TY - EJOU AU - GU, QIOU AU - LAI, CHUILIN AU - GUAN, XIAO AU - ZHU, JING AU - ZHAN, TIAN AU - ZHANG, JIANPING TI - A novel oxaliplatin-resistant gene signatures predicting survival of patients in colorectal cancer T2 - BIOCELL PY - 2024 VL - 48 IS - 2 SN - 1667-5746 AB - Objectives: Colorectal cancer (CRC) is a serious threat to human health worldwide. Oxaliplatin is a platinum analog and is widely used to treat CRC. However, resistance to oxaliplatin restricts its effectiveness and application while its target recognition and mechanism of action also remain unclear. Therefore, we aimed to develop an oxaliplatin-resistant prognostic model to clarify these aspects. Methods: We first obtained oxaliplatin-resistant and parental cell lines, and identified oxaliplatin-resistant genes using RNA sequencing (RNA-seq) and differential gene analysis. We then acquired relevant data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression were used to identify satisfactory resistance genes, and a prognostic model was established. Finally, small-molecule drugs targeting the high-risk (HR) and low-risk (LR) groups were predicted. Results: We identified 14 oxaliplatin-resistance genes in CRC. We built a model with these and used it to classify patients with CRC. Overall survival was better in the LR group than in the HR group (p < 0.001). Multivariate and univariate prognostic analyses revealed that this newly developed model had an independent prognostic value (p < 0.001). The risk score was found to be associated with the tumor microenvironment (TME) and 11 types of immune cells as per the CIBERSORT algorithm results. Finally, we screened 47 small-molecule drugs with half-maximal inhibitory concentration (IC50) values that were related to the risk scores. Conclusion: Our novel prognostic model for oxaliplatin resistance can be used to stratify the risk of CRC. KW - Colorectal cancer; Oxaliplatin; Prognostic model; Tumor microenvironment; Immune infiltration DO - 10.32604/biocell.2023.028336