Clinical value of anoikis-related genes and molecular subtypes identification in bladder urothelial carcinoma and in vitro validation

• DOI: 10.3389/fimmu.2023.1122570
• Publication Date: 2023-05-18T05:12:59Z
• Authors: Ying Dong; Chaojie Xu; Ganglin Su; Yanfeng Li; Bing Yan; Yuhan Liu; Tao Yin; Shuanzhu Mou; Hongbing Mei
• Keywords: Anoikis; Identification

Background Anoikis is a programmed cell death process that was proven to be associated with cancer. Uroepithelial carcinoma of the bladder (BLCA) malignant disease urinary tract and has strong metastatic potential. To determine whether anoikis-associated genes can predict prognosis BLCA accurately, we evaluated prognostic value in constructed best model prognosis. Method The transcriptome data were downloaded from TCGA GEO databases, differential expression selected then clustered using non-negative matrix factorization (NMF). most correlation anoikis screened identified univariate Cox regression, lasso multivariate regression. dataset used for external validation. Nomograms created based on risk characteristics combination clinical variants performance validated receiver operating characteristic (ROC) curves. immunotherapeutic significance this score assessed immune phenomenon (IPS). IC50 values predictive chemotherapeutic agents calculated. Finally, RT-qPCR mRNA four genes, CALR , FASN CASP6 RAD9A . Result We 406 tumor samples 19 normal tissue database. Based classified patients into two subtypes (C1 C2) NMF method. Subsequently, nine core by multiple methods after analysis, which construct profiles. design nomograms profiles variables, ROC, calibration curves confirmed could well have ability survival at 1, 3, 5 years. By predicting drugs, it learned high-risk group (HRG) more susceptible paclitaxel, gemcitabine, cisplatin, low-risk (LRG) veriparib afatinib. Conclusion In summary, applied as predictor practice.