Evidence map›Paper›PMID 36973645›Full record

ArticleBMC bioinformatics2023

Identification and validation of tumor-infiltrating lymphocyte-related prognosis signature for predicting prognosis and immunotherapeutic response in bladder cancer.

Canxuan Li, Weibin Xie

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Article in BMC bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Canxuan LiDepartment of Urology, Shenshan Medical Center, Memorial Hospital of Sun Yat-Sen University, Shanwei, Guangdong, People's Republic of China.
Weibin XieDepartment of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, People's Republic of China. xiewb3@mail.sysu.edu.cn.

Funding

Guangdong Provincial Clinical Research Center for Urological Diseases 2020B1111170006
6 · The paper itself

Abstract

backgroundIt has been discovered that tumor-infiltrating lymphocytes (TILs) are essential for the emergence of bladder cancer (BCa). This study aimed to research TIL-related genes (TILRGs) and create a gene model to predict BCa patients' overall survival.

methodsThe RNA sequencing and clinical data were downloaded from the TGCA and GEO databases. Using Pearson correlation analysis, TILRGs were evaluated. Moreover, hub TILRGs were chosen using a comprehensive analysis. By dividing the TCGA-BCa patients into different clusters based on hub TILRGs, we were able to explore the immune landscape between different clusters.

resultsHere, we constructed a model with five hub TILRGs and split all of the patients into two groups, each of which had a different prognosis and clinical characteristics, TME, immune cell infiltration, drug sensitivity, and immunotherapy responses. Better clinical results and greater immunotherapy sensitivity were seen in the low-risk group. Based on five hub TILRGs, unsupervised clustering analysis identify two molecular subtypes in BCa. The prognosis, clinical outcomes, and immune landscape differed in different subtypes.

conclusionsThe study identifies a new prediction signature based on genes connected to tumor-infiltrating lymphocytes, providing BCa patients with a new theoretical target.

Indexed as

Lymphocytes, Tumor-InfiltratingUrinary Bladder NeoplasmsCluster AnalysisDatabases, FactualHumansImmunotherapyTumor MicroenvironmentBladder cancerImmunotherapy responsePrognostic signatureTumor-infiltrating lymphocytes

Identifiers

PMID36973645
PMCPMC10041757

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