Drug resistance severely affects the clinical efficacy of therapeutic agents in patients with colon cancer. The aim of the present study was to identify genes involved in drug resistance in colon cancer using bioinformatics analysis and to identify the underlying mechanisms . Genes associated with cancer recurrence and chemotherapy resistance were identified using data mining. Immunohistochemistry was performed to analyze the protein expression level of genes of interest in human colon cancer tissues. Reverse transcription-quantitative PCR analysis was performed to analyze the gene expression level in patient samples and in colon cancer cell lines (HCT116 and LoVo). Cell viability was evaluated using the Cell Counting Kit-8 assay in the colon cancer cell lines. Apoptosis was measured using PI staining. The results from the present study revealed 602 genes using both 'cancer recurrence' and 'chemoresistance' terms on the GenCLiP3 website. Gene functional annotation was performed using the Database for Annotation, Visualization and Integrated Discovery then, the protein-protein interaction networks of the 602 genes were analyzed using STRING analysis. Further, in the GEPIA database, 14 genes (, , , , , , , , , , , , and ) were found to be upregulated in colon cancer tissue and were associated with poor prognosis in patients with colon cancer. Further analysis of 33 paired human colon cancer tissues revealed that 8 genes (, , , , , , and ) were significantly upregulated, which was consistent with the results obtained from the earlier analysis and 5 genes (, , , and ) were associated with patient prognosis. Silencing of these 5 genes using small interfering RNAs significantly enhanced the sensitivity of colon cancer cells to the chemotherapeutic agent, 5-fluorouracil (5-FU). Taken together, the results suggested that , , , and might play a role in chemotherapeutic resistance in colon cancer and represent potential targets for overcoming 5-FU resistance in colon cancer.