differentiation. On the contrary, intrinsic drug resistance refers to insignificant or no response to the therapy at the onset of treatment (Goldie, 2001; Haar et al., 2012). Regardless of this categorization, the mechanisms responsible for resistant phenotype are usually similar if not the same in both of the types of resistance, as they are based on natural mechanisms that play a role in protecting tissues from xenobiotic accumulation and their toxicity. Besides, several mechanisms of resistance are often combined and the resistance itself can be therefore described as a multifactorial phenomenon (Chlapek et al., 2018). Overview of the most important mechanisms contributing to retinoid-resistant phenotype is given in Figure 7.

Fig. 7 - Possible mechanisms of retinoid resistance. Retinoid-resistant phenotype observed in cancer cells may be caused by several mechanisms including (1) decreased retinoid uptake; (2) intracellular retinoid metabolism; (3) altered intracellular retinoid availability affected by CRAB protein binding; (4) intensive retinoid efflux through ABC transporters; (5) retinoid degradation catalyzed by cytochrome P450; (6) alterations in RAR and/or RXR expression; (7) inhibition of transcription mediated by retinoids caused by repressor complex; (8) impaired coactivator structure, expression, or activity; (9) imbalances in downstream target gene expression. (Dobrotkova et al., 2018)

First mechanism that may contribute to the development of resistance to retinoids is based on the decreased retinoid uptake that may be caused by altered expression of STRA6 receptor or protein transporters maintaining effective retinoid transport into the cell through the cell membrane (Pavone et al., 2010). Changes in retinol metabolism as the primary source of retinoids within cells represent the second mechanism possibly involved in RA resistant phenotype. Several enzymes are involved in regulation of retinol concentration in the cytoplasm and can therefore mediate resistance to retinoids by controlling the availability of retinol required for conversion to RA. For example, lecithin retinol acyltransferase (LRAT) knockdown was sufficient to restore sensitivity to retinoids in melanoma cells (Amann et al., 2014). Regulation of RA biosynthesis is another important process involved in maintaining appropriate levels of retinoids in the organism. Aldehyde dehydrogenase (ALDH) is an enzyme expressed in the liver and is necessary for retinol conversion to RA (Chute et al., 2006). Aldehyde dehydrogenase 1 family member A2 (ALDH1A2) enzyme, an isoform of the ALDH1 enzyme, was found to correlate with poor prognosis in NBL patients and with the resistance of NBL cells to 13-cis-RA (Hartomo et al., 2015). Aberrant expression of intracellular transporters of RA (CRABPI, CRABP II) can also be associated with resistance to retinoids. Not only do they transport RA to nuclear receptors to regulate transcription in the cell, but can also direct retinoids to locations for degradation. The subsequent clearance is regulated by enzymes from the cytochrome P450 family, especially by cytochrome P450 26 (CYP26) enzymes. Since ATRA itself is able to induce its own catabolic degradation via this enzyme, several inhibitors described as retinoic acid metabolism-blocking agents (RAMBAs) have recently been developed (Diaz et al., 2016; Chlapek et al., 2018). Even if retinoids are not degraded in processes mentioned above, their active efflux from the cell to the extracellular space may also result in their decreased concentration within the cell and therefore in reduced ability to regulate gene expression. In this process of active transport outside the cell, proteins from the superfamily of ATP-binding cassette (ABC) transmembrane transporters play a key role. As a result of overexpression of genes encoding these transporters (e.g. P-glycoprotein, Pgp; multidrug resistance protein 1, MRP1; breast cancer resistance protein, BCRP), multidrug resistance to a wide range of cytotoxic agents was reported in various tumor types (Peaston et al., 2001; Stromskaya et al., 2005; Alisi et al., 2013; Tarapcsák et al., 2017).

Since most of retinoid effects within the cell are exerted by retinoid nuclear receptors (RAR, RXR, and their subtypes α, β, γ), alterations in signaling through these receptors are unsurprisingly also very important in the development of resistance to retinoids. For example, expression of RARβ is frequently downregulated in solid tumors and its truncated isoform was identified in breast cancer cell lines in association with increased cell proliferation and ATRA resistance (Swift et al., 2006). Probably the most frequent aberration of retinoid receptors is connected to the APL disease in which a PML/RARα complex as a result of chromosomal translocation causes increased affinity of RAR receptor for co-repressors (de Thé et al., 1991). In addition to alterations in RAR or RXR expression, phosphorylation of these molecules was also reported to play an important role in maintaining their proper function. In breast cancer cell lines, deregulation of cytoplasmic signaling cascades led to the aberrant phosphorylation of RAR receptors, which subsequently caused RARα degradation or inhibition of its transcriptional activity (Tari et al., 2002; Duong and Rochette-Egly, 2011). As previously mentioned, regulation of gene transcription by retinoids is realized by constitutive binding of RAR-RAR homodimers or RAR-RXR heterodimers to RARE elements in the regulatory regions of target genes. In the absence of RA, these dimers are associated with corepressors which prevent gene transcription. After RA is delivered to the nucleus, a conformational change in RAR receptor causes release of corepressor complex and coactivators with histone acetyltransferase (HAT) activity bind to dimerized receptor instead. These coactivators induce a “loose” state of chromatin that is required for active gene transcription (Chlapek et al., 2018). Indeed, overexpression of xeroderma pigmentosum group A-binding protein 2 (XAB2), a component of the RAR corepressor complex was observed to inhibit ATRA-induced cell differentiation in human rhabdomyosarcoma cell line (Ohnuma-Ishikawa et al., 2007). On the other hand, overexpression of zinc finger protein 423 (ZNF423) cofactor for RARα-RXRα transactivation caused inhibition of proliferation and enhanced differentiation in NBL primary tumor samples (Huang et al., 2009).

2.2.3 Downstream protein markers of retinoid resistance

Another promising strategy in identification of tumor cells resistant/sensitive to retinoids is seeking for “downstream” protein markers involved in regulation of cell differentiation or apoptosis whose expressions are mediated (directly/indirectly) by retinoids. Nowadays, more than 500 genes have been identified as regulatory targets of RA either directly or indirectly by intermediate TFs or even more distant mechanisms (Balmer and Blomhoff, 2002). Many of the genes involved in cells differentiation are expressed ubiquitously, but a big amount of them are tissue-specific, suggesting that searching for these predictive markers of resistance to retinoids requires individual approach focused on each type of tumor exclusively. Since this dissertation thesis is aimed at candidate biomarkers of resistance to retinoids in NBL cell lines, only molecules recently discussed in relation to resistance in this particular tumor will be described below: DDX39A, HMGA1, HMGA2, HOXC9, and PBX1.

2.2.3.1 DDX39A

ATP-dependent RNA helicase DDX39A (DDX39A) is an ATP-dependent RNA helicase belonging to the highly conserved DEAD box protein family characterized by the motif Asp-Glu-Ala-Asp (D-E-A-D amino acid sequence). These helicases are involved in nearly all processes involving RNA, from transcription to RNA decay including pre-mRNA splicing, mRNA export, ribosome biogenesis or translation initiation (Linder, 2006). Moreover, DDX39A is required for global genome integrity and telomere protection (Yoo and Chung, 2011). According to several studies, DDX39A expression could be associated with poor clinical outcomes of cancer patients (Sugiura et al., 2007; Kikuta et al., 2012). In 2016, DDX39A was identified as a potential biomarker for unfavorable NBL, as its expression correlated with undifferentiated NBL cells both in vitro and in primary tumor samples before and after treatment with ATRA (Otake et al., 2016). Although no link to retinoid resistance was suggested in the mentioned study, DDX39A was involved in the group of examined candidate biomarkers in this thesis to gain a deeper understanding of its potential role in preventing cell differentiation.

2.2.3.2 HMGA1 and HMGA2

HMGA1 and HMGA2 are members of the high mobility group proteins family (HMG) which is a heterogeneous group of nonhistone DNA binding factors involved in the organization of active chromatin. These proteins typically contain three AT-hook DNA binding domains through which they bind to AT-rich sequences in the minor groove of the DNA helix and therefore work as ancillary transcription factors. HMGA proteins were also reported to participate in regulation of basic biological processes, such as cell growth, differentiation or apoptosis. Moreover, deregulation of HMGA expression has been indicated as a hallmark of cancer (Cerignoli et al., 2004). Both HMGA1 and HMGA2 genes were reported to affect retinoic acid responsiveness of NBL cell lines already in 1999 (Giannini et al., 1999). In this study, HMGA2 mRNA was detected only in RA-resistant NBL cell lines suggesting that HMGA2 expressing tumors might be less sensitive to retinoid-mediated differentiation and growth arrest. HMGA1, the second member of HMG family was found to contribute to tumorigenesis in several tissues (Bussemakers et al., 1991; Ram et al., 1993; Chiappetta et al., 1995, 1998; Fedele et al., 1996). In contrast to HMGA2, HMGA1 transcript was found to be expressed at different levels in all NBL cell lines. Moreover, HMGA1 downregulation after treatment with ATRA was observed in RA-sensitive subset of cell lines and HMGA1 upregulation in NBL cell lines resistant to ATRA (Giannini et al., 1999). In the following study, increase of HMGA1 protein expression as a response to ATRA treatment was detected in RA-resistant cell lines and only RA-resistant cell lines expressed HMGA2 protein whose expression was not affected by ATRA (Giannini et al., 2000). In the same study, immunohistochemical (IHC) analysis showed that higher levels of HMGA1 correlated with less differentiated status of NBL, suggesting that HMGA1 expression could serve as a potential diagnostic and prognostic marker in this disease.

2.2.3.3 HOXC9

Homeobox C9 protein is a member of conserved family of transcription factors named by the DNA-binding homeodomain which is encoded by the homeobox DNA sequence found within corresponding genes. Proteins from this family are typically involved in morphogenesis regulation, cellular differentiation, or maintaining pluripotency during early embryonic development in animals, fungi, plants, and numerous single cell eukaryotes (Bürglin and Affolter, 2016). Among HOX proteins, HOXC9 was suggested to be a key mediator of RA action in the development of nervous system. According to the study published in 2011, HOXC9 gene was expressed at significantly higher levels in differentiated NBL and in NBL cells undergoing RA-induced differentiation (Mao et al., 2011). Moreover, HOXC9 induction was found to be required for both RA-induced growth arrest and repression of growth-promoting genes indicating a tumor suppression function of HOXC9 in NBL pathogenesis. High HOXC9 gene expression was also identified as prognostic for favorable outcome in the same study. Besides, HOXC9 induction as a response to RA was detected in RA-sensitive cell lines and in RA-resistant cell lines, ATRA failed to induce HOXC9 expression. Furthermore, HOXC9 promoter was epigenetically primed into a RA-responsive state in ATRA-sensitive and in a silenced state in ATRA-resistant NBL cell lines.

2.2.3.4 PBX1

The last candidate biomarker of resistance to retinoids chosen for the purpose of this thesis is pre-B-cell leukemia transcription factor 1 (PBX1 protein) belonging to the three-amino-acid loop extension (TALE) family of atypical homeodomain proteins. Similarly to HOX proteins, TALE family genes are critical to differentiation processes, including retinoid-induced differentiation (Qin et al., 2004a). Moreover, PBX1-3 proteins have been shown to control endogenous retinoid synthesis within the nervous system (Vitobello et al., 2011). Since the function of TALE family genes is temporospatially specific, it is not rare that the same gene has divergent functions in different tissues. As an example, PBX1 acts as a tumor suppressor in prostate cancer (Chen et al., 2012), but is implicated as an oncogene in breast cancer, melanoma, or leukemia (Kamps et al., 1990; Shiraishi et al., 2007; Magnani et al., 2011). Therefore, a detailed investigation of PBX1 function specifically in NBL tissue or cell lines is necessary to gain a deeper 39

understanding of its role in NBL tumorigenesis. According to the study from 1997, PBX1 represents one of the key cofactors modulating the affinity and stability of HOX/DNA binding by heterodimerization with HOX proteins (Phelan and Featherstone, 1997). The potential role of PBX1 in predicting NBL cells response to retinoids was suggested in 2014 (Shah et al., 2014). Results of this study showed that induction of PBX1 expression was associated with 13-cis-RA responsiveness in NBL cell lines. When NBL patient data were analyzed, PBX1 expression was found to correlate with histological subtypes - the highest expression was identified in benign ganglioneuromas. Besides, reduced PBX1 protein level resulted in more aggressive phenotype and RA resistance among cell lines, indicating its essential role in enabling retinoid-induced differentiation of NBL cells. PBX1 could therefore serve as a novel prognostic biomarker and therapeutic target in NBL treatment.

3 Objectives

The aim of this work was a detailed analysis of the expression of five candidate biomarkers that were recently indicated to be associated with the resistance to retinoids in neuroblastoma to analyze the usefulness of these biomarkers in terms of predicting patient responses to such a treatment. For this purpose, DDX39A, HMGA1, HMGA2, HOXC9, and PBX1 candidate biomarkers were chosen. In order to achieve this main aim, following component objectives were set:

1. To analyze proliferation activity of the panel of NBL cell lines after the treatment with six types of retinoids to determine their responsiveness to antiproliferative effects of these compounds.

2. To determine the endogenous expression of candidate biomarkers on both mRNA and protein level in the panel of NBL cell lines in order to detect potential differences in the expression of these biomarkers between the group of NBL cell lines showing higher/lower sensitivity to retinoids.

3. To treat selected NBL cell lines with natural (ATRA, 9-cis-RA, 13-cis-RA) and synthetic (BEX, 4-HPR) retinoids to observe changes in expression of candidate biomarkers as a response to retinoid treatment.

4. To compare obtained results with the results of immunohistochemical analysis performed on corresponding FFPE samples of the tumors from which NBL cell lines were derived.

4 Materials and methods

4.1 Tumor samples and derivation of cell lines

Tumor samples taken from twenty patients suffering from NBL and the corresponding primary cell lines derived from these samples were used in this work. Moreover, two reference NBL cell lines were also included. Both reference cell lines were purchased from the European Collection of Cell Cultures (ECACC): SH-SY5Y (ECACC cat. no. 94030304) and SK-N-BE(2) (ECACC cat. no. 95011815; MYCN amp.). All primary NBL cell lines included in this work were derived in our laboratory from the tumor tissue of NBL patients that were treated for NBL in the Department of Pediatric Oncology (University Hospital Brno, Czech Republic) (Table 4). The procedure of primary cell line establishment was described in detail previously (Veselska et al., 2006). Cells were grown in a 1:1 mixture of Dulbecco´s modified Eagle´s medium (DMEM) and Ham´s F 12 medium supplemented with 20% fetal bovine serum, 100 IU/mL penicillin, 100 μg/mL streptomycin, 2 mM glutamine (all purchased from GE Healthcare), and 1% minimum essential media (MEM) nonessential amino acids (purchased from Biosera). The cell cultures were maintained under standard conditions at 37 °C in a humidified atmosphere containing 5% CO2 and subcultured 1-2 times weekly. Together with analysis of candidate biomarkers performed on NBL cell lines, IHC analysis of tumor samples was a second part of the project our team was working on. In this phase, IHC analysis was performed on FFPE surgical samples taken from the same patients as NBL cell lines were derived from, description of patients is given in Table 4. Representative sections from archival FFPE tumor samples were analyzed in the Department of Pathology, University Hospital Brno, Czech Republic according to a previously described procedure (Dobrotkova et al., 2019). Evaluation of IHC analysis is given in Table 5 and will be commented in relation to results obtained from the analysis performed on NBL cell lines in the Discussion section of this thesis.

