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Genetic variations using whole-exome sequencing might predict response for neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
Medical Oncology 2018 September 12
A good pathologic response to neoadjuvant chemoradiotherapy (CRT) in locally advanced rectal cancer (LARC) is associated with a better prognosis. However, there is no effective method to predict CRT response in LARC patients. Therefore, this study used whole-exome sequencing (WES) to identify novel biomarker predicting CRT benefit in LARC. Two independent tumor tissue sets were used to evaluate the genetic differences between the good CRT response group (15 patients achieved a pathologic complete response (pCR)) and the poor CRT response group (15 patients with pathologic stage III). After applying WES to the discovery set of 30 patients, additional samples (n = 67) were genotyped for candidate variants using TaqMan or Sanger sequencing for validation. Overall, this study included a total of 97 LARC patients. In the discovery and validation set, there was no known genetic mutation to predict response between two groups, while five candidate variants (BCL2L10 rs2231292, DLC1 rs3816748, DNAH14 rs3105571, ITIH5 rs3824658, and RAET1L rs912565) were found to be significantly associated with pCR. In the dominant model, the GC/CC genotype of DLC1 rs3816748 (p = 0.032), AC/CC genotype of DNAH14 rs3105571 (p = 0.009), and TT genotype of RAET1 rs912565 (p < 0.0001) were associated with a higher pCR rate. In the recessive model, BCL2L10 rs2231292 (p = 0.036) and ITIH5 rs3824658 (p = 0.003) were significantly associated with pCR. In the co-dominant model, 4 candidate variants (DLC1 rs3816748, DNAH14 rs3105571, ITIH5 rs3824658, and RAET1L rs912565) were significantly correlated with pCR. However, none of the candidate variants was associated with relapse-free or overall survival. The present results suggest that genetic variations of the BCL2L10 rs2231292, DLC1 rs3816748, DNAH14 rs3105571, ITIH5 rs3824658, and RAET1L rs912565 genes can be used as biomarkers predicting the CRT response for patients with LARC.
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