Survival prediction in patients with head and neck squamous cell carcinoma and novel mechanistic insights of S100A8/A9.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39546127", "kind": "science-record", "revision": 2, "content_hash": "sha256:99b679714a981ce04dd28a1312bba9fd74a5b2cc8eeb35670bfe0cac2fdaaab9", "created_at": "2026-11-01T20:29:48Z", "updated_at": "2026-11-01T21:34:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Survival prediction in patients with head and neck squamous cell carcinoma and novel mechanistic insights of S100A8/A9.", "doi": "10.1007/s12672-024-01540-w", "pmid": "39546127", "authors": ["Yihong Hu", "Minhui He", "Yucheng Han", "Lu Zeng", "Ziwei Ma", "Xianqiong Zou"], "journal": "Discover oncology", "year": 2024, "abstract": "BACKGROUND: S100A8/A9, an innate immune protein, significantly regulates inflammatory processes and immune responses. While S100A8/A9 has been linked to various diseases, its association with head and neck squamous cell carcinoma (HNSCC) remains unclear.\nMETHODS: Samples from the Cancer Genome Atlas (TCGA) were categorized into groups with low and high expression of S100A8/A9. R software, Sangerbox, UALCAN, GEPIA2, STRING, Cytoscape, TCGC Data Portal, miRcode, OncomiR and ENCORI databases were used to comprehensively study the expression, interactome and mutational profiles of S100A8/A9 and associated mechanism in HNSCC.\nRESULTS: The proteins S100A8/A9 were found to be associated with processes of 'epithelium development', 'regulating pluripotency of stem cells' and 'regulation of immune system'. The most frequent mutation observed in the S100A8 protein was E93K (3/37, MU4401889), while for the S100A9 protein, it was R10C (4/37, MU4633862). Furthermore, the group expressing high levels of S100A8/A9 showed increased infiltration by dendritic cells and neutrophils, but decreased infiltration by M2 macrophages, compared to the group with low S100A8/A9 expression. S100A8/A9 was also found to interact with a variety of mRNA transcripts, several of which were involved in initiation and progression of HNSCC. Through LASSO-Cox method, 20 genes (CALML5, MSX1, FZD3, STC2, SLC2A3, TMEM198B, DYNC1I1, SPHK2, ALMS1.IT1, SPPL2B, PDGFA, BCORL1, TEX101, SGCE, DNAJC12, RRN3P1, HOXB9, TMEM150C, METTL7B and PSPN) were screening to construct a prognostic model to distinguish favorable and poor prognosis of HNSCC patients. Besides, our prognostic model was also validated in GSE41613 cohort.\nCONCLUSIONS: S100A8/A9 may be a promising marker for the diagnostic and prognostic assessment of the HNSCC patients. Based on these insights, we have devised a new classification model for HNSCC, which has the potential to enhance the management and personalized treatment of HNSCC patients. The model should also be further optimized through the expansion of sample size and implemented experimental studies in future research.", "claims": [{"id": "claim-method", "statement": "Then, 20/34 genes were screened for the optimal prediction model in LASSO-Cox method.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39546127", "locator": "sections[8] \"Construction of prognostic model\" paragraph 2", "quote": "Then, 20/34 genes were screened for the optimal prediction model in LASSO-Cox method."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data generated or analyzed during this study are included in this published article.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39546127", "locator": "sections[28] \"notes\" paragraph 1", "quote": "All data generated or analyzed during this study are included in this published article."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study constructed a 20-gene LASSO-Cox prognostic model and validated it in the GSE41613 cohort.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39546127", "locator": "sections[8] \"Construction of prognostic model\" paragraph 2", "quote": "Then, 20/34 genes were screened for the optimal prediction model in LASSO-Cox method."}, {"asset": "source:pmid:39546127", "locator": "sections[9] \"Validation of the prognostic model\" paragraph 2", "quote": "Therefore, our prognostic model had good predictive capability for the prognosis of HNSCC patients."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study constructed a 20-gene LASSO-Cox prognostic model and validated it in the GSE41613 cohort.", "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:39546127"], "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. 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