Tab. 4 - Description of NBL patients from whom the primary cell lines were derived. Age, the age at biopsy given in months; INSS stage according to the International Neuroblastoma Staging System Committee; NBL risk category: LR, low risk; IR, intermediate risk; HR, high risk.

Sample INSS NBL risk Corresponding Age No. stage category cell line

1 1 2A LR NBL-01 2 13 2A LR NBL-13 3 6 2B LR NBL-14 4 5 3 IR NBL-15 5 102 2A LR NBL-17 6 236 4 HR NBL-18 7 37 4 HR NBL-20 8 11 3 IR NBL-22 9 6 4 IR NBL-23 10 42 4 HR NBL-24 11 1 1 LR NBL-25 12 6 1 LR NBL-26 13 1 2B LR NBL-28 14 60 4 HR NBL-29 15 3 4 IR NBL-30 16 26 1 LR NBL-31 17 16 4 HR NBL-34 18 10 3 HR NBL-36 19 31 4 HR NBL-38 20 36 4 HR NBL-40

Tab. 5 - Results of IHC analyses of DDX39A, HMGA1, HMGA2, HOXC9, and PBX1 expression in tumor samples. The percentage of antigen-positive tumor cells (TC) was counted and categorized into five levels: - (0% positive TC), +/- (1-10% positive TC), + (11-50% positive TC), ++ (51–80% positive TC), and +++ (81–100% positive TC). The intensity of immunostaining (immunoreactivity, IR) was classified as none (0), weak (1), medium (2), or strong (3). For a better orientation, various shades of green color are used illustrating the intensity of protein expression. PQ, poor quality of the specimen (impossible to perform a correct evaluation). (Dobrotkova et al., 2019)

Sample DDX39A HMGA1 HMGA2 HOXC9 PBX1 No. % TC IR % TC IR % TC IR % TC IR % TC IR 1 +++ 3 - 0 - 0 +++ 1 +++ 2 2 +++ 3 + 1 - 0 +++ 1 +++ 3 3 +++ 3 + 1 - 0 +++ 1 +++ 3 4 +++ 3 - 0 - 0 + 0-1 +++ 2 5 ++ 2 - 0 - 0 ++ 2 ++ 2 6 +++ 2 - 0 - 0 +++ 1-2 +++ 3 7 +++ 3 +/- 2 - 0 + 1 +/- 1 8 PQ - 0 - 0 +/- 1 PQ 9 +++ 3 - 0 - 0 + 1 ++ 3 10 ++ 2 - 0 - 0 + 1 +++ 3 11 +++ 3 - 0 - 0 + 2 +++ 2 12 +++ 3 - 0 - 0 ++ 2 +++ 2 15 +++ 3 - 0 - 0 ++ 2 +++ 3 16 +++ 3 - 0 - 0 + 1 +++ 3 17 PQ - 0 - 0 PQ +++ 3 18 +++ 3 + 1 - 0 ++ 1 +++ 3 19 PQ ++ 2 - 0 PQ PQ 20 ++ 3 +++ 2 - 0 - 0 +++ 2

4.2 Chemicals

Three natural (ATRA, 9-cis-RA, 13-cis-RA) and two synthetic (BEX, 4-HPR) retinoids were used in this work in order to investigate potential variability in NBL cells responsiveness to particular type of retinoid. ATRA and 13-cis-RA were prepared as stock solutions at a concentration of 100 mM in DMSO; 9-cis-RA, BEX and 4-HPR were prepared at a concentration of 10 mM in DMSO (all purchased from Merck). Reagents were stored at -20 °C under light-free conditions.

4.3 MTT assay

This colorimetric assay is based on the reduction of yellow tetrazolium salt MTT (3-[4,5-dimethylthiazole-2-yl]-2,5-diphenyltetrazolium bromide) to insoluble purple formazan crystals by the nicotinamide adenine dinucleotide phosphate-dependent (NAD(P)H-dependent) mitochondrial oxidoreductase enzymes reflecting the number of viable cells present. In order to determine the proliferative activity related to the differentiation status of NBL cells, 96-well plates were seeded with 2.5 x 104 cells per well in the culture medium volume of 200 μl per well. After 24 hours, the fresh medium containing one of the five retinoids at the concentration of 1 μM or a control medium was added. To evaluate changes in cell proliferation after 7 days of retinoid treatment under the standard cultivation conditions, the medium was removed carefully and replaced with 200 μl of fresh medium containing MTT (Merck) at the concentration of 0.5 mg/ml. At the next step, the plates were incubated at 37 °C for 4 hours. The medium was then removed and the formazan crystals were dissolved in 200 μl of DMSO for the subsequent absorbance measure at 570 nm with a reference absorbance at 620 nm using a Sunrise Absorbance Reader (Tecan). This procedure was applied for all NBL cell lines and all retinoids (separately) included in this work. Obtained data were analyzed using one-sample T-test (two-tailed); p<0.05 (*) and p<0.01 (**) were considered statistically significant. For the purpose of this study, NBL cell lines were categorized as more and less sensitive to retinoids according to the results of the MTT assay. Because half maximal inhibitory concentration (IC50) calculation was not proven effective in our experimental

setting, the responsiveness to retinoids was evaluated based on proliferation activity as measured by this assay.

4.4 RT-PCR

The relative expression levels of candidate biomarkers of response to retinoids on mRNA level were evaluated using reverse transcription polymerase chain reaction (RT-PCR) method. For this purpose, total RNA was extracted using the GenEluteTM Mammalian Total RNA Miniprep kit (Merck). RNA concentration was determined spectrophotometrically using NanoDropTM 2000 spectrophotometer (Thermo Fisher Scientific). In the next step, equal amounts of RNA (25 ng of RNA per 1 μl of total reaction volume) were reverse transcribed into cDNA using M-MLV reverse transcriptase (Top-Bio) (Table 6).

Tab. 6 - Reverse transcription master mix.

Component Manufacturer Volume [μl]

RNA + H2O Top-Bio 5

5x M-MLV RT buffer Top-Bio 2

100 mM DTT Top-Bio 1

10mM dNTP Mix Top-Bio 0.5 Elisabeth Oligo dT primers (50μM) 0.5 15,18 Pharmacon M-MLV reverse transcriptase (25 U/μl) Top-Bio 1

Total volume - 10

RT-PCR was realized in 20-μl reaction volumes using the GeneQ thermal cycler (BIOER) under the conditions listed in Table 7. To ensure that the amplification does not reach a saturation plateau and that the expression level of each gene is semi-quantified in the exponential phase of amplification, the suitable number of cycles was selected for each gene in question on the basis of comparison of RT-PCR products after 25, 30, 35 and 40 cycles of reaction. The products were then separated with 1% agarose gel electrophoresis and visualized in a UV transilluminator (UVITEC Cambridge) after Midori

green staining. Heat shock protein 90 alpha family class B member 1 (HSP90AB1) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) genes were used as an endogenous control. All the primers used for this analysis are given in Table 8. Visualized transcript bands were quantified using ImageJ. Data were analyzed using one-sample T-test (two-tailed); p<0.05 was considered statistically significant.

Tab. 7 - RT-PCR conditions.

Temperature [°C] Time [min.] Cycles

Initial denaturation 94 4 1 Denaturation 94 0.5

Annealing 62 0.5 25-30

Extension 72 1

Final extension 72 5 1

Cooling 4 30

Tab. 8 - Primers used for gene expression analysis. F, forward primer sequence; R, reverse primer sequence.

Gene Gene name Primer sequence symbol

F: 5´- GAACGGGGAGCCAGCATCAT - 3´ DDX39A DExD-box helicase 39A R: 5´-TTCTTAGGGGGAGCTGGTGT - 3´

high mobility group F: 5´-TCACTCTTCCACCTGCTCCT - 3´ HMGA1 AT-hook 1 R: 5´- TTGTTTTTGCTTCCCTTTGG - 3´

high mobility group F: 5´- GCAAGGCAACATTGACCTGAG - 3´ HMGA2 AT-hook 2 R: 5´- GCAAGGCAACATTGACCTGAG - 3´

F: 5´- AGCAAGCACAAAGAGGAGAAGG - 3´ HOXC9 homeobox C9 R: 5´- TTCCAGCGTCTGGTACTTGGT - 3´

F: 5´- CTCGGCTGGTGGATACCCTT - 3´ PBX1 PBX homeobox 1 R: 5´- TGCGATTGCTGGGAGATCAG - 3´

heat shock protein 90 F: 5´- CGCATGAAGGAGACACAGAA - 3´ HSP90AB1 alpha family class B R: 5´- TCCCATCAAATTCCTTGAGC - 3´ member 1 glyceraldehyde-3- F: 5´- AGCCACATCGCTCAGACACC - 3´ GAPDH -phosphate R: 5´- GTACTCAGCGCCAGCATCG - 3´ dehydrogenase

4.5 Immunoblotting

To analyze expression of candidate biomarkers on protein level, Western blotting with the subsequent immunodetection was used. Whole cell lysates harvested in radioimmunoprecipitation assay (RIPA) lysis buffer from all NBL cell lines were loaded onto a 10% or 12% sodium dodecyl sulfate (SDS)-polyacrylamide gels and separated by electrophoresis for 1.5 h at the room temperature. Proteins were then electroblotted onto polyvinylidene difluoride (PVDF) membranes (Bio Rad Laboratories) on ice for 60 min. The PVDF membranes were then blocked with 5% nonfat dry milk dissolved in tris-buffered saline (TBS) containing 0.1% Tween-20 for 60 min. and incubated overnight at 4°C with the corresponding primary antibody. In the next step, membranes were washed with TBS-Tween-20 and incubated with the horseradish peroxidase (HRP)-conjugated secondary antibody at room temperature for 60 min. Proteins of interest were visualized with the enhanced chemiluminescence (ECL) Prime Western Blotting Detection Reagent (GE Healthcare) according to the manufacturer´s instructions. Both primary and secondary antibodies used in this study are listed in Table 9. For all experiments related to investigation of changes in biomarkers protein expression influenced by retinoids, GAPDH protein served as a loading control. Visualized transcript bands were quantified using ImageJ. Data were analyzed using one-sample T-test (two-tailed); p<0.05 was considered statistically significant.

Tab. 9 - Primary and secondary antibodies.

Primary antibodies

Antigen Manufacturer Catalog No. Dilution

DDX39A Abcam ab180857 1:1000

GAPDH Cell Signaling Technology 2118S 1:20000

HMGA1 Cell Signaling Technology 12094S 1:500

HMGA2 Cell Signaling Technology 8179S 1:500

HOXC9 Abcam ab50839 1:250

PBX1 LifeSpan Biosciences, Inc. LS-C133363 1:1000

Secondary antibodies

Specificity Conjugate Manufacturer Catalog No. Dilution

Horseradish Anti-Mouse IgG Cell Signaling Technology 7076 1:5000 peroxidase

Horseradish Anti-Rabbit IgG Cell Signaling Technology 7074 1:5000 peroxidase

4.6 Retinoid treatment

After the initial screening of endogenous candidate biomarkers expression in all NBL cell lines both on mRNA and protein level, six primary and two reference NBL cell lines were chosen for the subsequent retinoid treatment. Based on the results of MTT assay, three of six primary NBL cell lines together with both reference cell lines were categorized as more sensitive (NBL-13, NBL-28, NBL-40) and remaining three primary cell lines as less sensitive to retinoids (NBL-17, NBL-25, NBL-36). For the purpose of retinoid treatment, stock solutions of both natural (ATRA, 9-cis-RA, 13-cis-RA) and synthetic (BEX, 4-HPR) retinoids were diluted in fresh cell culture medium to obtain final concentration of 1 μM. The final concentration of retinoids used in this work was chosen from the achievable range of retinoid plasma concentration in NBL patients (Veal et al., 2007). Cells were seeded onto Petri dishes 24 h prior to treatment in the equal amount for all experimental variants, untreated cells were used

as a control. Cell populations were treated with each of the natural or synthetic retinoids separately for seven days in order to analyze retinoid-influenced changes in biomarkers expression in relation to the responsiveness of particular cell line to retinoids. At the day seven of cultivation, cells were harvested either for mRNA or for protein expression analysis. Experiments were repeated in biological triplicates.

5 Results

5.1 Effect of retinoids on cell proliferation

At the initial phase of this work, the MTT assay was performed to analyze retinoid-mediated changes in proliferative activity of twenty primary and two reference NBL cell lines included in this study. Proliferative activity was measured on day 7 of retinoid treatment for each of five retinoids separately. The concentration of 1 μM was used for all retinoids (ATRA, 9-cis-RA, 13-cis-RA, BEX, and 4-HPR). According to obtained results, cell lines were categorized into three categories as RA-sensitive, RA-sensitive/resistant (those showing either RA-sensitive or RA-resistant phenotype based on type of retinoid used for MTT analysis), and RA-resistant, untreated cells were set as 100% (Table 10). For most of the experimental variants, statistically significant differences in the proliferative activity compared to untreated cells were observed. From the group of analyzed cell lines, six primary (NBL-13, NBL-14, NBL-18, NBL-22, NBL-28, NBL-40) and both reference (SK-N-BE(2), SH-SY5Y) NBL cell lines showed higher sensitivity to retinoids when compared to remaining cell lines. The highest decrease in proliferation activity up to 32 % was detected in NBL-18 cell line after the treatment with 1 μM BEX. Eight primary NBL cell lines (NBL-01, NBL-20, NBL-24, NBL-25, NBL-30, NBL-31, NBL-34, and NBL-36) were categorized as more resistant. In four cell lines (NBL-23, NBL-26, NBL-29, NBL-38), global responsiveness to retinoids was not clear as neither resistant, nor sensitive phenotype prevailed. We were unable to evaluate the proliferative activity of NBL-15 cell line reliably due to its growth parameters. Therefore, even though the endogenous expression of all selected candidate biomarkers was analyzed also in this cell line, obtained results were not further evaluated.

Tab. 10 - Results of MTT assay. Green cells, more sensitive phenotype, light green <0.6-0.8); dark green <0-0.6); red cells, more resistant phenotype, light red <0.8-0.9); dark red <0.9-1.2>. PQ, poor quality. The data represent the mean values, *P < 0.05; **P < 0.01 indicate statistically significant differences in proliferative activity of retinoid-treated cells compared to untreated cells from the corresponding NBL cell line.

