Quantification of m6A RNA methylation modulators pattern was a potential biomarker for prognosis and associated with tumor immune microenvironment of pancreatic adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34332578", "kind": "science-record", "revision": 7, "content_hash": "sha256:1bb44f99107bc33c70689579bd039293ff4e6b49903427de59ae1227121531b9", "created_at": "2026-11-01T15:41:46Z", "updated_at": "2026-11-01T22:04:22Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Quantification of m6A RNA methylation modulators pattern was a potential biomarker for prognosis and associated with tumor immune microenvironment of pancreatic adenocarcinoma.", "doi": "10.1186/s12885-021-08550-9", "pmid": "34332578", "authors": ["Lianzi Wang", "Shubing Zhang", "Huimin Li", "Yang Xu", "Qiang Wu", "Jilong Shen", "Tao Li", "Yuanhong Xu"], "journal": "BMC cancer", "year": 2021, "abstract": "BACKGROUND: m6A is the most prevalent and abundant form of mRNA modifications and is closely related to tumor proliferation, differentiation, and tumorigenesis. In this study, we try to conduct an effective prediction model to investigated the function of m6A RNA methylation modulators in pancreatic adenocarcinoma and estimated the potential association between m6A RNA methylation modulators and tumor microenvironment infiltration for optimization of treatment.\nMETHODS: Expression of 28 m6A RNA methylation modulators and clinical data of patients with pancreatic adenocarcinoma and normal samples were obtained from TCGA and GTEx database. Differences in the expression of 28 m6A RNA methylation modulators between tumour (n = 40) and healthy (n = 167) samples were compared by Wilcoxon test. LASSO Cox regression was used to select m6A RNA methylation modulators to analyze the relationship between expression and clinical characteristics by univariate and multivariate regression. A risk score prognosis model was conducted based on the expression of select m6A RNA methylation modulators. Bioinformatics analysis was used to explore the association between the m6Ascore and the composition of infiltrating immune cells between high and low m6Ascore group by CIBERSORT algorithm. Evaluation of m6Ascore for immunotherapy was analyzed via the IPS and three immunotherapy cohort. Besides, the biological signaling pathways of the m6A RNA methylation modulators were examined by gene set enrichment analysis (GSEA).\nRESULTS: Expression of 28 m6A RNA methylation modulators were upregulated in patients with PAAD except for MTEEL3. An m6Ascore prognosis model was established, including KIAA1429, IGF2BP2, IGF2BP3, METTL3, EIF3H and LRPPRC was used to predict the prognosis of patients with PAAD, the high risk score was an independent prognostic indicator for pancreatic adenocarcinoma, and a high risk score presented a lower overall survival. In addition, m6Ascore was related with the immune cell infiltration of PAAD. Patients with a high m6Ascore had lower infiltration of Tregs and CD8+T cells but a higher resting CD4+ T infiltration. Patients with a low m6Ascore displayed a low abundance of PD-1, CTLA-4 and TIGIT, however, the IPS showed no difference between the two groups. The m6Ascore applied in three immunotherapy cohort (GSE78220, TCGA-SKCM, and IMvigor210) did not exhibit a good prediction for estimating the patients' response to immunotherapy, so it may need more researches to figure out whether the m6A modulator prognosis model would benefit the prediction of pancreatic patients' response to immunotherapy.\nCONCLUSION: Modulators involved in m6A RNA methylation were associated with the development of pancreatic cancer. An m6Ascore based on the expression of IGF2BP2, IGF2BP3, KIAA1429, METTL3, EIF3H and LRPPRC is proposed as an indicator of TME status and is instrumental in predicting the prognosis of pancreatic cancer patients.", "claims": [{"id": "claim-method", "statement": "Cox regression analysis was used to examine the prognosis of pancreatic cancer.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34332578", "locator": "sections[11] \"Statistical analysis\" paragraph 2", "quote": "Cox regression analysis was used to examine the prognosis of pancreatic cancer."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed during the current study are available from TCGA database (https://cancergenome.nih.gov/), GTEx database (https://xenabrowser.net/), Immport database (https://immport.niaid.nih.gov/), TCIA database (https://www.tcia.at/home), GEO database (https://www.ncbi.nlm.nih.gov/geo/), Oncomine database (https://www.oncomine.org).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34332578", "locator": "sections[26] \"Availability of data and materials\" paragraph 2", "quote": "The datasets analyzed during the current study are available from TCGA database (https://cancergenome.nih.gov/), GTEx database (https://xenabrowser.net/), Immport database (https://immport.niaid.nih.gov/), TCIA database (https://www.tcia.at/home), GEO database (https://www.ncbi.nlm.nih.gov/geo/), Oncomine database (https://www.oncomine.org)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": null, "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:34332578"], "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": "blocked", "blocked_on": "data:accession_absent", "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": [], "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": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34332578", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12885-021-08550-9", "sha256": 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