Relationships of N6-Methyladenosine-Related Long Non-Coding RNAs With Tumor Immune Microenvironment and Clinical Prognosis in Lung Adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34777460", "kind": "science-record", "revision": 4, "content_hash": "sha256:f8b5fe9c6d72b0c052b6e3d11629805f4ca36dbd13952dfb6798ec804f1efad5", "created_at": "2026-11-01T17:36:28Z", "updated_at": "2026-11-01T22:05:09Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Relationships of N6-Methyladenosine-Related Long Non-Coding RNAs With Tumor Immune Microenvironment and Clinical Prognosis in Lung Adenocarcinoma.", "doi": "10.3389/fgene.2021.714697", "pmid": "34777460", "authors": ["Jianhui Zhao", "Xi Lin", "Jinman Zhuang", "Fei He"], "journal": "Frontiers in genetics", "year": 2021, "abstract": "Background: Lung adenocarcinoma (LUAD) is the major subtype of lung cancer and is associated with very high mortality. Emerging studies have shown that N6-methyladenosine (m6A)-related long non-coding (lnc) RNAs play crucial roles in tumor prognosis and the tumor immune microenvironment (TME). We aimed to explore the expression patterns of different m6A-related lncRNAs concerning patient prognosis and construct an m6A-related lncRNA prognostic model for LUAD. Methods: The prognostic value of m6A-related lncRNAs was investigated in LUAD samples from The Cancer Genome Atlas (TCGA). Potential prognostic m6A-related lncRNAs were selected by Pearson's correlation and univariate Cox regression analysis. Patients were divided into clusters using principal component analysis and the m6A-related lncRNA prognostic signature was calculated using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Results: Based on 91 prognostic m6A-related lncRNAs, we identified two m6A-related-lncRNA pattern clusters with different overall survival (OS) and different TMEs. We subsequently verified our findings multidimensionally by constructing a 13 m6A-related lncRNA prognostic signature (m6A-LPS) to calculate the risk score, which was robust in different subgroups. The receiver operating characteristic (ROC) curves and concordance index demonstrated that m6A-LPS harbored a promising ability to predict OS in TCGA data set and independent GSE11969 cohort. The risk score was also related to OS, TME, and clinical stage, and the risk score calculated by our model was also identified as independent prognostic predictive factors for LUAD patients after adjustment for age, smoking, gender, and stage. Enrichment analysis indicated that malignancy and drug resistance-associated pathways were more common in cluster2 (LUAD-unfavorable m6A-LPS). Furthermore, the results indicated that the signaling pathway enriched by the target gene of 13 m6A-related lncRNAs may be associated with metastasis and progression of cancer according to current studies. Conclusion: The current results indicated that different m6A-related-lncRNA patterns could affect OS and TME in patients with LUAD, and the prognostic signature based on 13 m6A-related lncRNAs may help to predict the prognosis in LUAD patients.", "claims": [{"id": "claim-method", "statement": "We identified potential m6A-related lncRNAs based on a correlation coefficient R > |0.5| (p-value < 0.001), according to Pearson’s correlation analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34777460", "locator": "sections[4] \"Identification of lncRNAs Related to m6A in LUAD Patients\" paragraph 2", "quote": "We identified potential m6A-related lncRNAs based on a correlation coefficient R > |0.5| (p-value < 0.001), according to Pearson’s correlation analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found here: http://cancergenome.nih.gov/.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34777460", "locator": "sections[25] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found here: http://cancergenome.nih.gov/."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Different m6A-related-lncRNA patterns could affect overall survival and the tumor immune microenvironment in patients with LUAD, and a prognostic signature based on 13 m6A-related lncRNAs may help predict prognosis in LUAD patients.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:34777460", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "The current results indicated that different m6A-related-lncRNA patterns could affect OS and TME in patients with LUAD, and the prognostic signature based on 13 m6A-related lncRNAs may help to predict the prognosis in LUAD patients."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Different m6A-related-lncRNA patterns could affect overall survival and the tumor immune microenvironment in patients with LUAD, and a prognostic signature based on 13 m6A-related lncRNAs may help predict prognosis in LUAD patients.", "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:34777460"], "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:GSE11969"], "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:GSE11969"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34777460", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fgene.2021.714697", "sha256": "sha256:8b5f8795513b5bc8e437b9d787ff9e13e8a81f1dc5f487fe8978eced896e8d58", "bytes": 40653, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fgene.2021.714697", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8585518", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE11969", "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=GSE11969", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE11969", "version": null, "note": "Publicly available datasets were analyzed in this study. 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