Cell line ATRA 9-cis-RA 13-cis-RA BEX 4-HPR Phenotype

NBL-01 0.95 0.82** 0.85** 0.99 0.84* resistant

NBL-13 0.65** 0.48** 0.54** 0.48** 0.53** sensitive

NBL-14 0.75** 0.61** 0.59** 0.56** 0.52** sensitive

NBL-15 PQ PQ PQ PQ PQ -

NBL-17 0.87 0.85 0.83 1.00 0,98 resistant

NBL-18 0.54** 0.46** 0.62** 0.32** 1.07 sensitive

NBL-20 1.01 0.88 0.95 1.13 0.98 resistant

NBL-22 0.65* 0.57** 0.58** 0.74* 0.71* sensitive resistant/ NBL-23 1.00 0.69 0.90 0.51* 0.83 sensitive NBL-24 0.87 0.73** 0.81* 0.81* 0.84* resistant

NBL-25 1.08 1.04 1.06 1.10 0.73** resistant resistant/ NBL-26 0.86 0.71* 0.77 0.81 0.75* sensitive NBL-28 0.61** 0.51** 0.59** 0.66** 0.53** sensitive resistant/ NBL-29 0.91* 0.86* 0.79** 0.79** 0.95 sensitive NBL-30 0.97 0.89 0.92 0.85 1.03 resistant

NBL-31 1.09 0.96 1.12 1.01 0.78** resistant

NBL-34 0.96 0.76** 0.91 0.86 0.84* resistant

NBL-36 0.78** 0.80** 0.84** 0.82** 0.89* resistant resistant/ NBL-38 1.06 0.69 0.95 0.71 0.75 sensitive NBL-40 0.64** 0.63** 0.70** 0.85** 0.74** sensitive

SK-N-BE(2) 0.68** 0.58** 0.53** 0.53** 0.94 sensitive

SH-SY5Y 0.51** 0.58** 0.45** 0.67** 0.70** sensitive

5.2 Endogenous gene expression of candidate biomarkers

After NBL cell lines were categorized as more/less sensitive to retinoids, mRNA from each of the cell lines was extracted and reverse transcribed. The relative endogenous expression of all five candidate biomarkers of resistance/sensitivity to retinoids was analyzed in order to evaluate potential differences in expression pattern between more and less sensitive/resistant NBL cell lines by RT-PCR: DDX39A, HMGA1, HMGA2, HOXC9, and PBX1.

DDX39A gene expression

DDX39A gene was found to be expressed in all NBL cell lines except for NBL-22 cell line (Figure 8). The absence of DDX39A mRNA in NBL-22 cell line could be partially caused by the very low level of HSP90AB1 reference gene expression indicating some error that could occur probably during the process of mRNA isolation resulting in poor quality of obtained mRNA sample. Since the procedure was repeated several times with the same results, expression pattern of this particular cell line will not be considered reliable in the performed experiments. Despite the fact that endogenous DDX39A expression varied among investigated cell lines, no specific expression pattern typical for either more RA-sensitive or more RA-resistant subset of cell lines was observed. In both RA-sensitive and RA-resistant cell lines, relative DDX39A expression ranged from low to high suggesting that its gene expression was not directly related to retinoid responsiveness in examined NBL cell lines.

Fig. 8 - DDX39A mRNA expression. Gel electrophoresis image captured using a UV transilluminator is shown for each sample including HSP90AB1 as a reference gene. Green circle, RA-sensitive cell line; red circle, RA-resistant cell line; Green/red circle, RA-sensitive/resistant cell line.

HMGA1 gene expression

HMGA1 mRNA was detected in all examined cell lines (Figure 9). Generally, most of the RA-sensitive cell lines showed lower level of HMGA1 expression compared to especially RA-sensitive/resistant, but also to RA-resistant subset of cell lines. However, NBL-18 and NBL-28 cell lines (also from RA-sensitive group) expressed relative high amount of HMGA1 and therefore did not fit into observation mentioned above. Most of the RA-resistant cell lines expressed HMGA1 on similar level, only NBL-36 cell line showed lower expression of this gene comparable to HMGA1 expression in RA-sensitive cell lines. These results suggest that in most of the examined cell lines, low HMGA1 gene expression correlated with higher sensitivity to retinoids. However, prediction of RA-responsiveness according to HMGA1 expression was evaluated as insufficient since such an observation could not be applied to all analyzed samples.

Fig. 9 - HMGA1 mRNA expression. Gel electrophoresis image captured using a UV transilluminator is shown for each sample including HSP90AB1 as a reference gene. Green circle, RA-sensitive cell line; red circle, RA-resistant cell line; Green/red circle, RA-sensitive/resistant cell line.

HMGA2 gene expression

HMGA2 mRNA was detected in nineteen NBL cell lines, in remaining three cell lines (NBL-22, SK-N-BE(2), SH-SY5Y), no HMGA2 mRNA was detected (Figure 10). All three HMGA2 negative cell lines were categorized as RA-sensitive, suggesting that such an expression pattern could be specific for the cells with higher sensitivity to retinoids. Interestingly, if HMGA2 expression in NBL-22 cell line was not considered as relevant (for previously mentioned reasons), HMGA2 negativity would be specifically observed only in reference NBL cell lines. Since HMGA2 expression ranged from low to relative high in each of the three groups of cell lines, no expression pattern globally correlating with RA-responsiveness could be identified from this experiment. According to obtained results, HMGA2 negativity could indicate RA-sensitive phenotype, but the opposite interpretation (RA-sensitive cell lines were HMGA2-negative) would be misleading, as all remaining RA-sensitive cell lines besides reference cell lines expressed this gene.

Fig. 10 - HMGA2 mRNA expression. Gel electrophoresis image captured using a UV transilluminator is shown for each sample including HSP90AB1 as a reference gene. Green circle, RA-sensitive cell line; red circle, RA-resistant cell line; Green/red circle, RA-sensitive/resistant cell line.

HOXC9 gene expression

HOXC9 gene was found to be expressed in sixteen NBL cell lines. In remaining six cell lines (NBL-01, NBL-22, NBL-30, NBL-31, NBL-34, NBL-36), no HOXC9 mRNA was detected (Figure 11). Interestingly, apart from NBL-22 cell line that was already mentioned as potentially non-evaluable, all five cell lines with HOXC9-negative profile belonged to RA-resistant group of NBL cell lines. These results could indicate that HOXC9-negative expression pattern could predict poor response of particular cell line to retinoids. Since remaining RA-resistant cell lines (NBL-17, NBL-20, NBL-24, NBL-25) expressed HOXC9, observed HOXC9 negativity could not be considered as universal characteristics of all RA-resistant cell lines included in this work. RA-sensitive cell lines all expressed HOXC9 and in most of these cells, comparable level of HOXC9 mRNA was detected.

Fig. 11 - HOXC9 mRNA expression. Gel electrophoresis image captured using a UV transilluminator is shown for each sample including HSP90AB1 as a reference gene. Green circle, RA-sensitive cell line; red circle, RA-resistant cell line; Green/red circle, RA-sensitive/resistant cell line.

PBX1 gene expression

PBX1 gene was expressed in all studied cell lines except for NBL-22 cell line (Figure 12). As is apparent from the figure, expression of this gene varied from low to high, but this variation was observed predominantly inside of each group of cell lines (RA-sensitive, RA-resistant). For example, while the highest expression of PBX1 was detected in RA-resistant NBL-17 cell line, NBL-01 cell line, which was also categorized as RA-resistant, expressed markedly lower amount of PBX1. Similar variations in PBX1 expression were identified also inside of RA-sensitive group of cell lines. Therefore, endogenous expression of PBX1 gene did not correlate with responsiveness to retinoid treatment in investigated NBL cell lines.

Fig. 12 - PBX1 mRNA expression. Gel electrophoresis image captured using a UV transilluminator is shown for each sample including HSP90AB1 as a reference gene. Green circle, RA-sensitive cell line; red circle, RA-resistant cell line; Green/red circle, RA-sensitive/resistant cell line.

5.3 Endogenous protein expression of candidate biomarkers

Together with analysis of candidate biomarkers expression on mRNA level, endogenous protein expression of these molecules was investigated as well to get more complex insight into their potential role as biomarkers predicting responsiveness of NBL cell lines to retinoids. For this purpose, endogenous protein expression of DDX39A, HMGA1, HMGA1, HOXC9, and PBX1 was analyzed by Western blotting followed by immunodetection in all patient-derived NBL cell lines except for NBL-30 cell line, for which we were unable to obtain a cell lysate in appropriate quality. Since looking for reliable loading control protein that would provide satisfactory results throughout all analyzed NBL cell lines was showed to be problematic, loaded amounts of proteins for each sample will be documented by the corresponding PVDF membrane scan.

DDX39A protein expression

DDX39A protein was expressed in all NBL cell lines except for NBL-29 cell line, which could be influenced also by the low amount of loaded protein sample (Figure 13). DDX39A expression ranged from very low to medium/high in all three groups of NBL cell lines. For example, the highest expression of this protein was detected in NBL-20 (RA-resistant) and NBL-13 (RA-sensitive) cell lines that showed completely different response to retinoids in the MTT assay. On the other hand, NBL-25 and NBL-40 cell lines expressed comparable amount of DDX39A protein which was very low, but these cells were again from RA-resistant and RA-sensitive groups, respectively. According to these results, no obvious correlation between DDX39A expression and sensitivity/resistance to retinoids could be drawn.

Fig. 13 - DDX39A protein (49k Da) expression. Immunoblot captured using X-ray film is shown for each sample, corresponding PVDF membrane with blotted proteins is supplemented instead of reference protein detection. Green circle, RA-sensitive cell line; red circle, RA-resistant cell line; Green/red circle, RA-sensitive/resistant cell line.

HMGA1 protein expression

Another protein analyzed in this work was HMGA1 whose expression was detected in fourteen NBL cell lines. In remaining five NBL cell lines (NBL-15, NBL-24, NBL-25, NBL-26, and NBL-40), no or very poor expression of HMGA1 was detected (Figure 14). Among examined cell lines, NBL-17 (RA-resistant), NBL-18 (RA-sensitive), NBL-20 (RA-resistant), and NBL-29 (RA-sensitive/resistant) expressed this protein in the highest level despite their different responsiveness to retinoids. Moreover, NBL cell lines showing HMGA1-negative expression profile were also from both RA-sensitive and RA-resistant groups of cell lines. Therefore, neither high nor low/no endogenous expression of HMGA1 protein were proved to predict responsiveness to retinoids in NBL cell lines included in this work reliably.

Fig. 14 - HMGA1 protein (18 kDa) expression. Immunoblot captured using X-ray film is shown for each sample, corresponding PVDF membrane with blotted proteins is supplemented instead of reference protein detection. Green circle, RA-sensitive cell line; red circle, RA-resistant cell line; Green/red circle, RA-sensitive/resistant cell line.

HMGA2 protein expression

HMGA2 is the protein whose expression was among cell lines detected with the lowest frequency. Namely, only NBL-17 (RA-resistant), NBL-18 (RA-sensitive), NBL-26, NBL-29 (RA-sensitive/resistant), NBL-31, and NBL-36 (RA-resistant) cell lines were identified as HMGA2-positive. In remaining thirteen cell lines, very poor or no HMGA2 expression was detected (Figure 15). Similarly to previously commented candidate biomarkers of sensitivity/resistance to retinoids, no clear HMGA2 expression pattern could be ascribed to either sensitivity or resistance to these compounds.

Fig. 15 - HMGA2 protein (18 kDa) expression. Immunoblot captured using X-ray film is shown for each sample, corresponding PVDF membrane with blotted proteins is supplemented instead of reference protein detection. Green circle, RA-sensitive cell line; red circle, RA-resistant cell line; Green/red circle, RA-sensitive/resistant cell line.

HOXC9 protein expression

Analysis of HOXC9 protein expression revealed that this protein was expressed in ten NBL cell lines (NBL-13, NBL-14, NBL-17, NBL-20, NBL-22, NBL-23, NBL-25, NBL-26, NBL-29, and NBL-34) (Figure 16). In most of these cell lines, HOXC9 was expressed in comparable level. From the subset of HOXC9-positive cell lines, three were categorized as RA-sensitive (NBL-13, NBL-14, NBL-22), four were RA-resistant (NBL-17, NBL-20, NBL-25, and NBL-34), and remaining three were RA-sensitive/resistant (NBL-23, NBL-26, NBL-29). Since cell lines with detectable level of HOXC9 protein belonged to all three groups based on their responsiveness to retinoids, endogenous HOXC9 expression did not seem to be significantly related to sensitivity/resistance to retinoids.

Fig. 16 - HOXC9 protein (29 kDa) expression. Immunoblot captured using X-ray film is shown for each sample, corresponding PVDF membrane with blotted proteins is supplemented instead of reference protein detection. Green circle, RA-sensitive cell line; red circle, RA-resistant cell line; Green/red circle, RA-sensitive/resistant cell line.

PBX1 protein expression

To finalize initial screening of endogenous candidate biomarkers expression, expression of PBX1 protein was analyzed as well. Both PBX1a and PBX1b isoforms that are present in cells as a result of alternative splicing were investigated. In general, PBX1 was detected in all examined NBL cell lines, even though not both isoforms of this protein were always present (especially in NBL-24 cell line) (Figure 17). Among all studied cell lines, relative big differences in expression of this protein were observed, ranging from the highest (NBL-34) to the lowest level (NBL-15; NBL-24). However, such differences in PBX1 expression were observed also inside of particular groups of cell lines. For example, NBL-24 and NBL-34 cell lines were both members of the RA-resistant group of cell lines. Very same situation was seen in RA-sensitive group (NBL-40 versus NBL-28). According to these results, variation in PBX1 protein expression among examined cell lines did not correlate with the sensitivity or resistance of particular cell line to retinoids.

Fig. 17 - PBX1 protein (38; 46 kDa) expression. Immunoblot captured using X-ray film is shown for each sample, corresponding PVDF membrane with blotted proteins is supplemented instead of reference protein detection. Green circle, RA-sensitive cell line; red circle, RA-resistant cell line; Green/red circle, RA-sensitive/resistant cell line.

5.4 Changes in candidate biomarkers gene expression as a response to retinoid treatment

After the initial screening phase of this work aimed at analysis of endogenous expression of all candidate biomarkers on both mRNA and protein level was finished, six patient-derived and both reference NBL cell lines were selected for further research: NBL-13, NBL-17, NBL-25, NBL-28, NBL-36, NBL-40, SH-SY5Y, SK-N-BE(2). The goal of this part of the project was to evaluate changes of expression of these candidate biomarkers influenced by retinoids in order to find potential differences among expression pattern in RA-sensitive and RA-resistant NBL cell lines that were suggested in previous studies. For this purpose, three of six selected patient-derived cell lines were selected from the retinoid-sensitive group (NBL-13, NBL-28, and NBL-40) and remaining three from the retinoid-resistant group of NBL cell lines (NBL-17, NBL-25, NBL-36). Both reference cell lines were sensitive to retinoids. As was previously mentioned in Material and methods section of this thesis, all eight NBL cell lines were treated with 3 natural and 2 synthetic retinoids (separately) for seven days. Changes in gene expression compared to untreated cells were analyzed by RT-PCR. An overview of all results obtained in this analysis is given in Table 11 at the end of the Results chapter.

Changes in DDX39A gene expression

After seven-day cultivation with each type of retinoids chosen for this project, expression of DDX39A gene was analyzed (Figure 18). As is evident from the Figure 18A, retinoids did not cause biologically significant change of DDX39A gene expression in the most of examined samples. Both mild upregulation and downregulation were observed, the highest decrease of DDX39A expression was detected in NBL-13 cells (4-HPR), NBL-28 cells (ATRA), and in NBL-36 cells (9-cis-RA). Since NBL-13 and NBL-28 cell lines were RA-sensitive and NBL-36 cell line was RA resistant, such a trend, even if it was more significant and globally detected, could not be ascribed neither to cells showing higher nor lower sensitivity to retinoids.

