Integrative genomic analyses of neurofibromatosis tumours identify SOX9 as a biomarker and survival gene
2009; Springer Nature; Volume: 1; Issue: 4 Linguagem: Inglês
10.1002/emmm.200900027
ISSN1757-4684
AutoresShyra J. Miller, Walter J. Jessen, Tapan Mehta, Atira Hardiman, Emily Sites, Sérgio Kaiser, Anil G. Jegga, Hua Li, Meena Upadhyaya, Marco Giovannini, David Muir, Margaret R. Wallace, Eva López, Eduard Serra, G. Petur Nielsen, Conxi Lázaro, Anat Stemmer‐Rachamimov, Grier P. Page, Bruce J. Aronow, Nancy Ratner,
Tópico(s)Chromatin Remodeling and Cancer
ResumoResearch Article10 July 2009Open Access Integrative genomic analyses of neurofibromatosis tumours identify SOX9 as a biomarker and survival gene Shyra J. Miller Shyra J. Miller Divisions of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, OH, USA Contributed equally to this work. Search for more papers by this author Walter J. Jessen Walter J. Jessen Divisions of Biomedical Informatics, Cincinnati Children's Hospital Research Foundation, University of Cincinnati College of Medicine, Cincinnati, OH, USA Contributed equally to this work. Search for more papers by this author Tapan Mehta Tapan Mehta Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, AL, USA Search for more papers by this author Atira Hardiman Atira Hardiman Divisions of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Emily Sites Emily Sites Divisions of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Sergio Kaiser Sergio Kaiser Divisions of Biomedical Informatics, Cincinnati Children's Hospital Research Foundation, University of Cincinnati College of Medicine, Cincinnati, OH, USA Present address: Novartis Pharma AG, Basel, Switzerland Search for more papers by this author Anil G. Jegga Anil G. Jegga Divisions of Biomedical Informatics, Cincinnati Children's Hospital Research Foundation, University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Hua Li Hua Li Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL, USA Search for more papers by this author Meena Upadhyaya Meena Upadhyaya Institute of Medical Genetics, University of Wales College of Medicine, Heath Park, Cardiff CF, UK Search for more papers by this author Marco Giovannini Marco Giovannini INSERM U434, Foundation Jean Dausset-CEPH, Paris, France Present address: House Ear Institute, Department of Neural Tumor Research, Los Angeles, CA, USA Search for more papers by this author David Muir David Muir Departments of Pediatrics and Neuroscience, University of Florida, Gainesville, FL, USA Search for more papers by this author Margaret R. Wallace Margaret R. Wallace Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL, USA Search for more papers by this author Eva Lopez Eva Lopez Centre de Genètica Mèdica i Molecular (EL and ES), Laboratori de Recerca Translacional, Institut Català d'Oncologia (CL); Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain Search for more papers by this author Eduard Serra Eduard Serra Centre de Genètica Mèdica i Molecular (EL and ES), Laboratori de Recerca Translacional, Institut Català d'Oncologia (CL); Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain Search for more papers by this author G. Petur Nielsen G. Petur Nielsen Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA Search for more papers by this author Conxi Lazaro Conxi Lazaro Centre de Genètica Mèdica i Molecular (EL and ES), Laboratori de Recerca Translacional, Institut Català d'Oncologia (CL); Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain Search for more papers by this author Anat Stemmer-Rachamimov Anat Stemmer-Rachamimov Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA Search for more papers by this author Grier Page Grier Page Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, AL, USA Search for more papers by this author Bruce J. Aronow Bruce J. Aronow Divisions of Biomedical Informatics, Cincinnati Children's Hospital Research Foundation, University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Nancy Ratner Corresponding Author Nancy Ratner [email protected] Divisions of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Shyra J. Miller Shyra J. Miller Divisions of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, OH, USA Contributed equally to this work. Search for more papers by this author Walter J. Jessen Walter J. Jessen Divisions of Biomedical Informatics, Cincinnati Children's Hospital Research Foundation, University of Cincinnati College of Medicine, Cincinnati, OH, USA Contributed equally to this work. Search for more papers by this author Tapan Mehta Tapan Mehta Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, AL, USA Search for more papers by this author Atira Hardiman