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Integrative genomic approaches to identify
  biomarkers and therapeutic targets in NF1

                                  ...
“Any living cell carries with it the
   experiences of a billion years of
   experimentation by its ancestors.”

         ...
Principle
   the whole is greater than the sum of its parts

   Research goal
   ‣ develop and apply integrative genomic
 ...
Neurofibromatosis (NF)
  ‣ Set of autosomal dominant genetic disorders of the nervous system that
     cause tumors to for...
% patients affected
NF1 tumor subtypes
Dermal neurofibromas (dNF)
 ‣ Tumors that appear as multiple, firm rubbery         ...
NF1 tumor composition is complex

Tumors contain all the cell types of normal
peripheral nerves, including:               ...
Two types of Schwann cells
Myelin: electrically insulating material (glycolipd and protein) produced by
Schwann cells that...
NF1 encodes neurofibromin, a GTPase activating protein
                                                         RAS activa...
Very little is known about the pathways that drive NF1
tumor progression
                                         Benign  ...
Study: Biological pathways that drive NF1 tumor progression

 Research objectives:
 1. Gain insight into the biological pa...
Profiling gene expression using Affymetrix DNA microarrays

 DNA microarray
 technology:
 Enables researchers
 to simultan...
Analyze gene expression data from DNA microarrays by
  clustering

              What is clustering?



    ‣ Technique us...
Two common types of clustering methods
 ‣ Hierarchical clustering: subdivides each cluster into smaller clusters,
   formi...
Robust Multi-array Average (RMA)

Robust Multi-array Average (RMA): an algorithm for normalizing and
summarizing probe-lev...
Affymetrix probe specificity and annotation issues

Chip definition file (CDF) and annotation library updates only affect ...
Analysis of Variance (ANOVA)
   Analysis of Variance (ANOVA): a statistical technique for helping to
   infer whether ther...
Hypothesis testing and error
‣ P-value was invented for testing individual hypotheses
‣ Problem with data collected by DNA...
Integrate genomic data from NF1 tumor-derived cell
culture samples and tumor samples

   Normal and NF-derived Schwann cel...
Genes differentially expressed in cultured Schwann cells
                                                                 ...
Genes similarly deregulated in NF1 cell cultures & human tumors

  Normal and benign Schwann cells                    dNF ...
Four stages of Schwann cell
     development




       Stage 1             Stage 2                        Stage 3        ...
Three activated
gene signatures
                                                                                          ...
Neurofibromas and MPNSTs have gene signatures
                                                  characteristic of differen...
Results are consistent with recently published data
Developed a mouse model:
DhhCre; Nf1 flox/flox                        ...
DhhCre; Nf1 flox/flox mice die by 13 months

                         100


                         75
      Percent surv...
Mice have dermal- and plexiform-like neurofibromas
                                                                       ...
SOX9
 ‣ Encodes a high-mobility group box-containing transcription factor
 ‣ Modulates glial specification and differentia...
Immunohistochemical analysis of SOX9 protein expression




                   42 NF1 tumor sections (10 independent)



 ...
Test a role for SOX9 in tumor survival
 ‣ Use shRNA to reduce SOX9 expression
 ‣ Infected cells with a lentivirus-expressi...
Test MPNST cells for survival
‣ Use shRNA to reduce SOX9 expression
‣ Infected cells with a lentivirus-expressing shSOX9 o...
Summary

    ‣ Gene expression distinguishes benign and malignant NF1 Schwann
       cell cultures and solid tumors

    ‣...
Model of NF1 tumor formation


                                                                                           ...
Study: Leverage mouse NF1 models for translation to
human therapeutics

   Onging research objectives:
   1. Identify core...
Evaluate three classes of transgenic mouse and human
samples

           Transgenic mice                                  ...
Method to identify similarly expressed gene orthologs
 conserved between mouse and human
                                 ...
Gene orthologs similarly expressed between mouse and human tumors
                                                        ...
Gene signatures shared or unique between NF1 tumors
and GEM NF1 models

