DNAprint Genomics (DNAG)

[IVRT]

Focused Plenary Session on Ovarian Cancer

http://www.sgo.org/meetings/33annual/abstracts/abstract.asp?abstractid=21

Determination of a Candidate Gene in Predicting In-Vivo Ovarian Cancer Response to Combination Therapy with Carboplatin and Paclitaxel
Ramin Mirhashemi*, J Fernando Arena, Tony Frudakis, Nicholas Lambrou, Jane Arboleda, Marsha Hunt, Hervy E Averette, Manuel A Penalver. Univ of Miami, Sch of Medicine, Miami, FL, DNAPrint Genomics, Sarrasota, FL.

Objectives: Patient response rates to primary treatment of ovarian cancer with combination of paclitaxel and the carboplatin agents is subject to a high degree of uncertainty and inter-individual variability. In an attempt to define the genetic determinants for this variability, we are conducting a pharmacogenomics study to predict response based on patient genomics.


Methods: Our approach is a systematic haplotype-based candidate gene approach, where we genotype each patient at each single nucleotide polymorphic (SNP) site for each gene known to be relevant for xenobiotic disposition, then computationally infer haplotypes, and geometrically model the data in order to identify associations between haplotypes and response. We have chosen this novel approach to objectively define an optimal pharmacogenomics solution.


Results: We have constructed SNP maps for 50 genes known to be involved in xenobiotic metabolism and/or the disposition of paclitaxel and carboplatin and have discovered an average of 30 candidate SNPs per gene, which, upon polymorphism screening, validated at a rate of about 18 SNPs per gene. Having obtained genotypes for 57 patients at each of the SNPs in several genes, preliminary results have revealed a statistically significant association (Fishers Exact p=0.00332 ± 0.00043) between haplotypes at the CYP3A4 gene and a lack of response to paclitaxel/carboplatin as measured by the CA-125 tumor marker. In particular, the GAC and GAT CYP3A4 haplotypes were only present in the non-responder group (n=22), when an absolute decrease in CA-125 was used to define responders (n=40). When a 20% decrease in CA-125 was used, a similar result was obtained (Fishers Exact p=0.016 ± 0.001); GAC was found in the non-responder group 71% of the time, and the GAT haplotype was found in the non-responder group 100% of the time.


Conclusions: SNPs in candidate genes being identified could potentially be used pre-treatment to individualize chemotherapy for patients with ovarian cancer. This in vivo assay could help classify ovarian cancer patients as potential responders or non-responders to our conventional chemotherapeutic agents.


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