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pmid:39717265

Bioinformatics Analysis of Biomarkers and Therapeutic Targets Related to Necroptosis in Intervertebral Disc Degeneration.

Fan Zhang · Lei Yuan · Heng Ding · Zhenkai Lou · Xingguo Li

BioMed research international · 2024 doi:10.1155/bmri/9922966

Paper

complete

Experiment

complete

Data

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title
Bioinformatics Analysis of Biomarkers and Therapeutic Targets Related to Necroptosis in Intervertebral Disc Degeneration.
doi
10.1155/bmri/9922966
pmid
39717265
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[0]
Fan Zhang
[1]
Lei Yuan
[2]
Heng Ding
[3]
Zhenkai Lou
[4]
Xingguo Li
journal
BioMed research international
year
2024
abstract
Necroptosis is a critical process in intervertebral disc degeneration (IDD). This research is aimed at identifying key genes regulating necroptosis in IDD to provide a theoretical basis for early diagnosis and treatment. Transcriptome data from patients with IDD and normal samples were obtained from the GSE34095 and GSE124272 datasets of the Gene Expression Omnibus (GEO) public database. Necroptosis-related genes (NRGs) were sourced from the GeneCards database and literature. Differentially expressed necroptosis-related genes (DE-NRGs) in IDD were identified by intersecting these sources. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for gene annotation analysis. The receiver operating characteristic (ROC) curve and nomogram analyses assessed the diagnostic efficiency of DE-NRGs. The miRWalk and starBase databases helped construct the competing endogenous RNA (ceRNA) regulatory network of DE-NRGs. We identified 517 differential genes in tissue and 2974 in blood, with 62 genes in common. DE-NRGs (AIFM1, CCT8, HNRNPA1, KHDRBS1, SERBP1) were identified by intersecting NRGs with these 62 common genes. The ROC curve showed an area under the curve (AUC) > 0.70 for DE-NRGs, and the nomogram indicated that a higher DE-NRG score correlates with a higher risk of IDD. CCT8, KHDRBS1, and AIFM1 emerged as potential therapeutic targets for IDD through target drug prediction. qRT-PCR (quantitative reverse transcription polymerase chain reaction), Western blot, and immunohistochemistry confirmed the expression of AIFM1, CCT8, HNRNPA1, KHDRBS1, and SERBP1 in patients' nucleus pulposus tissue, suggesting these genes as key targets for IDD risk assessment and drug therapy.
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To assess the diagnostic value of DE-NRGs for IDD patients, we plotted ROC curves and calculated area under the curve (AUC) values.
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sections[15] "3.2. Acquisition and Functional Analysis of Key Genes of Necroptosis" paragraph 4
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To assess the diagnostic value of DE-NRGs for IDD patients, we plotted ROC curves and calculated area under the curve (AUC) values.
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Five necroptosis-related diagnostic genes had an ROC AUC greater than 0.70, and higher DE-NRG scores were associated with greater IDD risk.
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The ROC curve showed an area under the curve (AUC) > 0.70 for DE-NRGs, and the nomogram indicated that a higher DE-NRG score correlates with a higher risk of IDD.
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sections[15] "3.2. Acquisition and Functional Analysis of Key Genes of Necroptosis" paragraph 4
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The analysis results showed that the AUC values of five DE-NRGs were greater than 0.7 (Figure 2(e)), and the AUC values of LR, RF, SVM, and ANN models were greater than 0.7 (Figure 2(f)).
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sections[15] "3.2. Acquisition and Functional Analysis of Key Genes of Necroptosis" paragraph 4
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In the nomogram, a higher score indicates a higher risk of IDD.
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Five necroptosis-related diagnostic genes had an ROC AUC greater than 0.70, and higher DE-NRG scores were associated with greater IDD risk.
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se transcription polymerase chain reaction), Western blot, and immunohistochemistry confirmed the expr
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red differential genes were enriched to some apoptosis and cell cycle–related pathways; next, we fo
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cycle–related pathways; next, we focused on apoptosis and analyzed necrotic apoptosis. We obtained
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e focused on apoptosis and analyzed necrotic apoptosis. We obtained a total 643 NRGs from different
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hway, mRNA regulatory pathways, spliceosome, apoptosis, necrosis, ribosomes, and more (Figure 2(d))
