Presentation is loading. Please wait.

Presentation is loading. Please wait.

COMPREHENSIVE ANALYSIS OF DNA COPY NUMBER VARIATIONS AND GENE EXPRESSION IN OSTEOSARCOMA Nalan Gokgoz, Atta Goudarzi, Cheryl Wolting Jay S. Wunder and.

Similar presentations


Presentation on theme: "COMPREHENSIVE ANALYSIS OF DNA COPY NUMBER VARIATIONS AND GENE EXPRESSION IN OSTEOSARCOMA Nalan Gokgoz, Atta Goudarzi, Cheryl Wolting Jay S. Wunder and."— Presentation transcript:

1 COMPREHENSIVE ANALYSIS OF DNA COPY NUMBER VARIATIONS AND GENE EXPRESSION IN OSTEOSARCOMA Nalan Gokgoz, Atta Goudarzi, Cheryl Wolting Jay S. Wunder and Irene L. Andrulis Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital Toronto, ON, Canada. Connective Tissue Oncology Society Meeting November 1, 2013

2 High resolution approaches to identify genes and pathways predictive of outcome in OS  Gene expression profiling by Microarray Analysis  Identification of the most relevant biological pathways for list of discriminative genes by Ingenuity Pathway Analysis  Identification of the significant effectors and organizing networks in OS metastasis by Dynamo (Taylor and Chuang)  Interrogation of biological pathways and networks  Investigation of Copy Number Changes by Illumina SNP array technology  Detection and characterization of alterations  Analysis and visualization by Genome Studio and GAP  Identification of significant recurrent targets by GISTIC Identification and Characterization of Molecular Alterations Identification and Characterization of Molecular Alterations in Osteosarcoma in Osteosarcoma

3 High-grade Intramedullary 63 patients No Metastasis at Diagnosis 46 patients Metastasis at Diagnosis 17 patients No Metastasis 4 years post Dx. (29 patients) Metastasis within 4 years Dx. (17 patients) AB A1 A2 PATIENT COHORT

4 No Metastases 4 years post Dx (A1) vs Metastases within 4 years Dx (A2) No Metastases 4 years post Dx (A1) vs Metastases within 4 years Dx (A2) cDNAs T-statistic p<0.001 (BrB Array Tools) n=53 genes for tumor classification/clustering Statistical validation by Leave-One Out cross-validation method Molecular validation by Real-Time Analysis Outcome of the Patients Presenting with “no Metastases” No Mets. 4 yrs post Dx. Mets. within 4 yrs post Dx. MICROARRAY ANALYSIS MICROARRAY ANALYSIS

5 Gene A Gene C. Gene X Gene Y Interactions and Relationships between molecules in set Networks Pathways with which molecules in set are associated Pathways Functions with which molecules in set are associated Functions Upstream regulators that may be responsible for observed increase/decrease in expression Upstream Regulators Molecule Set Ingenuity Pathway Analysis

6 Summary of IPA in OS metastasis Networks cell morphology, organization, hematopoiesis Pathways Rac/Rho, actin cytoskeleton Functions hematopoiesis, cell movement Regulators Fas, Fos, SP1, SREBF1

7 Signaling by Rho Family GTPases Lower expression in A2 Higher expression in A2 A1 – No mets A2 – Mets in 4 yrs

8 GENETIC NETWORKS in OS METASTASIS The PRKCε, RASGPR3 and GNB2 networks differentially activated DLG2 network differentially organized The PRKCε, RASGPR3 and GNB2 networks are potential effectors of DLG2 Significant Networks Transport Translation Signaling Protein Kinase C Epsilon and Genetic Networks in Osteosarcoma Metastasis; A Goudarzi, N Gokgoz, M Gill, D Pinnaduwage, D. Merico, J.S Wunder and IL Andrulis, Cancer, 2013, 5,

9 Osteosarcoma and Copy Number Alterations  Illumina 610-Quad Whole-genome genotyping beadchip  Coverage includes >14,000 CNV regions and 550K evenly spaced TagSNPs from HapMap data  High Resolution: Spacing 2.7 kb  Includes markers in the unSPNable Genome  Allows detection of SNPs, Copy Number Variation and Genotype  Reference Genotype: Canonical genotype clusters (200 HapMap DNA genotype data)  44 Osteosarcoma Tumor DNA  Validation by Real Time PCR  25 of them with matched blood DNA

