Identification of a Hypoxia-Related Molecular Classification and Hypoxic Tumor Microenvironment Signature for Predicting the Prognosis of Patients with Triple-Negative Breast Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34490098", "kind": "science-record", "revision": 8, "content_hash": "sha256:b2df7067c734f8341fcb7818616776eb80ec4314ad78f66716dea6a8ed7aa81c", "created_at": "2026-11-01T15:41:51Z", "updated_at": "2026-11-01T22:47:27Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of a Hypoxia-Related Molecular Classification and Hypoxic Tumor Microenvironment Signature for Predicting the Prognosis of Patients with Triple-Negative Breast Cancer.", "doi": "10.3389/fonc.2021.700062", "pmid": "34490098", "authors": ["Xiaoli Sun", "Huan Luo", "Chenbo Han", "Yu Zhang", "Cunli Yan"], "journal": "Frontiers in oncology", "year": 2021, "abstract": "PURPOSE: The hypoxic tumor microenvironment was reported to be involved in different tumorigenesis mechanisms of triple-negative breast cancer (TNBC), such as invasion, immune evasion, chemoresistance, and metastasis. However, a systematic analysis of the prognostic prediction models based on multiple hypoxia-related genes (HRGs) has not been established in TNBC before in the literature. We aimed to develop and verify a hypoxia gene signature for prognostic prediction in TNBC patients.\nMETHODS: The RNA sequencing profiles and clinical data of TNBC patients were generated from the TCGA, GSE103091, and METABRIC databases. The TNBC-specific differential HRGs (dHRGs) were obtained from differential expression analysis of hypoxia cultured TNBC cell lines compared with normoxic cell lines from the GEO database. Non-negative matrix factorization (NMF) method was then performed on the TNBC patients using the dHRGs to explore a novel molecular classification on the basis of the dHRG expression patterns. Prognosis-associated dHRGs were identified by univariate and multivariate Cox regression analysis to establish the prognostic risk score model.\nRESULTS: Based on the expressions of 205 dHRGs, all the patients in the TCGA training cohort were categorized into two subgroups, and the patients in Cluster 1 demonstrated worse OS than those in Cluster 2, which was validated in two independent cohorts. Additionally, the effects of somatic copy number variation (SCNV), somatic single nucleotide variation (SSNV), and methylation level on the expressions of dHRGs were also analyzed. Then, we performed Cox regression analyses to construct an HRG-based risk score model (3-gene dHRG signature), which could reliably discriminate the overall survival (OS) of high-risk and low-risk patients in TCGA, GSE103091, METABRIC, and BMCHH (qRT-PCR) cohorts.\nCONCLUSIONS: In this study, a robust predictive signature was developed for patients with TNBC, indicating that the 3-gene dHRG model might serve as a potential prognostic biomarker for TNBC.", "claims": [{"id": "claim-method", "statement": "The GSE104193 cohort was Counts data using RNA-Seq and was analyzed using the DESeq2 package in R. The GSE33950 cohort was chip data, which was analyzed using limma package in R.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34490098", "locator": "sections[4] \"Identification of TNBC-Specific HRGs\" paragraph 2", "quote": "The GSE104193 cohort was Counts data using RNA-Seq and was analyzed using the DESeq2 package in R. The GSE33950 cohort was chip data, which was analyzed using limma package in R."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The GSE104193, GSE33950, and GSE103091 datasets analyzed during the current study are available in the GEO repository (http://www.ncbi.nlm.nih.gov/geo/). The RNA sequencing data and clinical information of breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA, http://portal.gdc.cancer.gov/) and METABRIC (http://www.METABRIC.org/) datasets. The qPCR data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34490098", "locator": "sections[18] \"Data Availability Statement\" paragraph 2", "quote": "The GSE104193, GSE33950, and GSE103091 datasets analyzed during the current study are available in the GEO repository (http://www.ncbi.nlm.nih.gov/geo/). The RNA sequencing data and clinical information of breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA, http://portal.gdc.cancer.gov/) and METABRIC (http://www.METABRIC.org/) datasets. The qPCR data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:34490098"], "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:GSE103091"], "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:GSE103091"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34490098", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2021.700062", "sha256": "sha256:cd05f6b1762f6dd27a00a42b7db3ca227fe3d7d3aa20aa7a43a62dcb1388d0f2", "bytes": 44551, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2021.700062", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8416750", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE103091", "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=GSE103091", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE103091", "version": null, "note": "The GSE104193, GSE33950, and GSE103091 datasets analyzed during the current study are available in the GEO repository (http://www.ncbi.nlm.nih.gov/geo/). The RNA sequencing data and clinical information of breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA, http://portal.gdc.cancer.gov/) and METABRIC (http://www.METABRIC.org/) datasets. The qPCR data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The GSE104193, GSE33950, and GSE103091 datasets analyzed during the current study are available in the GEO repository (http://www.ncbi.nlm.nih.gov/geo/). The RNA sequencing data and clinical information of breast cancer patients were downloaded from The Cancer Genome Atlas (TCGA, http://portal.gdc.cancer.gov/) and METABRIC (http://www.METABRIC.org/) datasets. 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