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39717265", "kind": "science-record", "revision": 3, "content_hash": "sha256:bf9119165099e08db5a0fe8a23f60cb584b47cdbda6fcdec36540bdd1d5c384a", "created_at": "2026-11-01T20:30:02Z", "updated_at": "2026-11-01T22:13:25Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics Analysis of Biomarkers and Therapeutic Targets Related to Necroptosis in Intervertebral Disc Degeneration.", "doi": "10.1155/bmri/9922966", "pmid": "39717265", "authors": ["Fan Zhang", "Lei Yuan", "Heng Ding", "Zhenkai Lou", "Xingguo Li"], "journal": "BioMed research international", "year": 2024, "abstract": "Necroptosis is a critical process in intervertebral disc degeneration (IDD). This research is aimed at identifying key genes regulating necroptosis in IDD to provide a theoretical basis for early diagnosis and treatment. Transcriptome data from patients with IDD and normal samples were obtained from the GSE34095 and GSE124272 datasets of the Gene Expression Omnibus (GEO) public database. Necroptosis-related genes (NRGs) were sourced from the GeneCards database and literature. Differentially expressed necroptosis-related genes (DE-NRGs) in IDD were identified by intersecting these sources. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for gene annotation analysis. The receiver operating characteristic (ROC) curve and nomogram analyses assessed the diagnostic efficiency of DE-NRGs. The miRWalk and starBase databases helped construct the competing endogenous RNA (ceRNA) regulatory network of DE-NRGs. We identified 517 differential genes in tissue and 2974 in blood, with 62 genes in common. DE-NRGs (AIFM1, CCT8, HNRNPA1, KHDRBS1, SERBP1) were identified by intersecting NRGs with these 62 common genes. The ROC curve showed an area under the curve (AUC) > 0.70 for DE-NRGs, and the nomogram indicated that a higher DE-NRG score correlates with a higher risk of IDD. CCT8, KHDRBS1, and AIFM1 emerged as potential therapeutic targets for IDD through target drug prediction. qRT-PCR (quantitative reverse transcription polymerase chain reaction), Western blot, and immunohistochemistry confirmed the expression of AIFM1, CCT8, HNRNPA1, KHDRBS1, and SERBP1 in patients' nucleus pulposus tissue, suggesting these genes as key targets for IDD risk assessment and drug therapy.", "claims": [{"id": "claim-method", "statement": "To assess the diagnostic value of DE-NRGs for IDD patients, we plotted ROC curves and calculated area under the curve (AUC) values.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39717265", "locator": "sections[15] \"3.2. Acquisition and Functional Analysis of Key Genes of Necroptosis\" paragraph 4", "quote": "To assess the diagnostic value of DE-NRGs for IDD patients, we plotted ROC curves and calculated area under the curve (AUC) values."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data are available on request from the authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39717265", "locator": "sections[23] \"Data Availability Statement\" paragraph 2", "quote": "Data are available on request from the authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Five necroptosis-related diagnostic genes had an ROC AUC greater than 0.70, and higher DE-NRG scores were associated with greater IDD risk.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39717265", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The ROC curve showed an area under the curve (AUC) > 0.70 for DE-NRGs, and the nomogram indicated that a higher DE-NRG score correlates with a higher risk of IDD."}, {"asset": "source:pmid:39717265", "locator": "sections[15] \"3.2. Acquisition and Functional Analysis of Key Genes of Necroptosis\" paragraph 4", "quote": "The analysis results showed that the AUC values of five DE-NRGs were greater than 0.7 (Figure 2(e)), and the AUC values of LR, RF, SVM, and ANN models were greater than 0.7 (Figure 2(f))."}, {"asset": "source:pmid:39717265", "locator": "sections[15] \"3.2. Acquisition and Functional Analysis of Key Genes of Necroptosis\" paragraph 4", "quote": "In the nomogram, a higher score indicates a higher risk of IDD."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Five necroptosis-related diagnostic genes had an ROC AUC greater than 0.70, and higher DE-NRG scores were associated with greater IDD risk.", "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:39717265"], "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:GSE116726"], "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:GSE116726"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39717265", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/bmri/9922966", "sha256": 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(b) Western blot detection of MLKL activity (randomly select"], "order_basis": "paper_text_order:1567", "id": "assay:1"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["olymerase chain reaction), Western blot, and immunohistochemistry confirmed the expression of AIFM1, CCT8, HNR", "transcription polymerase chain reaction) and immunohistochemistry (IHC) experiments. 2.6. Therapeutic Drug Pre", "se chain reaction) and immunohistochemistry (IHC) experiments. 2.6. Therapeutic Drug Predicti", "tients than in S-IDD patients (Figure 5(b)). IHC assays similarly showed higher MLKL expressi"], "order_basis": "paper_text_order:1585", "id": "assay:2"}, {"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["red differential genes were enriched to some apoptosis and cell cycle–related pathways; next, we fo", "cycle–related pathways; next, we focused on apoptosis and analyzed necrotic apoptosis. We obtained", "e focused on apoptosis and analyzed necrotic apoptosis. We obtained a total 643 NRGs from different", "hway, mRNA regulatory pathways, spliceosome, apoptosis, necrosis, ribosomes, and more (Figure 2(d))"], "order_basis": "paper_text_order:3341", "id": "assay:3"}, {"role": "analysis", "definition_id": "group_comparison", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["group_summary", "welch_t", "bootstrap_mean_difference", "group_comparison_anova"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.8, "evidence": ["ANOVA"], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}