Genes involved in regulation of stem cell properties

[Cancer Biology & Therapy 8:13, 1300-1306; 1 July 2009]; ©2009 Landes Bioscience

Research Paper

Genes involved in regulation of stem cell properties Studies on their expression in a small cohort of neuroblastoma patients Mariarosa A.B. Melone,2,† Maria Giuliano,1,† Tiziana Squillaro,3 Nicola Alessio,4,7 Fiorina Casale,1 Eliseo Mattioli,6 Marilena Cipollaro,4 Antonio Giordano5-8 and Umberto Galderisi4,5,7,* 1Department of Pediatrics “F. Fede”; and 2Department of Neurology; 4Department of Experimental Medicine; Section of Biotechnology and Molecular Biology “A. Cascino”; Second University of Naples; Naples, Italy; 3Medical Genetics; 6Human Pathology and Oncology Deptartment; University of Siena; Italy; 5Sbarro Institute for Cancer Research and Molecular Medicine; Center for Biotechnology; Temple University; Philadelphia, PA USA; 7Human Health Foundation; Spoleto, Italy; 8Centro Ricerche Oncologiche Mercogliano “Fiorentino Lo Vuolo”; Mercogliano, Italy †These

authors contributed equally to this work.

Key words: cancer stem cells, gene expression, cell line

Cancer stem cells have been isolated from many tumors. Several evidences prove that neuroblastoma contains its own stem cell-like cancer cells. We chose to analyze 20 neuroblastoma tumor samples in the expression of 13 genes involved in the regulation of stem cell properties to evaluate if their misregulation could have a clinical relevance. In several specimens we detected the expression of genes belonging to the OCT3/SOX2/NANOG/ KLF4 core circuitry that acts at the highest level in regulating stem cell biology. This result is in agreement with studies showing the existence of malignant stem cells in neuroblastoma. We also observed differences in the expression of some stemness-related genes that may be useful for developing new prognostic analyses. In fact, preliminary data suggests that the presence/absence of UTF1 along with differences in BMI1 mRNA levels could distinguish low grade neuroblastomas from IV stage tumors.

Introduction The identification of reservoirs of stem cells within adult tissues demonstrates that all tissues may have stem cells. Stem cells within normal tissues are defined by common characteristics: self-renewal to maintain the stem cell pool over time; regulation of stem cell number through a strict balance between cell proliferation, cell differentiation and cell death; and the ability to spawn a broad range of differentiated cells.1,2 Like stem cells, cancer cells are widely thought to be able to proliferate indefinitely through a deregulated cellular self-renewal capacity. This raises the possibility that some of the clinical properties of tumor cells may be due to transformed stem cells.3,4 *Correspondence to: Umberto Galderisi; Department of Experimental Medicine; Section of Biotechnology and Molecular Biology; Second University of Naples; Via Costantinopoli 16; Napoli 80138 Italy; Tel.: +39.0815667508; Fax: +390815667547; Email: [email protected] Submitted: 02/08/09; Revised: 04/20/09; Accepted: 04/30/09 Previously published online as a Cancer Biology & Therapy E-publication: http://www.landesbioscience.com/journals/cbt/article/8890

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In previous research, stem cell-like cancer cells were isolated from several solid tumors. Now, evidence has shown that also neural cancers, such as glioblastomas, medulloblastomas, astrocytomas and neuroblastomas contain cells that may be multipotent neural stem cell-like cells.5-7 The obvious cellular heterogeneity characteristic of human neuroblastoma tumors, their differential disease course related to patient age at diagnosis, and their origin from the embryonic neural crest make this disease a logical candidate for a malignancy arising from cancer stem cells (CSCs) of the neural crest.5-9 The existence of stem-like cells in neuroblastoma tumors pave the way for the analysis of genes involved in the regulation of stem cell properties and help evaluate if their misregulation in neuroblastomas can be associated with cancer onset and/ or progression of the disease.

