Immunotherapy Response Predictive Score Based on Tumor Microenvironment Profiles for Predicting Immunotherapy Outcomes in Advanced Head and Neck Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41574715", "kind": "science-record", "revision": 3, "content_hash": "sha256:3f0ba4b3163e2a5060cfaabc6becce29c872ef1e97b3dd28faa3d60610800657", "created_at": "2026-11-01T20:31:32Z", "updated_at": "2026-11-01T22:15:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Immunotherapy Response Predictive Score Based on Tumor Microenvironment Profiles for Predicting Immunotherapy Outcomes in Advanced Head and Neck Cancer.", "doi": "10.1177/15330338251411026", "pmid": "41574715", "authors": ["Hui-Ching Wang", "Mei-Ren Pan", "Leong-Perng Chan", "Chun-Chieh Wu", "Yu-Hsuan Hung", "Jeng-Shiun Du", "Shih-Feng Cho", "Meng-Chun Chou", "Hui-Ting Tsai", "Che-Wei Wu", "Yi-Chang Liu", "Li-Tzong Chen", "Sin-Hua Moi"], "journal": "Technology in cancer research & treatment", "year": 2026, "abstract": "ObjectivesThis retrospective study presents an integrative transcriptomic approach for recurrent and/or metastatic head and neck squamous cell carcinoma (R/M HNSCC) by developing an immune response predictive score (IORPS) derived from tumor microenvironment (TME) transcriptomic profiles.MethodsA total of 30 R/M HNSCC patients treated with pembrolizumab or nivolumab, with available immune TME profiling data, were analyzed. IORPS was constructed based on the cumulative weighting of differentially expressed gene (DEG) expression levels. The predictive performance of conventional biomarkers, individual DEGs, and IORPS was evaluated for immunotherapy response and prognostic outcomes. The clinical relevance of IORPS was further validated using two external cohorts from the GEO database (CLB-IHN: GSE159067 and GHPS: GSE159141).ResultsBy comparing immune tumor microenvironment (TME) profiles between good and poor responders, GZMH, IFNG, and FASLG were identified as key DEGs with significantly higher expression in favorable immunotherapy responders. The IORPS, derived from transcriptomic profiling, demonstrated robust predictive accuracy for both immunotherapy response and survival outcomes in patients with R/M HNSCC.ConclusionCompared with the variable predictive performance of current biomarkers such as TPS and CPS, IORPS provides improved accuracy and reliability in identifying and stratifying patients most likely to benefit from immune checkpoint blockade therapy.", "claims": [{"id": "claim-data-access", "statement": "Data Availability Statement for This Work: The data for KMUH cohort generated in this study are not publicly available, as they do not meet the requirements for community recognized, structured repositories, but the data are available from the corresponding author upon written request and clarification from the requesting party about how the data will be utilized. Expression profile data for external validation cohort analyzed in this study are available from Gene Expression Omnibus (GEO) (RRID: SCR_005012, https://www.ncbi.nlm.nih.gov/geo/) at GSE159067 and GSE159141.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41574715", "locator": "sections[23] \"Footnotes\" paragraph 2", "quote": "Data Availability Statement for This Work: The data for KMUH cohort generated in this study are not publicly available, as they do not meet the requirements for community recognized, structured repositories, but the data are available from the corresponding author upon written request and clarification from the requesting party about how the data will be utilized. Expression profile data for external validation cohort analyzed in this study are available from Gene Expression Omnibus (GEO) (RRID: SCR_005012, https://www.ncbi.nlm.nih.gov/geo/) at GSE159067 and GSE159141."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "", "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:41574715"], "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:GSE159067"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:group_comparison_wilcoxon", "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:GSE159067"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:group_comparison_wilcoxon"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:41574715", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1177/15330338251411026", "sha256": "sha256:7fec254ef5bda6899e91d0045d063c3973f8ff544b0d66d5b91f2eb174841478", "bytes": 55553, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1177/15330338251411026", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12833181", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE159067", "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=GSE159067", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE159067", "version": null, "note": "Data Availability Statement for This Work: The data for KMUH cohort generated in this study are not publicly available, as they do not meet the requirements for community recognized, structured repositories, but the data are available from the corresponding author upon written request and clarification from the requesting party about how the data will be utilized. 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