Evidence map›Paper›PMID 39565540›Full record

ArticleDiscover oncology2024

Pyroptosis-related lncRNAs are potential biomarkers for predicting prognoses and immune landscapes in patients with gastric adenocarcinoma.

Haidu Hong, Yuancheng Huang, Zehong Yang, Xiaotao Jiang, Hong Liu

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Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Haidu Hong *School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, Guangdong, China.
Yuancheng Huang *Department of Oncology, Dongguan People's Hospital, The Tenth Affiliated Hospital of Southern Medical University, Dongguan, 523000, Guangdong, China.
Zehong YangFirst Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, 510405, Guangdong, China.
Xiaotao JiangFirst Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, 510405, Guangdong, China.
Hong LiuDepartment of Traditional Chinese Medicine, The First Affiliated Hospital of Guangdong Pharmaceutical University, Gonghexiheng Street 1, Yuexiu District, Guangzhou, 510080, Guangdong, China. 303280010@qq.com.

Funding

Basic and Applied Basic Research Fund Project of Guangdong Province 2020A1515110615Medical Research Foundation of Guangdong Province B2020043The National Natural Science Foundation 82205047
6 · The paper itself

Abstract

objectivesThe purpose of this study was to investigate the significance of pyroptosis-related lncRNAs (PRlncRNA) in predicting prognoses and immune landscapes of patients with gastric adenocarcinoma (STAD).

methodsTranscriptomic data and clinicopathological data were obtained from The Cancer Genome Atlas database. Based on correlation analysis and univariate Cox regression, prognostic PRlncRNA were identified. Subsequently, a PRlncRNA prognostic signature (PRLPS) was generated via least absolute shrinkage and selection operator (LASSO) regression, Kaplan-Meier method, receiver operating characteristic (ROC) curves, principal component analysis, and univariate and multivariate regression. Besides, the clinicopathological characteristics, tumor microenvironment (TME) scores, the immune landscapes in different risk subgroups were explored. Moreover, based on three PRlncRNA, we constructed a competing endogenous RNA (ceRNA) network. Additionally, Gene Set Enrichment Analysis (GSEA), Kyoto Encyclopedia of Genes and Genomes pathways (KEGG) and Gene Ontology (GO) analysis were performed for biological functional analysis based on the difference between high- and low- risk groups, which also used to screen out potential STAD drugs.

results21 PRlncRNA made up the prognostic signature, which had significant value in predicting the overall survival (OS), clinicopathological features, TME, immune checkpoint genes expression, and the response to immune checkpoint inhibitors of patients with STAD. In a addition, we constructed a ceRNA network comprising 3 PRlncRNAs and 69 mRNAs. The function of PRlncRNA was related to cancer-associated pathways. Ten small molecular drugs that might improve the prognosis of patients were screened out by connectivity maps.

conclusionsUsing PRlncRNA as a prognostic indicator for STAD, we identified predictive biomarkers and immunotherapy targets while refreshing our understanding.

Indexed as

Gastric adenocarcinomaImmunotherapyLong non-coding RNAsPrognostic signaturePyroptosisTumor microenvironment

Identifiers

PMID39565540
PMCPMC11579272

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