           Similar expression patterns            ...
Species-specific gene signatures


        Human-specific expression patterns                Mouse-specific expression pat...
Perform comparative enrichment analysis on expression
signatures
(ToppCluster facilitates co-functional enrichment analysi...
Structure based on the force-directed layout paradigm
yFiles (Java Graph Layout and Visualization Library) Organic Algorit...
HS unchanged, MM activated
HS activated, MM repressed                                        Four “Feature Domains”
Cell-c...
Gene orthologs and biological themes shared between mouse and human
                                                      ...
PTPRZ1
  ‣ Encodes a protein tyrosine phosphatase (receptor type Z)
  ‣ Expression is restricted to the nervous system (Le...
Genetic interaction network analysis
                                                          RAS activation stimulates d...
Genetic interaction network analysis


                                                                       Nodes are co...
Genetic interaction network analysis

                                                                All direct interacti...
All direct interactions
Genetic interaction network analysis                                   up-regulated in neurofibrom...
Gene is over-expressed in a subset of mesenchymal tumors
  that are aggressive
                                           ...
Expression signature for the gene in human tumors

                                                                       ...
Cancer drug is cytotoxic against 5 MPNST cell lines
(dose at days 2 and 4 relative to day 0)
       % Control




        ...
Summary
    ‣ Effective method for simultaneous comparison of transcriptional
       programs between mouse models and hum...
Mouse models                                   Human
Cincinnati, OH – CCHMC                         Cincinnati, OH – CCHMC...
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Integrative Genomic Approaches to Identify Biomarkers and Therapeutic Targets in NF1

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Integrative Genomic Approaches to Identify Biomarkers and Therapeutic Targets in NF1