10 Complexity of OS Tumour Genome (Analysis by Genome Studio) Blood DNA Tumour DNA Allele Frequency BBABAA LogR Ratio

11 OS-2550_Chromosome 3 Genome Alteration Print (GAP) Analysis

12 COL12A1 COL9A1 AF CDK4 MDM2 COL4A1 COL4A2 LIG4 MYR8 COPS3 NCORI PMP22 PPFIBP1 FGFR1OP2 Recurrent Copy Number Gains in OS identified by GISTIC (Genome Identification of Significant Targets in Cancer) * * * * Same family genes q value

13 Recurrent Copy Number Losses in OS identified by GISTIC LOC CNTNAP2 CDKN2A MTAP DLG2 RB1 TP53 GRIK2 * * * DOCK5 * Same family genes q value NAALADL2

14 11q14.1 deletion in a matched tumor-blood DNA DLG2

15  One of the most disorganized genetic networks in metastatic OS tumours.  The PRKCε, RASGPR3 and GNB2 networks are potential effectors of DLG2  Tumour suppressor function of dlg2 in Drosophila  Scribble complex (SCRIB, DLG1-4 and LGL1/2) deregulation in Prostate Cancer  DLG2 implicated in Wilms Tumour Implication of DLG2 as a tumour suppressor in cancer

16 DLG2 (discs, large homolog 2) Channel associated protein of synapse 110 Chromosome 11q14 Member of the membrane-associated guanylate kinase (MAGUK) family. PDZ domains; interaction with signalling proteins at postsynaptic sites SH3 domains are found in proteins of signaling pathways regulating the cytoskeleton and regulate the activity state of adaptor proteins and other tyrosine kinases GuKinase Domain; catalyzes ATP-dependent phosphorylation of GMP to GDP Gene: 2 MB, 33 alternative spliced transcripts Longest transcript :3.7KB, 26 Exons Expression site: Brain, hypothalamus

17 Relative Expression of DLG2 in OS tumours and cell-lines Deletion of DLG2 gene detected by SNP array

18  SiRNA Knockdown of the DLG2 Gene in U2OS 70% knockdown at 72 hours Work in Progress  The effect of DLG2 knockdown in  Cell viability and growth by XTT assay  Migration by scratch assay  Sequencing of DLG2 gene for inactivating mutations

19  We identified a 53-gene expression signature that may predict outcome of OS patients with localized tumours.  High-resolution approaches identified candidate pathways and networks that may be biologically relevant in OS.  Cell morphology and organization pathways may be involved in OS metastasis.  A large number of chromosomal aberrations were detected in OS tumours by SNP array technology.  The DLG2 gene that is deleted in 20 percent of the OS cases and belonging to a significantly disorganized metastatic OS network and was chosen for further functional analysis.  Further experiments will be performed to investigate the functional role of DLG2 in cell growth, proliferation and migration. CONCLUSION

20 Acknowledgement Mount Sinai Hospital Orthopedic Surgeons Hospital for Sick Children D.Malkin Vancouver General Hospital C.Beauchamp R. Kandel University of Washington E.Conrad III Royal Orthopedic Hospital R.Grimer Memorial Sloan-Kettering J.Healey Mayo Clinic M.Rock/ L.Wold Andrulis and Wunder Lab S. Bull R. Parkes I. Andrulis J. Wunder Andrew Seto

21 During progression from tumour growth to metastasis, specific integrin signals enable cancer cells to detach from neighbouring cells, re-orientate their polarity during migration, and survive and proliferate in foreign microenvironments. There is increasing evidence that certain integrins associate with receptor tyrosine kinases (RTKs) to activate signalling pathways that are necessary for tumour invasion and metastasis. The effect of these integrins might be especially important in cancer cells that have activating mutations, or amplifications, of the genes that encode these RTKs.


Download ppt "COMPREHENSIVE ANALYSIS OF DNA COPY NUMBER VARIATIONS AND GENE EXPRESSION IN OSTEOSARCOMA Nalan Gokgoz, Atta Goudarzi, Cheryl Wolting Jay S. Wunder and."

Similar presentations


Ads by Google