Chips? SNPs? or PCR? What do we really want and what do we need? Heinz-Josef Lenz, MD Professor of Medicine Co-Director, Colorectal Center Co-Director, GI Oncology Program USC/Norris Comprehensive Cancer Center USC Keck School of Medicine

Severe Neutropenia Risk: 7/7 vs 6/6 + 6/7 Genotypes Unadjusted Odds Ratio Author n/N (%) Est. Odds Ratio95% CI 7/76/6 + 6/7 Innocenti3/6 (50%)3/53 (6%) Rouits4/7 (57%)10/66 (15%) Marcuello a 4/10 (40%)18/85 (21%) Ando b 4/7 (57%)22/111 (20%) a Gr 3+ neutropenia. b Gr 4 leukopenia and/or Gr 3+ diarrhea. From Parodi et al, FDA Subcommittee presentation, November, 2004

Revised Camptosar ® label

UGT1A1 genotypeIFLFOLFOXIROXAll 6/6 6.8% (3/44) 19.4% (26/134) 9.6% (5/52) 14.8% (34/230) 6/7 11.1% (6/54) 22.2% (28/126) 15.0% (6/40) 18.2% (40/220) 7/7 18.2% (2/11) 36.0% (9/25) 54.5% (6/11) 36.2% (17/47) p-Value* Rates of grade 4 neutropenia for genotype by treatment. *Based on test of trend

UGT1A1 Screening: Do we need it? Not predictive for IFL! Only little data on FOLFORI! Wildtype (6/6) can develop grade 4 neutropenia! Other metabolic genes need to be tested to increase predictive value

Efficacy and Toxicity to CPT-11 Group1234 OATP-C Wild TWild TVariant C/CVariant C/C ABCB1 Wild CWild CVariant T/T Variant T/T UGT1A1*28 Wild 6/6 Variant 7 Wild 6/6 Variant 7

Array Technology/Gene Expression Profiles 1.) Prognostic Signature Tumor Recurrence: When To Treat 2)Predictive Signature Tailoring Chemotherapy for Efficacy and Toxicity 3) Validation of Target Inhibition

Eschrich, S. et al. J Clin Oncol; 23:

Gene Signatures: Limitations! Fresh Frozen Tissue versus Formalin- Fixed Paraffin-Embedded Tissue Tissue Specific Array versus Non Tissue Specific Arrays Quantitative Gene Expression Profiles versus Arrays

Pitfalls Microdissection? Arrays: Profile with no necessarily functional significance Candidate Gene Approach: Missing critical Genes or Pathways?

Tissue Specific Array with Colorectal Associated EST with ArraDx

Survival curves for the predicted stage II colorectal cancer patients

ArraDx Aproach Colon Tissue Specific Possible from FFPE (Age?, Microdissection?) Accuracy of the signature was 63% with a sensitivity of 80% and specificity of 55% Potential Identification of Novel Genes/Pathways in Colon Cancer Differences in Gene Signatures of the ArraDx versus the Genomic Health Approach versus the Affymetrix?

Candidate Gene Approach Genomic Health 142 genes exhibited a significant linear relationship with RFI (p<0.05) 78 genes exhibited a significant linear relationship with RFI (p<0.05) after controlling for important covariates The prognostic genes in colon cancer are different from those in breast cancer Preliminary analysis of NSABP C-04 indicate that many genes are confirmed to be prognostic in colon cancer

Genomic Health Approach RT-PCR based on gene selections FFPE tissue: Age? Amount? How many genes can be tested? Microdissected? Limited by the genes selected No novel genes/pathway Validation needed

Prognostic Signatures May depend on T and N staging May depend on Location of Primary Tumor

Hierarchical Clustering: Colon and Rectal Cancers as well as Stages Cluster Separately ColonRectalpT2pT3 p<0.005p< Rectal Kornmann and Danenberg, Unpublished results pT3

Scatter Plot: Colon and rectal pT2 and rectal pT3 are Separated by Principle Component Analysis. p<0.05 Yellow = Rectal pT3 Blue = Rectal pT2 Red = Colon Kornmann and Danenberg, Unpublished results

Differential Pathways are involved in Short and Long DFS in pT3 Colon or pT3 Rectal Cancer: Mapping of Significant Gene Sets on Ingenuity Pathway Analysis Light Blue – Colon Dark Blue - Rectal Kornmann and Danenberg, Unpublished results

Development of Molecular Signatures 1.Validation needed in independent sets 2.Goals dictate Technology to be used (PCR versus Array) 3.Validated Prospective Clinical Trials

Arrays RT-PCR profiling Germline polymorphisms