Genes Involved in Stem Cell Self-Renewal Studies on transcriptional profiling of stem cells allowed a preliminary identification of “stemness” genes participating in the control of stem cell properties, such as self-renewal ability and retention of an uncommitted state. Initially, genes that control “stemness” were identified in embryonic stem cells.10-14 In adult stem cells, some “stemness genes” are not expressed.15,16 We chose to analyze a panel of 13 embryonic stemness genes in several neuroblastoma tumor (NB) samples to evaluate which of them were expressed and if so, whether or not a correlation existed with the disease’s stage. We carried out a preliminary analysis on the expression of stemness genes in a neuroblastoma cell line that has been demonstrated to have multipotent tumor, stem cell-like components and can be induced to differentiate towards committed neuronal (N-type) phenotype or glial-schwann S (S-type) phenotype.6,8

Results Expression of stemness genes in SK-N-BE(2)-C neuroblastoma cell line. SK-N-BE(2)-C neuroblastoma cell line is a convenient model for studies on neural crest progenitor cells. This

Cancer Biology & Therapy

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Stemness genes and neuroblastoma

cell line derives from human cancers originating from malignant neural crest cells.18 They show an intermediate (I) phenotype that has been demonstrated to represent a multipotent embryonic precursor cell of the peripheral nervous system and hence can be induced to differentiate towards the committed neuronal N type and S type.8,19,20 In SK-N-BE(2)-C cells, we detected the expression of OCT3, NANOG and KLF4, which are part of the core transcriptional circuitry for regulation of embryonic stem cell properties (Fig. 1).21-24 Of interest is that SOX2, another component of this genenetwork, was not expressed. In I-type neuroblastoma cells we also evidenced the expression of ERAS, SOX15, BMI1 and SALL4 (Fig. 1); these are other genes with a role in embryonic stem cell physiology.10,12,14,21-24 Qualitative analysis of the expression of stemness genes in neuroblastoma tumor samples. Having analyzed the expression pattern of stemness genes in neuroblastoma cells, we decided to carry out the same expression studies on 20 neuroblastoma samples obtained from patients with different staging. The clinical characteristics of the patients are shown in Table 2. It has been generally recognized that stage I, II, and partial stage III patients may have a good prognosis, while stage IV have poor prognosis.25-27 In our cohort of patients, we had ten IV stage individuals (five of them died) and ten I-III stage patients (all alive). We determined the presence/absence of 13 stemness related genes in the clinical samples with RT-PCR technique. Some genes, such as BMI1, OCT3, SOX15, SALL4, ERAS and NANOG were expressed in most of the analyzed samples, others, such as ZFP42, were present only in a few (Fig. 2). Looking at the panel of genes expressed in each of the analyzed NBs, in only a few samples we observed the expression of the great majority of the stemness genes under study; the panel of expressed genes in NB samples ranged between 3–12, the mode of expressed genes was 7 and the mean was 6.8 (Fig. 2). We did not evidence any correlation between the number of expressed genes and the stage of disease. Of interest, the seven genes expressed in neuroblastoma cells were also evidenced in most NB samples (compare Figs. 1 and 2). In detail, in several NBs we detected mRNA molecules of some genes belonging to OCT3/SOX2/NANOG/KLF4 core circuitry. Also, in NBs showing the expression of a few stemness related genes (i.e., 3 or 4 out 13), we observed the activation of at least one component of core circuitry (Fig. 2). We carried out a closer analysis on gene expression patterns to determine if it was possible to find an expression algorithm that could differentiate I-III stages from poor prognosis IV stage. Looking at the several possible algorithms we found that the expression of UTF1 was related with stage IV neuroblastomas, in fact UTF1 is mainly expressed in I-III stage patients (Fig. 2). Statistical analysis on the identified algorithm was not significant (p > 0.05), since we had a small cohort of patients. Gene expression in tumor samples and cluster analysis. The data on the presence or absence of gene expression in the 20 samples under analysis were used to carry out a Minimum

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Figure 1. RT-PCR analysis. mRNA levels were normalized with respect to GAPDH, chosen as an internal control. Top: a representative picture of a SK-N-BE(2)-C neuroblastoma cell culture. Bottom left: the histogram shows the mean expression values (±SD, n = 3). Right: representative RT-PCR analysis. P.C. and N.C: are positive and negative RT-PCR controls, respectively.

