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Int J Cancer. 2016 Jun 15;138(12):2993-3001. doi: 10.1002/ijc.30026. Epub 2016 Feb 19.

SNPs in transporter and metabolizing genes as predictive markers for oxaliplatin treatment in colorectal cancer patients.

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Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Division of Preventive Oncology, National Center for Tumor Diseases (NCT) and DKFZ, Heidelberg, Germany.
Division of Clinical Epidemiology and Aging Research, DKFZ, Heidelberg, Germany.
Division of Biostatistics, DKFZ, Heidelberg, Germany.
Oslo Center for Biostatistics and Epidemiology, Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
Department of General, Visceral and Transplantation Surgery, University Hospital Heidelberg, University of Heidelberg, Heidelberg, Germany.
Huntsman Cancer Institute, University of Utah, Salt Lake City, UT.
Division of Molecular Epidemiology, DKFZ, Heidelberg, Germany.
Division of Molecular Biology of Breast Cancer, Department of Gynecology and Obstetrics, University of Heidelberg, Heidelberg, Germany.
German Cancer Consortium (DKTK), Heidelberg, Germany.
University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany.


Oxaliplatin is frequently used as part of a chemotherapeutic regimen with 5-fluorouracil in the treatment of colorectal cancer (CRC). The cellular availability of oxaliplatin is dependent on metabolic and transporter enzymes. Variants in genes encoding these enzymes may cause variation in response to oxaliplatin and could be potential predictive markers. Therefore, we used a two-step procedure to comprehensively investigate 1,444 single nucleotide polymorphisms (SNPs) from these pathways for their potential as predictive markers for oxaliplatin treatment, using 623 stage II-IV CRC patients (of whom 201 patients received oxaliplatin) from a German prospective patient cohort treated with adjuvant or palliative chemotherapy. First, all genes were screened using the global test that evaluated SNP*oxaliplatin interaction terms per gene. Second, one model was created by backward elimination on all SNP*oxaliplatin interactions of the selected genes. The statistical procedure was evaluated using bootstrap analyses. Nine genes differentially associated with overall survival according to oxaliplatin treatment (unadjusted p values < 0.05) were selected. Model selection resulted in the inclusion of 14 SNPs from eight genes (six transporter genes, ABCA9, ABCB11, ABCC10, ATP1A1, ATP1B2, ATP8B3, and two metabolism genes GSTM5, GRHPR), which significantly improved model fit. Using bootstrap analysis we show an improvement of the prediction error of 3.7% in patients treated with oxaliplatin. Several variants in genes involved in metabolism and transport could thus be potential predictive markers for oxaliplatin treatment in CRC patients. If confirmed, inclusion of these variants in a predictive test could identify patients who are more likely to benefit from treatment with oxaliplatin.


colorectal cancer; metabolism; oxaliplatin; predictive markers; transport

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