Bioinformatic analysis for the identification of potential gene targeting drug resistance in CRC

Abstract

Background Colorectal cancer (CRC) is one of the most common malignant tumors in the world, and chemotherapy is an effective treatment against it. However, the occurrence of drug resistance has always been a big problem hindering the treatment. Methods We used bioinformatics analysis to identify potential key genes and pathways to further understand the mechanism of oxaliplatin resistance in this study. GSE69657 was an expression profile dataset of advanced CRC patients receiving standard FOLFOX chemotherapy, which was used to identify differentially expressed genes (DEGs). Enriched terms and pathways were determined by gene ontology (GO) and Kyoto Encyclopedia of Genes (KEGG) analyses. The key modules and hub genes involved in oxaliplatin resistance were identified by protein-protein interaction (PPI) analysis. Results A total of 232 DEGs were identified. In Go biological process, cellular component, and molecular function analyses, muscle contraction, contractile fiber, and structural constituent of muscle were enriched obviously. The most significantly enriched pathway was vascular smooth muscle contraction. And we found that smooth muscle contraction, muscle contraction may be the critical module in the PPI network analysis. Ten up-regulated hub genes, including TPM1, TPM2, and MYH11, may play an important role in the chemotherapy resistance of CRC. In the transcription factors (TF) prediction, we also found that the serum response family (SRF) was involved in chemotherapeutic resistance. These hub genes and TF identified by us may be potential targets for reversing drug resistance of CRC. Conclusions A number of hub genes such as TPM1, TPM2 and MYH11, as well as smooth muscle contraction, muscle contraction played a crux role in drug resistance of CRC. They may be a novel target to reverse tumor drug resistance and function importantly in clinical treatment in the future.