Atira Hardiman Divisions of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Emily Sites Emily Sites Divisions of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Sergio Kaiser Sergio Kaiser Divisions of Biomedical Informatics, Cincinnati Children's Hospital Research Foundation, University of Cincinnati College of Medicine, Cincinnati, OH, USA Present address: Novartis Pharma AG, Basel, Switzerland Search for more papers by this author Anil G. Jegga Anil G. Jegga Divisions of Biomedical Informatics, Cincinnati Children's Hospital Research Foundation, University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Hua Li Hua Li Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL, USA Search for more papers by this author Meena Upadhyaya Meena Upadhyaya Institute of Medical Genetics, University of Wales College of Medicine, Heath Park, Cardiff CF, UK Search for more papers by this author Marco Giovannini Marco Giovannini INSERM U434, Foundation Jean Dausset-CEPH, Paris, France Present address: House Ear Institute, Department of Neural Tumor Research, Los Angeles, CA, USA Search for more papers by this author David Muir David Muir Departments of Pediatrics and Neuroscience, University of Florida, Gainesville, FL, USA Search for more papers by this author Margaret R. Wallace Margaret R. Wallace Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL, USA Search for more papers by this author Eva Lopez Eva Lopez Centre de Genètica Mèdica i Molecular (EL and ES), Laboratori de Recerca Translacional, Institut Català d'Oncologia (CL); Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain Search for more papers by this author Eduard Serra Eduard Serra Centre de Genètica Mèdica i Molecular (EL and ES), Laboratori de Recerca Translacional, Institut Català d'Oncologia (CL); Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain Search for more papers by this author G. Petur Nielsen G. Petur Nielsen Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA Search for more papers by this author Conxi Lazaro Conxi Lazaro Centre de Genètica Mèdica i Molecular (EL and ES), Laboratori de Recerca Translacional, Institut Català d'Oncologia (CL); Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain Search for more papers by this author Anat Stemmer-Rachamimov Anat Stemmer-Rachamimov Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA Search for more papers by this author Grier Page Grier Page Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, AL, USA Search for more papers by this author Bruce J. Aronow Bruce J. Aronow Divisions of Biomedical Informatics, Cincinnati Children's Hospital Research Foundation, University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Nancy Ratner Corresponding Author Nancy Ratner [email protected] Divisions of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, OH, USA Search for more papers by this author Author Information Shyra J. Miller1, Walter J. Jessen2, Tapan Mehta4, Atira Hardiman1, Emily Sites1, Sergio Kaiser2,3, Anil G. Jegga2, Hua Li5, Meena Upadhyaya6, Marco Giovannini7,8, David Muir9, Margaret R. Wallace5, Eva Lopez10, Eduard Serra10, G. Petur Nielsen11, Conxi Lazaro10, Anat Stemmer-Rachamimov11, Grier Page4, Bruce J. Aronow2 and Nancy Ratner *,1 1Divisions of Experimental Hematology and Cancer Biology, Cincinnati Children's Hospital, University of Cincinnati College of Medicine, Cincinnati, OH, USA 2Divisions of Biomedical Informatics, Cincinnati Children's Hospital Research Foundation, University of Cincinnati College of Medicine, Cincinnati, OH, USA 3Present address: Novartis Pharma AG, Basel, Switzerland 4Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, AL, USA 5Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL, USA 6Institute of Medical Genetics, University of Wales College of Medicine, Heath Park, Cardiff CF, UK 7INSERM U434, Foundation Jean Dausset-CEPH, Paris, France 8Present address: House Ear Institute, Department of Neural Tumor Research, Los Angeles, CA, USA 9Departments of Pediatrics and Neuroscience, University of Florida, Gainesville, FL, USA 10Centre de Genètica Mèdica i Molecular (EL and ES), Laboratori de Recerca Translacional, Institut Català d'Oncologia (CL); Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain 11Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA *Tel: +1 513 636 9469; Fax: +1 513 636 3549 EMBO Mol Med (2009)1:236-248https://doi.org/10.1002/emmm.200900027 PDFDownload PDF of article text and main figures. