The Significance of MAPK Signaling Pathway in the Diagnosis and Subtype Classification of Intervertebral Disc Degeneration.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40134951", "kind": "science-record", "revision": 4, "content_hash": "sha256:2818702af80c62c962e40f7ff3b677aa0c1ef63ff35c6317876dfccb064327db", "created_at": "2026-11-01T20:30:20Z", "updated_at": "2026-11-01T22:56:17Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "The Significance of MAPK Signaling Pathway in the Diagnosis and Subtype Classification of Intervertebral Disc Degeneration.", "doi": "10.1002/jsp2.70060", "pmid": "40134951", "authors": ["Yong Liu", "Xueyan Chen", "Jingwen Chen", "Chao Song", "Zhangchao Wei", "Zongchao Liu", "Fei Liu"], "journal": "JOR spine", "year": 2025, "abstract": "Background: Intervertebral disc degeneration (IDD) is a human aging disease related mainly to inflammation, cellular senescence, RNA/DNA methylation, and ECM. The mitogen-activated protein kinase (MAPK) signaling pathway is engaged in multiple biological functions by phosphorylating specific serine and threonine residues on target proteins through phosphorylation cascade effects, but the role and specific mechanisms of the MAPK signaling pathway in IDD are still unclear.\nMethods: We identified 20 MAPK-related differential genes by differential analysis of the GSE124272 and GSE150408 datasets from the GEO database. To explore the biological functions of these differential genes in humans, we performed GO and KEGG analyses. Additionally, we applied PPI networks, LASSO analysis, the RF algorithm, and the SVM-RFE algorithm to identify core MAPK-related genes. Finally, we conducted further validation using clinical samples.\nResults: We ultimately identified and validated four pivotal MAPK-related genes, namely, KRAS, JUN, RAP1B, and TNF, using clinical samples, and constructed the ROC curves to evaluate the predictive accuracy of the hub genes. A nomogram model was subsequently developed based on these four hub MAPK genes to predict the prevalence of IDD. Based on these four hub genes, we classified IDD patients into two MAP clusters by applying the consensus clustering method and identified 1916 DEGs by analyzing the differences between the two clusters. Further analysis using the same approach allowed us to identify two gene clusters based on these DEGs. We used a PCA algorithm to determine the MAPK score for each sample and discovered that MAPK cluster A and gene cluster A had higher scores, suggesting greater sensitivity to MAPK signaling pathway-associated agents in the subtype. We displayed the differing expression levels of four hub MAPK-related genes across the two clusters and their relationship with immune cell infiltration to highlight the distinctions between clusters A and B.\nConclusion: In summary, four hub MAPK signaling pathway-related genes, KRAS, JUN, RAP1B, and TNF, could be applied to the diagnosis and subtype classification of IDD and benefit the prevention and treatment of IDD.", "claims": [{"id": "claim-method", "statement": "The protein–protein interaction (PPI) network (interaction score > = 0.4) [23], least absolute shrinkage and selection operator (LASSO) analysis (10‐fold cross‐validation), random forest (RF) algorithm (ntree = 500), and support vector machine recursive feature elimination (SVM‐RFE) algorithm were used to identify hub MAPK‐related genes [24].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40134951", "locator": "sections[4] \"Identification and Validation of Hub MAPK‐Related Genes in IDD\" paragraph 2", "quote": "The protein–protein interaction (PPI) network (interaction score > = 0.4) [23], least absolute shrinkage and selection operator (LASSO) analysis (10‐fold cross‐validation), random forest (RF) algorithm (ntree = 500), and support vector machine recursive feature elimination (SVM‐RFE) algorithm were used to identify hub MAPK‐related genes [24]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article (Supporting Information Material); further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40134951", "locator": "sections[28] \"Data Availability Statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article (Supporting Information Material); further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The study identified and clinically validated four hub MAPK-related genes—KRAS, JUN, RAP1B, and TNF—as diagnostic and subtype-classification markers for intervertebral disc degeneration.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40134951", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We ultimately identified and validated four pivotal MAPK‐related genes, namely, KRAS, JUN, RAP1B, and TNF, using clinical samples, and constructed the ROC curves to evaluate the predictive accuracy of the hub genes."}, {"asset": "source:pmid:40134951", "locator": "sections[13] \"Identification of Hub MAPK‐Related Genes\" paragraph 2", "quote": "The AUC values of JUN, KRAS, RAP1B, and TNF were 0.728, 0.725, 0.776, and 0.737, respectively, indicating that the four hub MAPK‐related genes had a high accuracy and predictive value (Figure S2)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The study identified and clinically validated four hub MAPK-related genes—KRAS, JUN, RAP1B, and TNF—as diagnostic and subtype-classification markers for intervertebral disc degeneration.", "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:40134951"], "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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