Variance test to evaluate gene expression variability among different patients. We assumed that data on the presence or absence of gene expression in the 20 patients under analysis could be considered as a pool of points derived from a distribution, which contains several distinct clusters. Our assumption was made on the basis that accumulation of DNA mutations during cancer development leads to high heterogeneity in gene expression among tumors. On this premise, our goal was to obtain a minimum variance clustering based on a matrix constructed with the presence/absence gene expression points, such that patients having similar patterns of expressed/not expressed genes fall in the same cluster and have a more “genetic homogeneity” compared to those showing different expression patterns, which are then classified in distinct clusters. The Ward minimum variance clustering method allowed us to classify tumor samples according their degree of similarity in gene expression profiles. Looking at Figure 3, it is evident that there is no possibility of identifying any cluster that contains a homogenous group of patients, such as a cluster containing all IV stage patients. Consequently, gene expression patterns in the analyzed NBs showed a high grade of heterogeneity. Quantitative analysis of the expression of stemness genes in neuroblastoma tumor samples. Looking at quantitative gene expression profiles we find an expression pattern that could be useful for differentiation between I-III stage and IV stage NBs. In fact, BMI1 gene expression was higher in I-III stage group (2.923 ± 0.8824 N = 10) when compared to high grade tumors (0.795 ± 0.097 N = 9), (p = 0.0401) (Fig. 4A and B).


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Figure 2. Qualitative RT-PCR analysis of stemness-related genes in 20 NBs. The table summarizes the results on the presence (+) or absence (-) of gene expression for each patient. The histogram shows the number of expressed genes in the patients. I-III stage patients are in white, IV stage patients are in grey.

Discussion

Figure 3. Minimum Variance test to evaluate gene expression variability among different patients. The minimum variance tree shows the genetic similarity among patients. The tree was built taking into account results on the presence (+) or absence (-) of gene expression as shown in Figure 2. Genetic distance was expressed as squared Euclidean values. Deriving the Euclidean distance between two data points involves computing the square root of the sum of the squares of the differences between corresponding values. I-III stage patients are in white, IV stage patients are in grey. 1302

Several evidences show that a neuroblastoma could arise from its own cancer stem cells.5-9 In vitro, the neuroblastoma cancer stem cells may correspond with population having Intermediate phenotype (I-type). These cells express features of both N-type and S-type cells, possess multipotential differentiation properties, and can be induced to differentiate in neuroblastic or glial phenotypes. Of interest, I-type cells are more malignant than N-type and S-type cells in athymic mice. This further confirms that I-type cells may also be considered the “so-called” tumor initiating cells (TICs) or cancer stem cells.5-9 On these premises, we chose to evaluate the expression profile of several stemness-related genes in the SK-N-BE(2)-C neuroblastoma cell line that is composed of I-type cells.8,20 In neuroblastoma cells we detected the expression of 7 out 13 stemness related genes. Of interest, we detected the expression of OCT3, NANOG and KLF4, which are part of the core transcriptional regulatory circuitry for regulation of embryonic stem cell properties. The stemness gene expression patterns in the analyzed NBs showed a high grade of heterogeneity. Nevertheless, the seven genes expressed in


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Figure 4. (A) Quantitative RT-PCR analysis of stemness-related genes in 20 NBs. For each gene the expression values are reported in a graph, which shows two groups: I-III stage and IV stage patients. Means and standard deviation are indicated in each graph.

