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A novel 6-gene signature derived from tumor-infiltrating T cells and neutrophils predicts survival of bladder urothelial carcinoma.

ABSTRACT: Intratumoral immune cells were reported to be associated with prognosis of bladder urothelial carcinoma (BUC). However, the role of immune cells related genes in BUC prognosis is less well defined. In the study, we analyzed data retrieved from the Cancer Genome Atlas database and found higher neutrophils and lower T cells infiltration in BUC tumor tissues were significantly correlated with patients' worse prognosis. Additionally, the expression levels of 164 genes were significantly correlated with T cells and neutrophils proportions. A Cox proportional-hazards model integrating 6 genes expression (EMP1, RASGRP4, HSPA1L, AHNAK, SLC1A6, and PRSS8) was identified. The 6-gene signature outperformed other clinical factors in risk prediction and was an independent prognostic factor for BUC. The findings were further conformed in three Gene Expression Omnibus datasets (n=331) and Jiangsu Province Hospital cohort (n = 46). Gene set enrichment analysis revealed that the model was highly involved in some immune-related pathways. A comprehensive nomogram combining the model and other clinical parameters was finally constructed to facilitate clinical application. In conclusion, a T cell and neutrophil-associated 6-gene prognostic model was identified for the survival prediction of BUC patients.

SUBMITTER: Zou X

PROVIDER: S-EPMC8714163 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe tumor microenvironment (TME) regulates the proliferation and metastasis of solid tumors and the effectiveness of immunotherapy against them. We investigated the prognostic role of TME-related genes based on transcriptomic data of bladder urothelial carcinoma (BLCA) and formulated a prediction model of TME-related signatures.MethodsMolecular subtypes were identified using the non-negative matrix factorization (NMF) algorithm based on TME-related genes from the TCGA database. TME-related genes with prognostic significance were screened with univariate Cox regression analysis and lasso regression. Nomogram was developed based on risk genes. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used for inner and outer validation of the model. Risk scores (RS) of patients were calculated and divided into high-risk group (HRG) and low-risk group (LRG) to compare the differences in clinical characteristics and PD-L1 treatment responsiveness between HRG and LRG.ResultsWe identified two molecular subtypes (C1 and C2) according to the NMF algorithm. There were significant differences in overall survival (OS) (p<0.05), progression-free survival (PFS) (p<0.05), and immune cell infiltration between the two subtypes. A total of eight TME-associated genes (CABP4, ZNF432, BLOC1S3, CXCL11, ANO9, OAS1, FBN2, CEMIP) with independent prognostic significance were screened to build prognostic risk models. Age (p<0.001), grade (p<0.001), and RS (p<0.001) were independent predictors of survival in BLCA patients. The developed RS nomogram was able to predict the prognosis of BLCA patients at 1, 3, and 5 years more potentially than the models of other investigators according to ROC and DCA. RS showed significantly higher values (p = 0.047) in patients with stable disease (SD)/progressive disease (PD) compared to patients with complete response (CR)/partial response (PR).ConclusionsWe successfully clustered and constructed predictive models for TME-associated genes and helped guide immunotherapy strategies.

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A novel 6-gene signature derived from tumor-infiltrating T cells and neutrophils predicts survival of bladder urothelial carcinoma.

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