Identification of a six-gene signature predicting overall survival for Oxaliplatin and 5-Fluorouracil resistant Colon cancer and potential drug-repurposing [post]

Feng Yang, Shaoyi Cai, Riya Su, Li Ling, Liang Tao, Qin Wang
2020 unpublished
Background Oxaliplatin (L-OHP) and 5-fluorouracil (5-FU) resistance in colorectal cancer (CRC) is a major medical problem. Therefore, detailed mechanisms and predictive markers are urgently needed. The aim of this study was to identify key pathways, a robust prognostic gene signature and potential drug-repurposing. Methods In order to confirm the predictive markers and detailed molecular mechanisms of L-OHP and 5-Fu chemoresistant CRC, we performed weighted correlation network analysis (WGCNA),
more » ... k analysis (WGCNA), an unsupervised analysis method, to identify the chemoresistant CRC significantly related genes. Then, the gene prognostic model was conducted by Univariate Cox regression and Lasso penalized Cox regression analysis. Subsequently, the time-dependent receiver operating characteristic (ROC) and Kaplan-Meier survival curve were performed to assess the prognostic capacity of the model. Simultaneously, pathway enrichment was done to identify the key pathways involved in chemoresistant CRC. Moreover, we explored how the hub genes interacted with key pathways and transcription factors. Then, we found the potential drug target by the subcellular location fo hub genes. Finally, we identified the potential drug-repurposing by virtual screening for chemoresistant CRC according to ZINC 15 database. Results We identified the key pathways using KEGG over-representation test and Gene Set Enrichment Analysis (GSEA): Ribosome KEGG pathway. Moreover, six hub-genes prognostic model was conducted by Univariate Cox regression and Lasso penalized Cox regression analysis. Additionally, the detailed interactions among the pathway and hub genes (RBM6, PNN, LEF1, ANO1, PAFAH1B3 and BHLHE41) were examined by protein-protein interaction (PPI) network and shortest-pathway analysis. Furthermore, ANO1 was considered the potential drug target based on the subcellular location and ZINC000018043251 was verified the potential drug by virtual screening. Conclusions Our study identified a novel six-gene resistant signature for CRC prognosis prediction and the molecular details of these interactions between hub genes (RBM6, PNN, LEF1, ANO1, PAFAH1B3 and BHLHE41) and Ribosome key pathways. Furthermore, ZINC000018043251 was verified the potential drug for ANO1 by virtual screening, which might help to improve the outcome of CRC patients.
doi:10.21203/rs.3.rs-43698/v1 fatcat:uh4sfjes2renxalk5hrxxsgrxa