Sign in
Cancer BiologybioRxiv

Analysis and Identification of Necroptosis Landscape on Therapy and Prognosis in Bladder Cancer

Z. Zhao, N. Jiang, Y. Zhang, Y. Bai, T. Liu, T. Li, H. Guo, R. Yang

Abstract

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 patients 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.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISGarcía-Agul '26Zhang '26Gu '23Lilong '25Wang '23Salome '22
76% semantic matchCancer Biology
Juan García-Agulló, Vanesa Santos, Mark Kalisz+12 more·bioRxiv·May 18, 2026