A 13-gene expression-based radioresistance score highlights the heterogeneity in the response to radiation therapy across HPV-negative HNSCC molecular subtypes.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:28859688", "kind": "science-record", "revision": 7, "content_hash": "sha256:4b86f93761cff742120a94d98c45751efbd940c3274ea174e58e88d3382520c2", "created_at": "2026-11-01T15:40:28Z", "updated_at": "2026-11-01T21:59:29Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A 13-gene expression-based radioresistance score highlights the heterogeneity in the response to radiation therapy across HPV-negative HNSCC molecular subtypes.", "doi": "10.1186/s12916-017-0929-y", "pmid": "28859688", "authors": ["Jean-Philippe Foy", "Louis Bazire", "Sandra Ortiz-Cuaran", "Sophie Deneuve", "Janice Kielbassa", "Emilie Thomas", "Alain Viari", "Alain Puisieux", "Patrick Goudot", "Chloé Bertolus", "Nicolas Foray", "Youlia Kirova", "Pierre Verrelle", "Pierre Saintigny"], "journal": "BMC medicine", "year": 2017, "abstract": "BACKGROUND: Radiotherapy for head and neck squamous cell carcinomas (HNSCC) is associated with a substantial morbidity and inconsistent efficacy. Human papillomavirus (HPV)-positive status is recognized as a marker of increased radiosensitivity. Our goal was to identify molecular markers associated with benefit to radiotherapy in patients with HPV-negative disease.\nMETHODS: Gene expression profiles from public repositories were downloaded for data mining. Training sets included 421 HPV-negative HNSCC tumors from The Cancer Genome Atlas (TCGA) and 32 HNSCC cell lines with available radiosensitivity data (GSE79368). A radioresistance (RadR) score was computed using the single sample Gene Set Enrichment Analysis tool. The validation sets included two panels of cell lines (NCI-60 and GSE21644) and HPV-negative HNSCC tumor datasets, including 44 (GSE6631), 82 (GSE39366), and 179 (GSE65858) patients, respectively. We finally performed an integrated analysis of the RadR score with known recurrent genomic alterations in HNSCC, patterns of protein expression, biological hallmarks, and patterns of drug sensitivity using TCGA and the E-MTAB-3610 dataset (659 pancancer cell lines, 140 drugs).\nRESULTS: We identified 13 genes differentially expressed between tumor and normal head and neck mucosa that were associated with radioresistance in vitro and in patients. The 13-gene expression-based RadR score was associated with recurrence in patients treated with surgery and adjuvant radiotherapy but not with surgery alone. It was significantly different among different molecular subtypes of HPV-negative HNSCC and was significantly lower in the \"atypical\" molecular subtype. An integrated analysis of RadR score with genomic alterations, protein expression, biological hallmarks and patterns of drug sensitivity showed a significant association with CCND1 amplification, fibronectin expression, seven hallmarks (including epithelial-to-mesenchymal transition and unfolded protein response), and increased sensitivity to elesclomol, an HSP90 inhibitor.\nCONCLUSIONS: Our study highlights the clinical relevance of the molecular classification of HNSCC and the RadR score to refine radiation strategies in HPV-negative disease.", "claims": [{"id": "claim-method", "statement": "Using the ssGSEA tool, we then calculated the Pearson’s coefficient of correlation of the RadR score with the ES of a collection of 48 biological hallmark gene sets previously reported [44] in three independent datasets, namely TCGA, GSE39366, and GSE65858.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28859688", "locator": "sections[6] \"Integrated analysis of the RadR score with genomic alterations, biological hallmarks, and patterns of protein expression and drug sensitivity\" paragraph 2", "quote": "Using the ssGSEA tool, we then calculated the Pearson’s coefficient of correlation of the RadR score with the ES of a collection of 48 biological hallmark gene sets previously reported [44] in three independent datasets, namely TCGA, GSE39366, and GSE65858."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed during the current study are available from public repositories: CellMinerTM database version 2.1 (NCI-60), Gene Expression Omnibus (GSE79368; GSE21644; GSE6631; GSE39366; GSE69858), Array Express (E-MTAB-3610), and The Cancer Genome Atlas.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28859688", "locator": "sections[20] \"ack\" paragraph 1", "quote": "The datasets analyzed during the current study are available from public repositories: CellMinerTM database version 2.1 (NCI-60), Gene Expression Omnibus (GSE79368; GSE21644; GSE6631; GSE39366; GSE69858), Array Express (E-MTAB-3610), and The Cancer Genome Atlas."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study downloaded gene-expression profiles from public repositories and computed a 13-gene RadR score using single-sample Gene Set Enrichment Analysis; the score was associated with recurrence in patients treated with surgery and adjuvant radiotherapy but not with surgery alone.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:28859688", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Gene expression profiles from public repositories were downloaded for data mining."}, {"asset": "source:pmid:28859688", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "A radioresistance (RadR) score was computed using the single sample Gene Set Enrichment Analysis tool."}, {"asset": "source:pmid:28859688", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The 13-gene expression-based RadR score was associated with recurrence in patients treated with surgery and adjuvant radiotherapy but not with surgery alone."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study downloaded gene-expression profiles from public repositories and computed a 13-gene RadR score using single-sample Gene Set Enrichment Analysis; the score was associated with recurrence in patients treated with surgery and adjuvant radiotherapy but not with surgery alone.", "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:28859688"], "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:E-MTAB-3610"], "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:E-MTAB-3610"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:28859688", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12916-017-0929-y", "sha256": 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