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Novel single-nucleotide polymorphism markers predictive of pathologic response to preoperative chemoradiation therapy
Jin C Kim1, Ye J Ha, Seon A Roh
1Department of Surgery, University of Ulsan College of Medicine, Seoul, Korea. jckim@amc.seoul.kr
Purpose:
Studies aimed at predicting individual responsiveness to preoperative chemoradiation therapy (CRT) are urgently needed, especially considering the risks associated with poorly responsive patients.
Methods And Materials:
A 3-step strategy for the determination of CRT sensitivity is proposed based on (1) the screening of a human genome-wide single-nucleotide polymorphism (SNP) array in correlation with histopathologic tumor regression grade (TRG); (2) clinical association analysis of 113 patients treated with preoperative CRT; and (3) a cell-based functional assay for biological validation.
Results:
Genome-wide screening identified 9 SNPs associated with preoperative CRT responses. Positive responses (TRG 1-3) were obtained more frequently in patients carrying the reference allele (C) of the SNP CORO2A rs1985859 than in those with the substitution allele (T) (P=.01). Downregulation of CORO2A was significantly associated with reduced early apoptosis by 27% (P=.048) and 39% (P=.023) in RKO and COLO320DM colorectal cancer cells, respectively, as determined by flow cytometry. Reduced radiosensitivity was confirmed by colony-forming assays in the 2 colorectal cancer cells (P=.034 and .015, respectively). The SNP FAM101A rs7955740 was not associated with radiosensitivity in the clinical association analysis. However, downregulation of FAM101A significantly reduced early apoptosis by 29% in RKO cells (P=.047), and it enhanced colony formation in RKO cells (P=.001) and COLO320DM cells (P=.002).
Conclusion:
CRT-sensitive SNP markers were identified using a novel 3-step process. The candidate marker CORO2A rs1985859 and the putative marker FAM101A rs7955740 may be of value for the prediction of radiosensitivity to preoperative CRT, although further validation is needed in large cohorts.
