Effects of N6-Methyladenosine Regulators on LAG3 and Immune Infiltrates in Lung Adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36051357", "kind": "science-record", "revision": 4, "content_hash": "sha256:20700c9e0e13647e8469536277c4c23b4b5a9a67a765e414ffa0056eae97efb9", "created_at": "2026-11-01T18:15:13Z", "updated_at": "2026-11-01T22:07:25Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Effects of N6-Methyladenosine Regulators on LAG3 and Immune Infiltrates in Lung Adenocarcinoma.", "doi": "10.1155/2022/1829528", "pmid": "36051357", "authors": ["Nengchao Wang", "Yue Xu", "Linzhi Jin", "Xiaomin Wang", "Shouxin Wu", "Yu Wang", "Jiangman Zhao", "Fuyou Zhou", "Hong Ge"], "journal": "Disease markers", "year": 2022, "abstract": "Background: Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer, which is one of the most commonly diagnosed tumors and the leading causes of death from cancer around the world. Since RNA methylation is a posttranscriptional modification and affects so much biological progress, it is urged to explore the role of N6-methyladenosine (m6A) methylation in LUAD.\nMethods: We explored the expression of 24 m6A methylation genes, as well as their correlations with LAG3 in 561 LUAD samples from TCGA. Consensus clustering was applied to m6A methylation genes, and two LUAD subgroups were identified. The expression of m6A genes was analyzed by the Wilcoxon test. KEGG and GO enrichment analyses were performed to indicate the pathway affected by differentially expressed genes in the two groups. A prognostic model based on LASSO regression using an eleven-m6A gene signature was constructed according to the expression of these genes. Receiver operating characteristic (ROC) curve was used to confirm the accuracy of the model in the TCGA cohort, as well as in the test cohort from the Gene Expression Omnibus (GEO) database.\nResults: Compared to cluster 1, cluster 2 showed poorer overall survival (OS) and higher LAG3 expression. In addition, KEGG and GO enrichment analyses indicated that differentially expressed genes are enriched in the immune response. We also observed that the expression of LAG3 is positively correlated with IGF2BP2, CBLL1, and HNRNPA2B1 and negatively correlated with YTHDF2, YTHDF3, and FTO. For patients in the TCGA cohort, the AUC score is 0.7, and the AUC score for the GSE50081 cohort is 0.675. Patients with lower risk scores exhibited better overall survival and lower expression of LAG3 than patients with higher risk scores.\nConclusions: In brief, our results indicated the important role of m6 methylation in affecting the tumor immune microenvironment and the survival of patients with LUAD. The m6A methylation gene signatures might serve as promising therapeutic targets and help the immunotherapy of LUAD in the future.", "claims": [{"id": "claim-data-access", "statement": "The original datasets analyzed for this study can be found in The Cancer Genome Atlas program (https://portal.gdc.cancer.gov/) and Gene Expression Omnibus with the accession code GSE50081 (https://www.ncbi.nlm.nih.gov/geo/). All data generated during this study are included in this article.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36051357", "locator": "sections[15] \"Data Availability\" paragraph 2", "quote": "The original datasets analyzed for this study can be found in The Cancer Genome Atlas program (https://portal.gdc.cancer.gov/) and Gene Expression Omnibus with the accession code GSE50081 (https://www.ncbi.nlm.nih.gov/geo/). All data generated during this study are included in this article."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The prognostic risk signature achieved an AUC of 0.7 in the TCGA cohort and 0.675 in the GSE50081 validation cohort.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36051357", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "For patients in the TCGA cohort, the AUC score is 0.7, and the AUC score for the GSE50081 cohort is 0.675."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The prognostic risk signature achieved an AUC of 0.7 in the TCGA cohort and 0.675 in the GSE50081 validation 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:36051357"], "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:GSE50081"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:group_comparison_wilcoxon", "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:GSE50081"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:group_comparison_wilcoxon"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36051357", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/1829528", "sha256": "sha256:a8a0175e7ab1303a072f7d59f9d45431f1831f2e5979bd292b66444addaafeba", "bytes": 36193, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2022/1829528", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9427291", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE50081", "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=GSE50081", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE50081", "version": null, "note": "The original datasets analyzed for this study can be found in The Cancer Genome Atlas program (https://portal.gdc.cancer.gov/) and Gene Expression Omnibus with the accession code GSE50081 (https://www.ncbi.nlm.nih.gov/geo/). 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