Fig. 18 - relative DDX39A gene expression. (A) The data are presented as the mean + SD, experiments were repeated in biological triplicates. The black line indicating the 100% represents the relative biomarker expression in untreated cells. * p<0.05 indicates a significant difference compared to untreated cells. RA-sensitive cell lines are illustrated in green and RA-resistant cell lines in red color. (B) Representative gel electrophoresis image captured using a UV transilluminator is shown for each cell line including HSP90AB1 as a reference gene.

Changes in HMGA1 gene expression

Analysis of HMGA1 gene expression in relation to retinoid treatment showed various responses to this treatment when compared to control cells (Figure 19). However, in most cases, this change in expression was not biologically relevant. In RA-sensitive cell lines, ATRA and 9-cis-RA were treatments that resulted in the most relevant change of HMGA1 expression that was found to be downregulated in patient-derived NBL cell lines. On the other hand, HMGA1 upregulation was detected in some of RA-sensitive cells treated with synthetic retinoids, mainly in NBL-13 and NBL-28 cell lines. In the group of RA-resistant cell lines (NBL-17, NBL-25, and NBL-36), various responses to retinoid treatment were identified as well. While HMGA1 downregulation was observed in NBL-25 and NBL-36 cell lines treated with 9-cis-RA, treatment with synthetic retinoids (BEX, 4-HPR) resulted in mild upregulation of HMGA1 expression, especially in NBL-25 cell line. Therefore, neither RA-sensitive nor RA-resistant cell lines showed consistent change in HMGA1 gene expression as a response to retinoid treatment.

Fig. 19 - relative HMGA1 gene expression. (A) The data are presented as the mean + SD, experiments were repeated in biological triplicates. The black line indicating the 100% represents the relative biomarker expression in untreated cells. * p<0.05 indicates a significant difference compared to untreated cells. RA-sensitive cell lines are illustrated in green and RA-resistant cell lines in red color. (B) Representative gel electrophoresis image captured using a UV transilluminator is shown for each cell line including HSP90AB1 as a reference gene.

Changes in HMGA2 gene expression

Among all examined candidate biomarkers of responsiveness to retinoids, the impact of retinoid treatment on gene expression was most noticeable when HMGA2 gene expression was analyzed. HMGA2 was found to be expressed in NBL-13, NBL-28, NBL-17, NBL-25, and NBL-36 cell lines (Figure 20). Very low expression of HMGA2 was detected also in NBL-40 cell line, but it was not evaluated due to very low signal intensity. Both HMGA2-negative cell lines were from the RA-sensitive group and were the reference cell lines, supporting previously obtained results from the initial screening of endogenous HMGA2 gene expression (Figure 10). In all of the HMGA2-positive cell lines, downregulation of this gene was observed in cells treated with retinoids regardless of their resistance/sensitivity to these compounds. This downregulation was most significant in NBL-13 (RA-sensitive) and NBL-25 (RA-resistant) cell lines. In contrast, treatment with synthetic retinoids did not show any consistent effect on HMGA2 expression, since both up- and downregulation were observed among analyzed cell lines. These results suggest that natural retinoids caused more or less intensive decrease of HMGA2 expression in all NBL cell lines, in which this gene was found to be expressed both in sensitive and resistant groups. Such a response to retinoid treatment could therefore not be considered as a typical for neither RA-sensitive nor RA-resistant cells.

Fig. 20 - relative HMGA2 gene expression. (A) The data are presented as the mean + SD, experiments were repeated in biological triplicates. The black line indicating the 100% represents the relative biomarker expression in untreated cells. * p<0.05 indicates a significant difference compared to untreated cells. RA-sensitive cell lines are illustrated in green and RA-resistant cell lines in red color. (B) Representative gel electrophoresis image captured using a UV transilluminator is shown for each cell line including HSP90AB1 as a reference gene.

Changes in HOXC9 gene expression

The effect of retinoid treatment on gene expression was analyzed also for HOXC9. HOXC9 was expressed in all cell lines except for NBL-17 cell line (RA-resistant), both in control cells and in cells treated with retinoids (Figure 21). In RA sensitive group of cell lines, HOXC9 upregulation was observed as a response to retinoid treatment, namely in NBL-13 (ATRA), NBL-28 (9-cis-RA, 13-cis-RA), and in SK-N-BE(2) cell line (9-cis-RA). In remaining experimental variants, no or very small change of this gene expression were detected. No biologically significant change of HOXC9 expression was identified in cells treated with synthetic retinoids. In two RA-resistant cell lines that were HOXC9-positive, neither of retinoids used in this work caused change in HOXC9 expression. According to these results, the difference between more and less sensitive cell lines was slightly evident in cells treated with natural retinoids in which mild HOXC9 upregulation was detected in some of the more sensitive cell lines compared to those showing resistance to retinoids. However, HOXC9 upregulation was not found in all examined RA-sensitive cell lines and this trend could not be therefore generalized as a typical feature of cells showing sensitivity to retinoids.

Fig. 21 - relative HOXC9 gene expression. (A) The data are presented as the mean + SD, experiments were repeated in biological triplicates. The black line indicating the 100% represents the relative biomarker expression in untreated cells. * p<0.05 indicates a significant difference compared to untreated cells. RA-sensitive cell lines are illustrated in green and RA-resistant cell lines in red color. (B) Representative gel electrophoresis image captured using a UV transilluminator is shown for each cell line including HSP90AB1 as a reference gene.

Changes in PBX1 gene expression

Finally, changes of gene expression were analyzed also for PBX1 candidate biomarker. This gene was found to be expressed in all eight examined NBL cell lines (Figure 22). Treatment with natural retinoids resulted in significant upregulation of PBX1 expression in two RA-sensitive cell lines: NBL-13 and SK-N-BE(2). In remaining three RA-sensitive cell lines, PBX1 expression did not significantly differ between the untreated and treated cells. When compared to natural retinoids, synthetic retinoids showed less impact on PBX1 expression. On the other hand, RA-resistant cell lines used in this experiment (NBL-17, NBL-25, and NBL-36) showed opposite pattern of PBX1 expression in relation to retinoid treatment and they responded to the treatment mainly by PBX1 downregulation, especially when 9-cis-RA and 4-HPR were used. According to these results, RA-sensitive and RA-resistant groups of cell lines showed an opposite response to retinoids in terms of PBX1 expression. While PBX1 upregulation (or no change of expression) was identified in RA-sensitive NBL cell lines, retinoid treatment in RA-resistant cell lines resulted in downregulation of this gene in most of the experimental variants.

Fig. 22 - relative PBX1 gene expression. (A) The data are presented as the mean + SD, experiments were repeated in biological triplicates. The black line indicating the 100% represents the relative biomarker expression in untreated cells. * p<0.05 indicates a significant difference compared to untreated cells. RA-sensitive cell lines are illustrated in green and RA-resistant cell lines in red color. (B) Representative gel electrophoresis image captured using a UV transilluminator is shown for each cell line including HSP90AB1 as a reference gene.

5.5 Changes in candidate biomarkers protein expression as a response to retinoid treatment

To analyze changes of candidate biomarkers expression also on protein level, cells were treated with retinoids for seven days following the same procedure as for gene expression analysis. Changes of candidate biomarkers expression influenced by retinoids were therefore investigated in the same NBL cell lines: NBL-13, NBL-17, NBL-25, NBL-28, NBL-36, NBL-40, SH-SY5Y, and-SK-N-BE(2). Changes of particular protein expression after the treatment with retinoids compared to untreated cells were analyzed in relation to sensitivity/resistance of given NBL cell line to these compounds to observe potential differences among two groups of cell lines (RA-sensitive versus RA-resistant). Changes in candidate biomarkers protein expression were analyzed by Western blot. An overview of all results obtained in this analysis is given in Table 11 at the end of the Results chapter.

Changes in DDX39A protein expression

DDX39A protein was detected in all eight NBL cell lines chosen for this part of the work (Figure 23). In the group of RA-sensitive cell lines, DDX39A upregulation was the most frequently observed response to retinoid treatment among patient-derived NBL cell lines. Interestingly, upregulation od DDX39A was not observed in that significant manner in SH-SY5Y and SK-N-BE(2) reference cell lines that were also sensitive to retinoids. In RA-resistant group of cell lines, changes of DDX39A protein expression were less apparent. In NBL-17 cell line, DDX39A was upregulated especially when synthetic retinoids were used as a treatment. On the other hand, mild downregulation of this protein was detected in BL-25 cell line after the same treatment. In remaining experimental variants, no relevant difference in DDX39A expression was detected when compared to untreated cells. According to these results, effect of retinoids on DDX39A expression was more biologically significant in cells showing higher sensitivity to these compounds, in which overexpression of DDX39A as a response to retinoid treatment was detected.

Fig. 23 - relative DDX39A protein (49 kDa) expression. (A) The data are presented as the mean + SD, experiments were repeated in biological triplicates. The black line indicating the 100% represents the relative biomarker expression in untreated cells. * p<0.05 indicates a significant difference compared to untreated cells. RA-sensitive cell lines are illustrated in green and RA-resistant cell lines in red color. (B) Representative immunoblot captured using X-ray film is shown for each sample including GAPDH (36 kDa) as a loading control.

Changes in HMGA1 protein expression

Analysis of HMGA1 protein revealed that all cell lines except for NBL-40 cell line expressed this protein and that its expression ranged from very low to high (Figure 24). In several samples, HMGA1 expression was difficult to evaluate properly, since the obtained results were repeatedly in poor quality as can be seen in the Figure 24B. Nevertheless, HMGA1 upregulation after the treatment with retinoids was detected in both groups of cell lines, for example in RA-sensitive SK-N-BE(2) cells treated with 9-cis-RA or in RA-resistant NBL-36 cells mainly after the treatment with ATRA. On the other hand, HMGA1 downregulation was observed in RA-sensitive (NBL-28) and also in RA-resistant (NBL-17) cell lines. According to these results together with their relavite low quality, no specific change of HMGA1 expression as a response to retinoids typical for either group of cell lines was identified in this experiment.

Fig. 24 - relative HMGA1 protein (18 kDa) expression. (A) The data are presented as the mean + SD, experiments were repeated in biological triplicates. The black line indicating the 100% represents the relative biomarker expression in untreated cells. * p<0.05 indicates a significant difference compared to untreated cells. RA-sensitive cell lines are illustrated in green and RA-resistant cell lines in red color. (B) Representative immunoblot captured using X-ray film is shown for each sample including GAPDH (36 kDa) as a loading control.

Changes in HMGA2 protein expression

Expression of HMGA2 protein, the second member of HMG family of DNA binding proteins was also analyzed in all eight NBL cell lines (Figure 25). However, this protein was detected only in NBL-36 cell line and the expression was relatively poor also in this case. As was already apparent from the initial screening of endogenous HMGA2 protein expression among all cell lines included in this work, HMGA2 protein was expressed only in a small fraction of cell lines compared to HMGA2 gene expression. Since HMGA2 expression was relatively poor in NBL-36 cell line, no change of this protein expression in cells treated with retinoids was concluded.

Fig. 25 - relative HMGA2 protein (18 kDa) expression. Representative immunoblot captured using X-ray film is shown for each sample including GAPDH (36 kDa) as a loading control.

Changes in HOXC9 protein expression

HOX9 protein was expressed in all RA-sensitive cell lines included in this experiment (NBL-13, NBL-28, NBL-40, SH-SY5Y, SK-N-BE(2)). From RA-resistant group of cell lines, HOXC9 was detected only in NBL-25 cell line (Figure 26). As is apparent from the Figure 26A, this protein was upregulated in all HOXC9-positive cell lines. In the RA-sensitive group, such an expression pattern was more significant in cells treated with natural retinoids compared to those treated with BEX or 4-HPR, and was also more significant in primary patient-derived cell lines. On the other hand, NBL-28 cell line that was also sensitive to retinoids showed various responses to retinoids depending on the type of retinoid used as a treatment. While ATRA and 9-cis-RA treatment resulted in HOXC9 upregulation, remaining three retinoids caused downregulation of this protein in NBL-28 cells. In RA-resistant group, which was in this case represented only by NBL-25 cell line, HOXC9 was upregulated as well. Concluding from the data obtained in this experiment, treatment with retinoids caused significant changes of HOXC9 protein expression that was found to be upregulated in most of the samples. Since HOXC9 upregulation was detected in cells regardless of their responsiveness to retinoids, this expression pattern could not be used as a reliable predictor of sensitivity/resistance to retinoids.

Fig. 26 - relative HOXC9 protein (29 kDa) expression. (A) The data are presented as the mean + SD, experiments were repeated in biological triplicates. The black line indicating the 100% represents the relative biomarker expression in untreated cells. * p<0.05 indicates a significant difference compared to untreated cells. RA-sensitive cell lines are illustrated in green and RA-resistant cell lines in red color. (B) Representative immunoblot captured using X-ray film is shown for each sample including GAPDH (36 kDa) as a loading control.

Changes in PBX1 protein expression

PBX1 protein was detected in all eight analyzed NBL cell lines both in control cells and also in cells treated with retinoids (Figure 27). In RA-sensitive cell lines, mild PBX1 downregulation was detected in patient-derived cell lines, mainly in NBL-28 and NBL-40 cell lines. On the other hand, PBX1 was found to be upregulated in both reference cell lines that were also RA-sensitive. Interestingly, in RA-resistant group of cell lines, changes in PBX1 protein expression after retinoid treatment were more apparent in cells treated with synthetic retinoids. In NBL-17 and NBL-25 cell lines, PBX1 was upregulated after the treatment with BEX and also 4-HPR. According to these results, retinoid treatment had a bit different effect on PBX1 expression between sensitive and resistant cell lines, but this difference was not fully consistent among examined cell lines. Therefore, prediction of cells response to retinoids based on change of PBX1 expression was not confirmed to be absolutely reliable. Interestingly, the difference between the two groups of cell lines could be observed in the effect of natural and synthetic retinoids. While natural retinoids had bigger impact on PBX1 expression in RA-sensitive cell lines, the opposite was true in more resistant cell lines - treatment with natural retinoids did not result in any significant change of PBX1 expression in RA-resistant cells.

Fig. 27 - relative PBX1 protein (46 kDa) expression. (A) The data are presented as the mean + SD, experiments were repeated in biological triplicates. The black line indicating the 100% represents the relative biomarker expression in untreated cells. * p<0.05 indicates a significant difference compared to untreated cells. RA-sensitive cell lines are illustrated in green and RA-resistant cell lines in red color. (B) Representative immunoblot captured using X-ray film is shown for each sample including GAPDH (36 kDa) as a loading control.

