ArticleScientific reports2023
Identification and validation of tumor microenvironment-related signature for predicting prognosis and immunotherapy response in patients with lung adenocarcinoma.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed, 8 citations in OpenAlex.
- CD168 in lung adenocarcinoma: prognostic relevance, immune feature associations, and MAPK/ERK pathway enrichment.Medical oncology (Northwood, London, England) · 2026Article
- Automated quantification of tumor-infiltrating lymphocytes by machine learning reveals prognostic and immunogenomic features in lung cancer.Scientific reports · 2026Article
- Tumor prognostic risk stratification based on pseudo-time analysis of single-cell sequencing for patients with lung adenocarcinoma.Journal of thoracic disease · 2025Article
- A review of enhanced biosignature immunotherapy tools for predicting lung cancer immune phenotypes using deep learning.Discover oncology · 2025Review
- The role of the tumour microenvironment in lung cancer and its therapeutic implications.Medical oncology (Northwood, London, England) · 2025Review
- Single-Cell Transcriptomic Profiling Reveals KRAS/TP53-Driven Neutrophil Reprogramming in Luad: A Multi-Gene Prognostic Model and Therapeutic Targeting of RHOV.Oncology research · 2025Article
- Comprehensive landscape of junctional genes and their association with overall survival of patients with lung adenocarcinoma.Frontiers in molecular biosciences · 2024Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mounting evidence has found that tumor microenvironment (TME) plays an important role in the tumor progression of lung adenocarcinoma (LUAD). However, the roles of tumor microenvironment-related genes in immunotherapy and clinical outcomes remain unclear. In this study, 6 TME-related genes (PLK1, LDHA, FURIN, FSCN1, RAB27B, and MS4A1) were identified to construct the prognostic model. The established risk scores were able to predict outcomes at 1, 3, and 5 years with greater accuracy than previously known models. Moreover, the risk score was closely associated with immune cell infiltration and the immunoregulatory genes including T cell exhaustion markers. In conclusion, the TME risk score can function as an independent prognostic biomarker and a predictor for evaluating immunotherapy response in LUAD patients, which provides recommendations for improving patients' response to immunotherapy and promoting personalized tumor immunotherapy in the future.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.