Integrative analysis of lysine acetylation-related genes and identification of a novel prognostic model for oral squamous cell carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37705968", "kind": "science-record", "revision": 3, "content_hash": "sha256:c27261fe47e9bfb28c5dd3b604c78bd228e23141779f0338eb42cf1c908a2a65", "created_at": "2026-11-01T19:02:32Z", "updated_at": "2026-11-01T22:10:17Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrative analysis of lysine acetylation-related genes and identification of a novel prognostic model for oral squamous cell carcinoma.", "doi": "10.3389/fmolb.2023.1185832", "pmid": "37705968", "authors": ["Shi-Zhou Deng", "Xuechen Wu", "Jiezhang Tang", "Lin Dai", "Bo Cheng"], "journal": "Frontiers in molecular biosciences", "year": 2023, "abstract": "Introduction: Oral squamous cell carcinoma (OSCC), which accounts for a high proportion of oral cancers, is characterized by high aggressiveness and rising incidence. Lysine acetylation is associated with cancer pathogenesis. Lysine acetylation-related genes (LARGs) are therapeutic targets and potential prognostic indicators in various tumors, including oral squamous cell carcinoma. However, systematic bioinformatics analysis of the Lysine acetylation-related genes in Oral squamous cell carcinoma is still unexplored. Methods: We analyzed the expression of 33 Lysine acetylation-related genes in oral squamous cell carcinoma and the effects of their somatic mutations on oral squamous cell carcinoma prognosis. Consistent clustering analysis identified two lysine acetylation patterns and the differences between the two patterns were further evaluated. Least absolute shrinkage and selection operator (LASSO) regression analysis was used to develop a lysine acetylation-related prognostic model using TCGA oral squamous cell carcinoma datasets, which was then validated using gene expression omnibus (GEO) dataset GSE41613. Results: Patients with lower risk scores had better prognoses, in both the overall cohort and within the subgroups These patients also had \"hot\" immune microenvironments and were more sensitive to immunotherapy. Disscussion: Our findings offer a new model for classifying oral squamous cell carcinoma and determining its prognosis and offer novel insights into oral squamous cell carcinoma diagnosis and treatment.", "claims": [{"id": "claim-method", "statement": "GSE41613 was used as the test cohort, whereas the TCGA dataset was used as the training cohort. The LARGs-associated signature was used to set up the prognostic model in the training cohort. Next, univariate Cox regression analysis was used to identify the prognostic differentially expressed genes (DEGs) between the lysine acetylation-related patterns. LASSO regression analysis was then used to identify prognostic DEGs (p < 0.05) using the “glmnet” package", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37705968", "locator": "sections[7] \"2.5 Identification of a LARGs prognostic signature for OSCC\" paragraph 2", "quote": "GSE41613 was used as the test cohort, whereas the TCGA dataset was used as the training cohort. The LARGs-associated signature was used to set up the prognostic model in the training cohort. Next, univariate Cox regression analysis was used to identify the prognostic differentially expressed genes (DEGs) between the lysine acetylation-related patterns. LASSO regression analysis was then used to identify prognostic DEGs (p < 0.05) using the “glmnet” package"}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37705968", "locator": "sections[24] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The eight-gene multigene signature had significant prognostic value and distinguished patients with high and low survival rates.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37705968", "locator": "sections[16] \"3.4 Developing an independent prognostic risk model based on LARGs clustering\" paragraph 5", "quote": "These analyses indicate that the multigene signature had a significant prognostic value (Figure 4D) and that the risk scores distinguished patients with high and low survival rates (Figure 4F)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The eight-gene multigene signature had significant prognostic value and distinguished patients with high and low survival rates.", "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:37705968"], "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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