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Understanding the biological pathways critical for common neurofibromatosis type 1 (NF1) peripheral nerve tumours is essential, as there is a lack of tumour biomarkers, prognostic factors and therapeutics. We used gene expression profiling to define transcriptional changes between primary normal Schwann cells (n = 10), NF1-derived primary benign neurofibroma Schwann cells (NFSCs) (n = 22), malignant peripheral nerve sheath tumour (MPNST) cell lines (n = 13), benign neurofibromas (NF) (n = 26) and MPNST (n = 6). Dermal and plexiform NFs were indistinguishable. A prominent theme in the analysis was aberrant differentiation. NFs repressed gene programs normally active in Schwann cell precursors and immature Schwann cells. MPNST signatures strongly differed; genes up-regulated in sarcomas were significantly enriched for genes activated in neural crest cells. We validated the differential expression of 82 genes including the neural crest transcription factor SOX9 and SOX9 predicted targets. SOX9 immunoreactivity was robust in NF and MPSNT tissue sections and targeting SOX9 – strongly expressed in NF1-related tumours – caused MPNST cell death. SOX9 is a biomarker of NF and MPNST, and possibly a therapeutic target in NF1. The paper explained PROBLEM: Neurofibromatosis type 1 (NF1) is one of the most common inherited human diseases worldwide. Effective therapies are lacking. Peripheral nerve sheath tumours (neurofibromas) are the hallmark of NF1. They consist of benign dermal and plexiform subtypes, but plexiform neurofibroma can transform to malignant peripheral nerve sheath tumour (MPNST), a highly aggressive, life-threatening sarcoma. Neurofibromas are composed of multiple cell types, including Schwann cells, the pathogenic cell type of NF1. The molecular changes that drive tumourigenesis are largely unknown. RESULTS: The authors used DNA microarrays to profile the gene expression in normal Schwann cells, Schwann cells cultured from primary benign neurofibromas (dermal and plexiform subtypes), MPNST cell lines and solid tumours. It was found that neurofibromas repress gene programmes normally expressed in late-developing immature Schwann cells, while MPNSTs activate gene programmes normally expressed earlier in the development at the neural crest stage. Strong expression of the transcription factor SOX9 is seen in neurofibroma and MPNST tissue sections, while schwannomas show weak or absent expression. Synovial sarcomas, which may histologically mimic MPNST, are mainly negative. Reduction of SOX9 expression in MPNST cell lines causes cell death. IMPACT: SOX9 expression provides a biomarker of neurofibroma and MPNST. Therapeutics aimed at decreasing SOX9 expression or SOX9 transcriptional targets represent a strategy for killing MPNST cells. INTRODUCTION A genetic defect underlies NF1, which is inherited as an autosomal dominant trait affecting 1:3,000 humans (Rasmussen & Friedman, 2000). Analysis of progressive changes downstream of NF1 mutation has been complicated by the spectrum of clinical manifestations in NF1 patients and the diversity of cell types involved. The hallmark of NF1 is the development of peripheral nerve sheath tumours. At least 95% of NF1 patients have multiple dermal NFs, benign tumours that typically appear in adolescence (Rasmussen & Friedman, 2000). Approximately, 30% develop plexiform NFs that are larger, may cause significant morbidity, and can occur congenitally. Questions as fundamental as whether there are molecular differences between dermal and plexiform NF are to date unanswered. Differences between the types of NF are implied as a plexiform NF may transform to an MPNST, a life threatening sarcoma (Evans et al, 2002). The sequence of biological events driving MPNST formation is unknown. Beyond mutations in both copies of the NF1 tumour suppressor gene (Wimmer et al, 2006), few molecular alterations have been associated with NFs and/or MPNSTs. These alterations include the epidermal growth factor receptor (EGFR), detected in MPNST cell lines and in a subpopulation of NFSCs, as well as amplification of KIT, PDGFRA and PDGFRA mutations, detected in MPNSTs. Loss of tumour suppressor genes, including TP53, RB or INK4A, have been documented in NF1-associated MPNSTs but not NFs (reviewed in Carroll & Ratner, 2008). Dermal and plexiform NFs are composed of cell types present in normal nerves but in a disorganized form. Axon–Schwann cell contact, which regulates key aspects of normal Schwann cell function, is disrupted in NFs. NFSCs are found distant from axons in a collagen-rich extracellular matrix, admixed with mast cells and fibroblasts (Cichowski & Jacks, 2001). Methods were developed to purify normal human Schwann cells (NHSCs) and NFSCs (Serra et al, 2000). We hypothesized that comparing the gene expression in cultured Schwann cells could identify changes relevant to