neuroblastoma cells were present also in the great majority of NB samples (compare Fig. 1 and Fig. 2). Cluster analysis showed a high genetic heterogeneity among analyzed NBs. Generally speaking, it is reasonable to hypothesize that genetic heterogeneity in cancer may arise by multistep process of mutational accumulations during progression of disease from low grade to high grade status. The observation that NBs show genetic heterogeneity among all analyzed samples irrespective of tumor grade may signify that each neuroblastoma could start with patient specific mutations. This hypothesis about the origin of www.landesbioscience.com

variability in the expression profiles among NBs could be considered in good agreement with the high phenotypic heterogeneity observed in neuroblastomas.26 These data may have a clinical relevance. In fact, tumor heterogeneity and clonal evolution at the genetic level may explain differences in patients’ response to therapies as well as the development of malignant or resistant disease during clinical progression of neuroblastoma. It should be emphasized that in spite of high gene expression variability, both in NBs and neuroblastoma cell cultures we observed the activation of some genes belonging OCT3/SOX2/


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Figure 4. (B) Quantitative RT-PCR analysis of stemness-related genes in 20 NBs. For each gene the expression values are reported in a graph, which shows two groups: I-III stage and IV stage patients. Means and standard deviation are indicated in each graph.

NANOG/KLF4 core circuitry. These studies may represent an indirect evidence to further confirm the presence of cancer stem cell-like in neuroblastomas. Preliminary data suggest that presence/absence of UTF1 along with differences in BMI1 mRNA levels could be useful for differentiating I-III stage NBs from IV stage tumors. Statistical analyses on these expression patterns were significant (p < 0.05) only for the BMI1 gene expression pattern, probably because we had a small cohort of patients. Nevertheless, these data are interesting and could represent a starting point to identify new prognostic factors. The two genes indicated above regulate specific aspects of stem cell biology. UTF1 is a transcriptional coactivator expressed in embryonic stem cells (ESCs) and is involved in the initial phase of 1304

the differentiation process.28,29 BMI1 is a member of the Polycomb gene family that plays a key role in epigenetic phenomena associated with stem cell self-renewal and oncogenesis.30 This latter aspect is of great interest. It has been suggested that BMI1 expression level is associated with the progression of non-small lung cancer (NSLC).31 Other studies showed that BMI1 is highly expressed in ovarian cancer, and its expression level correlates with the histological grade and clinical phase of patients.32 These two studies, along with our preliminary data, suggest that BMI1 may have a clinical relevance.

Material and Methods Patients and tumor samples. Between 1992 and 2008, clinical tumor samples were collected from 20 patients. The samples were


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Table 1 Primers for RT-PCR

Table 2 Clinical Characteristics of patients

Gene Primer Sequence Annealing Amplicon T (°C) Length (bp) GAPDH 121 5'-GGAGTCAACGGATTTGGTCGT-3' 58 161

Patients Stage Located ID

281

5'-ACGGTGCCATGGAATTTGC-3'

SOX2 1563 5'-CCATCCACACTCACGCAAAA-3'

ERAS

1689

5'-GGTCGCATTTTTGGCACTG-3'

969

5'-AATGTAGACCTTTCCCCAGGC-3'

887 441

5'-GCGTCGATCCTGAAAATGGA-3'

DPPA2 798

5'-AGCCATGTTGGCATCATGG-3'

60

182

250

5'-TTCTCGGAGCTCTCTGCTTTG-3'

TCL1

667

5'-CTCGGCTTTTTCTCAGCTGGAT-3'

793

5'-GGTGAATCGGCTGTGTTCTCA-3'

ZFP42 953 5'-ATGACAGTCTGAGCGCAATCG-3' 1085 876

5'-CGACATCGCGAACATCCTG-3'

992

5'-AGAATGAAGCCCACGGCCA-3'

BMI1

437

5'-AATGTCTTTTCCGCCCGCT-3'

575 5'-ACCCTCCACAAAGCACACACAT-3'

