Construction of an eight-basement membrane related gene signature for predicting prognosis and immune response in hepatocellular carcinoma

Background The basement membrane plays a very vital role in impeding cancer progression and metastatic colonization. However, the relationship between basement membrane-related genes (BMRGs) and hepatocellular carcinoma (HCC) remains poorly understood. Methods The transcriptome and clinical data of HCC patients were gathered from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) database, and segmented into training and testing sets, respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses enrichment subsequently analyzed the differentially expressed BMRGs. A novel prognostic BMRGs signature model was constructed by LASSO (least absolute shrinkage and selection operator) in training set and stratified patients into high-risk and low-risk groups, and which was verified in the testing set. Moreover, the accuracy of the new BMRGs signature was detected by receiver operating characteristic curve (ROC) analysis, followed by clinical correlation analysis, immune function analysis and multi-drug resistance analysis to verify the accuracy and clinical practical application value of the new signature. Results We created and verified a novel prognostic BMRGs signature for the prognosis of patients with HCC. The ROC analysis demonstrated that the 1-, 3-, and 5-year survival rates of HCC patients predicted by the prognostic BMRGs signature model based on the BMRGs signature were consistent with those of real patients. In clinical correlation analysis, univariate and multivariate Cox regression analyses validated that the model supports that the prognostic BMRGs signature can be independent risk factors for overall survival (OS) of HCC patients. In addition, the new signature can indeed differentiate the immunological analysis of HCC patients at different risk groups. In the drug sensitivity analysis, the expression levels of the BMRGs in the signatures were found to be related to the sensitivity of common chemotherapy drugs in HCC patients. Conclusion The newly prognostic BMRGs signature can be used as a prognostic indicator to predict the potential progression trajectory and therapeutic response in HCC, which may also provide sensible recommendations for immunotherapy and the selection of chemotherapeutic agents. Our findings provided a promising insight into BMRGs in HCC and a personalized prediction tool for prognosis and immune responses in patients.