Genetic Variants as Predictors of the Success of Colorectal Cancer Treatments

Author:

Garcia-Etxebarria Koldo12ORCID,Etxart Ane3ORCID,Barrero Maialen3,Nafria Beatriz3ORCID,Segues Merino Nerea Miren3,Romero-Garmendia Irati4,Goel Ajay5ORCID,Franke Andre6,D’Amato Mauro789ORCID,Bujanda Luis23

Affiliation:

1. Biodonostia, Gastrointestinal Genetics Group, 20014 San Sebastián, Spain

2. Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), 08036 Barcelona, Spain

3. Biodonostia, Gastrointestinal Disease Group, Universidad del País Vasco (UPV/EHU), 20014 San Sebastián, Spain

4. Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (Universidad del País Vasco/Euskal Herriko Unibertsitatea), 48940 Leioa, Spain

5. Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA

6. Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, 24105 Kiel, Germany

7. Gastrointestinal Genetics Lab, CIC bioGUNE, Basque Research and Technology Alliance, 48160 Derio, Spain

8. IKERBASQUE, Basque Foundation for Sciences, 48009 Bilbao, Spain

9. Department of Medicine and Surgery, LUM University, 70010 Casamassima, Italy

Abstract

Background: Some genetic polymorphisms (SNPs) have been proposed as predictors for different colorectal cancer (CRC) outcomes. This work aims to assess their performance in our cohort and find new SNPs associated with them. Methods: A total of 833 CRC cases were analyzed for seven outcomes, including the use of chemotherapy, and stratified by tumor location and stage. The performance of 63 SNPs was assessed using a generalized linear model and area under the receiver operating characteristic curve, and local SNPs were detected using logistic regressions. Results: In total 26 of the SNPs showed an AUC > 0.6 and a significant association (p < 0.05) with one or more outcomes. However, clinical variables outperformed some of them, and the combination of genetic and clinical data showed better performance. In addition, 49 suggestive (p < 5 × 10−6) SNPs associated with one or more CRC outcomes were detected, and those SNPs were located at or near genes involved in biological mechanisms associated with CRC. Conclusions: Some SNPs with clinical data can be used in our population as predictors of some CRC outcomes, and the local SNPs detected in our study could be feasible markers that need further validation as predictors.

Funder

Diputación Foral de Gipuzkoa

Publisher

MDPI AG

Subject

Cancer Research,Oncology

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