I

Abd parav sn

2

Alive

I

Adr dx

13

Alive

20

I

Abd parav sn

2

Alive

395

I

Abd parav sn

109

Alive

428

I

Tho parav dx

24

Alive

1731

II

Tho parav dx

113

Alive

1337

II

Abd parav dx

34

Alive

32

II

Abd parav sn

80

Alive

19+

II

Cer tho parav sn

5

Alive

1022

III

Tho parav sn

42

Alive

4+

IV

Abd adr dx

81

Alive

IV

Abd parav dx

44

Alive

29+

60

110

15

IV

Adr dx

31

Alive

42

IV

Adr sn

43

Alive

59

127

LA

IV

Adr sn

131

Alive

22+

IV

Abd adr dx

56

Death

58

108

1144

IV

1

Death

720

IV

Abd Adr

31

Death

60

115

25

IV

Adr dx

19

Death

1096

IV

35

Death

59

127

Abd, Abdome; Adr, Adrenal; Cer, Cervical; Parav, Paraventral; Tho, Thoracic; Dx, Right; Sn, Left.

60

133

64

117

59

139

either frozen tissues stored at -80°C or formalin fixed paraffin embedded tissues. We obtained a small amount of RNA from one paraffin sample (patient ID 720) (see RNA extraction paragraph). Cell cultures. SK-N-BE(2)-C neuroblastoma cells were grown in monolayers and maintained at 37°C under 5%CO2 in RPMI 1640 containing 10% foetal bovine serum, 2 mM L-glutamine, 50 units/ml penicillin and 100 μg/ml streptomycin. RNA extraction and RT-PCR. Total RNA was extracted from cell cultures using TRI REAGENT (Molecular Research Center Inc., OH, USA) according to the manufacturer’s protocol. RNA from paraffin-embedded tissues was extracted with RNeasy FFPE kit (Qiagen Italia, Milano, Italy). The mRNA levels of the genes analysed were measured by RT-PCR amplification, as previously reported.17 Sequences for mRNAs from the nucleotide data bank (National Center for Biotechnology Information, USA) were used to design primer pairs for RT-PCR reactions (Primer Express, Applied Biosystems, CA, USA). Appropriate regions of GAPDH cDNA www.landesbioscience.com

014 1035

135

5'-AACGCTTTCCCACATTCCG-3'

UTF1

Status

58

905 5'-GAGGCTTGCAGCAAAAAGGC-3'

SALL4 2394 5'-GCCCAGATATCCTGGAAACCA-3'

142

5'-GCAATGATCCACTTGTGCCAA-3'

SOX15 315 5'-GAACAGGTTGGAAGCAAAGGC-3'

59

1103 5'-AAAGCCCCTCACCAAGTGAA-3'

GDF3 778 5'-AAAAGGAAGAGCAGCCATCCCT-3'

103

1310 5'-CGTTGATTAGGCTCCAACCAT-3'

KLF4 1508 5'-CTGCGGCAAAACCTACACAA-3'

60

1223 5'-CCAAAAACCCTGGCACAAACT-3'

NANOG 1169 5'-TGGACACTGGCTGAATCCTTC-3'

139

1701 5'-TATACAAGGTCCATTCCCCCG-3'

OCT3 1121 5'-TCCCATGCATTCAAACTGAGG-3'

59

Age (months)

were used as controls. Each RT-PCR reaction was repeated at least three times. PCR cycles were adjusted to have linear amplification for all the targets. Quantitative analysis of mRNA levels was carried out by the “GEL DOC UV SYSTEM” (Biorad Company, CA, USA). List of primers for PCR is located in Table 1. When minimal differences in gene expression were detected, experiments were repeated using quantitative reverse-transcription PCR. These assays were run on an Opticon 4 machine (MJ, Research, Waltham, MT, USA). Reactions were performed according to the manufacturer’s instructions by using SYBR green PCR Master mix. Primer sequences were designed with Primer express software. For one patient (ID720), the quality and quantity of extracted RNA did not allow a complete gene expression analysis. Gene expression in tumor samples and cluster analysis. The Multivariate Statistical Package (Kovach Computing Service, Isle of Anglesey, UK) was used for Ward’s Minimum variance clustering method to evaluate gene expression variability among different tumor samples. Statistical analysis. Statistical analyses (Fisher’s exact test; ANOVA test followed by Student’s t- and Bonferroni’s tests) were evaluated using Prism software (Graphpad Software, La Jolla, CA, USA).

