A novel molecular classification based on TP53 mutation to predict bladder cancer prognosis and immunotherapy efficacy

Abstract

Abstract Background The efficacy of TP53, the most widely researched mutation genetic genes in tumor, in tumor metabolic reprogramming remains unclear. Methods The differential analysis of gene expression data information of TP53 mutation and TP53 wild-type patients were conducted to identify TP53 mutation-associated metabolic genes (TMGs), which were used to identify and verify a TP53 mutation-associated metabolic signature (TMMS). Comprehensive bioinformatics analyses were performed to explore biological interpretability and clinical application value of TMMS. Results According to TP53 mutation, 218 TMGs were detected. The TMMSscore including GFPT2, ATP6V1C2, IMPDH1, CKMT2, PPT2, CAD, HNMT, INPP1 and PLCH1 genes were constructed and verified to determine a low TMMSscore group, which showed more favorable prognosis in the TCGA and GEO cohort compared to a high TMMSscore group. The high TMMSscore group contained more reprogrammed metabolic pathways, which had glycan-related metabolism and less immune infiltration. The low TMMSscore group showed more immune cell infiltration, which included anti-tumor cells in BC, for instance CD8(+) T cells, Treg cells and less metabolic reprogramming. In two immunotherapy cohorts of anti-PD-1 treated lung and kidney cancers, TMMSscore was used to distinguish a low TMMSscore group with better immunotherapy efficacy from a high TMMSscore group and identify a key differentially expressed genes (DEGs) termed COL1A2. In immunohistochemistry experiments on three tumor tissue samples and three normal tissue samples from three bladder cancer patients, COL1A2 showed high expression characteristics in tumors. Conclusions The TMMS based on metabolic genes affected by TP53 mutations predicted the prognosis of BC and develop a guiding strategy for immune checkpoint therapy. This research brought a new insight into the involvement of TP53 mutations in tumor metabolic reprogramming.