Development and Validation of a Machine Learning Prognostic Model of m5C Related immune Genes in Lung Adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38537151", "kind": "science-record", "revision": 4, "content_hash": "sha256:b9bf8265b2fcad8f161186e93173c69450599947f13f567b05c0431b148e74e2", "created_at": "2026-11-01T19:20:29Z", "updated_at": "2026-11-01T22:53:58Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Development and Validation of a Machine Learning Prognostic Model of m5C Related immune Genes in Lung Adenocarcinoma.", "doi": "10.1177/10732748241237414", "pmid": "38537151", "authors": ["Xiong Cao", "Yuxing Ji", "Jiajia Li", "Zhikang Liu", "Chang Chen"], "journal": "Cancer control : journal of the Moffitt Cancer Center", "year": 2024, "abstract": "BACKGROUND: The aim of this retrospective research was to develop an immune-related genes significantly associated with m5C methylation methylation (m5C-IRGs)-related signature associated with lung adenocarainoma (LUAD).\nMETHODS: We introduced transcriptome data to screen out m5C-IRGs in The Cancer Genome Atlas (TCGA)-LUAD dataset. Subsequently, the m5C-IRGs associated with survival were certificated by Kaplan Meier (K-M) analysis. The univariate Cox, least absolute shrinkage and selection operator (LASSO) regression, and xgboost.surv tool were adopted to build a LUAD prognostic signature. We further conducted gene functional enrichment, immune microenvironment and immunotherapy analysis between 2 risk subgroups. Finally, we verified m5C-IRGs-related prognostic gene expression in transcription level.\nRESULTS: A total of 76 m5C-IRGs were identified in TCGA-LUAD dataset. Furthermore, 27 m5C-IRGs associated with survival were retained. Then, a m5C-IRGs prognostic signature was build based on the 3 prognostic genes (HLA-DMB, PPIA, and GPI). Independent prognostic analysis suggested that stage and RiskScore could be used as independent prognostic factors. We found that 4104 differentially expressed genes (DEGs) between the 2 risk subgroups were mainly concerned in immune receptor pathways. We found certain distinction in LUAD immune microenvironment between the 2 risk subgroups. Then, immunotherapy analysis and chemotherapeutic drug sensitivity results indicated that the m5C-IRGs-related gene signature might be applied as a therapy predictor. Finally, we found significant higher expression of PPIA and GPI in LUAD group compared to the normal group.\nCONCLUSIONS: The prognostic signature comprised of HLA-DMB, PPIA, and GPI based on m5C-IRGs was established, which might provide theoretical basis and reference value for the research of LUAD.\nPUBLIC DATASETS ANALYZED IN THE STUDY: TCGA-LUAD dataset was collected from the TCGA (https://portal.gdc.cancer.gov/) database, GSE31210 (validation set) was retrieved from GEO (https://www.ncbi.nlm.nih.gov/geo/) database.", "claims": [{"id": "claim-method", "statement": "Least absolute shrinkage and selection operator (LASSO) regression, XGBoot-Surv analysis were applied to screen prognostic DE-m5C-IRG associated with survival in TCGA dataset.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38537151", "locator": "sections[7] \"Risk Score-based Subgroup Analysis of LUAD Patients\" paragraph 2", "quote": "Least absolute shrinkage and selection operator (LASSO) regression, XGBoot-Surv analysis were applied to screen prognostic DE-m5C-IRG associated with survival in TCGA dataset."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The RNA and miRNA sequencing information of LUAD (with survival information) was collected from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38537151", "locator": "sections[3] \"Data Source\" paragraph 2", "quote": "The RNA and miRNA sequencing information of LUAD (with survival information) was collected from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A prognostic signature based on three m5C-immune-related prognostic genes, HLA-DMB, PPIA, and GPI, was established for LUAD.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38537151", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Then, a m5C-IRGs prognostic signature was build based on the 3 prognostic genes (HLA-DMB, PPIA, and GPI)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A prognostic signature based on three m5C-immune-related prognostic genes, HLA-DMB, PPIA, and GPI, was established for LUAD.", "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:38537151"], "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:GSE31210"], "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:GSE31210"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38537151", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1177/10732748241237414", "sha256": 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