  1. 1. Integrative genomic approaches to identify biomarkers and therapeutic targets in NF1 Walter J. Jessen, Ph.D. Cincinnati Children’s Hospital Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  2. 2. “Any living cell carries with it the experiences of a billion years of experimentation by its ancestors.” Max Delbrück, theoretical physicist Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  3. 3. Principle the whole is greater than the sum of its parts Research goal ‣ develop and apply integrative genomic approaches to better organize and evaluate high-throughput genomic data ‣ effectively interpret the results and achieve a greater understanding of the signals and mechanisms regulating disease development and progression Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  4. 4. Neurofibromatosis (NF) ‣ Set of autosomal dominant genetic disorders of the nervous system that cause tumors to form on peripheral nerves ‣ Approximately 50% of those affected have a prior family history of NF ‣ The other 50% are a result of spontaneous genetic mutation ‣ Although most tumors are benign, can cause serious morbidity Two major forms of NF: - Type 1 (NF1) von Recklinghausen NF or Peripheral NF ‣ Most common hereditary tumor predisposition syndrome ‣ Occurs in 1:3500 births ‣ Tumors (neurofibromas) form on peripheral nerves - Type 2 (NF2) Bilateral Acoustic NF ‣ Occurs in 1:40,000 births ‣ Tumors (schwannomas) form on cranial and spinal nerves Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  5. 5. % patients affected NF1 tumor subtypes Dermal neurofibromas (dNF) ‣ Tumors that appear as multiple, firm rubbery 95% bumps of varying size on the skin ‣ Benign, but a significant source of morbidity Plexiform neurofibromas (pNF) ‣ Associated with major nerve trunks ‣ Expand within the perineurium to displace 25% surrounding tissue ‣ Capable of becoming malignant Malignant peripheral nerve sheath tumors (MPNST) ‣ Highly aggressive soft tissue sarcomas 10 – 13% ‣ Localized recurrence, chemo-resistance, frequent metastasis ‣ Median age of onset: 26, five year survival: 34% No effective treatments exist for either neurofibroma or MPNST Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  6. 6. NF1 tumor composition is complex Tumors contain all the cell types of normal peripheral nerves, including: Neurofibroma ‣ Schwann cells (ensheath axons) ‣ Fibroblasts (give rise to connective tissue) ‣ Mast cells (wound healing) Nerve ‣ Axons (nerve fiber) Lines of evidence 1. LOH is observed in NF1-derived Schwann cells but not fibroblasts 2. NF1-derived Schwann cells are invasive 3. Mice with Schwann cell lineage-specific ablation of Nf1 develop tumors Schwann cells are the pathogenic cell type in peripheral nerve tumors Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  7. 7. Two types of Schwann cells Myelin: electrically insulating material (glycolipd and protein) produced by Schwann cells that ensheathes axons; increases speed of electrical impulses A. Myelinated Axon B. Unmyelinated Axons Ax S S Schwann cell nucleus S Ax Axon Ax myelin sheath Corfas et al., Mechanisms and roles of axon-Schwann cell interactions. J Neurosci. 2004 Oct 20;24(42):9250-60. Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  8. 8. NF1 encodes neurofibromin, a GTPase activating protein RAS activation stimulates downstream signaling pathways Reduced NF1 expression results in increased Ras activation Downward J, Cancer: A tumour gene's fatal flaws. Nature. 2009 Nov 5;462(7269):44-5. Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  9. 9. Very little is known about the pathways that drive NF1 tumor progression Benign Malignant Dermal neurofibroma Normal Schwann cell NF1-associated Plexiform neurofibroma MPNST Transformation EGFR p53 PDGFRA Growth factor Rb NF1 mutation receptors KIT Tumor CDKN2A suppressor (p16) S6kinase genes H-, K-, N-Ras Signaling cAMP CDKN2D (p19) Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  10. 10. Study: Biological pathways that drive NF1 tumor progression Research objectives: 1. Gain insight into the biological pathways and processes that drive NF1 tumor formation and transformation 2. Identify molecular differences between tumor subtypes - dermal vs. plexiform - benign vs. malignant 3. Provide candidate genes for diagnostics and treatment strategies Hypothesis: purified Schwann cells from NF1 tumors will continue to express tumor gene programs in culture INTEGRATE Human cell culture, human tumor, mouse Schwann cell development Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  11. 11. Profiling gene expression using Affymetrix DNA microarrays DNA microarray technology: Enables researchers to simultaneously survey the expression of a large number of genes. Microarray or GeneChip: A tool used to analyze gene expression, consisting of a small glass slide containing samples of many genes arranged in a regular pattern. Samples: Sets of probes which represent gene transcripts Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  12. 