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Polymorphisms contribute to inter-individual differences and show a promising predictive role for chemotherapy-related toxicity in colon cancer (CC). TOSCA is a multicentre, randomized, non-inferiority, phase III study conducted in high-risk stage II/stage III CC patients treated with 6 vs 3 months of FOLFOX-4 or XELOX adjuvant chemotherapy. During this post-hoc analysis, 218 women and 294 men were genotyped for 17 polymorphisms: TYMS (rs34743033, rs2853542, rs11280056), MTHFR (rs1801133, rs1801131), ERCC1 (rs11615), XRCC1 (rs25487), XRCC3 (rs861539), XPD (rs1799793, rs13181), GSTP1 (rs1695), GSTT1/GSTM1 (deletion +/-), ABCC1 (rs2074087), and ABCC2 (rs3740066, rs1885301, rs4148386). The aim was to assess the interaction between these polymorphisms and sex, on safety in terms of time to grade ≥3 haematological (TTH), grade ≥3 gastrointestinal (TTG) and grade ≥2 neurological (TTN) toxicity. Interactions were detected on TTH for rs1801133 and rs1799793, on TTG for rs13181 and on TTN for rs11615. Rs1799793 GA genotype (p = 0.006) and A allele (p = 0.009) shortened TTH in men. In women, the rs11615 CC genotype worsened TTN (co-dominant model p = 0.008, recessive model p = 0.003) and rs13181 G allele improved the TTG (p = 0.039). Differences between the two sexes in genotype distribution of rs1885301 (p = 0.020) and rs4148386 (p = 0.005) were found. We highlight that polymorphisms could be sex-specific biomarkers. These results, however, need to be confirmed in additional series.
Pubmed ID: 31395900
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A web-based application designed from a genetic epidemiology point of view to analyze association studies using single nucleotide polymorphisms (SNPs). For each selected SNP, you will receive: * Allele and genotype frequencies * Test for Hardy-Weinberg equilibrium * Analysis of association with a response variable based on linear or logistic regression * Multiple inheritance models: co-dominant, dominant, recessive, over-dominant and additive * Analysis of interactions (gene-gene or gene-environment) If multiple SNPs are selected: * Linkage disequilibrium statistics * Haplotype frequency estimation * Analysis of association of haplotypes with the response * Analysis of interactions (haplotypes-covariate)
View all literature mentionsDatabase and central repository for genetic, genomic, molecular and cellular phenotype data and clinical information about people who have participated in pharmacogenomics research studies. The data includes, but is not limited to, clinical and basic pharmacokinetic and pharmacogenomic research in the cardiovascular, pulmonary, cancer, pathways, metabolic and transporter domains. PharmGKB welcomes submissions of primary data from all research into genes and genetic variation and their effects on drug and disease phenotypes. PharmGKB collects, encodes, and disseminates knowledge about the impact of human genetic variations on drug response. They curate primary genotype and phenotype data, annotate gene variants and gene-drug-disease relationships via literature review, and summarize important PGx genes and drug pathways. PharmGKB is part of the NIH Pharmacogenomics Research Network (PGRN), a nationwide collaborative research consortium. Its aim is to aid researchers in understanding how genetic variation among individuals contributes to differences in reactions to drugs. A selected subset of data from PharmGKB is accessible via a SOAP interface. Downloaded data is available for individual research purposes only. Drugs with pharmacogenomic information in the context of FDA-approved drug labels are cataloged and drugs with mounting pharmacogenomic evidence are listed.
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