tumourigenesis because within NFs, only Schwann cells exhibit biallelic NF1 mutations (Serra et al, 2000). NFSCs also show elevated levels of Ras-guanosine triphosphate (GTP) (Sherman et al, 2000), consistent with neurofibromin functioning as a GTPase activating protein (GAP) that inactivates Ras (Le & Parada, 2007), and invade basement membranes and stimulate angiogenesis whereas normal Schwann cells do not (Sheela et al, 1990). Thus, while the data strongly support the view that Schwann cells are the crucial pathogenic cell type in NFs, the molecular changes in NFSCs that drive tumourigenesis are largely unknown. The critical period(s) in Schwann cell development at which an NF1 mutation results in NF and/or MPNST is also not clear (Carroll & Ratner, 2008; Le et al, 2009; Williams et al, 2008). Schwann cells originate from neural crest stem cells and develop into Schwann cell precursors, then immature Schwann cells and finally mature Schwann cells (Jessen & Mirsky, 2005). The SOX family of transcription factors is important for neural crest stem cell survival (Cheung et al, 2005); SOX10 is required for glial specification in the peripheral nervous system (Britsch et al, 2001). Analysing the expression of these genes might provide insight into the timing of tumourigenesis. Gene expression in NF1-associated tumours has been analysed by quantitative real time-polymerase chain reaction (qPCR) (Levy et al, 2004), subtractive hybridization (Holtkamp et al, 2004) and cDNA (Miller et al, 2003) and oligonucleotide (Levy et al, 2007; Miller et al, 2006) microarray analyses. Direct comparison of these studies is unfortunately limited due to the multiplicity of platforms and technical variability in sample processing among the different laboratories. To identify a molecular progression model for NF1 peripheral nerve tumourigenesis, we formed the NF1 microarray consortium and analysed primary tumour-derived Schwann cells, MPNST cell lines and NF1 solid tumours. RESULTS Creation of a comprehensive gene expression data set consisting of primary tumour-derived Schwann cells, MPNST cell lines and NF1 peripheral nerve tumours NF tissue samples contain NF1+/− and NF1−/− Schwann cells, fibroblasts, perineurial cells, endothelial cells and mast cells. To avoid this inherent variability and to describe gene expression changes that correspond to a single cell type, we used purified Schwann cells as the basis for our analysis. To ensure data quality, we minimized non-biological variability in sample batch processing by running samples from each experimental group in each processing batch. To minimize the technical variability, a single individual (AH) isolated RNA and we conducted microarray hybridization at a single site. We also hybridized a universal reference RNA in each processing batch along with 11 NF related RNAs as a technical control for batch-to-batch variation. Analysis after each processing batch assessed the power for statistical comparisons (Page et al, 2006). We also used power analysis as a futility analysis in the comparison of dermal and plexiform NFs to determine that a difference between the groups would not be detectable without a far larger sample size (at minimum, 5× more samples). Schwann cell culture transcription profiles distinguish benign from malignant NF1 tumours but fail to discriminate NF subtypes To discover gene expression programs that underlie the differences between cultured NHSCs, dermal and plexiform NFSCs (dNFSCs and pNFSCs, respectively) and MPNST cell lines, after referencing (see the Materials and Methods section), analysis of variance (ANOVA) identified 2,827 transcripts (FDR ≤ 0.001) as differentially expressed that we, then, subjected to two-way hierarchical tree clustering (Fig 1 and Table S1 of Supporting Information). Most MPNST cell lines display a unique transcriptional signature and cluster to the far right of the heat map, separately from benign NF-derived Schwann cells. Although we anticipated gene expression signatures that were unique to dNFSCs or pNFSCs, transcripts that passed the ANOVA failed to partition the two NF subtypes. Direct comparison of dNFSCs and pNFSCs also failed to identify a statistically significant signature. Instead, we observed two classes of NFSCs, with genes in Class 1 NFSCs (Fig 1; green bar beneath heat map) less up- or down-regulated than genes in Class 2 NFSCs (Fig 1; blue bar beneath heat map). Class type did not correlate with any known patient parameters or sample handling. Five principal patterns of gene expression were identified and genes were assigned to each using k-means clustering (clusters C1–C5; Fig 1 and Table S2 of Supporting Information; see Table