12. Analyze gene expression data from DNA microarrays by clustering What is clustering? ‣ Technique used to group similar genes and samples together ‣ Allows for the identification of potentially meaningful relationships ‣ Genes that have similar patterns of expression are grouped together in clusters ‣ Cluster genes are likely to be co-regulated or part of the same biological process or pathway ‣ Statistics are used to identify over-representation or enrichment of biological processes or pathways in gene clusters Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  13. 13. Two common types of clustering methods ‣ Hierarchical clustering: subdivides each cluster into smaller clusters, forming a dendrogram (tree-shaped data structure) Algorithm summary 1. Place all points into their own clusters 2. While there is more than one cluster, merge the closest pair of clusters Weakness: doesn’t really produce clusters, user must decide where to split the tree into groups ‣ K-means clustering: subdivides data into a predetermined number of clusters without any implied hierarchical relationship between clusters Algorithm summary 1. Assign all points to a cluster at random 2. Repeat until stable: a. Compute the centroid for each cluster b. Reassign each point to the nearest centroid Weakness: must choose k parameter in advance; sensitive to outliers, which can distort centroid positions ➡ Comparative studies have shown that K-means outperforms hierarchical clustering on expression data Walter Jessen Integrative genomic approaches to identify (Gibbons et al., 2002; Datta and Datta, 2003; Costa et al., 2004) Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  14. 14. Robust Multi-array Average (RMA) Robust Multi-array Average (RMA): an algorithm for normalizing and summarizing probe-level intensity measurements from DNA microarrays The normalization procedure is intended to make the intensity distributions identical across arrays Boxplot and histogram of signal Boxplot and histogram of signal intensities before RMA pre-processing intensities after RMA pre-processing R: language and environment for Walter Jessen computing and graphics statistical Integrative genomic al. Evolving gene/transcript definitions significantly alter Dai et approaches to identify the Bioconductor: open source software interpretation of GeneChip data. Nucleic Acids Res. 2005 Nov 10;33(20):e175. Walter@WalterJessen.com analysisbiomarkers and therapeutic targets in NF1 project for genomic data
  15. 15. Affymetrix probe specificity and annotation issues Chip definition file (CDF) and annotation library updates only affect the qualitative attributes of probe sets without any degree of control on the effective matching of probes and genome sequences Novel system for associating probes with genomic information; custom defined probes meet the following criteria: 1. Probes must have only one perfect match on the genomic sequence 2. Because EST sequences are subject to a relatively high error rate, probes must perfectly match a genomic region that can be aligned with mRNA/EST sequences in the UniGene database 3. Probes must target the same transcript strand 4. Updated probe sets must contain a minimum of 3 probes 5. Transcript annotation is based on updated reference sequences (RefSeq) Reorganize probes and use updated transcript definitions to increase gene detection confidence and identification R: language and environment for Walter Jessen computing and graphics statistical Integrative genomic al. Evolving gene/transcript definitions significantly alter Dai et approaches to identify the Bioconductor: open source software interpretation of GeneChip data. Nucleic Acids Res. 2005 Nov 10;33(20):e175. Walter@WalterJessen.com analysisbiomarkers and therapeutic targets in NF1 project for genomic data
  16. 16. Analysis of Variance (ANOVA) Analysis of Variance (ANOVA): a statistical technique for helping to infer whether there are real differences between the means of three or more groups in a population based on sample data In general, an ANOVA: ‣ measures the overall variation within a group ‣ finds the variation between group means ‣ combines these to calculate a single test statistic ‣ uses this to carry out a hypothesis test Assumptions with an ANOVA: 1. observations are independent 2. dependent variable is normally distributed 3. homogeneity of variances ➡ The advantage of using ANOVA rather than making multiple comparisons using individual t-tests is that it reduces the probability of a false positive (type-I error) Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  17. 