ArticleOncogene2021
A risk model developed based on tumor microenvironment predicts overall survival and associates with tumor immunity of patients with lung adenocarcinoma.
Article in Oncogene, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 196 papers.
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196 citing papers in PubMed, 262 citations in OpenAlex.
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- Development and validation of a 5mC-based prognostic model for lung adenocarcinoma survival.Cell reports. Medicine · 2026Article
- Research progress on long non‑coding RNAs in lung cancer (Review).Molecular medicine reports · 2026Review
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- Regulation of G protein-coupled receptor kinase 2 and its role in tumors.Journal of translational medicine · 2026Review
- Harnessing machine learning-driven multiomics integration: deciphering programmed cell death networks for prognostication and immunotherapy prediction in lung adenocarcinoma.Cell biology and toxicology · 2026Article
- Identification and validation of prognostic genes related to glycolysis and M2 macrophage in hepatocellular carcinoma: an integrated analysis of bulk RNA sequencing and single-cell RNA sequencing.Frontiers in immunology · 2026Article
- The efferocytosis-related genes of SLC26A6, TYRO3, and PDK4 have been identified as predictors of prognosis in hepatocellular carcinoma and are associated with the immune status.International journal of medical sciences · 2026Article
- Prognostic value of vascular endothelial growth factor subtypes and risk models constructed based on the common pathway of ulcerative colitis and colon cancer.Open medicine (Warsaw, Poland) · 2026Article
- Article
- Machine learning-based construction of an oxidative stress-related model reveals molecular subtypes and tumor microenvironment infiltration signatures in colon cancer.Discover oncology · 2025Article
- CYP27A1 suppresses brain metastasis via ferroptosis in lung adenocarcinoma: a six-gene signature predicting the immunotherapy response and clinical outcomes.Cancer cell international · 2025Article
136 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumor microenvironment (TME) has been reported to exhibit a crucial effect in lung cancer. Therefore, this study was aimed to investigate the genes associated with TME and develop a risk score to predict the overall survival (OS) of patients with lung adenocarcinoma (LUAD) based on these genes. The immune and stromal scores were generated by the ESTIMATE algorithm for LUAD patients in The Cancer Genome Atlas (TCGA) database. Differentially expressed gene and weighted gene co-expression network analyses were used to derive immune- and stromal-related genes. The Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression was applied for further selection and the selected genes were inputted into stepwise regression to develop TME-related risk score (TMErisk) which was further validated in Gene Expression Omnibus (GEO) datasets. TMErisk-related biological phenotypes were analyzed in function enrichment, tumor immune signature, and tumor mutation signature. The patient's response to immunotherapy was inferred by the tumor immune dysfunction and exclusion (TIDE) score and immunophenoscore (IPS). According to our results, TMErisk was developed based on SERPINE1, CX3CR1, CD200R1, GBP1, IRF1, STAP1, LOX, and OR7E47P. Furthermore, high TMErisk was identified as a poor factor for OS in TCGA and GEO datasets, as well as in subgroup analysis with different gender, smoking status, age, race, anatomic site, therapies, and tumor-node-metastasis (TNM) stages. Higher TMErisk is also associated negatively with the abundance of B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and other stromal or immune cells. Several genes of the human leukocyte antigen (HLA) family and immune checkpoints were less expressed in the high-TMErisk group. Mutations of 19 genes occurred more frequently in the high-TMErisk group. These mutations may be associated with TME change and indicate patients' response to immunotherapy. According to our analyses, a lower TMErisk score may indicate better response and OS outcome of immunotherapy.
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