Cross-Talk between N6-Methyladenosine and Their Related RNAs Defined a Signature and Confirmed m6A Regulators for Diagnosis of Endometriosis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36675186", "kind": "science-record", "revision": 3, "content_hash": "sha256:9d579c33d77f2766e69299752716dbe234f22f7db6f476a7a8777d57755724c0", "created_at": "2026-11-01T19:01:13Z", "updated_at": "2026-11-01T22:08:35Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Cross-Talk between N6-Methyladenosine and Their Related RNAs Defined a Signature and Confirmed m6A Regulators for Diagnosis of Endometriosis.", "doi": "10.3390/ijms24021665", "pmid": "36675186", "authors": ["Xiaotong Wang", "Xibo Zhao", "Jing Wang", "Han Wu", "Yan Cheng", "Qiuyan Guo", "Tian Liang", "Guangmei Zhang"], "journal": "International journal of molecular sciences", "year": 2023, "abstract": "An RNA modification known as N6-methyladenosine (m6A) interacts with a range of coding and non-coding RNAs. The majority of the research has focused on identifying m6A regulators that are differentially expressed in endometriosis, but it has ignored their mechanisms that are derived from the alterations of modifications among RNAs, affecting the disease progression primarily. Here, we aimed to investigate the potential roles of m6A regulators in the diagnostic potency, immune microenvironment, and clinicopathological features of endometriosis through interacting genes. A GEO cohort was incorporated into this study. Variance expression profiling was executed via the \"limma\" R package. Pearson analysis was performed to investigate the correlations among 767 interacting lncRNAs, 374 interacting mRNAs, and 23 m6A regulators. K-means clustering analysis, based on patterns of mRNA modifications, was applied to perform clinical feature analysis. Infiltrating immune cells and stromal cells were calculated using the Cibersort method. An m6A-related risk model was created and supported by an independent risk assay. LASSO regression analysis and Cox analyses were implemented to determine the diagnostic genes. The diagnostic targets of endometriosis were verified using PCR and the WB method. Results: A thorough investigation of the m6A modification patterns in the GEO database was carried out, based on mRNAs and lncRNAs related to these m6A regulators. Two molecular subtypes were identified using unsupervised clustering analysis, resulting in further complex infiltration levels of immune microenvironment cells in diversified endometriosis pathology types. We identified two m6A regulators, namely METTL3 and YTHDF2, as diagnostic targets of endometriosis following the usage of overlapping genes to construct a diagnostic m6A signature of endometriosis through multivariate logistic regression, and we validated it using independent GSE86534 and GSE105764 cohorts. Finally, we found that m6A alterations might be one of the important reasons for the progression of endometriosis, especially with significant downregulation of the expressions of METTL3 and YTHDF2. Finally, m6A modification patterns have significant effects on the diversity and complexity of the progression and immune microenvironment, and might be key diagnostic markers for endometriosis.", "claims": [{"id": "claim-method", "statement": "These m6As were integrated based on LASSO binomial analysis with 10-fold cross-validation (Figure 6B).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36675186", "locator": "sections[9] \"2.7. Construction and Validation of an m6A-Related Diagnostic Signature\" paragraph 2", "quote": "These m6As were integrated based on LASSO binomial analysis with 10-fold cross-validation (Figure 6B)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "We are ready to provide details regarding this if published.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36675186", "locator": "sections[33] \"notes\" paragraph 1", "quote": "We are ready to provide details regarding this if published."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The model was further validated using two independent cohorts, and the AUC remained at 0.875 and 0.984, representing an excellent generalization (Figure 6F).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36675186", "locator": "sections[9] \"2.7. 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