predicting outcome in osteosarcoma using a genome-wide approach
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PREDICTING OUTCOME IN OSTEOSARCOMA USING A GENOME-WIDE APPROACH. N Gokgoz ,T Yan, M Ghert, S Eskandarian W He, R Parkes, SB Bull, RS Bell, IL Andrulis and JS Wunder. Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Canada. OSTEOSARCOMA. - PowerPoint PPT PresentationTRANSCRIPT
PREDICTING OUTCOME IN PREDICTING OUTCOME IN OSTEOSARCOMA USING A OSTEOSARCOMA USING A GENOME-WIDE APPROACHGENOME-WIDE APPROACH
N Gokgoz ,T Yan, M Ghert, S Eskandarian N Gokgoz ,T Yan, M Ghert, S Eskandarian W He, R Parkes, SB Bull, RS Bell,W He, R Parkes, SB Bull, RS Bell,
IL Andrulis and JS WunderIL Andrulis and JS Wunder
Samuel Lunenfeld Research Institute, Mount Sinai Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, CanadaHospital, Toronto, Canada
• Treatment involves (neo)adjuvant chemotherapy and wide surgical resection
•Patients with Metastases at Diagnosis:
5 year disease-free survival 10-20%.
•Patients without Metastases at Diagnosis:
5 year disease-free survival 50-78%.
•Few accurate clinical predictors of outcome
•Molecular markers ( e.g. p53, RB, cdk4,SAS): not prognostic
OSTEOSARCOMAOSTEOSARCOMA
CAN GENE EXPRESSION PREDICT CAN GENE EXPRESSION PREDICT
METASTASES IN OSTEOSARCOMA?METASTASES IN OSTEOSARCOMA?
•Expression patterns of multiple genes may be more predictive than one or two alone
Hypothesis: The study of global gene expression patterns in osteosarcomas may improve classification of these tumors and prediction of disease outcome.
•Microarray Analysis to characterize “gene expression signatures”.
An Emerging Molecular ParadigmAn Emerging Molecular Paradigm
Tumor SamplesTumor Samples
• Osteosarcoma Tumor Bank• 64 fresh frozen, high grade intramedullary
osteosarcoma• all tumor specimens were from open
biopsies performed prior to chemotherapy• tumor specimen chosen based on frozen
section histological analysis• minimum follow-up 24 months or metastasis
High Grade
Intramedullary
N=64 patients
No Metastases
at Diagnosis
N=46 patients
Metastases
at Diagnosis
N=18 patients
No metastases at follow-up N=29
Metastases at follow-up N=17
What are the underlying molecular differences What are the underlying molecular differences between Mets at Dx vs. No Mets at Dx ?between Mets at Dx vs. No Mets at Dx ?
OSA Patients
Microarray Analysis of OS TumorsMicroarray Analysis of OS Tumors on 19 K chipson 19 K chips
Each hybridization compared Cy5 labeled cDNA from one of the tumor samples with Cy3 labeled cDNA from the reference sample (a pool of 11 tumor cell lines). The arrows indicate the genes that have
high (red) Cy5/Cy3 and low (green) Cy5/Cy3 ratios.
Cy5 Cy3 Cy5/Cy3 Ratio
Ontario Cancer Institute
Toronto Canada
Image Acquisition : Axon ScannerSpot Analysis : GenePix Pro.5Data Storage: IobianTM Gene Traffic
Reference PoolTumor
Statistical AnalysisStatistical Analysis
• replication and reproducibility studies for validity• local background subtraction• log transformation• normalization – subarray effects• single gene differential expression
(T-test using BrB ArrayTools)• adjust for multiple testing• multiple gene tumor classification• “honest” tumor class prediction using cross-
validation
Metastases at Dx Metastases at Dx vs vs
No Metastases at DxNo Metastases at Dx
7352 cDNAs
T-statistic p<0.001
(BrB Array Tools)
n=1368 genesfor tumor classification/clustering
““Honest” Tumor Class Prediction Honest” Tumor Class Prediction using Cross-Validation (CV)using Cross-Validation (CV)
• Leave-One Out (LOO) cross-validation method
• Several prediction methods were applied on expression data set to examine their accuracy for the metastatic status of the patients.
““Honest” Tumor Class Prediction Honest” Tumor Class Prediction using Cross-Validation (CV)using Cross-Validation (CV)
•Metastasis Suppressor1 (MTSS1)•Cell Adhesion Integrins and Selectin-P•Cell cycle checkpoint genes PARC (a regulator of p53 localization and degradation) Cyclin dependent kinases CDK4-6•Chromosome instability MCC (Mutated in Colorectal Carcinoma)•Genes related to chemotherapy sensitivity/resistance MSRP (multidrug resistance-related protein) DNA metyhyltransferase 1 associated protein, •Cytoskeleton Organization
Ezrin (Villin2)
POTENTIAL GENE PATHWAYS IN 1368 GENE LIST POTENTIAL GENE PATHWAYS IN 1368 GENE LIST
C. Khanna et al., Cancer Research, 2001.P. Leonard et al., BJC, 2003. C. Khanna et al., Nature Medicine ,2004. Y. Yu et al., Nature Medicine, 2004.
•Ezrin has been shown to be involved in promotion of metastasis in a number of cancer systems including osteosarcoma.
Linker between membrane molecules and actin cytoskeleton
EZRINEZRIN
•MA Analysis: Different Platforms OCI Arrays - 2 Spots for Ezrin Gene - Only 1 spot was in our
discriminative gene list
Ezrin GeneEzrin Gene
UTR
Spot 1 Spot 2
Conclusions:Conclusions:
• There is a very large disparity in outcome for patients with osteosarcoma who have Metastases at Diagnosis vs No Metastases at Diagnosis
• Gene expression profiles generated by microarray analysis discriminated these 2 groups with a 94 % prediction accuracy
• Genes that are differentially expressed between the 2 groups require further follow–up (Ezrin)
High Grade
Intramedullary
N=64 patients
No Metastases at Diagnosis
N=46 Metastases at follow-up N=17Metastases at
Diagnosis N=18
No Metastases at follow-up N=29
Future AnalysesFuture Analyses
1. Mets at Dx vs No Mets at Dx.• Determine classifiers • Identify pathways related to genes in the classifier
2. Patients developed mets during follow-up and not.• Determine classifiers • Chemotherapy response• Identify pathways related to genes in the classifier
3. Characterization of biological pathways • e.g. Ezrin
AcknowledgementAcknowledgementMount Sinai Hospital
IL Andrulis
JS Wunder
T.Yan, M. GhertS.Eskandarian
Hospital for Sick Children D.Malkin
Vancouver General Hospital C.Beauchamp
S Bull
W He
R Parkes
R Kandel
RS Bell
University of Washington E.Conrad III
Royal Orthopaedic Hospital R.Grimer
Memorial Sloan-Kettering J.Healey
Mayo Clinic M.Rock/ L.Wold
AcknowledgementsAcknowledgements
• 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