Abstract
Inherited change in individual patients can govern not only the risk of developing Multiple Myeloma (MM), but also treatment related side effects and clinical outcome. The challenge is to identify and observe the changes clinically. This can be done by the use of genome wide scans with regularly placed SNPs or by the use of a candidate functional SNPs. Several genotyping platforms are available, which allow assaying of 1000’s of SNP’s simultaneously. We have been evaluating the use of Parallele’s MegAllele™ System with the Affymetrix® GeneChip® 3000 Scanner system. The system uses a Molecular Inversion Probes (MIP) based technology. MIP is a oligonucleotide that can undergo a unimolecular rearrangement from a molecule that cannot be amplified, into one that can be amplified. The rearrangement is mediated by hybridization to gDNA and an enzymatic “gap fill” process that occurs in an allele-specific manner. The circularized probe can then be separated from cross-reacted or unreacted probes by an exonuclease reaction. The unimolecular design of this assay allows multiplexing 10,000 targeted SNPs without background from cross-reactions among probes in a single assay. Initial evaluation, using a 10K non-synonymous cSNP panel was run on 22 patients from the S9321 trial and correlated with ISS stage. 101 SNPs with a univariate p value from a fisher’s exact test <0.05 were found; 18 SNPs were found p<0.01. Cluster algorithms demonstrated SNP groupings associated with stage; however, the sample size is small and the reported p-values were not adjusted for an inflated error rate associated with multiple comparisons. Examination of the SNP panel content revealed significant omissions relevant to MM. For this reason we designed a 3K Custom panel containing 3,500 targeted SNPs with possible functional interest in MM. Pertinent candidate genes were selected through discussions between MM groups in an International Myeloma Foundation led Bank On A CureTM collaboration. We supplemented an initial list with referencing pathway databases such as BioCarta, KEGG, and Pathway Assist. The list was sectioned into 25 groups including: Angiogenesis, Drug Transport & Metabolism, DNA repair and covering some 67 molecular pathways important in MM. SNPs were systematically selected from the gene list by: Literature searches to identify SNPs cited with a suspected association with etiology or treatment; A dbSNP database search for all non-synonymous SNPs with a minor allele frequency (MAF) >2%; A search of promoter SNPs present in homologous regions between Human and Mouse with a MAF > 2%, lying in or adjacent to transcription binding sites using Promolign. Additional promoter SNPs were identified using FESD. SNPs were also selected for the panel by the addition of: TagSNPs across selected candidate genes; admixture SNPs from the X chromosome; pharmacologically functional SNPs; Affymetrix validated SNPs and by selecting all Non-synonymous SNPs in Phosphatase, Kinase, and Transferase genes with a MAF > 2%. This panel is currently being assembled and we will present results on its use for the analysis of inherited genetic variation in several large European and American clinical trial series.
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