ArticleAmerican journal of translational research2022
Epithelial-mesenchymal transition-related lncRNAs associated with prognosis and immune cell infiltration in lung adenocarcinoma.
Article in American journal of translational research, 2022. 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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Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- Construction of an EMT-related lncRNA prognostic signature for lung adenocarcinoma and functional verification of its hub gene LINC01615.Journal of cancer research and clinical oncology · 2023Article
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLung adenocarcinoma (LUAD) remains the most common type of lung cancer and is associated with distant metastasis and poor prognosis. Epithelial-mesenchymal transition (EMT) plays crucial roles in carcinogenesis, embryogenesis, and wound healing. EMT-related molecules may be adopted for early diagnosis and prognosis of cancer and targeting them may constitute an attractive strategy for treatment. This study aims to identify the EMT-related long non-coding RNAs (lncRNAs) and develop a risk signature to accurately predict the prognosis of LUAD patients.
methodsThe RNA-seq data and corresponding clinical profiles were obtained from LUAD cohort of The Cancer Genome Atlas (TCGA) database. EMT-related lncRNAs significantly associated with prognosis were identified by Pearson correlation analysis and univariate regression analysis. Subsequently, an EMT-related prognostic risk signature was developed through LASSO and multivariate regression analyses. Kaplan Meier and receiver operating characteristic curve analysis were implemented to assess the predictive performance of the signature. The nomogram was constructed to predict the 1-year, 3-year, and 5-year overall survival of LUAD patients. Additionally, enrichment analyses were carried out to identify probable biologic processes and cellular pathways involved in the signature. The correlation of immune cell infiltration and risk score was also evaluated by CIBERSORT algorithm. Finally, we constructed a ceRNA network to further study possible downstream targets and molecular mechanisms of EMT-related lncRNAs in LUAD.
resultsEight EMT-related lncRNAs were identified to develop a prognostic risk signature in LUAD. Patients with high-risk scores had worse survival outcomes than those with low-risk scores. The signature showed robust predictive potential, and was verified to be an independent prognostic factor. Moreover, the risk score based on the signature was significantly correlated with immune cell infiltration in LUAD.
conclusionsWe established and validated a prognostic signature that reflects the tumor microenvironment characteristics and predicts the outcomes for LUAD.
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36398231PMC9641461W4309412228What OpenQuestion holds
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