A Novel m1A-Score Model Correlated With the Immune Microenvironment Predicts Prognosis in Hepatocellular Carcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35401564", "kind": "science-record", "revision": 5, "content_hash": "sha256:9628bdb373570f07bb0d0e886ff66305aee09b6786dd0d528b6c9c84ee4675d2", "created_at": "2026-11-01T18:14:13Z", "updated_at": "2026-11-01T22:48:48Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A Novel m1A-Score Model Correlated With the Immune Microenvironment Predicts Prognosis in Hepatocellular Carcinoma.", "doi": "10.3389/fimmu.2022.805967", "pmid": "35401564", "authors": ["Mingxing Zhao", "Shen Shen", "Chen Xue"], "journal": "Frontiers in immunology", "year": 2022, "abstract": "RNA methylation plays crucial roles in gene expression and has been indicated to be involved in tumorigenesis, while it is still unclear whether m1A modifications have potential roles in the prognosis of hepatocellular carcinoma (HCC). In this study, we comprehensively analyzed RNA sequencing (RNA-seq) data and clinical information using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We collected 10 m1A regulators and performed consensus clustering to determine m1A modification patterns in HCC. The CIBERSORT method was utilized to evaluate the level of immune cell infiltration. Principal component analysis was used to construct the m1A-score model. In the TCGA-LIHC cohort, the expression of all 10 m1A regulators was higher in tumor tissues than in normal control tissues, and 8 of 10 genes were closely related to the prognosis of HCC patients. Two distinct m1A methylation modification patterns (Clusters C1 and C2) were identified by the 10 regulators and were associated with different overall survival, TNM stage and tumor microenvironment (TME) characteristics. Based on the differentially expressed genes (DEGs) between C1 and C2, we identified three gene clusters (Clusters A, B and C). C1 with a better prognosis was mainly distributed in Cluster C, while Cluster A contained the fewest samples of C1. An m1A-score model was constructed using five m1A regulators related to prognosis. Patients with higher m1A scores showed a poorer prognosis than those with lower scores in the TCGA-LIHC and GSE14520 datasets. In conclusions, our study showed the vital role of m1A modification in the TME and progression of HCC. Quantitative evaluation of the m1A modification patterns of individual patients facilitates the development of more effective biomarkers for predicting the prognosis of patients with HCC.", "claims": [{"id": "claim-method", "statement": "First, we identified the differentially expressed genes (DEGs) between distinct m1A clusters. The survival data and DEGs were analyzed by univariate Cox regression analysis. Second, least absolute shrinkage and selection operator (LASSO) Cox regression analysis was utilized to further narrow down the DEGs associated with prognosis. Finally, we performed multivariate Cox regression analysis to establish the prognostic model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35401564", "locator": "sections[5] \"Construction and Validation of a Prognostic Risk Model\" paragraph 2", "quote": "First, we identified the differentially expressed genes (DEGs) between distinct m1A clusters. The survival data and DEGs were analyzed by univariate Cox regression analysis. Second, least absolute shrinkage and selection operator (LASSO) Cox regression analysis was utilized to further narrow down the DEGs associated with prognosis. Finally, we performed multivariate Cox regression analysis to establish the prognostic model."}], "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:35401564", "locator": "sections[25] \"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": "Patients with higher m1A scores showed a poorer prognosis than those with lower scores in the TCGA-LIHC and GSE14520 datasets.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35401564", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Patients with higher m1A scores showed a poorer prognosis than those with lower scores in the TCGA-LIHC and GSE14520 datasets."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Patients with higher m1A scores showed a poorer prognosis than those with lower scores in the TCGA-LIHC and GSE14520 datasets.", "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:35401564"], "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:GSE14520"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "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:GSE14520"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35401564", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2022.805967", "sha256": "sha256:8feb812ea1320387f71d83d19c0dc1663cf762ea8f8f56c4303a07bfc2ed35e3", "bytes": 41059, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2022.805967", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8987777", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE14520", "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=GSE14520", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE14520", "version": null, "note": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are included in the article/ Supplementary Material . 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In this study, we comprehensively analyzed RNA sequencing (RNA-seq) data and clinical information usin"], "order_basis": "paper_text_order:350", "id": "assay:1"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["e Academy of Sciences (Shanghai, China). The cell lines were maintained in Dulbecco’s modified Eagle’s medium (DMEM,", "ll line L02 and human liver cancer cell line HepG2 were obtained from the Chinese Academy of Sc", "H1, and ALKBH3) were highly expressed in the HepG2 cell line compared with the normal liver cel", "was not significantly different between the HepG2 and L02 cell lines ( Figure 1B ). 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