Eight types of RNA modification regulators define clinical outcome and immune response in gastric cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39309865", "kind": "science-record", "revision": 3, "content_hash": "sha256:7dc28b8ba3cf87d456c4b5ff488d128f95ab22f3ce9d81892ae65d3e9beee568", "created_at": "2026-11-01T20:29:29Z", "updated_at": "2026-11-01T22:12:45Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Eight types of RNA modification regulators define clinical outcome and immune response in gastric cancer.", "doi": "10.1016/j.heliyon.2024.e37076", "pmid": "39309865", "authors": ["Danhong Dong", "Pengfei Yu", "Xin Guo", "Jinqiang Liu", "Xisheng Yang", "Gang Ji", "Xiaohua Li", "Jiangpeng Wei"], "journal": "Heliyon", "year": 2024, "abstract": "Background: RNA modifications represent a novel category of biological molecule alterations, characterized by three primary classes of proteins: writers, erasers, and readers. Numerous studies indicate that the dysregulation of these RNA modifications is linked to cancer development and may offer new therapeutic avenues for treatment. In our research, we focused on eight specific genes associated with RNA modifications (RMRGs) to comprehensively analyze their distinct functions in gastric cancer (GC). Furthermore, we aimed to elucidate the roles of RMRGs concerning clinicopathological characteristics, tumor microenvironment, and patient prognosis.\nMethods: In this study, we examined the expression and mutations of RMRGs in gastric cancer (GC) using data from TCGA-STAD (The Cancer Genome Atlas; Stomach adenocarcinoma) and the gene expression omnibus (GSE66229). We identified two subtypes of RMRGs and three gene clusters through consensus clustering analysis, assessing their differences in prognosis and immune cell infiltration patterns. Subsequently, we developed an RMRGs score to evaluate GC prognosis and highlight general immune features within the tumor microenvironment (TME). Lastly, we focused on MAMDC2 to validate its expression in GC and explore the effects of a MAMDC2 inhibitor on GC tumor cells.\nResults: We discovered 94 differentially expressed RMRGs common to both the TCGA-STAD and GEO datasets. Notable differences in prognosis and immune cell infiltration were observed between the two RMRGs subtypes and three gene clusters. The RMRGs score emerged as an independent prognostic factor related to the tumor microenvironment (TME) characteristics in gastric cancer (GC). Reducing MAMDC2 levels enhanced cell migration and invasion while decreasing proliferation in vitro.\nConclusions: In conclusion, this study comprehensively analyzed the role of RMRGs on GC. Our study firstly proposed RMRGs score and demonstrated its potential to be biomarkers for prognosis and immune characteristics. Consequently, RMRGs score is of great clinical significance and can be utilized to develop individualized.", "claims": [{"id": "claim-method", "statement": "Using the expression profiles of DE-RMRGs in the merged datasets, we applied the consensus clustering method via the ‘ConsensusCluster-Plus’ package in R software to estimate unsupervised classes of STAD samples, yielding two distinct RNA modification patterns.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39309865", "locator": "sections[5] \"Consensus clustering analysis of RMRGs\" paragraph 2", "quote": "Using the expression profiles of DE-RMRGs in the merged datasets, we applied the consensus clustering method via the ‘ConsensusCluster-Plus’ package in R software to estimate unsupervised classes of STAD samples, yielding two distinct RNA modification patterns."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All data come from the publicly available datasets in present study. These datasets can be found here: TCGA database (http://cancergenome.nih.gov/), the GEO database (GSE66229) (GSE62254) (GSE84437) were included in this study, MSigDB datasets (http://www.gsea-msigdb.org/gsea/msigdb/index.jsp).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39309865", "locator": "sections[30] \"Data availability statement\" paragraph 2", "quote": "All data come from the publicly available datasets in present study. These datasets can be found here: TCGA database (http://cancergenome.nih.gov/), the GEO database (GSE66229) (GSE62254) (GSE84437) were included in this study, MSigDB datasets (http://www.gsea-msigdb.org/gsea/msigdb/index.jsp)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We discovered 94 differentially expressed RMRGs common to both the TCGA-STAD and GEO datasets.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39309865", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We discovered 94 differentially expressed RMRGs common to both the TCGA-STAD and GEO datasets."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We discovered 94 differentially expressed RMRGs common to both the TCGA-STAD and GEO datasets.", "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:39309865"], "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:GSE62254"], "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:GSE62254"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39309865", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1016/j.heliyon.2024.e37076", "sha256": "sha256:e3116e8d31b670441bd9d66cdc0fe8a4cceb3feb1fe2dcbd484738c6c778ba97", "bytes": 47334, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1016/j.heliyon.2024.e37076", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11415870", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE62254", "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=GSE62254", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE62254", "version": null, "note": "All data come from the publicly available datasets in present study. 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