Conclusions Our study evidenced that: (1) NB samples expressed several stemness-related genes. This lends further credit to the hypothesis


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of the presence of cancer stem cells in neuroblastoma tumors; (2) in high grade NBs there is a high heterogeneity in gene expression profiles; (3) differences in the expression of some stemness genes may be useful for innovative prognostic analyses. Acknowledgements

This work was partially supported by Sbarro Health Research Organization funds to U.G. and A.G. and by OPEN neuroblastoma association to F.C. We thank Maria Rosaria Cipollaro for technical assistance and Dr. Carla Schettino for critically reading the text. References 1. Gage FH. Mammalian neural stem cells. Science 2000; 287:1433-8. 2. Morrison SJ, Shah NM, Anderson DJ. Regulatory mechanisms in stem cell biology. Cell 1997; 88:287-98. 3. Galderisi U, Cipollaro M, Giordano A. Stem cells and brain cancer. Cell Death Differ 2006; 13:5-11. 4. Reya T, Morrison SJ, Clarke MF, Weissman IL. Stem cells, cancer and cancer stem cells. Nature 2001; 414:105-11. 5. Hansford LM, McKee AE, Zhang L, George RE, Gerstle JT, Thorner PS, et al. Neuroblastoma cells isolated from bone marrow metastases contain a naturally enriched tumor-initiating cell. Cancer Res 2007; 67:11234-43. 6. Ross RA, Spengler BA. Human neuroblastoma stem cells. Semin Cancer Biol 2007; 17:241-7. 7. Tong QS, Zheng LD, Tang ST, Ruan QL, Liu Y, Li SW, et al. Expression and clinical significance of stem cell marker CD133 in human neuroblastoma. World J Pediatr 2008; 4:58-62. 8. Ross RA, Spengler BA, Domenech C, Porubcin M, Rettig WJ, Biedler JL. Human neuroblastoma I-type cells are malignant neural crest stem cells. Cell Growth Differ 1995; 6:449-56. 9. Walton JD, Kattan DR, Thomas SK, Spengler BA, Guo HF, Biedler JL, et al. Characteristics of stem cells from human neuroblastoma cell lines and in tumors. Neoplasia 2004; 6:838-45. 10. Cai J, Weiss ML, Rao MS. In search of “stemness”. Exp Hematol 2004; 32:585-98. 11. Glover CH, Marin M, Eaves CJ, Helgason CD, Piret JM, Bryan J. Meta-analysis of differentiating mouse embryonic stem cell gene expression kinetics reveals early change of a small gene set. PLoS Comput Biol 2006; 2:158. 12. Mikkers H, Frisen J. Deconstructing stemness. EMBO J 2005; 24:2715-9. 13. Sun Y, Li H, Yang H, Rao MS, Zhan M. Mechanisms controlling embryonic stem cell self-renewal and differentiation. Crit Rev Eukaryot Gene Expr 2006; 16:211-31. 14. Takahashi K, Yamanaka S. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell 2006; 126:663-76. 15. Di Bernardo G, Squillaro T, Dell’aversana C, Miceli M, Cipollaro M, Cascino A, et al. Histone Deacetylase inhibitors promote apoptosis and senescence in human mesenchymal stem cells. Stem Cells Dev 2009;18:573-81. 16. Squillaro T, Hayek G, Farina E, Cipollaro M, Renieri A, Galderisi U. A case report: bone marrow mesenchymal stem cells from a Rett syndrome patient are prone to senescence and show a lower degree of apoptosis. J Cell Biochem 2008; 103:1877-85. 17. Galderisi U, Di Bernardo G, Cipollaro M, Peluso G, Cascino A, Cotrufo R, et al. Differentiation and apoptosis of neuroblastoma cells: role of N-myc gene product. J Cell Biochem 1999; 73:97-105. 18. de Bernardi B, Rogers D, Carli M, Madon E, de Laurentis T, Bagnulo S, et al. Localized neuroblastoma. Surgical and pathologic staging. Cancer 1987; 60:1066-72. 19. Ciccarone V, Spengler BA, Meyers MB, Biedler JL, Ross RA. Phenotypic diversification in human neuroblastoma cells: expression of distinct neural crest lineages. Cancer Res 1989; 49:219-25. 20. Jori FP, Galderisi U, Piegari E, Peluso G, Cipollaro M, Cascino A, et al. RB2/p130 ectopic gene expression in neuroblastoma stem cells: evidence of cell-fate restriction and induction of differentiation. Biochem J 2001; 360:569-77. 21. Ezeh UI, Turek PJ, Reijo RA, Clark AT. Human embryonic stem cell genes OCT4, NANOG, STELLAR and GDF3 are expressed in both seminoma and breast carcinoma. Cancer 2005; 104:2255-65. 22. Maruyama M, Ichisaka T, Nakagawa M, Yamanaka S. Differential roles for Sox15 and Sox2 in transcriptional control in mouse embryonic stem cells. J Biol Chem 2005; 280:24371-9. 23. Masui S, Nakatake Y, Toyooka Y, Shimosato D, Yagi R, Takahashi K, et al. Pluripotency governed by Sox2 via regulation of Oct3/4 expression in mouse embryonic stem cells. Nat Cell Biol 2007; 9:625-35. 24. Matoba R, Niwa H, Masui S, Ohtsuka S, Carter MG, Sharov AA, et al. Dissecting Oct3/4-regulated gene networks in embryonic stem cells by expression profiling. PLoS ONE 2006; 1:26.