17. Hypothesis testing and error ‣ P-value was invented for testing individual hypotheses ‣ Problem with data collected by DNA microarrays, usually involves testing thousands of hypotheses simultaneously ‣ The False Discovery Rate (FDR) is a statistical method used for testing multiple hypotheses that corrects for multiple comparisons ‣ False Discovery Rate (FDR): the expected proportion of false positives (type I errors) among the results declared significant example: 1,000 genes at an FDR = 0.05 - expect a maximum of 50 genes to be false positives (1000 x 0.05) - no such interpretation exists for P-value ‣ At least four factors determine FDR characteristics for a microarray study (Pawitan et al., 2005) 1. proportion of truly differentially expressed genes 2. distribution of the true differences 3. measurement variability 4. sample size ➡ Benjamini and Hochberg FDR Walter Jessen Integrative Benjamini and Hochberg, Controlling the false discovery rate: a practical and genomic approaches to identify Walter@WalterJessen.com biomarkerspowerful approach to multiple testing. J. Roy. Statist. Soc. Ser. 1995, B 57 289-300. and therapeutic targets in NF1
  18. 18. Integrate genomic data from NF1 tumor-derived cell culture samples and tumor samples Normal and NF-derived Schwann cells Human tumors # samples # samples NHSC Normal human Schwann cells 10 dNF Dermal NF 13 dNFSC Dermal NF Schwann cells 11 pNF Plexiform NF 13 pNFSC Plexiform NF Schwann cells 11 MPNST MPNST 6 MPNST cell MPNST cell lines 13 Analysis strategy: 1. Identify genes differentially expressed in cultured Schwann cells 2. Identify genes similarly deregulated in NF1 cell cultures & human tumors Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  19. 19. Genes differentially expressed in cultured Schwann cells Principle patterns Statistical test: ANOVA, FDR ≤ 0.001 Genes upregluated in MPNST cell lines Genes upregluated in NFSC Genes upregluated in all Genes downregulated in MPNST cell lines Genes downregulated in MPNST cell lines and class 2 NFSC Two classes of NFSC Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com Miller*, Jessen* et al., Integrative genomic analyses of neurofibromatosis tumors identify biomarkers and therapeutic targets in NF1 SOX9 as biomarker and survival gene. EMBO Mol Med 2009 July, 1(4);236-248.
  20. 20. Genes similarly deregulated in NF1 cell cultures & human tumors Normal and benign Schwann cells dNF and pNF MPNST Functional enrichment ‣ Cytoskeletal organization and Cell culture Tumors biogenesis ‣Glycoprotein metabolism ‣Nervous system development ‣ Neurogenesis ‣ Sphingolipid metabolism ‣ Cell adhesion ‣Nervous system development ‣ Chromosome organization and biogenesis ‣ Extracellular matrix organization and biogenesis Dermal and plexiform ‣Nervous system development neurofibromas mix together ‣ Cell adhesion ‣ JAK-STAT cascade ‣ Skeletal development ‣ Cell adhesion ‣Morphogenesis ‣ WNT receptor signaling pathway Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com Miller*, Jessen* et al., Integrative genomic analyses of neurofibromatosis tumors identify biomarkers and therapeutic targets in NF1 SOX9 as biomarker and survival gene. EMBO Mol Med 2009 July, 1(4);236-248.
  21. 21. Four stages of Schwann cell development Stage 1 Stage 2 Stage 3 Stage 4 Buchstaller et al. Efficient isolation and gene expression profiling of small numbers of neural crest stem cells and developing Schwann cells. J Neurosci. 2004 Mar 10;24(10):2357-65. Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  22. 22. Three activated gene signatures Immature Schwann cell of Schwann cell gene signature development 4,750 probe sets Neural crest cell gene signature Schwann cell precursor gene signature E9 E12 E14 E16 E18 P0 E12 E14 E16 Statistical test: Compare genes to Walter Jessen Integrative genomic approaches to identify ANOVA, FDR ≤ 0.2 clusters C6 – C11 Walter@WalterJessen.com biomarkers and therapeutic targets in NF1 Stage 1 Stage 2 Stage 3
  23. 23. Neurofibromas and MPNSTs have gene signatures characteristic of different stages of Schwann cell development Stage 1 Stage 2 Stage 3 Genes expressed in NF1 cell cultures and tumors Boxes in red (up-regulated) or blue (down-regulated) are statistically significant Walter Jessen Integrative genomic approaches to identify Miller*, Jessen* et al., Integrative genomic analyses of neurofibromatosis tumors identify Walter@WalterJessen.com biomarkers and therapeutic targets inEMBO Mol Med 2009 July, 1(4);236-248. SOX9 as biomarker and survival gene. NF1
