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Nalan Gokgoz, Taiqiang Yan, Michelle Ghert, Mona Gill, Shelley B Bull, Robert S Bell, Jay S Wunder, Irene L Andrulis

A GENOME-WIDE APPROACH TO PREDICT OUTCOME IN OSTEOSARCOMA . Nalan Gokgoz, Taiqiang Yan, Michelle Ghert, Mona Gill, Shelley B Bull, Robert S Bell, Jay S Wunder, Irene L Andrulis Mount Sinai Hospital and Samuel Lunenfeld Research Institute  Toronto, Ontario, Canada. OSTEOSARCOMA.

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Nalan Gokgoz, Taiqiang Yan, Michelle Ghert, Mona Gill, Shelley B Bull, Robert S Bell, Jay S Wunder, Irene L Andrulis

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  1. A GENOME-WIDE APPROACH TO PREDICT OUTCOME IN OSTEOSARCOMA Nalan Gokgoz, Taiqiang Yan, Michelle Ghert, Mona Gill,Shelley B Bull, Robert S Bell, Jay S Wunder, Irene L Andrulis Mount Sinai Hospital and Samuel Lunenfeld Research Institute  Toronto, Ontario, Canada

  2. OSTEOSARCOMA • Treatment involves (neo)adjuvant chemotherapy and wide surgical resection • Patients without Metastases at Diagnosis: • 5 year disease-free survival 50-78% • Patients with Metastases at Diagnosis: • 5 year disease-free survival 10-20%. • Few accurate clinical predictors of outcome • Molecular markers ( e.g. p53, RB, cdk4,SAS): not prognostic

  3. An Emerging Molecular Paradigm • Prediction of disease outcome. Analysis of global gene expression • Classification of OSA tumors Microarray Analysis

  4. PATIENTS A B A1 A2

  5. TUMOR SAMPLES • 63 fresh frozen, primary,high-grade intramedullary osteosarcoma samples • Tumor specimens from open biopsies obtained prior to chemotherapy. • Tumor specimen chosen based on frozen section histological analysis. • Minimum follow-up 4years or metastasis

  6. Clinical Charactersitics of Patients Presenting with Non-metastatic OSA

  7. Microarray Analysis • 19K cDNA microarrays Image Acquisition : Axon Scanner Spot Analysis : GenePix Pro5 Data Storage: IobianTM Gene Traffic • Statistical Analysis Quality Control Reproducibility

  8. Aim 1: Outcome of the Patients Presenting with no Metastases No Metastases 4 years post Dxvs Metastases within 4 years Dx 18981 cDNAs T-statistic p<0.001 (BrB Array Tools) n=50 genes for tumor classification/clustering

  9. 50 Most Significant Genes No Mets 4 yrs post Dx. Mets within 4 yrs Dx.

  10. STATISTICAL VALIDATION Leave-One Out (LOO) cross-validationmethod Diagonal Linear Discriminant Analysis (DLDA) Class Prediction Prediction Accuracy 74%

  11. Differentially expressed genes that are higher in metastasis group • RB1-inducible coiled-coil 1 (RB1CC1) • HBV preS1-transactivated protein 4 (PS1TP4) • Hypothetical protein FLJ11184 (FLJ11184) • Yippee-like 3 (Drosophila) (YPEL3) • AP1 gamma subunit binding protein 1 (AP1GBP1) • Protein phosphatase 2, regulatory subunit B', beta isoform (PPP2R5B) • Tubulin folding cofactor A (TBCA) • EP400 N-terminal like (EP400NL) • GTP-binding protein 10 (putative) (GTPBP10) • Melanoma cell adhesion molecule (MCAM) • Potassium channel tetramerisation domain containing 20 (KCTD20) • Pentatricopeptide repeat domain 3 (PTCD3) • Adenosine deaminase-like (ADAL) • Leucine rich repeat containing 3B (LRRC3B) • Flotillin 2 (FLOT2) • 12 ESTs

  12. Differentially expressed genes that are lower in metastasis group • Adaptor protein, phosphotyrosine interaction, PH domain and leucine zipper containing 2 (APPL2) • Hypothetical protein MGC39715 (MGC39715) • DIP2 disco-interacting protein 2 homolog B (Drosophila) (DIP2B) • PHD finger protein 19 (PHF19) • Solute carrier family 6 (neurotransmitter transporter, creatine), member 8 (SLC6A8) • Ras-associated protein Rap1 (RBJ) • Muscleblind-like (Drosophila) (MBNL1) • Fc fragment of IgG, low affinity IIIa, receptor (CD16a) (FCGR3A) • Glial cells missing homolog 2 (Drosophila) (GCM2) • Chromosome 9 open reading frame 123C9orf123 Chromosome 2 open reading frame 29 (C2orf29) • Phospholipase D2 (PLD2) • Ribosomal protein L27a (RPL27) • Hypothetical protein LOC339400 (LOC339400) • Chromosome 12 open reading frame 49 (C12orf49) • Platelet-activating factor acetylhydrolase 2, 40kDa (PAFAH2) • Solute carrier family 5 (sodium-dependent vitamin transporter), member 6(SLC5A6) • 7 ESTs

  13. Aim 2: Analysis of gene expression profiles of OSA patients presenting with metastasis Metastases at Dx vs No Metastases at Dx 18981 cDNAs n=2161 genes for tumor classification/clustering T-statistics p<0.001 (BrB Array Tools) DLDA Class Prediction 94% Prediction Accuracy

  14. MOLECULAR VALIDATION by REAL TIME PCR STAM2 was selected as the internal control gene after assessing 6 housekeeping genes by a statistical model described by Szabo et.al.(2004).

  15. DPF2 (Requiem) • member of the d4 domain family with a Kruppel type zinc-finger • Functions as a transcription factor for the apoptotic response • Induction of apoptosis by extracellular signals • Examples: Deprivation of survival factors in myeloid cells Drug treatment in OS cells?

  16. Work in Progress • U2OS, SaOS, HOS Cells • Knock down the DPF2 gene by SiRNA • Drug Treatment • Investigate the effect for the Apotosis

  17. CONCLUSIONS • The use of this genome-wide approach identified a number of genes that may play a role in osteosarcoma. • Genes and pathways not previously implicated in osteosarcoma have been elucidated by this study.

  18. FUTURE STUDIES Identify pathways related to genes in the classifier Protein-Protein Interactions found by Pathway Studio for 50 Significant Genes in A1vs A2 groups

  19. FUTURE STUDIES Online Predicted Human Interactive Database (OPHID) Protein-Protein Interactions found in OPHID for Significant Genes in A vs B groups

  20. Acknowledgement Mount Sinai Hospital Orthopedic Surgeons IL Andrulis JS Wunder RS Bell Hospital for Sick Children D.Malkin Vancouver General Hospital C.Beauchamp T.Yan M. Ghert Mona Gill University of Washington E.Conrad III Royal Orthopedic Hospital R.Grimer S Bull W He R Parkes R Kandel Memorial Sloan-Kettering J.Healey Mayo Clinic M.Rock/ L.Wold

  21. Acknowledgements • Ontario Cancer Research Network (OCRN) • National Cancer Institute of Canada (NCIC) • Canadian Institute of Health Research (CIHR) Interdisciplinary Health Research Team (IHRT) in Musculoskeletal Neoplasia • Rubinoff-Gross Chair in Orthopaedic Oncology at Mount Sinai Hospital, University of Toronto

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