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25. Bordow SB, Norris MD, Haber PS, Marshall GM, Haber M. Prognostic significance of MYCN oncogene expression in childhood neuroblastoma. J Clin Oncol 1998; 16:3286-94. 26. Brodeur GM. Molecular basis for heterogeneity in human neuroblastomas. Eur J Cancer 1995; 31:505-10. 27. Sawada T, Hirayama M, Nakata T, Takeda T, Takasugi N, Mori T, et al. Mass screening for neuroblastoma in infants in Japan. Interim report of a mass screening study group. Lancet 1984; 2:271-3. 28. Okuda A, Fukushima A, Nishimoto M, Orimo A, Yamagishi T, Nabeshima Y, et al. UTF1, a novel transcriptional coactivator expressed in pluripotent embryonic stem cells and extra-embryonic cells. EMBO J 1998; 17:2019-32. 29. van den Boom V, Kooistra SM, Boesjes M, Geverts B, Houtsmuller AB, Monzen K, et al. UTF1 is a chromatin-associated protein involved in ES cell differentiation. J Cell Biol 2007; 178:913-24. 30. Metsuyanim S, Pode-Shakked N, Schmidt-Ott KM, Keshet G, Rechavi G, Blumental D, et al. Accumulation of malignant renal stem cells is associated with epigenetic changes in normal renal progenitor genes. Stem Cells 2008; 26:1808-17. 31. Vrzalikova K, Skarda J, Ehrmann J, Murray PG, Fridman E, Kopolovic J, et al. Prognostic value of Bmi-1 oncoprotein expression in NSCLC patients: a tissue microarray study. J Cancer Res Clin Oncol 2008; 134:1037-42. 32. Zhang F, Sui L, Xin T. Correlations of BMI-1 expression and telomerase activity in ovarian cancer tissues. Exp Oncol 2008; 30:70-4.


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