Tab. 11 - An overview of detected changes in putative biomarker expression in sensitive and resistant NBL cell lines after treatment with natural or synthetic retinoids. The upward arrow indicates an increase in expression of the respective mRNA and/or protein, and the downward arrow indicates a decrease in mRNA and/or protein expression.

mRNA protein putative marker natural retinoids synthetic retinoids natural retinoids synthetic retinoids

in sensitive in sensitive patient-derived patient-derived cell lines cell lines DDX39A not changed not changed various response various response in resistant and in resistant and reference reference (sensitive) cell lines (sensitive) cell lines

HMGA1 not changed not changed various response various response

in all cell HMGA2 lines with various response poor expression poor expression detected mRNA

in all HOXC9 not changed not changed various response cell lines

in sensitive in sensitive not changed in in resistant patient-derived cell lines sensitive cell lines cell lines cell lines PBX1 various various response in response in resistant various response in reference and in resistant cell lines sensitive cell lines resistant cell lines cell lines

7 Conclusion

Although resistance to retinoids is a known phenomenon, only little is known about downstream mechanisms involved in regulation of retinoid action within the cell. During previous years, several downstream retinoid-regulated proteins have been suggested as possible predictive biomarkers of clinical response to retinoid treatment. The aim of this thesis was to analyze expression of five candidate biomarkers of responsiveness to retinoids that were recently reported as promising in NBL cell lines and tumor samples: DDX39A, HMGA1, HMGA2, HOXC9, and PBX1. Moreover, the present work aimed to bring new information to this field thanks to the multiple analysis of all these biomarkers in a single experimental study. The results showed that among examined putative biomarkers, HOXC9 and PBX1 were the most promising when mRNA level of their expression was analyzed. According to their endogenous expression, HOXC9 negativity could predict poor response of NBL cells to retinoids. Besides, HOXC9 and PBX1 mRNA upregulation as a response to retinoid treatment were identified as potentially useful in predicting RA-sensitivity in investigated cell lines. Further analysis of these biomarkers on protein level did not reveal that promising results and their endogenous expression did not seem to correlate neither with sensitivity nor with resistance to retinoids. Based on analysis of changes of these proteins expression, mild PBX1 downregulation could be considered as a marker of higher sensitivity among NBL cell lines. As was subsequently indicated by IHC analysis of FFPE tumor samples, higher expression of PBX1 was significantly associated with a poor response to induction chemotherapy and with worse clinical outcome of NBL patients supporting the usefulness of this biomarker in clinical practice. According to many studies that were published in recent years, tumor-specific proteins regulated directly or indirectly by retinoids could indeed help in understanding the mechanisms responsible for resistance to these compounds. One of the biggest challenges is undoubtedly to choose the most appropriate material (e.g. cell culture model, tumor tissue samples) for such research. Immortalized cancer cell lines derived from tumor samples represent the most commonly used experimental models in cancer research. While they preserve many properties of tumors, they may also acquire several genotype/phenotype changes during the process of immortalization and also during maintenance in culture. Analyses performed on tumor samples taken from patients have

undoubtedly a potential to bring more valuable results since they reflect the real microenvironment inside the tumor tissue. However, the most limiting factor in pediatric oncology research is relatively small number of patients suffering from particular type of disease making it difficult to obtain sufficient amount of material, especially when responsiveness to particular type of treatment needs to be investigated. Therefore, choosing the most suitable material for each research project undoubtedly represents a technical challenge and it depends on the goal of given study. All things considered, further research of downstream molecular markers predicting responsiveness to retinoids represents a very important and relatively little explored aspect of retinoid resistance phenomenon across human malignancies and is therefore worth investing in it.

8 References

Alisi, A., Cho, W.C., Locatelli, F., and Fruci, D. (2013). Multidrug resistance and cancer stem cells in neuroblastoma and hepatoblastoma. Int J Mol Sci 14, 24706–24725.

Alsayed, Y., Uddin, S., Mahmud, N., Lekmine, F., Kalvakolanu, D.V., Minucci, S., Bokoch, G., and Platanias, L.C. (2001). Activation of Rac1 and the p38 Mitogen- activated Protein Kinase Pathway in Response to All-trans-retinoic Acid. J. Biol. Chem. 276, 4012–4019.

Amann, P.M., Czaja, K., Bazhin, A.V., Rühl, R., Skazik, C., Heise, R., Marquardt, Y., Eichmüller, S.B., Merk, H.F., and Baron, J.M. (2014). Knockdown of lecithin retinol acyltransferase increases all-trans retinoic acid levels and restores retinoid sensitivity in malignant melanoma cells. Exp. Dermatol. 23, 832–837.

Ambros, I.M., Zellner, A., Roald, B., Amann, G., Ladenstein, R., Printz, D., Gadner, H., and Ambros, P.F. (1996). Role of ploidy, chromosome 1p, and Schwann cells in the maturation of neuroblastoma. N. Engl. J. Med. 334, 1505–1511.

Anding, A.L., Jones, J.D., Newton, M.A., Curley, R.W., and Clagett-Dame, M. (2018). 4-HPR Is an Endoplasmic Reticulum Stress Aggravator and Sensitizes Breast Cancer Cells Resistant to TRAIL/Apo2L. Anticancer Res. 38, 4403–4416.

Antunes, N.L., Khakoo, Y., Matthay, K.K., Seeger, R.C., Stram, D.O., Gerstner, E., Abrey, L.E., and Dalmau, J. (2000). Antineuronal antibodies in patients with neuroblastoma and paraneoplastic opsoclonus-myoclonus. J. Pediatr. Hematol. Oncol. 22, 315–320.

Aouad, P., Saikali, M., Abdel-Samad, R., Fostok, S., El-Houjeiri, L., Pisano, C., Talhouk, R., and Darwiche, N. (2017). Antitumor activities of the synthetic retinoid ST1926 in two-dimensional and three-dimensional human breast cancer models. Anticancer Drugs 28, 757–770.

Baba, A., Shimizu, M., Ohno, T., Shirakami, Y., Kubota, M., Kochi, T., Terakura, D., Tsurumi, H., and Moriwaki, H. (2013). Synergistic growth inhibition by acyclic retinoid and phosphatidylinositol 3-kinase inhibitor in human hepatoma cells. BMC Cancer 13, 465.

Balmer, J.E., and Blomhoff, R. (2002). Gene expression regulation by retinoic acid. J. Lipid Res. 43, 1773–1808.

Bhosale, P.G., Cristea, S., Ambatipudi, S., Desai, R.S., Kumar, R., Patil, A., Kane, S., Borges, A.M., Schäffer, A.A., Beerenwinkel, N., et al. (2017). Chromosomal Alterations and Gene Expression Changes Associated with the Progression of Leukoplakia to Advanced Gingivobuccal Cancer. Transl Oncol 10, 396–409.

Blatt, J., Olshan, A.F., Lee, P.A., and Ross, J.L. (1997). Neuroblastoma and related tumors in Turner’s syndrome. J. Pediatr. 131, 666–670.

Bluhm, E.C., Daniels, J., Pollock, B.H., Olshan, A.F., and Children’s Oncology Group (United States) (2006). Maternal use of recreational drugs and neuroblastoma in offspring: a report from the Children’s Oncology Group (United States). Cancer Causes Control 17, 663–669.

Borriello, L., Seeger, R.C., Asgharzadeh, S., and DeClerck, Y.A. (2016). More than the genes, the tumor microenvironment in neuroblastoma. Cancer Lett 380, 304–314.

Breitman, T.R., Selonick, S.E., and Collins, S.J. (1980). Induction of differentiation of the human promyelocytic leukemia cell line (HL-60) by retinoic acid. PNAS 77, 2936– 2940.

Breitman, T.R., Collins, S.J., and Keene, B.R. (1981). Terminal differentiation of human promyelocytic leukemic cells in primary culture in response to retinoic acid. Blood 57, 1000–1004.

Brendolan, A., Ferretti, E., Salsi, V., Moses, K., Quaggin, S., Blasi, F., Cleary, M.L., and Selleri, L. (2005). A Pbx1-dependent genetic and transcriptional network regulates spleen ontogeny. Development 132, 3113–3126.

Brodeur, G.M., Pritchard, J., Berthold, F., Carlsen, N.L., Castel, V., Castelberry, R.P., De Bernardi, B., Evans, A.E., Favrot, M., and Hedborg, F. (1993). Revisions of the international criteria for neuroblastoma diagnosis, staging, and response to treatment. J. Clin. Oncol. 11, 1466–1477.

Brodeur, G.M., Minturn, J.E., Ho, R., Simpson, A.M., Iyer, R., Varela, C.R., Light, J.E., Kolla, V., and Evans, A.E. (2009). Trk receptor expression and inhibition in neuroblastomas. Clin. Cancer Res. 15, 3244–3250.

Bürglin, T.R., and Affolter, M. (2016). Homeodomain proteins: an update. Chromosoma 125, 497–521.

Bussemakers, M.J.G., Ven, W.J.M. van de, Debruyne, F.M.J., and Schalken, J.A. (1991). Identification of High Mobility Group Protein I(Y) as Potential Progression Marker for Prostate Cancer by Differential Hybridization Analysis. Cancer Res 51, 606–611.

Cañón, E., Cosgaya, J.M., Scsucova, S., and Aranda, A. (2004). Rapid effects of retinoic acid on CREB and ERK phosphorylation in neuronal cells. Mol. Biol. Cell 15, 5583– 5592.

Caron, H., van Sluis, P., de Kraker, J., Bökkerink, J., Egeler, M., Laureys, G., Slater, R., Westerveld, A., Voûte, P.A., and Versteeg, R. (1996). Allelic Loss of Chromosome 1p as a Predictor of Unfavorable Outcome in Patients with Neuroblastoma. New England Journal of Medicine 334, 225–230.

Cerignoli, F., Ambrosi, C., Mellone, M., Assimi, I., Di MARCOTULLIO, L., Gulino, A., and Giannini, G. (2004). HMGA Molecules in Neuroblastic Tumors. Annals of the New York Academy of Sciences 1028, 122–132.

Challis, G.B., and Stam, H.J. (1990). The spontaneous regression of cancer. A review of cases from 1900 to 1987. Acta Oncol 29, 545–550.

Charron, J., Malynn, B.A., Fisher, P., Stewart, V., Jeannotte, L., Goff, S.P., Robertson, E.J., and Alt, F.W. (1992). Embryonic lethality in mice homozygous for a targeted disruption of the N-myc gene. Genes Dev. 6, 2248–2257.

Chen, J., Cao, X., An, Q., Zhang, Y., Li, K., Yao, W., Shi, F., Pan, Y., Jia, Q., Zhou, W., et al. (2018). Inhibition of cancer stem cell like cells by a synthetic retinoid. Nature Communications 9, 1406.

Chen, J.L., Li, J., Kiriluk, K.J., Rosen, A.M., Paner, G.P., Antic, T., Lussier, Y.A., and Vander Griend, D.J. (2012). Deregulation of a Hox protein regulatory network spanning prostate cancer initiation and progression. Clin. Cancer Res. 18, 4291– 4302.

Chen, Y., Takita, J., Choi, Y.L., Kato, M., Ohira, M., Sanada, M., Wang, L., Soda, M., Kikuchi, A., Igarashi, T., et al. (2008). Oncogenic mutations of ALK kinase in neuroblastoma. Nature 455, 971–974.

Cheung, N.K. (1991). Immunotherapy. Neuroblastoma as a model. Pediatr. Clin. North Am. 38, 425–441.

Cheung, N.-K.V., and Dyer, M.A. (2013). Neuroblastoma: developmental biology, cancer genomics and immunotherapy. Nat. Rev. Cancer 13, 397–411.

Cheung, Y.-T., Lau, W.K.-W., Yu, M.-S., Lai, C.S.-W., Yeung, S.-C., So, K.-F., and Chang, R.C.-C. (2009). Effects of all-trans-retinoic acid on human SH-SY5Y neuroblastoma as in vitro model in neurotoxicity research. Neurotoxicology 30, 127– 135.

Chiappetta, G., Bandiera, A., Berlingieri, M.T., Visconti, R., Manfioletti, G., Battista, S., Martinez-Tello, F.J., Santoro, M., Giancotti, V., and Fusco, A. (1995). The expression of the high mobility group HMGI (Y) proteins correlates with the malignant phenotype of human thyroid neoplasias. Oncogene 10, 1307–1314.

Chiappetta, G., Tallini, G., De Biasio, M.C., Manfioletti, G., Martinez-Tello, F.J., Pentimalli, F., de Nigris, F., Mastro, A., Botti, G., Fedele, M., et al. (1998). Detection of high mobility group I HMGI(Y) protein in the diagnosis of thyroid tumors: HMGI(Y) expression represents a potential diagnostic indicator of carcinoma. Cancer Res. 58, 4193–4198.

Chlapek, P., Zitterbart, K., Kren, L., Filipova, L., Sterba, J., and Veselska, R. (2017). Uniformity under in vitro conditions: Changes in the phenotype of cancer cell lines derived from different medulloblastoma subgroups. PLoS ONE 12, e0172552.

Chlapek, P., Slavikova, V., Mazanek, P., Sterba, J., and Veselska, R. (2018). Why Differentiation Therapy Sometimes Fails: Molecular Mechanisms of Resistance to Retinoids. Int J Mol Sci 19.

Chou, J.Y. (1982). Effects of retinoic acid on differentiation of choriocarcinoma cells in vitro. J. Clin. Endocrinol. Metab. 54, 1174–1180.

100

Chute, J.P., Muramoto, G.G., Whitesides, J., Colvin, M., Safi, R., Chao, N.J., and McDonnell, D.P. (2006). Inhibition of aldehyde dehydrogenase and retinoid signaling induces the expansion of human hematopoietic stem cells. PNAS 103, 11707–11712.

Cohen, P.S., Letterio, J.J., Gaetano, C., Chan, J., Matsumoto, K., Sporn, M.B., and Thiele, C.J. (1995). Induction of Transforming Growth Factor β1 and Its Receptors during all-trans-Retinoic Acid (RA) Treatment of RA-responsive Human Neuroblastoma Cell Lines. Cancer Res 55, 2380–2386.

Cohn, S.L., Pearson, A.D.J., London, W.B., Monclair, T., Ambros, P.F., Brodeur, G.M., Faldum, A., Hero, B., Iehara, T., Machin, D., et al. (2009). The International Neuroblastoma Risk Group (INRG) classification system: an INRG Task Force report. J. Clin. Oncol. 27, 289–297.

Cozzi, D.A., Mele, E., Ceccanti, S., Natale, F., Clerico, A., Schiavetti, A., and Dominici, C. (2013). Long-term follow-up of the “wait and see” approach to localized perinatal adrenal neuroblastoma. World J Surg 37, 459–465.

Cruz, F.D., and Matushansky, I. (2012). Solid tumor differentiation therapy - is it possible? Oncotarget 3, 559–567.

Cunningham, T.J., and Duester, G. (2015). Mechanisms of retinoic acid signalling and its roles in organ and limb development. Nature Reviews Molecular Cell Biology 16, 110–123.

D’Angio, GiulioJ., Evans, AudreyE., and Koop, C.E. (1971). SPECIAL PATTERN OF WIDESPREAD NEUROBLASTOMA WITH A FAVOURABLE PROGNOSIS. The Lancet 297, 1046–1049.

Davidoff, A.M. (2012). Neuroblastoma. Semin. Pediatr. Surg. 21, 2–14.

De Mariano, M., Stigliani, S., Moretti, S., Parodi, F., Croce, M., Bernardi, C., Pagano, A., Tonini, G.P., Ferrini, S., and Longo, L. (2017). A genome-wide microRNA profiling indicates miR-424-5p and miR-503-5p as regulators of ALK expression in neuroblastoma. Oncotarget 8, 56518–56532.

Decock, A., Ongenaert, M., Vandesompele, J., and Speleman, F. (2011). Neuroblastoma epigenetics: from candidate gene approaches to genome-wide screenings. Epigenetics 6, 962–970.

