Development of a 5-mRNAsi-related gene signature to predict the prognosis of colon adenocarcinoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38025763", "kind": "science-record", "revision": 2, "content_hash": "sha256:02a5ead161dd0e86677f3c65a2d4683ec035e6e478e3274df3810e9678837f18", "created_at": "2026-11-01T19:02:57Z", "updated_at": "2026-11-01T21:32:03Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Development of a 5-mRNAsi-related gene signature to predict the prognosis of colon adenocarcinoma.", "doi": "10.7717/peerj.16477", "pmid": "38025763", "authors": ["Haifu Huang", "Lin Lu", "Yaoxuan Li", "Xiumei Chen", "Meng Li", "Meiling Yang", "Xuewu Huang"], "journal": "PeerJ", "year": 2023, "abstract": "Aim: To create a prognosis model based on mRNA-based stem index (mRNAsi) for evaluating the prognostic outcomes of colon adenocarcinoma (COAD).\nBackground: Generation of heterogeneous COAD cells could be promoted by the self-renewal and differentiation potential of cancer stem cells (CSCs). Biomarkers contributing to the development of COAD stem cells remained to be discovered.\nObjective: To develop and validate an mRNAsi-based risk model for estimating the prognostic outcomes of patients suffering from COAD.\nMethods: Samples were collected from Rectal Adenocarcinoma (TCGA-READ) PanCancer Atlas datasets, The Cancer Genome Atlas Colon Adenocarcinoma (TCGA-COAD), and the GSE87211 dataset. MRNAsi was calculated by one-class logistic regression (OCLR) algorithm. Under the criterion of correlation greater than 0.4, genes related to mRNAsi were screened and clustered. Meanwhile, differentially expressed genes (DEGs) between molecular subtypes were identified to establish a risk model. According to the median risk score value for immunotherapy and results from immune cell infiltration and clinicopathological analyses, clusters and patients were divided into high-RiskScore and low-RiskScore groups. Cell apoptosis and viability were detected by flow cytometer and Cell Counting Kit-8 (CCK-8) assay, respectively.\nResults: A negative correlation between mRNAsi and clinical stages was observed. Three clusters of patients (C1, C2, and C3) were defined based on a total of 165 survival-related mRNAsi genes. Specifically, C1 patients had greater immune cell infiltration and a poorer prognosis. A 5-mRNAsi-gene signature (HEYL, FSTL3, FABP4, ADAM8, and EBF4) served as a prediction index for COAD prognosis. High-RiskScore patients had a poorer prognosis and higher level of immune cell infiltration. In addition, the five genes in the signature all showed a high expression in COAD cells. Knocking down HEYL promoted COAD cell apoptosis and inhibited viability.\nConclusion: Our mRNAsi risk model could better predict the prognosis of COAD patients.", "claims": [{"id": "claim-method", "statement": "LASSO analysis in glmnet package showed trajectory and confidence interval of lambda (Figs. S1A–S1B). When lambda = 0.0244, 5 genes were used as model genes: RiskScore = 0.278*HEYL+0.091*FSTL3+0.07*FABP4+0.115*ADAM8+0.057*EBF4", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38025763", "locator": "sections[22] \"Establishment of a RiskScore model for predicting COAD prognosis\" paragraph 2", "quote": "LASSO analysis in glmnet package showed trajectory and confidence interval of lambda (Figs. S1A–S1B). When lambda = 0.0244, 5 genes were used as model genes: RiskScore = 0.278*HEYL+0.091*FSTL3+0.07*FABP4+0.115*ADAM8+0.057*EBF4"}], "state": "complete"}, {"id": "claim-data-access", "statement": "The following information was supplied regarding data availability:The data is available at NCBI GEO: GSE87211.The data analyzed in this study is available at Github and Zenodo:–https://github.com/xuewuhu/Raw-data.git – xuewuhu. (2023). xuewuhu/Raw-data: First release of my data (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.8417835", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38025763", "locator": "sections[29] \"Additional Information and Declarations\" paragraph 4", "quote": "The following information was supplied regarding data availability:The data is available at NCBI GEO: GSE87211.The data analyzed in this study is available at Github and Zenodo:–https://github.com/xuewuhu/Raw-data.git – xuewuhu. (2023). xuewuhu/Raw-data: First release of my data (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.8417835"}], "state": "complete"}, {"id": "claim-target-result", "statement": "A five-gene mRNAsi signature (HEYL, FSTL3, FABP4, ADAM8, and EBF4) was developed to predict COAD prognosis, and the high-RiskScore group had poorer survival.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38025763", "locator": "sections[0] \"Abstract\" paragraph 5", "quote": "A 5-mRNAsi-gene signature (HEYL, FSTL3, FABP4, ADAM8, and EBF4) served as a prediction index for COAD prognosis. High-RiskScore patients had a poorer prognosis and higher level of immune cell infiltration."}, {"asset": "source:pmid:38025763", "locator": "sections[22] \"Establishment of a RiskScore model for predicting COAD prognosis\" paragraph 2", "quote": "Based on our identification of the three molecular subtypes, we screened a total of 656 DEGs among the three subtypes using the limma package. Subsequently, 110 prognosis-associated genes were further identified by univariate Cox analysis, and 20 genes with the most significant correlation with mRNAsi were determined. LASSO analysis in glmnet package showed trajectory and confidence interval of lambda (Figs. S1A–S1B). When lambda = 0.0244, 5 genes were used as model genes: RiskScore = 0.278*HEYL+0.091*FSTL3+0.07*FABP4+0.115*ADAM8+0.057*EBF4"}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A five-gene mRNAsi signature (HEYL, FSTL3, FABP4, ADAM8, and EBF4) was developed to predict COAD prognosis, and the high-RiskScore group had poorer 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:38025763"], "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:GSE87211"], "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:GSE87211"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38025763", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7717/peerj.16477", "sha256": "sha256:4247ef6a8b571ff300016a823dd77e0b59716ca8d39a9d8fadda0d84eba8f257", "bytes": 34865, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.7717/peerj.16477", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC10680455", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE87211", "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=GSE87211", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE87211", "version": null, "note": "The following information was supplied regarding data availability:The data is available at NCBI GEO: GSE87211.The data analyzed in this study is available at Github and Zenodo:–https://github.com/xuewuhu/Raw-data.git – xuewuhu. 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S1A–S1B). 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