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pmid:36193316
Integrated Analyses of m6A Regulator-Based Signature on Its Clinical Application and Immunogenomic Landscape in Stomach Adenocarcinoma.
Lan Zhang · Qing Zhang · Zebo Huang · Mingxia Zhu · Tongshan Wang · Wei Zhu · Xiaping Wang · Xin Zhou
BioMed research international · 2022 doi:10.1155/2022/2053719
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Experiment
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Complete file
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Our study is aimed at exploring the association between m6A modification patterns, TME cell-infiltrating levels, and patients' prognosis in stomach adenocarcinoma (STAD) patients.\nMethods: Consensus clustering was performed based on the integrated analyses of 17 m6A regulators and 229 m6A-related hallmark genes in STAD (The Cancer Genome Atlas (TCGA) cohort, n = 443; Gene Expression Omnibus (GEO) GSE57303, n = 70, GSE62254 n = 300, and GSE84437 n = 433). A m6ASig scoring system was calculated by the principal component analysis (PCA), and its prognostic value was validated in an independent dataset GES15459.\nResults: Three m6A clusters were identified among 1246 STAD patients, which had significant overall survival (OS) differences and demonstrated different TME immune cell infiltration and biological behaviors. According to the m6ASig score, which was generated from the m6A-related hallmark genes, STAD patients were divided into the high-m6ASig group (n = 585) and low-m6ASig group (n = 586). Patients in the high-m6ASig group had a notably prolonged OS and higher immune cell infiltration. Moreover, patients with higher m6ASig score were associated with higher microsatellite instability (MSI); higher PD-L1, CTLA4, and ERBB2 expressions; and greater tumor mutation burden (TMB). Patients with higher m6ASig score demonstrated a better immune response and drug sensitivity.\nConclusion: Our m6ASig scoring system could characterize TME immune cell infiltration, thus predict patient's prognosis and immunotherapy and chemotherapy efficacy, offering a novel tool for the individualized therapeutic implications for STAD patients.", "claims": [{"id": "claim-method", "statement": "Additionally, an m6ASig model was constructed with the combination of PC1 and PC2 from PCA analysis of m6A cluster hallmark genes: m6ASig = PC1 + PC2.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36193316", "locator": "sections[9] \"2.7. 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Construction and Validation of a Novel Signature m6ASig Based on DEGs\" paragraph 2", "quote": "K-M curves showed that patients in the high-m6ASig score group had a notably better OS than the low-m6ASig score group (Figure 5(a), P < 0.001)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The m6ASig score divided 1,171 STAD patients into high- and low-score groups, and the high-m6ASig group had significantly better overall survival.", "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:36193316"], "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. 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A run that reproduces the effect is judged against this threshold."}], "gaps": ["method.reader_differs_from_extractor"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["pca_fit"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: pca."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE57303", "GSE62254", "GSE84437"], "resolved_accessions": ["GSE57303", "GSE62254", "GSE84437"], "statements": ["The data that support the findings of this study are available from the corresponding authors upon reasonable request."], "basis": "The paper names GSE57303, GSE62254, GSE84437 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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