S3 of Supporting Information for biological associations and Table S2 of Supporting Information for detailed cluster and biological association gene lists). Figure 1. Heat map of transcripts differentially expressed between cultured NHSCs and cultured dNFSCs, pNFSCs and MPNST cell lines. Two-way hierarchical clustering grouped samples as either NHSCs, mixed benign dNFSC and pNFSC or malignant tumour (MPNST) cell lines. Two classes of NFSCs are identifiable, with Class 1 NFSC (green bar beneath the heat map) expression levels attenuated relative to Class 2 NFSC (blue bar beneath the heat map) levels. Genes in clusters C1 and C4, which show decreased or increased expression in benign tumours, respectively, and opposite expression in MPNST cell lines (indicated with asterisks), are abundant in genes associated with cell cycle (AURKA, CDC25B, CDKN2A, CNAP1, INHBA, MCM7, PDGFB) and cell differentiation (ADAM12, ANGPTL4, BMP1, CHL1, IL11, INHBA, PPL, SERPINE2). The bar to the right of the heat map shows five clusters (C1–C5), corresponding to k-means functional clusters listed in Tables S2 and S3 of Supporting Information. Download figure Download PowerPoint Transcripts differentially expressed in NF1 tumour cell cultures share gene expression signatures with NF1 solid tumours Each cluster from Fig 1 was re-clustered across NHSCs, primary NFs and primary MPNSTs. We identified sub-cluster(s) that were similarly expressed across cell cultures and their respective solid tumour type. After assigning genes using k-means clustering (Fig 2; Table S5 of Supporting Information), we evaluated clusters C6–C11 to explore the potential biological significance of transcripts deregulated in both NF1 tumour cell cultures and solid tumours (Tables S5 and S6 of Supporting Information). Two-way hierarchical cluster analysis of the transcripts (n = 1,708; 1,108 unique genes) that were similarly expressed in cell cultures and solid tumours again failed to segregate dermal and plexiform NF tumours (Fig 2). The complete list of genes is shown in Table S4 of Supporting Information. Figure 2. Heat map of transcripts similarly expressed in NF1 cell cultures and tumours. Differentially expressed transcripts in NF1 peripheral nerve cell culture samples were filtered to identify genes with similar patterns of expression in solid tumours. A total of 1,708 transcripts (60%) were identified and clustered across NHSCs, dNFSCs, pNFSCs, MPNST cell lines (annotated as in Fig 1), and dNFs, pNFs and MPNSTs. The bar to the right of the heat map shows five clusters (C6–C11), corresponding to k-means functional clusters listed in Table S5 of Supporting Information. Download figure Download PowerPoint Analysis of functional enrichment for genes in clusters C6–C11 showed significant associations with nervous system development. We used GATACA1 to identify transcripts from each over-represented ontology or pathway in each cluster associated with nerve development and/or NF or MPNST. Genes in cluster C6 were associated with nervous system development and were down-regulated in most of the sample types (variably down-regulated in class 1 NFSCs and some NFs). Cluster C6 included EMP2, EPB41L3, GFAP, HLA-DQB1, KLK6, L1CAM, LGI1, MBP and NGFR. Genes in cluster C7 were associated with neurogenesis. Cluster C7 consisted of genes down-regulated in MPNST cell lines, MPNSTs and most of the NFs (variable in Class 2 NFSCs and some NFs) and included CDKN2A, CTSD, GJB1, GNAI2, HPCAL1, KNS2, MF12, NES and NFKB1. Genes in cluster C8 were associated with nervous system development. Cluster C8 exhibited decreased expression in most of the MPNST cell lines (variable in MPNSTs and class 2 NFSCs) and contained transcripts that included BCL2, BCL2L2, EDNRB, ERBB3, MPZ, PDGFA, PDGFB and S100β. Transcripts in cluster C9 were associated with morphogenesis and nervous system development. Genes in cluster C9 were up-regulated in MPNST cell lines and MPNSTs and included EN2, HGF, MDK, PAX6, SMAD3 and WT1. Transcripts in clusters C10 and C11 were associated with skeletal development, and C11 with morphogenesis. Genes in cluster C10, variably up-regulated in Class 1 NFSCs and up-regulated in all others, included APOD, CASP1, CD36, EGFR, KIT, LEPR, MME and SOCS3. Cluster C11 was composed of transcripts that were up-regulated in class 2 NFSCs, MPNST cell lines and MPNSTs (variable in class 1 NFSCs and NFs) and contained ADM, CAPN1, FBN2, IGFBP3, PDGFRA, PIAS3, PLAU, PTGES, PTGS2 and TFPI. Cluster C11 also included the neural crest markers TWIST1 and SOX9, and exhibited increased expression in all samples. Additional functional annotation categories for each cluster are shown in Tables S5 and S6 of