Dheer, Y., Chitranshi, N., Gupta, V., Abbasi, M., Mirzaei, M., You, Y., Chung, R., Graham, S.L., and Gupta, V. (2018). Bexarotene Modulates Retinoid-X-Receptor Expression and Is Protective Against Neurotoxic Endoplasmic Reticulum Stress Response and Apoptotic Pathway Activation. Mol. Neurobiol. 55, 9043–9056.

Diaz, P., Huang, W., Keyari, C.M., Buttrick, B., Price, L., Guilloteau, N., Tripathy, S., Sperandio, V.G., Fronczek, F.R., Astruc-Diaz, F., et al. (2016). Development and characterization of novel and selective inhibitors of cytochrome P450 CYP26A1, the human liver retinoic acid hydroxylase. J Med Chem 59, 2579–2595.

101

Dobrotkova, V., Chlapek, P., Mazanek, P., Sterba, J., and Veselska, R. (2018). Traffic lights for retinoids in oncology: molecular markers of retinoid resistance and sensitivity and their use in the management of cancer differentiation therapy. BMC Cancer 18, 1059.

Dobrotkova, V., Chlapek, P., Jezova, M., Adamkova, K., Mazanek, P., Sterba, J., and Veselska, R. (2019). Prediction of neuroblastoma cell response to treatment with natural or synthetic retinoids using selected protein biomarkers. PLOS ONE 14, e0218269.

Dragnev, K.H., Rigas, J.R., and Dmitrovsky, E. (2000). The Retinoids and Cancer Prevention Mechanisms. The Oncologist 5, 361–368.

Dragnev, K.H., Whyman, J.D., Hahn, C.K., Kebbekus, P.E., Kokko, S.F., Bhatt, S.M., and Rigas, J.R. (2018). A phase I/II study of bexarotene with carboplatin and weekly paclitaxel for the treatment of patients with advanced non-small cell lung cancer. J Thorac Dis 10, 5531–5537.

Duffy, D.J., Krstic, A., Halasz, M., Schwarzl, T., Konietzny, A., Iljin, K., Higgins, D.G., and Kolch, W. (2017). Retinoic acid and TGF-β signalling cooperate to overcome MYCN-induced retinoid resistance. Genome Medicine 9, 15.

Duong, V., and Rochette-Egly, C. (2011). The molecular physiology of nuclear retinoic acid receptors. From health to disease. Biochim. Biophys. Acta 1812, 1023–1031.

Farina, A.R., Masciulli, M.-P., Tacconelli, A., Cappabianca, L., De Santis, G., Gulino, A., and Mackay, A.R. (2002). All-trans-Retinoic Acid Induces Nuclear Factor {kappa}B Activation and Matrix Metalloproteinase-9 Expression and Enhances Basement Membrane Invasivity of Differentiation-resistant Human SK-N-BE 9N Neuroblastoma Cells. Cell Growth & Differentiation 13, 343.

Fedele, M., Bandiera, A., Chiappetta, G., Battista, S., Viglietto, G., Manfioletti, G., Casamassimi, A., Santoro, M., Giancotti, V., and Fusco, A. (1996). Human colorectal carcinomas express high levels of high mobility group HMGI(Y) proteins. Cancer Res. 56, 1896–1901.

Felsted, R.L., Gupta, S.K., Glover, C.J., Fischkoff, S.A., and Gallagher, R.E. (1983). Cell surface membrane protein changes during the differentiation of cultured human promyelocytic leukemia HL-60 cells. Cancer Res. 43, 2754–2761.

Fredlund, E., Ringnér, M., Maris, J.M., and Påhlman, S. (2008). High Myc pathway activity and low stage of neuronal differentiation associate with poor outcome in neuroblastoma. PNAS 105, 14094–14099.

Friedman, G.K., and Castleberry, R.P. (2007). Changing trends of research and treatment in infant neuroblastoma. Pediatr Blood Cancer 49, 1060–1065.

Friend, C., Scher, W., Holland, J.G., and Sato, T. (1971). Hemoglobin synthesis in murine virus-induced leukemic cells in vitro: stimulation of erythroid differentiation by dimethyl sulfoxide. Proc. Natl. Acad. Sci. U.S.A. 68, 378–382.

102

George, R.E., Attiyeh, E.F., Li, S., Moreau, L.A., Neuberg, D., Li, C., Fox, E.A., Meyerson, M., Diller, L., Fortina, P., et al. (2007). Genome-Wide Analysis of Neuroblastomas using High-Density Single Nucleotide Polymorphism Arrays. PLoS One 2.

George, R.E., Sanda, T., Hanna, M., Fröhling, S., Luther, W., Zhang, J., Ahn, Y., Zhou, W., London, W.B., McGrady, P., et al. (2008). Activating mutations in ALK provide a therapeutic target in neuroblastoma. Nature 455, 975–978.

Giannini, G., Di Marcotullio, L., Ristori, E., Zani, M., Crescenzi, M., Scarpa, S., Piaggio, G., Vacca, A., Peverali, F.A., Diana, F., et al. (1999). HMGI(Y) and HMGI-C genes are expressed in neuroblastoma cell lines and tumors and affect retinoic acid responsiveness. Cancer Res. 59, 2484–2492.

Giannini, G., Kim, C.J., Marcotullio, L.D., Manfioletti, G., Cardinali, B., Cerignoli, F., Ristori, E., Zani, M., Frati, L., Screpanti, I., et al. (2000). Expression of the HMGI(Y) gene products in human neuroblastic tumours correlates with differentiation status. Br J Cancer 83, 1503–1509.

Gigueère, V. (1994). Retinoic Acid Receptors and Cellular Retinoid Binding Proteins: Complex Interplay in Retinoid Signaling. Endocrine Reviews 15, 61–79.

Gligorich, K., Vaden, R., Shelton, D., Wang, G., Matsen, C., Looper, R., Sigman, M., and Welm, B. (2013). Development of a screen to identify selective small molecules active against patient-derived metastatic and chemoresistant breast cancer cells. Breast Cancer Research : BCR 15, R58.

Gniadecki, R., Assaf, C., Bagot, M., Dummer, R., Duvic, M., Knobler, R., Ranki, A., Schwandt, P., and Whittaker, S. (2007). The optimal use of bexarotene in cutaneous T-cell lymphoma. Br. J. Dermatol. 157, 433–440.

Goldie, J.H. (2001). Drug resistance in cancer: a perspective. Cancer Metastasis Rev. 20, 63–68.

Haar, C.P., Hebbar, P., Wallace, G.C., Das, A., Vandergrift, W.A., Smith, J.A., Giglio, P., Patel, S.J., Ray, S.K., and Banik, N.L. (2012). Drug Resistance in Glioblastoma: A Mini Review. Neurochem Res 37, 1192–1200.

Han, B.B., Li, S., Tong, M., Holpuch, A.S., Spinney, R., Wang, D., Border, M.B., Liu, Z., Sarode, S., Pei, P., et al. (2015). Fenretinide Perturbs Focal Adhesion Kinase in Premalignant and Malignant Human Oral Keratinocytes. Fenretinide’s Chemopreventive Mechanisms Include ECM Interactions. Cancer Prev Res (Phila) 8, 419–430.

Hansford, L.M., Thomas, W.D., Keating, J.M., Burkhart, C.A., Peaston, A.E., Norris, M.D., Haber, M., Armati, P.J., Weiss, W.A., and Marshall, G.M. (2004). Mechanisms of embryonal tumor initiation: Distinct roles for MycN expression and MYCN amplification. Proc Natl Acad Sci U S A 101, 12664–12669.

103

Harris, M.H., DuBois, S.G., Glade Bender, J.L., Kim, A., Crompton, B.D., Parker, E., Dumont, I.P., Hong, A.L., Guo, D., Church, A., et al. (2016). Multicenter Feasibility Study of Tumor Molecular Profiling to Inform Therapeutic Decisions in Advanced Pediatric Solid Tumors: The Individualized Cancer Therapy (iCat) Study. JAMA Oncol.

Hartomo, T.B., Van Huyen Pham, T., Yamamoto, N., Hirase, S., Hasegawa, D., Kosaka, Y., Matsuo, M., Hayakawa, A., Takeshima, Y., Iijima, K., et al. (2015). Involvement of aldehyde dehydrogenase 1A2 in the regulation of cancer stem cell properties in neuroblastoma. Int. J. Oncol. 46, 1089–1098.

Hiyama, E., Hiyama, K., Yokoyama, T., Matsuura, Y., Piatyszek, M.A., and Shay, J.W. (1995). Correlating telomerase activity levels with human neuroblastoma outcomes. Nature Medicine 1, 249–255.

Huang, M.E., Ye, Y.C., Chen, S.R., Chai, J.R., Lu, J.X., Zhao, L., Gu, L.J., and Wang, Z.Y. (1989). Use of all-trans retinoic acid in the treatment of acute promyelocytic leukemia. Haematol Blood Transfus 32, 88–96.

Huang, S., Laoukili, J., Epping, M.T., Koster, J., Hölzel, M., Westerman, B.A., Nijkamp, W., Hata, A., Asgharzadeh, S., Seeger, R.C., et al. (2009). ZNF423 Is Critically Required for Retinoic Acid-Induced Differentiation and Is a Marker of Neuroblastoma Outcome. Cancer Cell 15, 328–340.

Hur, H., Lee, J.-Y., Yang, S., Kim, J.M., Park, A.E., and Kim, M.H. (2016). HOXC9 Induces Phenotypic Switching between Proliferation and Invasion in Breast Cancer Cells. J Cancer 7, 768–773.

Irwin, M.S., and Park, J.R. (2015). Neuroblastoma: Paradigm for Precision Medicine. Pediatric Clinics of North America 62, 225–256.

Iskakova, M., Karbyshev, M., Piskunov, A., and Rochette-Egly, C. (2015). Nuclear and extranuclear effects of vitamin A. Can. J. Physiol. Pharmacol. 93, 1065–1075.

Janoueix-Lerosey, I., Lequin, D., Brugières, L., Ribeiro, A., de Pontual, L., Combaret, V., Raynal, V., Puisieux, A., Schleiermacher, G., Pierron, G., et al. (2008). Somatic and germline activating mutations of the ALK kinase receptor in neuroblastoma. Nature 455, 967–970.

Janoueix-Lerosey, I., Schleiermacher, G., Michels, E., Mosseri, V., Ribeiro, A., Lequin, D., Vermeulen, J., Couturier, J., Peuchmaur, M., Valent, A., et al. (2009). Overall Genomic Pattern Is a Predictor of Outcome in Neuroblastoma. JCO 27, 1026–1033.

Jin, C.-J., Hong, C.Y., Takei, M., Chung, S.-Y., Park, J.-S., Pham, T.-N.N., Choi, S.-J.-N., Nam, J.-H., Chung, I.-J., Kim, H.-J., et al. (2010). All-trans retinoic acid inhibits the differentiation, maturation, and function of human monocyte-derived dendritic cells. Leuk. Res. 34, 513–520.

Jung, J.-G., Shih, I.-M., Park, J.T., Gerry, E., Kim, T.H., Ayhan, A., Handschuh, K., Davidson, B., Fader, A.N., Selleri, L., et al. (2016). Ovarian Cancer Chemoresistance Relies on the Stem Cell Reprogramming Factor PBX1. Cancer Res. 76, 6351–6361. 104

Kaltschmidt, B., Kaltschmidt, C., and Widera, D. (2012). Adult Craniofacial Stem Cells: Sources and Relation to the Neural Crest. Stem Cell Rev and Rep 8, 658–671.

Kamps, M.P., Murre, C., Sun, X.H., and Baltimore, D. (1990). A new homeobox gene contributes the DNA binding domain of the t(1;19) translocation protein in pre-B ALL. Cell 60, 547–555.

Kelly, M., and von Lintig, J. (2015). STRA6: role in cellular retinol uptake and efflux. Hepatobiliary Surg Nutr 4, 229–242.

Kikuta, K., Kubota, D., Saito, T., Orita, H., Yoshida, A., Tsuda, H., Suehara, Y., Katai, H., Shimada, Y., Toyama, Y., et al. (2012). Clinical proteomics identified ATP- dependent RNA helicase DDX39 as a novel biomarker to predict poor prognosis of patients with gastrointestinal stromal tumor. J Proteomics 75, 1089–1098.

Klopper, J., Kane, M., Jimeno, A., Sams, S., French, J., Pike, L., Tompkins, K., and Haugen, B. (2015). A Phase II Trial of Bexarotene for Advanced Differentiated Thyroid Cancer. Thyroid 25, 563–564.

Knoepfler, P.S., and Kamps, M.P. (1997). The Pbx family of proteins is strongly upregulated by a post-transcriptional mechanism during retinoic acid-induced differentiation of P19 embryonal carcinoma cells. Mech. Dev. 63, 5–14.

Kocak, H., Ackermann, S., Hero, B., Kahlert, Y., Oberthuer, A., Juraeva, D., Roels, F., Theissen, J., Westermann, F., Deubzer, H., et al. (2013). Hox-C9 activates the intrinsic pathway of apoptosis and is associated with spontaneous regression in neuroblastoma. Cell Death Dis 4, e586.

Koeffler, H.P. (1983). Induction of differentiation of human acute myelogenous leukemia cells: therapeutic implications. Blood 62, 709–721.

Kushner, B.H., Cheung, N.K., LaQuaglia, M.P., Ambros, P.F., Ambros, I.M., Bonilla, M.A., Gerald, W.L., Ladanyi, M., Gilbert, F., Rosenfield, N.S., et al. (1996). Survival from locally invasive or widespread neuroblastoma without cytotoxic therapy. J. Clin. Oncol. 14, 373–381.

Kwiatkowski, J.L., Rutkowski, J.L., Yamashiro, D.J., Tennekoon, G.I., and Brodeur, G.M. (1998). Schwann cell-conditioned medium promotes neuroblastoma survival and differentiation. Cancer Res. 58, 4602–4606.

Lanvers, C., Hempel, G., Blaschke, G., and Boos, J. (1998). Chemically induced isomerization and differential uptake modulate retinoic acid disposition in HL-60 cells. FASEB J. 12, 1627–1633.

Lehtonen, E., Lehto, V.-P., Badley, R.A., and Virtanen, I. (1983). Formation of vinculin plaques precedes other cytoskeletal changes during retinoic acid-induced teratocarcinoma cell differentiation. Experimental Cell Research 144, 191–197.

Linder, P. (2006). Dead-box proteins: a family affair—active and passive players in RNP- remodeling. Nucleic Acids Res 34, 4168–4180.

105

Liss, C., Fekete, M.J., Hasina, R., and Lingen, M.W. (2002). Retinoic acid modulates the ability of macrophages to participate in the induction of the angiogenic phenotype in head and neck squamous cell carcinoma. Int. J. Cancer 100, 283–289.

London, W.B., Castleberry, R.P., Matthay, K.K., Look, A.T., Seeger, R.C., Shimada, H., Thorner, P., Brodeur, G., Maris, J.M., Reynolds, C.P., et al. (2005). Evidence for an age cutoff greater than 365 days for neuroblastoma risk group stratification in the Children’s Oncology Group. J. Clin. Oncol. 23, 6459–6465.