  24. 24. Results are consistent with recently published data Developed a mouse model: DhhCre; Nf1 flox/flox E18.5 Jianqiang Wu E12.5 E8.5 Stage 1 Stage 2 Stage 3 Stage 4 Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  25. 25. DhhCre; Nf1 flox/flox mice die by 13 months 100 75 Percent survival 50 Nf1 flox/flox; DhhCre (n=28) Nf1 flox/+; DhhCre (n=22) Nf1 flox/flox (n=10) 25 Nf1 flox/+ (n=8) 0 0 2 4 6 8 10 12 14 Months Jianqiang Wu Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  26. 26. Mice have dermal- and plexiform-like neurofibromas Human tumors DhhCre; Nf1 fl/fl mouse model Dermal neurofibromas DhhCre; Nf1 flox/flox mice show symptoms of tumor development as early as 5½ months of age Normal mouse Plexiform neurofibromas Bioinformatics and biology suggest NF1 loss later in Schwann cell development gives rise to neurofibromas Jianqiang Wu Walter Jessen Integrative genomic approaches to identify Wu et al., Plexiform and dermal neurofibromas and pigmentation are caused by Nf1 Walter@WalterJessen.com biomarkers and desert hedgehog-expressing cells. Cancer Cell. 2008 Feb;13(2):105-16. loss in therapeutic targets in NF1
  27. 27. SOX9 ‣ Encodes a high-mobility group box-containing transcription factor ‣ Modulates glial specification and differentiation in the peripheral nervous system and spinal cord (Kordes et al., 2005) ‣ Regulates neural crest stem cell survival (Cheung et al., 2005) Schwann cell culture Human tumor Fold change Fold change Fold change Fold change Fold change Fold change NHSC to dNFSC NHSC to pNFSC NHSC to MPNST cell lines NHSC to dNF NHSC to pNF NHSC to MPNST 9.72 7.76 46.46 27.97 28.08 63.06 Perform immunohistochemistry on tumor sections to evaluate protein expression Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  28. 28. Immunohistochemical analysis of SOX9 protein expression 42 NF1 tumor sections (10 independent) SOX9 is a biomarker for NF1 Brown = SOX9+ Miller*, Jessen* et al., Integrative genomic analyses of neurofibromatosis tumors identify Anat Stemmer-Rachamimov SOX9 as biomarker and survival gene. EMBO Mol Med 2009 July, 1(4);236-248. Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  29. 29. Test a role for SOX9 in tumor survival ‣ Use shRNA to reduce SOX9 expression ‣ Infected cells with a lentivirus-expressing shSOX9 or shGFP control ‣ Plated 7 days post-selection in puromycin, measured survival (MTS) ‣ Plated 3 days post-selection in puromycin, counted cells Neurofibroma Schwann cells Corresponding phase MPNST cells Corresponding phase contrast images contrast images p ≤ 0.05 * Miller*, Jessen* et al., Integrative genomic analyses of neurofibromatosis tumors identify Shyra Miller SOX9 as biomarker and survival gene. EMBO Mol Med 2009 July, 1(4);236-248. Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  30. 30. Test MPNST cells for survival ‣ Use shRNA to reduce SOX9 expression ‣ Infected cells with a lentivirus-expressing shSOX9 or shGFP control ‣ Plated 1–4 days post-selection in puromycin, measured survival (MTS) ‣ Plated 3 days post-selection in puromycin, assayed for apoptosis MPNST cells p ≤ 0.002 SOX9 is a survival gene for NF1 and a potential therapeutic target Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  31. 31. Summary ‣ Gene expression distinguishes benign and malignant NF1 Schwann cell cultures and solid tumors ‣ Gene expression fails to distinguish dermal and plexiform neurofibroma subtypes ‣ NF1 Schwann cell culture and tumor transcription patterns are enriched for genes activated during Schwann cell development ‣ SOX9 is biomarker and survival gene for NF1 ‣ Reduction in SOX9 expression kills MPNST cells Human cell culture, human tumor, mouse cell development Identify enrichment of developmental programs in NF1 tumors Miller*, Jessen* et al., Integrative genomic analyses of neurofibromatosis tumors identify SOX9 as biomarker and survival gene. EMBO Mol Med 2009 July, 1(4);236-248. Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  32. 32. Model of NF1 tumor formation Mature Schwann cells Neural Crest Schwann cell Immature Stage 4 Cell precursors Schwann cells Stage 1 Stage 2 Stage 3 Miller*, Jessen* et al., Integrative genomic analyses of neurofibromatosis tumors identify SOX9 as biomarker and survival gene. EMBO Mol Med 2009 July, 1(4);236-248. Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  33. 33. Study: Leverage mouse NF1 models for translation to human therapeutics Onging research objectives: 1. Identify core biological processes and pathways for tumorigenesis and malignancy that are conserved between mouse and human 2. Translate findings from mouse NF1 models to human therapeutics Hypothesis: there are biological processes and pathways similarly changed in human NF1 tumors and tumors from mouse models of NF1 INTEGRATE Mouse tumor, human tumor Walter Jessen Integrative genomic approaches Walter.Jessen@cchmc.org to peripheral nerve tumorigenesis
