ArticleFrontiers in genetics2022
Characterization of the Immune Cell Infiltration Landscape Uncovers Prognostic and Immunogenic Characteristics in Lung Adenocarcinoma.
Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed, 8 citations in OpenAlex.
- Metabolic signature of phosphoethanolamine and arginine pathways predicts prognosis and immunotherapy resistance in lung adenocarcinoma.Translational cancer research · 2026Article
- A mutational signature for brain metastasis tropism in lung adenocarcinoma.Discover oncology · 2026Article
- Immune cell metabolic reprogramming in hepatocellular carcinoma: mechanisms, tumor microenvironment, and future immunotherapeutic directions.Frontiers in immunology · 2025Review
- ZNF197-AS1/miR-425/GABARAPL1 axis: a novel regulatory mechanism in uveal melanoma.American journal of physiology. Cell physiology · 2024Article
- Epithelial-Mesenchymal Transition in Non-Small Cell Lung Cancer Management: Opportunities and Challenges.Biomolecules · 2024Review
- Construction of a multiple-class classifier based on mRNAs and lncRNA FAM66A and PSORS1C3 for predicting distant metastasis in lung adenocarcinoma.Annals of translational medicine · 2022Article
- Tumor-infiltrating immune cells based TMEscore and related gene signature is associated with the survival of CRC patients and response to fluoropyrimidine-based chemotherapy.Frontiers in oncology · 2022Article
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8 authors at 3 institutions in 1 country.
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Abstract
The immune cell infiltration in TME has been reported to be associated with prognosis and immunotherapy efficiency of lung cancers. However, to date, the immune infiltrative landscape of lung adenocarcinoma (LUAD) has not been elucidated yet. Therefore, this study aimed to identify a new transcriptomic-based TME classification and develop a risk scoring system to predict the clinical outcomes of patients with LUAD. We applied "CIBERSORT" algorithm to analyze the transcriptomic data of LUAD samples and classified LUAD into four discrete subtypes according to the distinct immune cell infiltration patterns. Furthermore, we established a novel predictive tool (TMEscore) to quantify the immune infiltration patterns for each LUAD patient by principal component analysis. The TMEscore displayed as a reliable and independent prognostic biomarker for LUAD, with worse survival in TMEscrore-high patients and better survival in TMEscrore-low patients in both TCGA and other five GEO cohorts. In addition, enriched pathways and genomic alterations were also analyzed and compared in different TMEscore subgroups, and we observed that high TMEscore was significantly correlated with more aggressive molecular changes, while the low TMEscore subgroup enriched in immune active-related pathways. The TMEscore-low subtype showed overexpression of PD-1, CTLA4, and associations of other markers of sensitivity to immunotherapy, including TMB, immunophenoscore (IPS) analysis, and tumor immune dysfunction and exclusion (TIDE) algorithm. Conclusively, TMEscore is a promising and reliable biomarker to distinguish the prognosis, the molecular and immune characteristics, and the benefit from ICIs treatments in LUAD.
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