Louis, C.U., and Shohet, J.M. (2015). Neuroblastoma: Molecular Pathogenesis and Therapy. Annu Rev Med 66, 49–63.

Louis, C.U., Savoldo, B., Dotti, G., Pule, M., Yvon, E., Myers, G.D., Rossig, C., Russell, H.V., Diouf, O., Liu, E., et al. (2011). Antitumor activity and long-term fate of chimeric antigen receptor–positive T cells in patients with neuroblastoma. Blood 118, 6050–6056.

Ma, J., Chang, W, and Zhang, W (2018). Relationship between the expression of DDX39 protein and prognosis of colorectal cancer. Zhonghua Wei Chang Wai Ke Za Zhi 21, 336–341.

Magnani, L., Ballantyne, E.B., Zhang, X., and Lupien, M. (2011). PBX1 genomic pioneer function drives ERα signaling underlying progression in breast cancer. PLoS Genet. 7, e1002368.

Mao, L., Ding, J., Zha, Y., Yang, L., McCarthy, B.A., King, W., Cui, H., and Ding, H.-F. (2011). HOXC9 links cell-cycle exit and neuronal differentiation and is a prognostic marker in neuroblastoma. Cancer Res. 71, 4314–4324.

Marchetti, M.-N., Sampol, E., Bun, H., Scoma, H., Lacarelle, B., and Durand, A. (1997). IN VITRO METABOLISM OF THREE MAJOR ISOMERS OF RETINOIC ACID IN RATS: Intersex and Interstrain Comparison. Drug Metab Dispos 25, 637–646.

Masetti, R., Biagi, C., Zama, D., Vendemini, F., Martoni, A., Morello, W., Gasperini, P., and Pession, A. (2012). Retinoids in Pediatric Onco-Hematology: the Model of Acute Promyelocytic Leukemia and Neuroblastoma. Adv Therapy 29, 747–762.

Matthay, K.K., Villablanca, J.G., Seeger, R.C., Stram, D.O., Harris, R.E., Ramsay, N.K., Swift, P., Shimada, H., Black, C.T., Brodeur, G.M., et al. (1999). Treatment of high- risk neuroblastoma with intensive chemotherapy, radiotherapy, autologous bone marrow transplantation, and 13-cis-retinoic acid. Children’s Cancer Group. N. Engl. J. Med. 341, 1165–1173.

Matthay, K.K., Maris, J.M., Schleiermacher, G., Nakagawara, A., Mackall, C.L., Diller, L., and Weiss, W.A. (2016). Neuroblastoma. Nature Reviews Disease Primers 2, 16078.

Maurer, B.J., Kang, M.H., Villablanca, J.G., Janeba, J., Groshen, S., Matthay, K.K., Sondel, P.M., Maris, J.M., Jackson, H.A., Goodarzian, F., et al. (2013). Phase I trial of fenretinide delivered orally in a novel organized lipid complex in patients with relapsed/refractory neuroblastoma: a report from the New Approaches to Neuroblastoma Therapy (NANT) consortium. Pediatr Blood Cancer 60, 1801–1808. 106

Molday, R.S., and Zhang, K. (2010). Defective lipid transport and biosynthesis in recessive and dominant Stargardt macular degeneration. Prog. Lipid Res. 49, 476–492.

Monclair, T., Brodeur, G.M., Ambros, P.F., Brisse, H.J., Cecchetto, G., Holmes, K., Kaneko, M., London, W.B., Matthay, K.K., Nuchtern, J.G., et al. (2009). The International Neuroblastoma Risk Group (INRG) Staging System: An INRG Task Force Report. J Clin Oncol 27, 298–303.

Moreno, L., Marshall, L.V., and Pearson, A.D.J. (2013). At the frontier of progress for paediatric oncology: the neuroblastoma paradigm. Br. Med. Bull. 108, 173–188.

Mosse, Y.P., Laudenslager, M., Khazi, D., Carlisle, A.J., Winter, C.L., Rappaport, E., and Maris, J.M. (2004). Germline PHOX2B Mutation in Hereditary Neuroblastoma. Am J Hum Genet 75, 727–730.

Mossé, Y.P., Laudenslager, M., Longo, L., Cole, K.A., Wood, A., Attiyeh, E.F., Laquaglia, M.J., Sennett, R., Lynch, J.E., Perri, P., et al. (2008). Identification of ALK as a major familial neuroblastoma predisposition gene. Nature 455, 930–935.

Mossé, Y.P., Lim, M.S., Voss, S.D., Wilner, K., Ruffner, K., Laliberte, J., Rolland, D., Balis, F.M., Maris, J.M., Weigel, B.J., et al. (2013). Safety and activity of crizotinib for paediatric patients with refractory solid tumours or anaplastic large-cell lymphoma: a Children’s Oncology Group phase 1 consortium study. Lancet Oncol. 14, 472–480.

Muñoz, J., Vendrell, E., Aiza, G., Nistal, M., Pestaña, A., Peinado, M.A., and Castresana, J.S. (2006). Determination of genomic damage in neuroblastic tumors by arbitrarily primed PCR: MYCN amplification as a marker for genomic instability in neuroblastomas. Neuropathology 26, 165–169.

Murakami, K., Sakukawa, R., Sano, M., Hashimoto, A., Shibata, J., Yamada, Y., and Saiki, I. (1999). Inhibition of angiogenesis and intrahepatic growth of colon cancer by TAC-101. Clin. Cancer Res. 5, 2304–2310.

Nakagawara, A., Azar, C.G., Scavarda, N.J., and Brodeur, G.M. (1994). Expression and function of TRK-B and BDNF in human neuroblastomas. Mol. Cell. Biol. 14, 759– 767.

Nakagawara, A., Li, Y., Izumi, H., Muramori, K., Inada, H., and Nishi, M. (2018). Neuroblastoma. Japanese Journal of Clinical Oncology 48, 214–241.

Napoli, J.L. (2017). Cellular retinoid binding-proteins, CRBP, CRABP, FABP5: Effects on retinoid metabolism, function and related diseases. Pharmacol. Ther. 173, 19–33.

Nara, K., Kusafuka, T., Yoneda, A., Oue, T., Sangkhathat, S., and Fukuzawa, M. (2007). Silencing of MYCN by RNA interference induces growth inhibition, apoptotic activity and cell differentiation in a neuroblastoma cell line with MYCN amplification. Int. J. Oncol. 30, 1189–1196.

107

Negroni, A., Scarpa, S., Romeo, A., Ferrari, S., Modesti, A., and Raschellà, G. (1991). Decrease of proliferation rate and induction of differentiation by a MYCN antisense DNA oligomer in a human neuroblastoma cell line. Cell Growth Differ. 2, 511–518.

Nemecek, E.R., Sawin, R.W., and Park, J. (2003). Treatment of neuroblastoma in patients with neurocristopathy syndromes. J. Pediatr. Hematol. Oncol. 25, 159–162.

Newman, E.A., and Nuchtern, J.G. (2016). Recent biologic and genetic advances in neuroblastoma: Implications for diagnostic, risk stratification, and treatment strategies. Seminars in Pediatric Surgery 25, 257–264.

Nguyen, T., Hocker, J.E., Thomas, W., Smith, S.A., Norris, M.D., Haber, M., Cheung, B., and Marshall, G.M. (2003). Combined RARα- and RXR-specific ligands overcome N-myc-associated retinoid resistance in neuroblastoma cells. Biochemical and Biophysical Research Communications 302, 462–468.

Nowak, D., Stewart, D., and Koeffler, H.P. (2009). Differentiation therapy of leukemia: 3 decades of development. Blood 113, 3655–3665.

Ochoa, W.F., Torrecillas, A., Fita, I., Verdaguer, N., Corbalán-García, S., and Gomez- Fernandez, J.C. (2003). Retinoic acid binds to the C2-domain of protein kinase C(alpha). Biochemistry 42, 8774–8779.

Ohnuma-Ishikawa, K., Morio, T., Yamada, T., Sugawara, Y., Ono, M., Nagasawa, M., Yasuda, A., Morimoto, C., Ohnuma, K., Dang, N.H., et al. (2007). Knockdown of XAB2 enhances all-trans retinoic acid-induced cellular differentiation in all-trans retinoic acid-sensitive and -resistant cancer cells. Cancer Res. 67, 1019–1029.

Okusaka, T., Ueno, H., Ikeda, M., Takezako, Y., and Morizane, C. (2012). Phase I study of TAC-101, an oral synthetic retinoid, in Japanese patients with advanced hepatocellular carcinoma. Cancer Sci. 103, 1524–1530.

Osajima-Hakomori, Y., Miyake, I., Ohira, M., Nakagawara, A., Nakagawa, A., and Sakai, R. (2005). Biological role of anaplastic lymphoma kinase in neuroblastoma. Am. J. Pathol. 167, 213–222.

Otake, K., Uchida, K., Ide, S., Kobayashi, Y., Kobayashi, I., and Kusunoki, M. (2016). Identification of DDX39A as a Potential Biomarker for Unfavorable Neuroblastoma Using a Proteomic Approach. Pediatr Blood Cancer 63, 221–227.

Pan, J., Kao, Y.-L., Joshi, S., Jeetendran, S., Dipette, D., and Singh, U.S. (2005). Activation of Rac1 by phosphatidylinositol 3-kinase in vivo: role in activation of mitogen-activated protein kinase (MAPK) pathways and retinoic acid-induced neuronal differentiation of SH-SY5Y cells. J. Neurochem. 93, 571–583.

Papac, R.J. (1998). Spontaneous regression of cancer: possible mechanisms. In Vivo 12, 571–578.

108

Park, J.R., Bagatell, R., London, W.B., Maris, J.M., Cohn, S.L., Mattay, K.K., Mattay, K.M., Hogarty, M., and COG Neuroblastoma Committee (2013). Children’s Oncology Group’s 2013 blueprint for research: neuroblastoma. Pediatr Blood Cancer 60, 985–993.

Pavone, M.E., Reierstad, S., Sun, H., Milad, M., Bulun, S.E., and Cheng, Y.-H. (2010). Altered retinoid uptake and action contributes to cell survival in endometriosis. J. Clin. Endocrinol. Metab. 95, E300-309.

Peaston, A.E., Gardaneh, M., Franco, A.V., Hocker, J.E., Murphy, K.M., Farnsworth, M.L., Catchpoole, D.R., Haber, M., Norris, M.D., Lock, R.B., et al. (2001). MRP1 gene expression level regulates the death and differentiation response of neuroblastoma cells. Br. J. Cancer 85, 1564–1571.

Pegoraro, C., and Monsoro-Burq, A.H. (2013). Signaling and transcriptional regulation in neural crest specification and migration: lessons from xenopus embryos. Wiley Interdiscip Rev Dev Biol 2, 247–259.

Pei, D., Luther, W., Wang, W., Paw, B.H., Stewart, R.A., and George, R.E. (2013). Distinct neuroblastoma-associated alterations of PHOX2B impair sympathetic neuronal differentiation in zebrafish models. PLoS Genet. 9, e1003533.

Phelan, M.L., and Featherstone, M.S. (1997). Distinct HOX N-terminal arm residues are responsible for specificity of DNA recognition by HOX monomers and HOX.PBX heterodimers. J. Biol. Chem. 272, 8635–8643.

Pierce, G.B., and Verney, E.L. (1961). An in vitro and in vivo study of differentiation in teratocarcinomas. Cancer 14, 1017–1029.

Piskunov, A., and Rochette-Egly, C. (2012). A retinoic acid receptor RARα pool present in membrane lipid rafts forms complexes with G protein αQ to activate p38MAPK. Oncogene 31, 3333–3345.

Pontual, L. de, Kettaneh, D., Gordon, C.T., Oufadem, M., Boddaert, N., Lees, M., Balu, L., Lachassinne, E., Petros, A., Mollet, J., et al. (2011). Germline gain-of-function mutations of ALK disrupt central nervous system development. Human Mutation 32, 272–276.

Pule, M.A., Savoldo, B., Myers, G.D., Rossig, C., Russell, H.V., Dotti, G., Huls, M.H., Liu, E., Gee, A.P., Mei, Z., et al. (2008). Virus-specific T cells engineered to coexpress tumor-specific receptors: persistence and antitumor activity in individuals with neuroblastoma. Nature Medicine 14, 1264–1270.

Puntoni, M., Petrera, M., Campora, S., Garrone, E., Defferrari, C., Torrisi, R., Johansson, H., Bruno, S., Curotto, A., and DeCensi, A. (2016). Prognostic Significance of VEGF after Twenty-Year Follow-up in a Randomized Trial of Fenretinide in Non- Muscle-Invasive Bladder Cancer. Cancer Prev Res (Phila) 9, 437–444.

109

Qin, P., Haberbusch, J.M., Zhang, Z., Soprano, K.J., and Soprano, D.R. (2004a). Pre-B cell leukemia transcription factor (PBX) proteins are important mediators for retinoic acid-dependent endodermal and neuronal differentiation of mouse embryonal carcinoma P19 cells. J. Biol. Chem. 279, 16263–16271.

Qin, P., Haberbusch, J.M., Soprano, K.J., and Soprano, D.R. (2004b). Retinoic acid regulates the expression of PBX1, PBX2, and PBX3 in P19 cells both transcriptionally and post-translationally. Journal of Cellular Biochemistry 92, 147– 163.

Ram, T.G., Reeves, R., and Hosick, H.L. (1993). Elevated High Mobility Group-I(Y) Gene Expression Is Associated with Progressive Transformation of Mouse Mammary Epithelial Cells. Cancer Res 53, 2655–2660.

Reboul, E., and Borel, P. (2011). Proteins involved in uptake, intracellular transport and basolateral secretion of fat-soluble vitamins and carotenoids by mammalian enterocytes. Prog. Lipid Res. 50, 388–402.

Reynolds, C.P. (2000). Differentiating agents in pediatric malignancies: Retinoids in neuroblastoma. Curr Oncol Rep 2, 511–518.

Riley, R.D., Heney, D., Jones, D.R., Sutton, A.J., Lambert, P.C., Abrams, K.R., Young, B., Wailoo, A.J., and Burchill, S.A. (2004). A Systematic Review of Molecular and Biological Tumor Markers in Neuroblastoma. Clin Cancer Res 10, 4–12.

Sachs, L. (1978). Control of normal cell differentiation and the phenotypic reversion of malignancy in myeloid leukaemia. Nature 274, 535–539.

Sakashita, A., Kizaki, M., Pakkala, S., Schiller, G., Tsuruoka, N., Tomosaki, R., Cameron, J.F., Dawson, M.I., and Koeffler, H.P. (1993). 9-cis-retinoic acid: effects on normal and leukemic hematopoiesis in vitro. Blood 81, 1009–1016.

Samaraweera, L., Grandinetti, K.B., Huang, R., Spengler, B.A., and Ross, R.A. (2014). MicroRNAs define distinct human neuroblastoma cell phenotypes and regulate their differentiation and tumorigenicity. BMC Cancer 14, 309.

Sandberg, R., and Ernberg, I. (2005). The molecular portrait of in vitro growth by meta- analysis of gene-expression profiles. Genome Biol. 6, R65.

Schilling, F.H., Spix, C., Berthold, F., Erttmann, R., Sander, J., Treuner, J., and Michaelis, J. (2003). Children may not benefit from neuroblastoma screening at 1 year of age. Updated results of the population based controlled trial in Germany. Cancer Lett. 197, 19–28.