  34. 34. Evaluate three classes of transgenic mouse and human samples Transgenic mice Human # samples of # samples each genotype Control nerve 5–5–5 Normal nerve 3 Neurofibroma 4–7–4 Neurofibroma 26 MPNST 3–3–5–3–4 MPNST 6 ‣ Each data set is referenced to control/normal nerve ‣ Evaluate gene signatures that are shared across tumor subtypes for each species Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  35. 35. Method to identify similarly expressed gene orthologs conserved between mouse and human Human Mouse Identify genes ANOVA (FDR ≤ 0.05) ANOVA (FDR ≤ 0.05) statistically different Nerve vs. NF vs. MPNST Control nerve vs. NF vs. MPNST integrate, identify orthologous genes Human Mouse Human Mouse Filter for genes 398 414 similar in neurofibroma UP UP DOWN DOWN in 80% of samples >1.2 in 80% of samples >1.2 in 80% of samples <0.8 in 80% of samples <0.8 Human Mouse Human Mouse Filter for genes 1,016 758 similar in MPNST UP UP DOWN DOWN in 80% of samples >1.2 in 80% of samples >1.2 in 80% of samples <0.8 in 80% of samples <0.8 2,212 orthologs similarly expressed Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  36. 36. Gene orthologs similarly expressed between mouse and human tumors Functional enrichment Transgenic mice Human Neurofibroma ‣ Axonogenesis ‣ Induction of apoptosis ‣ Negative regulation of MAP kinase activity ‣ Regulation of neurotransmitter levels ‣ Actomyosin structure and organization 2,212 Transcripts ‣ Negative regulation of cell cycle progression ‣ Peripheral nervous system development MPNST ‣ Apoptosis ‣ Negative regulation of MAP kinase activity ‣ Phosphoinositide- mediated signaling ‣ Regulation of mitosis ‣ Axon ensheathment ‣ Axonogenesis ‣ Catecholamine metabolism C1 C2 C3 C4 ‣ Peripheral nervous Statistical test: system development ANOVA, FDR ≤ 0.05 Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  37. 37. Gene signatures shared or unique between NF1 tumors and GEM NF1 models Similar expression patterns Contrasting expression patterns Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  38. 38. Species-specific gene signatures Human-specific expression patterns Mouse-specific expression patterns Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  39. 39. Perform comparative enrichment analysis on expression signatures (ToppCluster facilitates co-functional enrichment analysis of multiple gene signatures) ToppGene: uses cluster assignment as a classification parameter and the Gene Set Enrichment Algorithm to identify significant gene set over-representation of several features: gene ontologies, pathways, co-expression, gene-disease, gene-drug, mouse and human phenotypes, microRNAs, cytobands and transcription factor binding site (TFBS). http://toppcluster.cchmc.org/ 17 clusters C11 – C27 ToppGene: FDR ≤ 0.05 Generates relationships in high-dimensional space, visualize interaction network using the open source bioinformatics software platform Cytoscape. Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  40. 40. Structure based on the force-directed layout paradigm yFiles (Java Graph Layout and Visualization Library) Organic Algorithm Clusters Gene Ontology Pathway TFBS Cytoband Protein domain Drug Gene sets (disease associations) Nodes: 2,653 Edges: 7,938 Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  41. 41. HS unchanged, MM activated HS activated, MM repressed Four “Feature Domains” Cell-cell signaling Glutathione metabolism GABA-B receptor signaling Potassium/calcium transport Shared repression Small GTPase mediated signal Cell-cell signaling transduction Lipid metabolism Synaptic vesicle trafficking Myelination Nervous system development Shared activation Apoptosis Cell cycle control Cell proliferation Regulation of MAP kinase activity HS unchanged/repressed, MM activated Walter Jessen Integrative genomic approaches to identify Angiogenesis, Apoptosis, Immune response, Walter@WalterJessen.com biomarkers and therapeutic targets in NF1 transduction Note: only ontologies and pathways are listed Ras protein signal
  42. 42. Gene orthologs and biological themes shared between mouse and human Functional enrichment Transgenic mice Human Neurofibroma ‣ Axonogenesis ‣ Induction of apoptosis ‣ Negative regulation of MAP kinase activity ‣ Regulation of neurotransmitter levels ‣ Actomyosin structure and organization 2,212 Transcripts ‣ Negative regulation of cell cycle progression ‣ Peripheral nervous system development MPNST ‣ Apoptosis ‣ Negative regulation of MAP kinase activity ‣ Phosphoinositide- mediated signaling ‣ Regulation of mitosis ‣ Axon ensheathment ‣ Axonogenesis ‣ Catecholamine metabolism C1 C2 C3 C4 ‣ Peripheral nervous Statistical test: system development ANOVA, FDR ≤ 0.05 Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  43. 43. PTPRZ1 ‣ Encodes a protein tyrosine phosphatase (receptor type Z) ‣ Expression is restricted to the nervous system (Levy et al., 1993) ‣ Plays a critical role in functional recovery from demyelinating lesions (Harroch et al., 2002) ‣ In the top 100 genes discriminating MPNST from 13 other soft tissue sarcomas (Francis et al., 2007) Transgenic mice Human Fold change Fold change Fold change Fold change Controls to NF Controls to MPNST Nerve to NF Nerve to MPNST 13.22 7.77 2.56 -2.26 Expression profile suggests PTPRZ1 could be important for tumorigenesis Use PTPRZ1 to select orthologs that have a similar Walter Jessen expression profile and evaluate genetic interactions Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  44. 