Identification of signature genes and relationship with immune cell infiltration in intervertebral disc degeneration.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40270539", "kind": "science-record", "revision": 2, "content_hash": "sha256:26ccec68ab51a96995ae892644af2b4e7e7e41edc454b9ec07c445923fccacd4", "created_at": "2026-11-01T20:30:25Z", "updated_at": "2026-11-01T21:35:03Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of signature genes and relationship with immune cell infiltration in intervertebral disc degeneration.", "doi": "10.3389/fgene.2025.1551124", "pmid": "40270539", "authors": ["Kun Mu", "JingChao Geng", "Yu Dong", "Wei Guo"], "journal": "Frontiers in genetics", "year": 2025, "abstract": "Background: Early diagnosis of intervertebral disc (IVD) degeneration is of great significance for prevention of the disease from progressing to a serious stage. This study aimed to investigate the signature genes and their association with immune cells in IVD degeneration.\nMethods: We analyzed differentially expressed genes (DEGs) in a dataset of IVD degeneration samples from the GEO database. Weighted gene coexpression network analysis (WGCNA) and DEGs were employed to pinpoint the key modules and IVD degeneration genes. Functional enrichment analysis was performed for these IVD degeneration genes. Signature genes were identified using least absolute shrinkage and selection operator (LASSO) analysis. Gene set enrichment analysis (GSEA) was used to explore signaling pathways related to signature genes, and CIBERSORT® was used to classify immune cell infiltration. Function of the hub gene was confirmed by PCR, Western blotting and ELISA.\nResults: 2,254 DEGs were identified from GSE56081, and WGCNA grouped the data into 9 modules. MEbrown module had a significant correlation with IVD degeneration (cor = 0.99, P = 8.00 × 10-8). LASSO analysis selected HSPA1B, TOB1, ECM1, PTTG1IP as signature genes with excellent diagnostic efficiency. Furthermore, we assessed the diagnostic efficacy of every signature gene in predicting IVD degeneration using an external validation group (GSE70362). The results showed that two of the signature genes (TOB1, ECM1) had significant diagnostic effect in predicting the degeneration of IVD. GSEA analysis showed TOB1 and ECM1 involve in NOD like receptor signaling pathway, phenylalanine metabolism. Ether lipid metabolism, glycosaminoglycan biosynthesis keratin sulfate, RNA degradation pathway. CIBERSORT® suggested TOB1 and ECM1 may participate in immune cells infiltration. Finally, we identified TOB1 as a crucial molecule in the process of NP cell pyroptosis and NLRP3 inflammasome activation.\nConclusion: TOB1 may show remarkable diagnostic performance in IVD degeneration and may be implicated in the infiltration of immune cells.", "claims": [{"id": "claim-method", "statement": "In this study, LASSO analysis was applied to screen out signature genes from signature genes of IVD degeneration. And a total of 4 signature genes were identified, including HSPA1B, TOB1, ECM1, PTTG1IP (Figures 5A,B).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40270539", "locator": "sections[23] \"Selection of signature genes through LASSO analysis\" paragraph 2", "quote": "In this study, LASSO analysis was applied to screen out signature genes from signature genes of IVD degeneration. And a total of 4 signature genes were identified, including HSPA1B, TOB1, ECM1, PTTG1IP (Figures 5A,B)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are publicly available. This data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE56081 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE70362.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40270539", "locator": "sections[29] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are publicly available. This data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE56081 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE70362."}], "state": "complete"}, {"id": "claim-target-result", "statement": "TOB1 may show remarkable diagnostic performance in IVD degeneration and may be implicated in the infiltration of immune cells.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40270539", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "TOB1 may show remarkable diagnostic performance in IVD degeneration and may be implicated in the infiltration of immune cells."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "TOB1 may show remarkable diagnostic performance in IVD degeneration and may be implicated in the infiltration of immune cells.", "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:40270539"], "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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This data can be found here: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE56081 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE70362.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The original contributions presented in the study are publicly available. 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Single-cell transcriptomic profiles of the NP tissue from IVD degenerat"], "order_basis": "paper_text_order:4856", "id": "assay:4"}, {"role": "data_generation", "definition_id": "scrna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "unsupported", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ion and control samples This study utilized (Single-cell RNA sequencing) scRNA-seq data (GSE165722) to analyze and i", "study utilized (Single-cell RNA sequencing) scRNA-seq data (GSE165722) to analyze and identify dif"], "order_basis": "paper_text_order:4960", "id": "assay:5"}]}