ArticleCellular oncology (Dordrecht, Netherlands)2020
Systematic profiling of immune signatures identifies prognostic predictors in lung adenocarcinoma.
Article in Cellular oncology (Dordrecht, Netherlands), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- 17-hydroxy-jolkinolide B potentiated CTLA4ab therapy through targeting tumor suppression and immune activation by downregulating PD-L1 expression in lung adenocarcinoma.Journal of thoracic disease · 2024Article
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- circ_0004140 promotes LUAD tumor progression and immune resistance through circ_0004140/miR-1184/CCL22 axis.Cell death discovery · 2022Article
- Identification of MAP3K15 as a potential prognostic biomarker and correlation with immune infiltrates in osteosarcoma.Annals of translational medicine · 2021Article
- Identification of Tumor Microenvironment-Related Prognostic lncRNAs in Lung Adenocarcinoma.Frontiers in oncology · 2021Article
- Development and external validation of a composite immune-clinical prognostic model associated with EGFR mutation in East-Asian patients with lung adenocarcinoma.Therapeutic advances in medical oncology · 2021Article
- Exploration of predictive and prognostic alternative splicing signatures in lung adenocarcinoma using machine learning methods.Journal of translational medicine · 2020Article
- Identification of 5-Gene Signature Improves Lung Adenocarcinoma Prognostic Stratification Based on Differential Expression Invasion Genes of Molecular Subtypes.BioMed research international · 2020Article
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Authors and funding
14 authors.
Funding
Abstract
purposeLung adenocarcinoma (LUAD) is the predominant subtype of lung cancer, with increasing evidence showing clinical benefits of immunotherapy. However, a lack of integrated profiles of complex LUAD immune microenvironments hampers the application of immunotherapy, resulting in limited eligible patient populations as well as drug resistance problems. Here, we aimed to systematically profile the immune signatures of LUADs and to assess the role of the immune microenvironment in patient outcome.
methodsWe systematically profiled the immune signatures of LUADs deposited in the TCGA and GEO databases using a total of 730 immune-related genes. Differential expression analysis was used to identify dysregulated genes. Univariate Cox analysis followed by robust likelihood-based survival analysis and multivariate Cox analysis were applied to construct an immune-related prognostic model.
resultsWe found that differentially expressed immune genes were mainly enriched in immune cell proliferation, migration, activation and the NF-κB and TNF signaling pathways. The 10-immune gene predictive model that we constructed could differentiate LUAD patients with different overall survival times in several datasets, with areas under the curve (AUCs) of 0.67, 0.69, 0.72 and 0.74. LUAD patients with high- or low-risk scores exhibited distinct immune cell compositions, which may explain the prognostic significance of our model.
conclusionsOur results add to the current knowledge of immune processes in LUADs and underscore the critical role of the immune microenvironment in LUAD patient outcome.
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