44. Genetic interaction network analysis RAS activation stimulates downstream signaling pathways Hypothesis: transcripts having a similar pattern of expression as PTPRZ1 and interacting with genes in the MAP kinase pathway will include critical regulators of survival in NF1 Analysis strategy: 1. Identify the top 100 gene orthologs that correlate and anti-correlate with PTPRZ1 2. Add transcripts from clusters C1 and C3 associated with Negative regulation of MAP kinase activity 3. Add ERK genes (MAPK1, MAPK3, MAPK6, MAPK7, MAPK12) 4. Identify genetic interactions, removing those entities that don’t have connections Downward J, Cancer: A tumour gene's fatal flaws. Nature. 2009 Nov 5;462(7269):44-5. Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  45. 45. Genetic interaction network analysis Nodes are colored according to the degree of fold change from human nerve to neurofibroma Orange: ERK/MAP kinase genes Direct interaction Indirect interaction Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  46. 46. Genetic interaction network analysis All direct interactions ‣ Up-regulated gene targeted by a up-regulated in neurofibroma currently used cancer drug ‣ Directly interacts with a number of genes highly up-regulated in human neurofibroma - c-Kit - beta-catenin - breast cancer anti-estrogen resistance 1 - p21 protein (Cdc42/Rac)- Genes associated activated kinase 2 with cell death, - arrestin beta 1 neurological disorders, cell proliferation and survival Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  47. 47. All direct interactions Genetic interaction network analysis up-regulated in neurofibroma ‣ Move one step further down the interaction pathway, number of pivotal genes in critical signaling pathways ‣ Two genes have been targeted therapeutically: KIT and EGFR ‣ Data suggests that the gene is a potential promoter of malignant transformation in NF1 Pivotal genes in critical signaling pathways Akt CDKN2A (p16) HIF1A NFkB1 VEGFA Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  48. 48. Gene is over-expressed in a subset of mesenchymal tumors that are aggressive MPNST (4) Dedifferentiated Chondrosarcoma (3) Myxoid Liposarcoma (6) Alveolar Rhabdomyosarcoma (4) Desmoid Fibromatosis (5) Embryonal Rhabdomyosarcoma (3) Monophasic Synovial Sarcoma (10) Neurofibroma (4) ‣ Walter mesenchymal 19 Jessen tumor subtypes approaches to identifyal., A molecular map of mesenchymal tumors. Integrative genomic Henderson et Walter@WalterJessen.com biomarkers and therapeutic targets in NF1 2005;6(9):R76. Epub 2005 Aug 26. Genome Biol.
  49. 49. Expression signature for the gene in human tumors Functional enrichment ‣ DNA repair ‣Ensheathment of neurons ‣Integrin-mediated signaling ‣ Mitotic cell cycle 854 Transcripts ‣Ras protein signal transduction ‣ Vesicle-mediated transport Statistical test: ANOVA, FDR ≤ 0.05 7,174 Gene signature Neurofibroma MPNST 854 Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  50. 50. Cancer drug is cytotoxic against 5 MPNST cell lines (dose at days 2 and 4 relative to day 0) % Control [drug] nM Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  51. 51. Summary ‣ Effective method for simultaneous comparison of transcriptional programs between mouse models and human tumors ‣ Human NF1 tumors and mouse NF1 model tumors share activation of genes associated with negative regulation of MAP kinase activity and repression of genes associated with peripheral nervous system development ‣ Genes down-regulated in human NF1 tumors but up-regulated in mouse NF1 models are associated with Ras protein signal transduction and immune response ‣ Use gene interaction network analysis to identify a gene that is a potential promoter of malignant progression in NF1 and a potential therapeutic target Mouse tumor, human tumor Cross-species profiling, genetic network analysis Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1
  52. 52. Mouse models Human Cincinnati, OH – CCHMC Cincinnati, OH – CCHMC Nancy Ratner, Jianqiang Wu, Tilat Rizvi Nancy Ratner, Shrya Miller, Atira Hardiman Paris, France – Fondation Jean Dausset Boston, MA – MGH/Harvard Marco Giovannini, Jan Manent Anat Stemmer-Rachamimov Gainseville, FL – University of Florida Bioinformatics/Biostatistics Margaret Wallace Cincinnati, OH – CCHMC Bruce Aronow, Walter Jessen Barcelona, Spain – LʼHospitalet de Llobregat Concepcion Lazaro, Eduard Serra Birmingham, AL – University of Alabama Grier Page, Tapan Mehta Funding DOD: W81XWH-04-1-0273 NIH: T32 HL07382-30 Walter Jessen Integrative genomic approaches to identify Walter@WalterJessen.com biomarkers and therapeutic targets in NF1

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