No abstract

Bladder cancer (BLCA) is one of the most common malignant tumors of the urinary system, but the current therapeutic strategy based on chemotherapy and immune checkpoint inhibitor (ICI) therapy cannot meet the treatment needs, mainly owing to the endogenous or acquired apoptotic resistance of cancer cells. Targeting necroptosis provides a novel strategy for chemotherapy and targeted drugs and improves the efficacy of ICIs because of strong immunogenicity of necroptosis. Therefore, we systemically analyzed the necroptosis landscape on therapy and prognosis in BLCA. We first divided BLCA patients from The Cancer Genome Atlas (TCGA) database into two necroptosis-related clusters (C1 and C2). Necroptosis C2 showed a significantly better prognosis than C1, and the differential genes of C2 and C1 were mainly related to the immune response according to GO and KEGG analyses. Next, we constructed a novel necroptosis-related gene (NRG) signature consisting of SIRT6, FASN, GNLY, FNDC4, SRC, ANXA1, AIM2, and IKBKB to predict the survival of TCGA-BLCA cohort, and the accuracy of the NRG score was also verified by external datasets. In addition, a nomogram combining NRG score and several clinicopathological features was established to more accurately and conveniently predict the BLCA patient’s survival. We also found that the NRG score was significantly related to the infiltration levels of CD8 T cells, NK cells, and iDC cells, the gene expression of CTLA4, PD-1, TIGIT, and LAG3 of TME, and the sensitivity to chemotherapy and targeted agents in BLCA patients. In conclusion, the NRG score has an excellent performance in evaluating the prognosis, clinicopathologic features, tumor microenvironment (TME), and therapeutic sensitivity of BLCA patients, which could be utilized as a guide for chemotherapy, ICI therapy, and combination therapy.

Bladder cancer (BLCA) is one of the most common malignant tumors of the urinary system, but current therapeutic strategy based on chemotherapy and immune checkpoint inhibitors (ICIs) therapy cannot meet the treatment needs, which mainly owing to the endogenous or acquired apoptotic resistance of cancer cells. Targeting necroptosis provides a novel strategy for chemotherapy, targeted drugs, and improves the efficacy of ICIs because of strong immunogenicity of necroptosis. Therefore, we systemically analyzed necroptosis landscape on therapy and prognosis in BLCA. We firstly divided BLCA patients from The Cancer Genome Atlas (TCGA) database into two necroptosis-related clusters (C1 and C2). Necroptosis C2 showed a significantly better prognosis than C1, and the differential genes of C2 and C1 were mainly related to the immune response according to GO and KEGG analysis. Next, we constructed a novel necroptosis related genes (NRGs) signature consisting of SIRT6, FASN, GNLY, FNDC4, SRC, ANXA1, AIM2, and IKBKB to predict the survival of TCGA-BLCA cohort, the accuracy of NRGsocre was also verified by external datasets. In addition, a nomogram combining NRGscore and several clinicopathological features was established to predict the BLCA patient’s OS more accurately and conveniently. We also found that NRGscore was significantly related to the infiltration levels of CD8 T cells, NK cells, and iDC cells, the gene expression of CTLA4, PD1, TIGIT, and LAG3 of TME, the sensitivity to chemotherapy and targeted agents in BLCA patients. In conclusion, the NRGscore has an excellent performance in evaluating the prognosis, clinicopathologic features, tumor microenvironment (TME) and therapeutic sensitivity of BLCA patients, which could be utilized as a guide for chemotherapy, ICIs therapy, and combination therapy.

Objectives To analyze the correlations between the expression and effect of DNA damage repair genes and the immune status and clinical outcomes of urothelial bladder cancer (BLCA) patients. In addition, we evaluate the value of utilizing DNA damage repair genes signatures as a prognosis model. Methods Two subtype groups (C1 and C2) were produced based on the varied expression of DNA damage repair genes. Significantly differentiated genes and predicted enriched pathways were obtained between the two subtypes. Through infiltrating and screening, 7 key genes were obtained and a 7-gene signature prognosis model was established based on the key genes. The efficacy and accuracy of this model in prognosis prediction was evaluated and verified in two independent databases. Also, the difference in biological functions, drug sensitivity, immune infiltration and affinity between the high-risk group and low-risk group was analyzed. Results DNA damage repair gene signature could significantly differentiate the BLCA into two molecular subgroups with varied genetic expression and enriched pathways. 7 key genes were screened out from the 232 candidate genes for prognosis prediction and helped establish a 7-gene signature prognosis model. Two independent patient cohorts (TCGA cohort and GEO cohort) were utilized to validate the efficacy of the prognosis model, which demonstrated an effective capability to differentiate and predict the overall survival of BLCA patients. Also, the high-risk group and low-risk group derived from the 7-gene model exhibited significantly difference in drug sensitivity, immune infiltration status and biological pathways enrichment. Conclusions Our established 7-gene signature model based on the DNA damage repair genes could serve as a novel prognosis predictive tool for BLCA. The differentiation of BLCA patients based on the 7-gene signature model may be of great value for the appropriate selection of specific chemotherapy agents and immune-checkpoint blockade therapy administration.