Schleiermacher, G., Mosseri, V., London, W.B., Maris, J.M., Brodeur, G.M., Attiyeh, E., Haber, M., Khan, J., Nakagawara, A., Speleman, F., et al. (2012). Segmental chromosomal alterations have prognostic impact in neuroblastoma: a report from the INRG project. British Journal of Cancer 107, 1418–1422.

110

Schmidt, M.L., Lukens, J.N., Seeger, R.C., Brodeur, G.M., Shimada, H., Gerbing, R.B., Stram, D.O., Perez, C., Haase, G.M., and Matthay, K.K. (2000). Biologic factors determine prognosis in infants with stage IV neuroblastoma: A prospective Children’s Cancer Group study. J. Clin. Oncol. 18, 1260–1268.

Schulte, J.H., Lindner, S., Bohrer, A., Maurer, J., De Preter, K., Lefever, S., Heukamp, L., Schulte, S., Molenaar, J., Versteeg, R., et al. (2013). MYCN and ALKF1174L are sufficient to drive neuroblastoma development from neural crest progenitor cells. Oncogene 32, 1059–1065.

Seeger, R.C., Brodeur, G.M., Sather, H., Dalton, A., Siegel, S.E., Wong, K.Y., and Hammond, D. (1985). Association of multiple copies of the N-myc oncogene with rapid progression of neuroblastomas. N. Engl. J. Med. 313, 1111–1116.

Shah, N., Wang, J., Selich-Anderson, J., Graham, G., Siddiqui, H., Li, X., Khan, J., and Toretsky, J. (2014). PBX1 is a favorable prognostic biomarker as it modulates 13-cis retinoic acid-mediated differentiation in neuroblastoma. Clin. Cancer Res. 20, 4400– 4412.

Shahar, E., and Shinawi, M. (2003). Neurocristopathies presenting with neurologic abnormalities associated with Hirschsprung’s disease. Pediatr. Neurol. 28, 385–391.

Shakhova, O., and Sommer, L. (2008). Neural crest-derived stem cells. In StemBook, (Cambridge (MA): Harvard Stem Cell Institute), p.

Shiraishi, K., Yamasaki, K., Nanba, D., Inoue, H., Hanakawa, Y., Shirakata, Y., Hashimoto, K., and Higashiyama, S. (2007). Pre-B-cell leukemia transcription factor 1 is a major target of promyelocytic leukemia zinc-finger-mediated melanoma cell growth suppression. Oncogene 26, 339–348.

Sholler, G.L.S., Ferguson, W., Bergendahl, G., Currier, E., Lenox, S.R., Bond, J., Slavik, M., Roberts, W., Mitchell, D., Eslin, D., et al. (2012). A Pilot Trial Testing the Feasibility of Using Molecular-Guided Therapy in Patients with Recurrent Neuroblastoma. 2012.

Shtukmaster, S., Schier, M.C., Huber, K., Krispin, S., Kalcheim, C., and Unsicker, K. (2013). Sympathetic neurons and chromaffin cells share a common progenitor in the neural crest in vivo. Neural Dev 8, 12.

Sidell, N., Altman, A., Haussler, M.R., and Seeger, R.C. (1983). Effects of retinoic acid (RA) on the growth and phenotypic expression of several human neuroblastoma cell lines. Experimental Cell Research 148, 21–30.

Sinha, R., Schultz, N., and Sander, C. (2015). Comparing cancer cell lines and tumor samples by genomic profiles. BioRxiv 028159.

Smiraglia, D.J., Rush, L.J., Frühwald, M.C., Dai, Z., Held, W.A., Costello, J.F., Lang, J.C., Eng, C., Li, B., Wright, F.A., et al. (2001). Excessive CpG island hypermethylation in cancer cell lines versus primary human malignancies. Hum. Mol. Genet. 10, 1413– 1419.

111

Smith, V., and Foster, J. (2018). High-Risk Neuroblastoma Treatment Review. Children 5, 114.

Song, M.M., Makena, M.R., Hindle, A., Koneru, B., Nguyen, T.H., Verlekar, D.U., Cho, H., Maurer, B.J., Kang, M.H., and Reynolds, C.P. (2019). Cytotoxicity and molecular activity of fenretinide and metabolites in T-cell lymphoid malignancy, neuroblastoma, and ovarian cancer cell lines in physiological hypoxia. Anticancer Drugs 30, 117–127.

Song, X., Liu, W., Xie, S., Wang, M., Cao, G., Mao, C., and Lv, C. (2013). All- transretinoic acid ameliorates bleomycin-induced lung fibrosis by downregulating the TGF-β1/Smad3 signaling pathway in rats. Laboratory Investigation 93, 1219– 1231.

Soriano, A., París-Coderch, L., Jubierre, L., Martínez, A., Zhou, X., Piskareva, O., Bray, I., Vidal, I., Almazán-Moga, A., Molist, C., et al. (2016). MicroRNA-497 impairs the growth of chemoresistant neuroblastoma cells by targeting cell cycle, survival and vascular permeability genes. Oncotarget 7, 9271–9287.

Sramek, M., Neradil, J., Sterba, J., and Veselska, R. (2016). Non-DHFR-mediated effects of methotrexate in osteosarcoma cell lines: epigenetic alterations and enhanced cell differentiation. Cancer Cell Int 16.

Sterba, J. (2002). Contemporary therapeutic options for children with high risk neuroblastoma. Neoplasma 49, 133–140.

Strobl-Mazzulla, P.H., and Bronner, M.E. (2012). Epithelial to mesenchymal transition: new and old insights from the classical neural crest model. Semin. Cancer Biol. 22, 411–416.

Stromskaya, T.P., Rybalkina, E.Y., Zabotina, T.N., Shishkin, A.A., and Stavrovskaya, A.A. (2005). Influence of RARα gene on MDR1 expression and P-glycoprotein function in human leukemic cells. Cancer Cell Int 5, 15.

Sugiura, T., Nagano, Y., and Noguchi, Y. (2007). DDX39, upregulated in lung squamous cell cancer, displays RNA helicase activities and promotes cancer cell growth. Cancer Biology & Therapy 6, 957–964.

Sun, H., and Kawaguchi, R. (2011). The membrane receptor for plasma retinol-binding protein, a new type of cell-surface receptor. Int Rev Cell Mol Biol 288, 1–41.

Swift, M.E., Wallden, B., Wayner, E.A., and Swisshelm, K. (2006). Truncated RAR beta isoform enhances proliferation and retinoid resistance. J. Cell. Physiol. 209, 718– 725.

Tan, L., Xu, H., Chen, G., Wei, X., Yu, B., Ye, J., Xu, L., and Tan, H. (2018). Silencing of HMGA2 reverses retardance of cell differentiation in human myeloid leukaemia. Br J Cancer 118, 405–415.

112

Tarapcsák, S., Szalóki, G., Telbisz, Á., Gyöngy, Z., Matúz, K., Csősz, É., Nagy, P., Holb, I.J., Rühl, R., Nagy, L., et al. (2017). Interactions of retinoids with the ABC transporters P-glycoprotein and Breast Cancer Resistance Protein. Sci Rep 7.

Tari, A.M., Lim, S.-J., Hung, M.-C., Esteva, F.J., and Lopez-Berestein, G. (2002). Her2/neu induces all-trans retinoic acid (ATRA) resistance in breast cancer cells. Oncogene 21, 5224–5232. de Thé, H., Lavau, C., Marchio, A., Chomienne, C., Degos, L., and Dejean, A. (1991). The PML-RAR alpha fusion mRNA generated by the t(15;17) translocation in acute promyelocytic leukemia encodes a functionally altered RAR. Cell 66, 675–684.

Thiele, C.J., Reynolds, C.P., and Israel, M.A. (1985). Decreased expression of N-myc precedes retinoic acid-induced morphological differentiation of human neuroblastoma. Nature 313, 404.

Tivnan, A., Orr, W.S., Gubala, V., Nooney, R., Williams, D.E., McDonagh, C., Prenter, S., Harvey, H., Domingo-Fernández, R., Bray, I.M., et al. (2012). Inhibition of neuroblastoma tumor growth by targeted delivery of microRNA-34a using anti- disialoganglioside GD2 coated nanoparticles. PLoS ONE 7, e38129.

Trochet, D., Bourdeaut, F., Janoueix-Lerosey, I., Deville, A., de Pontual, L., Schleiermacher, G., Coze, C., Philip, N., Frébourg, T., Munnich, A., et al. (2004). Germline mutations of the paired-like homeobox 2B (PHOX2B) gene in neuroblastoma. Am. J. Hum. Genet. 74, 761–764.

Tsubono, Y., and Hisamichi, S. (2004). A Halt to Neuroblastoma Screening in Japan. New England Journal of Medicine 350, 2010–2011.

Tsuji, K., Kawauchi, S., Saito, S., Furuya, T., Ikemoto, K., Nakao, M., Yamamoto, S., Oka, M., Hirano, T., and Sasaki, K. (2010). Breast cancer cell lines carry cell line- specific genomic alterations that are distinct from aberrations in breast cancer tissues: comparison of the CGH profiles between cancer cell lines and primary cancer tissues. BMC Cancer 10, 15.

Van heusden, J., Wouters, W., Ramaekers, F.C., Krekels, M.D., Dillen, L., Borgers, M., and Smets, G. (1998). All-trans-retinoic acid metabolites significantly inhibit the proliferation of MCF-7 human breast cancer cells in vitro. Br. J. Cancer 77, 26–32.

Veal, G.J., Cole, M., Errington, J., Pearson, A.D.J., Foot, A.B.M., Whyman, G., and Boddy, A.V. (2007). Pharmacokinetics and metabolism of 13-cis-retinoic acid (isotretinoin) in children with high-risk neuroblastoma – a study of the United Kingdom Children’s Cancer Study Group. British Journal of Cancer 96, 424–431.

Veselska, R., Kuglik, P., Cejpek, P., Svachova, H., Neradil, J., Loja, T., and Relichova, J. (2006). Nestin expression in the cell lines derived from glioblastoma multiforme. BMC Cancer 6, 32.

Vitobello, A., Ferretti, E., Lampe, X., Vilain, N., Ducret, S., Ori, M., Spetz, J.-F., Selleri, L., and Rijli, F.M. (2011). Hox and Pbx factors control retinoic acid synthesis during hindbrain segmentation. Dev. Cell 20, 469–482. 113

Waetzig, V., Haeusgen, W., Andres, C., Frehse, S., Reinecke, K., Bruckmueller, H., Boehm, R., Herdegen, T., and Cascorbi, I. (2019). Retinoic acid-induced survival effects in SH-SY5Y neuroblastoma cells. J. Cell. Biochem. 120, 5974–5986.

Wang, H., Zhang, Y., and Du, Y. (2013a). Ovarian and breast cancer spheres are similar in transcriptomic features and sensitive to fenretinide. Biomed Res Int 2013, 510905.

Wang, W., Zhong, Q., Teng, L., Bhatnagar, N., Sharma, B., Zhang, X., Luther, W., Haynes, L.P., Burgoyne, R.D., Vidal, M., et al. (2014). Mutations that disrupt PHOXB interaction with the neuronal calcium sensor HPCAL1 impede cellular differentiation in neuroblastoma. Oncogene 33, 3316–3324.

Wang, X., Choi, J.-H., Ding, J., Yang, L., Ngoka, L.C., Lee, E.J., Zha, Y., Mao, L., Jin, B., Ren, M., et al. (2013b). HOXC9 directly regulates distinct sets of genes to coordinate diverse cellular processes during neuronal differentiation. BMC Genomics 14, 830.

Wei, J.S., Johansson, P., Chen, Q.-R., Song, Y.K., Durinck, S., Wen, X., Cheuk, A.T., Smith, M.A., Houghton, P., Morton, C., et al. (2009). microRNA Profiling Identifies Cancer-Specific and Prognostic Signatures in Pediatric Malignancies. Clin Cancer Res 15, 5560–5568.

Wood, A.C., Krytska, K., Ryles, H.T., Infarinato, N.R., Sano, R., Hansel, T.D., Hart, L.S., King, F.J., Smith, T.R., Ainscow, E., et al. (2017). Dual ALK and CDK4/6 Inhibition Demonstrates Synergy against Neuroblastoma. Clin. Cancer Res. 23, 2856–2868.

Woods, W.G., Tuchman, M., Robison, L.L., Bernstein, M., Leclerc, J.M., Brisson, L.C., Brossard, J., Hill, G., Shuster, J., Luepker, R., et al. (1996). A population-based study of the usefulness of screening for neuroblastoma. Lancet 348, 1682–1687.

Woods, W.G., Gao, R.-N., Shuster, J.J., Robison, L.L., Bernstein, M., Weitzman, S., Bunin, G., Levy, I., Brossard, J., Dougherty, G., et al. (2002). Screening of infants and mortality due to neuroblastoma. N. Engl. J. Med. 346, 1041–1046.

Worst, B.C., van Tilburg, C.M., Balasubramanian, G.P., Fiesel, P., Witt, R., Freitag, A., Boudalil, M., Previti, C., Wolf, S., Schmidt, S., et al. (2016). Next-generation personalised medicine for high-risk paediatric cancer patients - The INFORM pilot study. Eur. J. Cancer 65, 91–101.

Wright, J.H. (1910). NEUROCYTOMA OR NEUROBLASTOMA, A KIND OF TUMOR NOT GENERALLY RECOGNIZED. J Exp Med 12, 556–561.

Wu, J.M., DiPietrantonio, A.M., and Hsieh, T.-C. (2001). Mechanism of fenretinide (4- HPR)-induced cell death. Apoptosis 6, 377–388.

Xu, W.P., Zhang, X., and Xie, W.F. (2014). Differentiation therapy for solid tumors. Journal of Digestive Diseases 15, 159–165.

Yang, R.K., and Sondel, P.M. (2010). Anti-GD2 Strategy in the Treatment of Neuroblastoma. Drugs Future 35, 665.

114

Yang, H., Zhan, Q., and Wan, Y.-J.Y. (2011). Enrichment of Nur77 mediated by retinoic acid receptor β leads to apoptosis of human hepatocellular carcinoma cells induced by fenretinide and histone deacetylase inhibitors. Hepatology 53, 865–874.

Yoo, H.H., and Chung, I.K. (2011). Requirement of DDX39 DEAD box RNA helicase for genome integrity and telomere protection. Aging Cell 10, 557–571.

Yu, A.L., Gilman, A.L., Ozkaynak, M.F., London, W.B., Kreissman, S.G., Chen, H.X., Smith, M., Anderson, B., Villablanca, J.G., Matthay, K.K., et al. (2010). Anti-GD2 antibody with GM-CSF, interleukin-2, and isotretinoin for neuroblastoma. N. Engl. J. Med. 363, 1324–1334.

Yu, Z., Lin, J., Xiao, Y., Han, J., Zhang, X., Jia, H., Tang, Y., and Li, Y. (2005). Induction of Cell-Cycle Arrest by all-trans Retinoic Acid in Mouse Embryonic Palatal Mesenchymal (MEPM) Cells. Toxicol Sci 83, 349–354.

Zage, P.E. (2018). Novel Therapies for Relapsed and Refractory Neuroblastoma. Children (Basel) 5.

115