In silico development and clinical validation of novel 8 gene signature based on lipid metabolism related genes in colon adenocarcinoma

摘要: Abstract Background Changes in lipid metabolism pathways play a major role colon carcinogenesis and development. Hence, we conducted systematic analysis of metabolism-related genes to explore new markers that predict the prognosis adenocarcinoma (COAD). Methods The non-negative Matrix Factorization (NMF) algorithm was applied identify molecular subtypes based on genes. A weighted correlation network (WCGNA) used co-expressed genes, Lasso multivariate Cox performed build risk model. timer database analyze immune infiltration gene signature GSCALite for genome-wide signature. Results TCGA-COAD samples were divided into 3 2739 identified by WGCNA analysis. Finally, an 8-gene (RTN2, FYN, HEYL, FAM69A, FBXL5, HMGN2, LGALS4, STOX1) constructed demonstrated good robustness different datasets, as well independent factor cancer patients’ prognosis. In addition, our model’s predictive efficacy overall higher than other published models, 8 genes’ expression indicated RTN2, STOX1 all expressed highly significantly COAD, while FYN HMGN2 poorly tissues, which confirmed immunohistochemistry. differently COAD correlated with clinical variables. Genome-wide revealed mutation frequency highest, genome methylation influenced significantly; further, HEYL FBXL5 positively Copy number variation (CNV) regulated CNV most cancers. austocystin d bafilomycin played important anti-tumor immunotherapy. RTN2 associated EMT pathway’s activation, LGALS4 inhibition. Conclusion This study novel marker survival.