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

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 in Osteosarcoma

High-grade Intramedullary 63 patients

No Metastasis at Diagnosis46 patients

Metastasis at Diagnosis17 patients

No Metastasis 4 years post Dx. (29 patients)

Metastasis within 4 years Dx.(17 patients)

A B

A1

A2

PATIENT COHORT

No Metastases 4 years post Dx (A1)vs

Metastases within 4 years Dx (A2)

18981 cDNAs

T-statistic p<0.001

(BrB Array Tools)

n=53 genesfor tumor classification/clustering

Statistical validation by Leave-One Out cross-validation methodMolecular 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

Gene AGene C

.

.Gene XGene 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

Summary of IPA in OS metastasis

Networks cell morphology, organization, hematopoiesisPathways Rac/Rho, actin cytoskeletonFunctions hematopoiesis, cell movementRegulators Fas, Fos, SP1, SREBF1

Signaling by Rho Family GTPases

Lower expression in A2Higher expression in A2

A1 – No metsA2 – Mets in 4 yrs

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, 372-403

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

Complexity of OS Tumour Genome (Analysis by Genome Studio)

Blood DNA

Tumour DNA

Allele Frequency

BB AB AA

LogR Ratio

OS-2550_Chromosome 3

Genome Alteration Print (GAP) Analysis

COL12A1COL9A1

AF086303

CDK4MDM2

COL4A1COL4A2

LIG4MYR8

COPS3NCORIPMP22PPFIBP1

FGFR1OP2

Recurrent Copy Number Gains in OS identified by GISTIC (Genome Identification of Significant Targets in Cancer)

**

*

*Same family genes

q va

lue

Recurrent Copy Number Losses in OS identified by GISTIC

LOC285194

CNTNAP2

CDKN2A

MTAP

DLG2

RB1

TP53

GRIK2

**

*

DOCK5

*Same family genes

q va

lue

NAALADL2

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

DLG2

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

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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20U2OS

SaOS

SaOs-L

M7LM

70.000

0.050

0.100

0.150

0.200

0.250

0.300

OS Tumours

DLG2

/STA

M2

Relative Expression of DLG2 in OS tumours and cell-lines

Deletion of DLG2 gene detected by SNP array

SiRNA Knockdown of the DLG2 Gene in U2OS 70% knockdown at 72 hours

48 72 960

20

40

60

80

100

120

140

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

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

Acknowledgement

Mount Sinai HospitalOrthopedic 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. BullR. Parkes

I. AndrulisJ. Wunder

Andrew Seto

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.