Supporting Information. NF1 tumour cell culture and solid tumour expression patterns show broad dysregulation of genes activated in developing Schwann cells The high representation of genes associated with Schwann cell development in the NF1 tumour signature led us to compare the 1,708 gene signature (1,108 unique genes) to gene orthologues activated in migrating neural crest cells and two stages of Schwann cell development, Schwann cell precursor and immature Schwann cell, based on a published data set (Buchstaller et al, 2004) (Table 1). Strikingly, all down-regulated clusters (C6–C8) showed significant enrichment for gene orthologues activated in immature Schwann cells. Genes up-regulated in MPNST (cluster C9) demonstrated significant over-representation of gene orthologues activated in migrating neural crest cells. The repression of transcripts normally expressed late in Schwann cell development and activation of genes normally expressed early is consistent with significant over-representation of developmental themes identified in our functional analysis (see Tables S4 and S5 of Supporting Information). Table 1. NF-related peripheral nerve cell culture and tumour transcription patterns are enriched for genes regulated during Schwann cell development Cluster Expression pattern Unique genes Unique in 9,137 Migrating neural crest 2,033 of 9,137 unique genes Schwann cell precursor 778 of 9,137 unique genes Immature Schwann cell 1,421 of 9,137 unique genes Expect Observed Significance Expect Observed Significance Expect Observed Significance C6 Down in all, variable in class 1 NFSCs and some NFs 232 88 20 8 1.80E-03 7 12 8.53E-02 14 26 9.08E-04 C7 Down in all except class 1 NFSCs, variable in class 2 NFSCs and some NFs 321 133 30 22 1.16E-01 11 19 2.65E-02 21 34 2.42E-03 C8 Down in most MPNST cell lines, variable in MPNSTs and class 2 NFSCs 245 91 20 6 1.08E-04 8 6 7.04E-01 14 54 2.20E-16 C9 Up in MPNST cell lines and MPNST 175 69 15 31 2.84E-05 6 2 1.25E-01 11 7 2.46E-01 C10 Up in all, variable in class 1 NFSCs 90 46 10 5 7.41E-02 4 7 1.09E-01 7 10 2.26E-01 C11 Up class 2 NFSCs, MPNST cell lines and MPNSTs, variable in class 1 NFSCs and NFs 123 71 16 15 8.87E-01 6 10 1.29E-01 11 12 7.42E-01 Each of the k-means clusters identified in Fig 2 (C6–C11) was evaluated for over-representation of gene orthologues characteristic of three stages of Schwann cell development. We first generated orthologue gene lists for transcripts up-regulated in migrating neural crest, Schwann cell precursors and immature Schwann cells (Buchstaller et al, 2004). After correcting for redundant probe sets, lack of corresponding gene orthologues and platform-specific gene representation differences, Fisher's exact test was used to calculate the expected overlaps between k-means clusters and each of the orthologue gene lists. All down-regulated clusters (C6–C8) showed significant enrichment for gene orthologues activated late in Schwann cell development (i.e., immature Schwann cells). Up-regulated gene clusters characteristic of MPNST were C9, enriched for gene orthologues activated early in Schwann cell development (i.e., migrating neural crest) and C10, enriched for gene orthologues up-regulated in Schwann cell precursors. Gene orthologues activated in Schwann cell precursors but down-regulated in all samples except Class 1 NFSCs, variable in Class 2 NFSCs and variable in some NFs were also significantly over-represented in cluster C7. In cluster C11, we identified the neural crest markers TWIST1 and SOX9. TWIST1 inhibits MPNST cell chemotaxis (Miller et al, 2006). Many SOX family members are differentially expressed in NF1 samples relative to normal Schwann cells, including down-regulation of SOX5 (clusters C6 and C7), SOX2, SOX2OT, SOX8, SOX10 and SOX 13 (cluster C8) and up-regulation of SOX11 (cluster C9) and SOX9 (cluster C11). For technical and biological validation, we measured the expression of 82 genes in at least one sample from each sample type by qPCR. Differential expression of 41/82 genes was confirmed in all samples and 77/82 genes in at least 50% of the samples (Table S7 of Supporting Information). This confirmation rate is comparable to that reported in other studies. The entire data set is publicly available via Gene Expression Omnibus2 (Accession number GSE14038). SOX9 is over-expressed in NF1-derived peripheral nerve tumours SOX9 is a neural crest transcription factor required for stem cell survival (Cheung et al, 2005). Our microarray data show over-expression of SOX9 in all NF1 tumour samples, ranging from 1.5- to 137-fold on the microarray. Average SOX9 expression values were at le
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