A panel of Transcription factors identified by data mining can predict the prognosis of head and neck squamous cell carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31787845", "kind": "science-record", "revision": 6, "content_hash": "sha256:aca13e6c5d2aacc397e26ee8bb318ed6e6702d2f046c8e2ea3d2f4fce4cca72f", "created_at": "2026-11-01T15:40:52Z", "updated_at": "2026-11-01T21:22:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A panel of Transcription factors identified by data mining can predict the prognosis of head and neck squamous cell carcinoma.", "doi": "10.1186/s12935-019-1024-6", "pmid": "31787845", "authors": ["Boxin Zhang", "Haihui Wang", "Ziyan Guo", "Xinhai Zhang"], "journal": "Cancer cell international", "year": 2019, "abstract": "BACKGROUND: Transcription factors (TFs) are responsible for the regulation of various activities related to cancer like cell proliferation, invasion, and migration. It is thought that, the measurement of TFs levels could assist in developing strategies for diagnosis and prognosis of cancer detection. However, due to lack of effective genome-wide tests, this cannot be carried out in clinical settings.\nMETHODS: A complete assessment of RNA-seq data in samples of a head and neck squamous cell carcinoma (HNSCC) cohort in The Cancer Genome Atlas (TCGA) database was carried out. From the expression data of six TFs, a risk score model was developed and further validated in the GSE41613 and GSE65858 series. Potential functional roles were identified for the six TFs via gene set enrichment analysis.\nRESULTS: Based on our multi-TF signature, patients are stratified into high- and low-risk groups with significant variations in overall survival (OS) (median survival 2.416 vs. 5.934 years, log-rank test P < 0.001). The sensitivity and specificity evaluation of our multi-TF for 3-year OS in TCGA, GSE41613 and GSE65858 was 0.707, 0.679 and 0.605, respectively, demonstrating good reproducibility and robustness for predicting overall survival of HNSCC patients. Through multivariate Cox regression analyses (MCRA) and stratified analyses, we confirmed that the predictive capability of this risk score (RS) was not dependent on any of other factors like clinicopathological parameters.\nCONCLUSIONS: With the help of a RS obtained from a panel of TFs expression signatures, effective OS prediction and stratification of HNSCC patients can be carried out.", "claims": [{"id": "claim-method", "statement": "TFs that passed this filter criterion were further analyzed with a multivariate Cox stepwise regression (MCSR) algorithm, as described previously [14, 15].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31787845", "locator": "sections[4] \"Identification of predictive TFs\" paragraph 2", "quote": "TFs that passed this filter criterion were further analyzed with a multivariate Cox stepwise regression (MCSR) algorithm, as described previously [14, 15]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The RNA-seq data and microarray data of HNSCC patients were deposited in the Gene Expression Omnibus (GSE41613 and GSE65858) and TCGA database. Besides, please contact the author for data and materials requests.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:31787845", "locator": "sections[22] \"notes\" paragraph 1", "quote": "The RNA-seq data and microarray data of HNSCC patients were deposited in the Gene Expression Omnibus (GSE41613 and GSE65858) and TCGA database. Besides, please contact the author for data and materials requests."}], "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:31787845"], "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:GSE41613"], "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:GSE41613"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:31787845", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12935-019-1024-6", "sha256": "sha256:9202691412ad11fd7893b5289a9fb5e16e78d9e3f88bc4386d35f5ffa79f7c5f", "bytes": 27404, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12935-019-1024-6", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC6858662", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE41613", "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=GSE41613", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE41613", "version": null, "note": "The RNA-seq data and microarray data of HNSCC patients were deposited in the Gene Expression Omnibus (GSE41613 and GSE65858) and TCGA database. 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"group_sizes_basis": null, "platform": "10558", "taxon": "Homo sapiens", "title": "Gene expression patterns and TP53 mutations are associated with HPV RNA status, lymph node metastasis, and survival in head and neck cancer", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:31787845:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:de61f2132a5cb154ca4f33613d178e7de579e8ac3fbe2259e29e877638c30874", "bytes": 923, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[8]/table-wrap[1]#Tab1", "version": null, "note": "Six TFs that were significantly correlated with overall survival in HNSCC patients", "structure": {"pmcid": "PMC6858662", "section_index": 8, "section_title": "Development of a multi-TF predictive 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"section[8]/table-wrap[1]#Tab1"}}, {"id": "asset:table:pmid:31787845:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:c173744b21d18981ddaed234361e2020e2d2e9b87287e9beb54d9e31d251501a", "bytes": 1217, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[10]/table-wrap[1]#Tab2", "version": null, "note": "Univariate and multivariate Cox regression analyses in TCGA cohort", "structure": {"pmcid": "PMC6858662", "section_index": 10, "section_title": "Determination of independent predictive activity of the multi-TF signature", "row_count": 13, "column_count": 6}, "table": {"label": "Table 2", "caption": "Univariate and multivariate Cox regression analyses in TCGA cohort", "rows": [["Variables", "Patients", "Univariable analysis", "Multivariate analysis"], ["HR (95% CI)", "P value", "HR (95% CI)", "P value"], ["Gender (male/female)", "366/132", "0.329–1.926", "0.612", "", ""], ["Age (60 vs. > 60)", "217/281", "0.978–1.616", "0.069", "", ""], ["Alcohol (no/yes)", "157/330", "0.731–1.296", "0.893", "", ""], ["HPV (no/yes)", "64/19", "0.622–2.481", "0.416", "", ""], ["Lymph node neck dissection (yes/no)", "405/90", "0.971–1.888", "0.074", "", ""], ["Histologic grade (G1/G2/G3/G4)", "61/297/119/2", "0.893–1.354", "0.370", "", ""], ["TNM stage (I/II/III/IV)", "25/70/78/257", "1.186–1.701", "< 0.001", "0.805–1.541", "0.541"], ["Lympho-vascular invasion (no/yes)", "218/119", "1.208–2.384", "0.002", "0.588–1.442", "0.691"], ["Perineural invasion present (no/yes)", "186/163", "1.557–3.116", "< 0.001", "1.162–2.862", "0.009"], ["Extranodal extension (no/yes)", "290/106", "1.989–3.716", "< 0.001", "1.488–3.817", "< 0.001"], ["Risk (low-risk/high-risk)", "357/141", "2.119–3.668", "< 0.001", "1.182–2.750", "0.006"]], "row_count": 13, "column_count": 6, "numeric_cells": 46, "header_rows": 2, "locator": "section[10]/table-wrap[1]#Tab2"}}], 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