An investigation to identify tumor microenvironment-related genes of prognostic value in lung squamous cell carcinoma based on The Cancer Genome Atlas.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35116510", "kind": "science-record", "revision": 4, "content_hash": "sha256:e82bbed6ece8cb764521c068ea2e3eeb723f3b430aeb9179387d1b3c2159b433", "created_at": "2026-11-01T17:36:50Z", "updated_at": "2026-11-01T22:05:44Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "An investigation to identify tumor microenvironment-related genes of prognostic value in lung squamous cell carcinoma based on The Cancer Genome Atlas.", "doi": "10.21037/tcr-21-401", "pmid": "35116510", "authors": ["Huan Liu", "Boxuan Liu", "Lei Zhang", "Mingzhen Li", "Cheng Chen", "Shaohua He", "Tingting Luo", "Xiaohui He", "Liming Tan"], "journal": "Translational cancer research", "year": 2021, "abstract": "BACKGROUND: Lung 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.\nMETHODS: Estimation 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.\nRESULTS: The 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.\nCONCLUSIONS: In 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.", "claims": [{"id": "claim-data-access", "statement": "The publicly accessible LUSC dataset was downloaded from TCGA (http://portal.gdc.cancer.gov/). The dataset included patients’ gene expression profiling data (level 3), as well as clinical details such as sex, age, histological type, and survival time.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35116510", "locator": "sections[3] \"Data source\" paragraph 2", "quote": "The publicly accessible LUSC dataset was downloaded from TCGA (http://portal.gdc.cancer.gov/). The dataset included patients’ gene expression profiling data (level 3), as well as clinical details such as sex, age, histological type, and survival time."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Six TME-related genes with prognostic value in LUSC—BHMT2, FES, HSPB7, NOVA2, LPAP2, and SEMA3B—were identified and verified using GEO datasets.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35116510", "locator": "sections[13] \"Survival analysis and verification with gene expression omnibus data\" paragraph 2", "quote": "Finally, BHMT2, FES, HSPB7, NOVA2, LPAP2, and SEMA3B (BFHNLS) were identified as potential predictors of a poor prognosis (Figure 4), and were verified using the PrognoScan online tool and Gene Expression Omnibus datasets GSE4573 and GSE17710 (Figure 5)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Six TME-related genes with prognostic value in LUSC—BHMT2, FES, HSPB7, NOVA2, LPAP2, and SEMA3B—were identified and verified using GEO datasets.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35116510"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE17710"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE17710"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35116510", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tcr-21-401", "sha256": "sha256:3d1dcefb325763306b2817f87edfcedfa469fed042c19c757bd606457e32238f", "bytes": 38647, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.21037/tcr-21-401", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8798203", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE17710", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17710", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE17710", "version": null, "note": "The publicly accessible LUSC dataset was downloaded from TCGA (http://portal.gdc.cancer.gov/). 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