Abstract
INDELs and CNVs are structural variations that may play roles in cancer susceptibility and patient outcomes. Our objectives were a) to computationally detect and examine the genome‐wide INDEL/CNV profiles in a cohort of colorectal cancer patients, and b) to examine the associations of frequent INDELs/CNVs with relapse‐free survival time. We also identified unique variants in 13 Familial Colorectal Cancer Type X (FCCX) cases. The study cohort consisted of 495 colorectal cancer patients. QuantiSNP and PennCNV algorithms were utilized to predict the INDELs/CNVs using genome‐wide signal intensity data. Duplex PCR was used to validate predictions for 10 variants. Multivariable Cox regression models were used to test the associations of 106 common variants with relapse‐free survival time. Score test and the multivariable Cox proportional hazards models with time‐varying coefficients were applied to identify the variants with time‐varying effects on the relapse‐free survival time. A total of 3486 distinct INDELs/CNVs were identified in the patient cohort. The majority of these variants were rare (83%) and deletion variants (81%). The results of the computational predictions and duplex PCR results were highly concordant (93–100%). We identified four promising variants significantly associated with relapse‐free survival time (P < 0.05) in the multivariable Cox proportional hazards regression models after adjustment for clinical factors. More importantly, two additional variants were identified to have time‐varying effects on the risk of relapse. Finally, 58 rare variants were identified unique to the FCCX cases; none of them were detected in more than one patient. This is one of the first genome‐wide analyses that identified the germline INDEL/CNV profiles in colorectal cancer patients. Our analyses identified novel variants and genes that can biologically affect the risk of relapse in colorectal cancer patients. Additionally, for the first time, we identified germline variants that can potentially be early‐relapse markers in colorectal cancer.
Highlights
Colorectal cancer is the third most commonly diagnosed cancer and the fourth leading cause of cancer-related deaths worldwide [1]
Assuming that the proportional hazards (PH) assumption held for all variables, our results showed that two copy number variation (CNV)
Similar to other studies, QuantiSNP and PennCNV detected different numbers of variants in the patient genomes, which can be attributed to the different methodologies applied by these algorithms [34, 35]
Summary
Colorectal cancer is the third most commonly diagnosed cancer and the fourth leading cause of cancer-related deaths worldwide [1] Both the incidence and mortality rates of this disease show variability around the world; the incidence rates are higher in developed countries, such as Japan, Australia/New Zealand, USA, Europe, and Canada [2, 3]. The root cause of this geographic disparity is unknown, but variable lifestyle, socioeconomic, or environmental factors, or widespread screening and diagnostic programs in developed countries compared to the developing countries are suspected factors [2, 3] In addition to these factors, genetic factors may influence the risk of susceptibility and disease outcomes in patients. The promise of the personalized medicine is that such genetic factors influencing the susceptibility may be used for prevention and screening purposes, while those predicting the prognosis may be used to predict the potential course of the disease, and to inform the treatment decisions [5, 6]
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