Dataset Information

Integrative analysis of LAG3 immune signature and identification of a LAG3-related genes prognostic signature in kidney renal clear cell carcinoma.

ABSTRACT: Immune checkpoint blockade (ICB) therapy has resulted in improved overall survival in kidney renal clear cell carcinoma (KIRC), but most treated patients fail to show durable clinical responses. Lymphocyte activation gene-3 (LAG3) is a novel inhibitory immune checkpoint, but its expression pattern, prognostic value, and immunological role in KIRC remain unknown. In this study, we utilized TCGA_KIRC RNA-sequencing data to analyze the relationship between LAG3 expression and clinical features. The single-cell sequencing data and tissue immunofluorescence are employed to investigate the subcellular localization of LAG3 in KIRC. Kaplan-Meier plotter, TIMER, and TISIDB were used to assess the association between LAG3 expression and prognosis, as well as its correlation with immune-related components. We constructed the LAG3 interaction network by using STRING, GeneMANIA, BioGRID, and HitPredict databases. We found that LAG3 is upregulated and correlates with poor prognostic phenotype in KIRC. LAG3 is predominantly expressed on exhausted CD8+ T cells and shows strong co-expression with PDCD1 in KIRC. Moreover, our findings indicated that LAG3 not only inhibits T cell activation but also potentially regulates cell adhesion in KIRC. In conclusion, our study implies that LAG3 can serve as a potential prognostic biomarker for KIRC. Furthermore, blocking both LAG3 and PDCD1 may alleviate resistance to anti-PDCD1 therapy, providing novel insights for immunotherapy decision-making in KIRC patients.

SUBMITTER: Li J

PROVIDER: S-EPMC10911349 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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Integrative analysis of LAG3 immune signature and identification of a LAG3-related genes prognostic signature in kidney renal clear cell carcinoma.

Li Jie J Liu Chungan C Su Hui H Dong Hao H Wang Zhiqian Z Wang Yuqi Y Zhao Peng P Zhang Chaowei C Zhao Yi Y Ma Xuezhen X

Aging 20240125 3

Immune checkpoint blockade (ICB) therapy has resulted in improved overall survival in kidney renal clear cell carcinoma (KIRC), but most treated patients fail to show durable clinical responses. Lymphocyte activation gene-3 (LAG3) is a novel inhibitory immune checkpoint, but its expression pattern, prognostic value, and immunological role in KIRC remain unknown. In this study, we utilized TCGA_KIRC RNA-sequencing data to analyze the relationship between LAG3 expression and clinical features. The ...[more]

PMID: 38277212

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Project description:BackgroundKidney renal clear cell carcinoma (KIRC) lacks effective prognostic biomarkers and the role and mechanism of N6-methyladenosine (m6A) modification of long noncoding RNAs (lncRNAs) in KIRC remain unclear.MethodsWe extracted standard mRNA-sequencing and clinical data from the TCGA database. The prognostic risk model was obtained by Lasso regression and Cox regression. We randomly divided the samples into training and test sets, each taking half of the cases. Based on Lasso regression and Cox regression for training set, the prognostic risk signature was constructed; risk scores were calculated with the R package "glmnet." Based on the median value of the prognostic risk score, risk scores were calculated for each patient and we divided all KIRC samples into high-risk and low-risk groups. Then, high- and low-risk subtypes were established and their prognosis, clinical features, and immune infiltration microenvironment were evaluated in test set and the entire sampled data set. The reliability of the prognostic model was confirmed by receiver operating characteristic curve analysis.ResultsWe found 28 prognostic m6A-related lncRNAs and established a m6A-related lncRNAs prognostic signature. Risk score=AC015813.1∗(0.0086)+EMX2OS∗(-0.0101)+LINC00173∗(0.0309)+PWAR5∗(-0.0146)+SNHG1∗(0.0043). The signature showed a better predictive ability than other clinical indicators, including tumor node metastasis classification (TNM), histological, and pathological stages. In the high-risk group, M0 macrophages, CD8+ T cells, and regulatory T cells had significantly higher scores. Contrarily, in the low-risk group, activated dendritic cells, M1 macrophages, mast resting cells, and monocytes had significantly higher scores. In the high-risk group, LSECtin was overexpressed. In the low-risk group, PD-L1 was overexpressed. Moreover, high-risk patients may benefit more from AZ628.ConclusionsIn conclusion, prognosis prediction of patients with KIRC and new insights for immunotherapy are provided by the m6A-related lncRNA prognostic signature.

Project description:BackgroundNecroptosis is progressively becoming an important focus of research because of its role in the pathogenesis of cancer and other inflammatory diseases. Our study is designed to anticipate the survival time of kidney renal clear cell carcinoma (KIRC) by constructing a prognostic signature of necroptosis-related genes.MaterialsClinical information and RNA-seq data were acquired from Renal Cell Cancer-European Union (RECA-EU) and The Cancer Genome Atlas- (TCGA-) KIRC, respectively. ConsensusClusterPlus was used to identify molecular subtypes, and the distribution of immune cell infiltration, anticancer drug sensitivity, and somatic gene mutations was studied in these subtypes. Subsequently, LASSO-Cox regression and univariate Cox regression were also carried out to construct a necroptosis-related signature. Cox regression, survival analysis, clinicopathological characteristic correlation analysis, nomogram, cancer stem cell analysis, and receiver operating characteristic (ROC) curve were some tools employed to study the prognostic power of the signature.ResultsBased on the expression patterns of 66 survival-related necroptosis genes, we classified the KIRC into three subtypes (C1, C2, and C3) that are associated with necroptosis, which had significantly different tumor stem cell components. Among these, C2 patients had a longer survival time and enhanced immune status and were more sensitive to conventional chemotherapeutic drugs. Moreover, in order to predict the prognosis of KIRC patients, five genes (BMP8A, TLCD1, CLGN, GDF7, and RARB) were used to develop a necroptosis-related prognostic signature, which had an acceptable predictive potency. The results from Cox regression and stratified survival analysis revealed that the signature was an independent prognostic factor, whereas the nomogram and calibration curve demonstrated satisfactory survival time prediction based on the risk score.ConclusionsThree molecular subtypes and five necroptosis-related genes were discovered in KIRC using data from TCGA-KIRC and RECA-EU. Thus, a new biomarker and a potentially effective therapeutic approach for KIRC patients were provided in the current study.

Dataset Information

Integrative analysis of LAG3 immune signature and identification of a LAG3-related genes prognostic signature in kidney renal clear cell carcinoma.

Publications

Integrative analysis of LAG3 immune signature and identification of a LAG3-related genes prognostic signature in kidney renal clear cell carcinoma.

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