ArticleTranslational cancer research2021
An investigation to identify tumor microenvironment-related genes of prognostic value in lung squamous cell carcinoma based on The Cancer Genome Atlas.
Article in Translational cancer research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 7 citations in OpenAlex.
- Effects of Camrelizumab Combined with First-Line Chemotherapy on Serum SCC, VEGF Levels, and Adverse Reactions in Patients with Advanced Squamous Cell Carcinoma of the Lung.Computational intelligence and neuroscience · 2022Trial
- The role of the tumor microenvironment in drug resistance acquisition in lung squamous cell carcinoma.Journal of experimental & clinical cancer research : CR · 2026Review
- Article
- Mendelian randomization study on the causal relationships among fasting blood glucose, plasma proteins, and squamous cell lung cancer.Discover oncology · 2025Article
- A novel tumor microenvironment-related gene signature with immune features for prognosis of lung squamous cell carcinoma.Journal of cancer research and clinical oncology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLung squamous cell carcinoma (LUSC) is a prevalent and lethal malignancy with a poor clinical prognosis. Major constituents of the tumor microenvironment (TME) include infiltrating immune cells and stromal cells, which play a pivotal role in the progression and growth of the disease. To improve the understanding of the prognostic influence of immune and stromal cell-related genes for patients with the disease, we performed a comprehensive bioinformatics analysis to identify TME-relevant biomarkers, and investigated the potential role of these candidate signatures in LUSC.
methodsEstimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) assessed the samples of LUSC obtained from The Cancer Genome Atlas (TCGA). The samples were grouped according to their immune/stromal scores (high or low). Multivariate cox regression and receiver operating characteristic curves (ROC) were implemented to construct the risk assessment model for prognosis prediction. The co-upregulated differentially expressed genes (DEGs) in the immune and stromal groups were used for further analyses. Overall survival (OS) curves were used to determine the prognostic value of the DEGs, and the TME-related DEGs were verified with Gene Expression Omnibus (GEO) datasets. The functional assessments were performed include Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) analyses.
resultsThe immune/stromal scores calculated by ESTIMATE showed significant associations with OS (log-rank P<0.05). In addition, the prognostic risk score model based on immune and stromal scores also showed significant correlations with OS. A total of 94 TME-related genes were obviously related to poor OS. Among them, BHMT2, FES, HSPB7, NOVA2, LPAP2, and SEMA3B (BFHNLS) were confirmed using GSE4573 and GSE17710 datasets. The functional assessments exhibited those TME-related genes mostly participate in immune response, cytokine-cytokine receptor interaction, and metabolic pathways, which elucidated the probable correlation of TME with tumorigenesis in LUSC.
conclusionsIn this study, 6 potential biomarkers named BFHNLS were identified as TME-related genes with prognostic value based on immune and stromal scores of LUSC patients of TCGA, and were verified using GEO datasets, which might serve as therapeutic targets.
Indexed as
Identifiers
What OpenQuestion holds
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.