Assessment of alterations in histone modification function and guidance for death risk prediction in cervical cancer patients.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36199574", "kind": "science-record", "revision": 4, "content_hash": "sha256:8fc7176c0d95ae4ee0de13e98c1ff71b99baf552ccfdee2d6005993a626a2eea", "created_at": "2026-11-01T18:15:30Z", "updated_at": "2026-11-01T22:07:43Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Assessment of alterations in histone modification function and guidance for death risk prediction in cervical cancer patients.", "doi": "10.3389/fgene.2022.1013571", "pmid": "36199574", "authors": ["Tingting Zhao", "Bairong Liu", "Mengyuan Zhang", "Shiguo Li", "Can Zhao", "Li Cheng"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Background: Cervical cancer is the second most lethal malignancy among women, and histone modification plays a fundamental role in most biological processes, but the prognostic value of histone modification in cervical cancer has not been evaluated. Methods: A total of 594 cervical cancer patients from TCGA-CESC, GSE44001, and GSE52903 cohorts were enrolled in the current study, along with the corresponding clinicopathological features. Patients with a follow-up time less than one month were removed. A total of 122 histone modification-associated signaling pathways were obtained from the MSigDB. The activation scores of these pathways were evaluated using the \"GSVA\" package, differentially expressed genes were identified by the \"limma\" package, and pathway enrichment was conducted using the \"clusterProfiler 4.0\" package. The subsequent least absolute shrinkage and selection operator (LASSO) regression analysis was performed using the \"glmnet\" package, and a prognostic nomogram was established using the \"regplot\" package. For the prediction of potential therapeutic drugs, we used the data from GDSC2016 and visualized them via \"MOVICS\". Results: Nine of 23 histone modification-associated prognostic genes were identified to construct the prognostic signature by LASSO analysis, named the histone modification-associated gene (HMAG) signature. Cervical patients with HMAG-H in TCGA-CESC cohort showed a 2.68-fold change of death risk, with the 95% CI from 1.533 to 4.671 (p < 0.001), as well as the increased death risk of HMAG-H in the GSE44001 cohort (HR: 2.83, 95% CI: 1.370-5.849, p = 0.005) and GSE44001 cohort (HR: 4.59, 95% CI: 1.658-12.697, p = 0.003). We observed the preferable AUC values of the HMAG signature in TCGA-CESC cohort (1-year: 0.719, 3-year: 0.741, and 5-year: 0.731) and GSE44001 cohort (1-year: 0.850, 3-year: 0.781, and 5-year: 0.755). The C-index of the nomogram showed a prognostic value as high as 0.890, while the C-index for age was only 0.562, and that for grade was only 0.542. Patients with high HMAG scores were more suitable for the treatment of CHIR-99021, embelin, FTI-277, JNK-9L, JQ12, midostaurin, PF-562271, pyrimethamine, and thapsigargin, and patients with low HMAG scores were more suitable for the treatment of BMS-536924, CP466722, crizotinib, PHA-665752, rapamycin, and TAE684. Conclusion: We comprehensively evaluated the histone modification status in cervical cancer patients and revealed histone modification-associated prognostic genes to construct the HMAG signature, aiming to provide a new insight into prognosis prediction and precise clinical treatment.", "claims": [{"id": "claim-method", "statement": "The subsequent least absolute shrinkage and selection operator (LASSO) regression analysis was performed using the “glmnet” package, and a prognostic nomogram was established using the “regplot” package.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36199574", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The subsequent least absolute shrinkage and selection operator (LASSO) regression analysis was performed using the “glmnet” package, and a prognostic nomogram was established using the “regplot” 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:36199574", "locator": "sections[22] \"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 HMAG signature showed better prognostic value than the four published signatures, with an AUC of 0.711 and a C-index of 0.757 in TCGA-CESC.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36199574", "locator": "sections[19] \"The HMAG signature showed better prognostic value than other published signatures\" paragraph 2", "quote": "We observed that the HMAG signature showed more excellent prognostic value than any other signature based on the AUC value (HMAG: 0.711, Yu et al.: 0.632, Zhou et al.: 0.572, Qi et al.: 0.652, and Chen et al.: 0.661, Figure 8A) and C-index (HMAG: 0.757, Yu et al.: 0.723, Zhou et al.: 0.626, Qi et al.: 0.637, and Chen et al.: 0.718, Figure 8B)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The HMAG signature showed better prognostic value than the four published signatures, with an AUC of 0.711 and a C-index of 0.757 in TCGA-CESC.", "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:36199574"], "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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