Identification of a basement membrane-based risk scoring system for prognosis prediction and individualized therapy in clear cell renal cell carcinoma.

ABSTRACT

Clear cell renal cell carcinoma (ccRCC) belongs to one of the 10 most frequently diagnosed cancers worldwide and has a poor prognosis at the advanced stage. Although multiple therapeutic agents have been proven to be curative in ccRCC, their clinical application was limited due to the lack of reliable biomarkers. Considering the important role of basement membrane (BM) in tumor metastasis and TME regulation, we investigated the expression of BM-related genes in ccRCC and identified prognostic BM genes through differentially expression analysis and univariate cox regression analysis. Then, BM-related ccRCC subtypes were recognized through consensus non-negative matrix factorization based on the prognostic BM genes and evaluated with regard to clinical and TME features. Next, utilizing the differentially expressed genes between the BM-related subtypes, a risk scoring system BMRS was established after serial analysis of univariate cox regression analysis, lasso regression analysis, and multivariate cox regression analysis. Time-dependent ROC curve revealed the satisfactory prognosis predictive capacity of BMRS with internal, and external validation. Multivariate analysis proved the independent predictive ability of BMRS and a BMRS-based nomogram was constructed for clinical application. Some featured mutants were discovered through genomic analysis of the BMRS risk groups. Meanwhile, the BMRS groups were found to have distinct immune scores, immune cell infiltration levels, and immune-related functions. Moreover, with the help of data from The Cancer Immunome Atlas (TCIA) and Genomics of Drug Sensitivity in Cancer (GDSC), the potential of BMRS in predicting therapeutic response was evaluated and some possible therapeutic compounds were proposed through ConnectivityMap (CMap). For the practicability of BMRS, we validated the expression of BMRS-related genes in clinical samples. After all, we identified BM-related ccRCC subtypes with distinct clinical and TME features and constructed a risk scoring system for the prediction of prognosis, therapeutic responses, and potential therapeutic agents of ccRCC. As ccRCC systemic therapy continues to evolve, the risk scoring system BMRS we reported may assist in individualized medication administration.