The aim of our study was to set up a panel for targeted sequencing of chemoresistance genes and the main transcription factors driving their expression and to evaluate their predictive and prognostic value in breast cancer patients. Coding and regulatory regions of 509 genes, selected from PharmGKB and Phenopedia, were sequenced using massive parallel sequencing in blood DNA from 105 breast cancer patients in the testing phase. In total, 18,245 variants were identified of which 2565 were novel variants (without rs number in dbSNP build 150) in the testing phase. Variants with major allele frequency over 0.05 were further prioritized for validation phase based on a newly developed decision tree. Using emerging in silico tools and pharmacogenomic databases for functional predictions and associations with response to cytotoxic therapy or disease-free survival of patients, 55 putative variants were identified and used for validation in 805 patients with clinical follow up using KASPTM technology. In conclusion, associations of rs2227291, rs2293194, and rs4376673 (located in ATP7A, KCNAB1, and DFFB genes, respectively) with response to neoadjuvant cytotoxic therapy and rs1801160 in DPYD with disease-free survival of patients treated with cytotoxic drugs were validated and should be further functionally characterized.
Keywords: breast cancer; chemoresistance; in silico prediction; next generation sequencing; pharmacogenomics.