Construction of m6A-based prognosis signature and prediction for immune and anti-angiogenic response.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36339715", "kind": "science-record", "revision": 2, "content_hash": "sha256:9abac1c8cd60fa8d27787e6cf66023595936bdbb911d80cce73d415b8360ccfe", "created_at": "2026-11-01T18:15:46Z", "updated_at": "2026-11-01T19:00:46Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction of m6A-based prognosis signature and prediction for immune and anti-angiogenic response.", "doi": "10.3389/fmolb.2022.1034928", "pmid": "36339715", "authors": ["Xiang-Xu Wang", "Li-Hong Wu", "Qiong-Yi Dou", "Liping Ai", "Yajie Lu", "Shi-Zhou Deng", "Qing-Qing Liu", "Hongchen Ji", "Hong-Mei Zhang"], "journal": "Frontiers in molecular biosciences", "year": 2022, "abstract": "Background: Increasing evidence illustrated that m6A regulator-mediated modification plays a crucial role in regulating tumor immune and angiogenesis microenvironment. And the combination of immune checkpoint inhibitor and anti-angiogenic therapy has been approved as new first-line therapy for advanced HCC. This study constructed a novel prognosis signature base on m6A-mediated modification and explored the related mechanism in predicting immune and anti-angiogenic responses. Methods: Gene expression profiles and clinical information were collected from TCGA and GEO. The ssGSEA, MCPCOUNT, and TIMER 2.0 algorithm was used to Estimation of immune cell infiltration. The IC50 of anti-angiogenic drugs in GDSC was calculated by the \"pRRophetic\" package. IMvigor210 cohort and Liu et al. cohort were used to validate the capability of immunotherapy response. Hepatocellular carcinoma single immune cells sequencing datasets GSE140228 were collected to present the expression landscapes of 5 hub genes in different sites and immune cell subpopulations of HCC patients. Results: Three m6A clusters with distinct immune and angiogenesis microenvironments were identified by consistent cluster analysis based on the expression of m6A regulators. We further constructed a 5-gene prognosis signature (termed as m6Asig-Score) which could predict both immune and anti-angiogenic responses. We illustrated that high m6Asig-Score is associated with poor prognosis, advanced TNM stage, and high TP53 mutation frequency. Besides, the m6Asig-Score was negatively associated with immune checkpoint inhibitors and anti-angiogenic drug response. We further found that two of the five m6Asig-Score inner genes, B2M and SMOX, were associated with immune cell infiltration, immune response, and the sensitivity to sorafenib, which were validated in two independent immunotherapy cohorts and the Genomics of Drug Sensitivity in Cancer (GDSC) database. Conclusion: We constructed a novel prognosis signature and identified B2M and SMOX for predicting immune and anti-angiogenic efficacy in HCC, which may guide the combined treatment strategies of immunotherapy and anti-angiogenic therapy in HCC.", "claims": [{"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 author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36339715", "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 author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "In the TCGA-LIHC training cohort, the ROC curve analysis exhibited that the AUC values of 1-, 2-,3-, and 5-year survival was 0.760, 0.775, 0.816, and 0.721, respectively (Figure 5M).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36339715", "locator": "sections[17] \"Construction of a prognosis signature base on m6A-related DEGs\" paragraph 4", "quote": "In the TCGA-LIHC training cohort, the ROC curve analysis exhibited that the AUC values of 1-, 2-,3-, and 5-year survival was 0.760, 0.775, 0.816, and 0.721, respectively (Figure 5M)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "In the TCGA-LIHC training cohort, the ROC curve analysis exhibited that the AUC values of 1-, 2-,3-, and 5-year survival was 0.760, 0.775, 0.816, and 0.721, respectively (Figure 5M).", "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:36339715"], "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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