Multi-omics-based construction of a palmitoylation-driven prognostic model reveals tumor immune phenotypes in osteosarcoma.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40802135", "kind": "science-record", "revision": 2, "content_hash": "sha256:3f5eba1713cf93995efaba26c838d015c302e723332d6dc5ac23d069f859a9fa", "created_at": "2026-11-01T20:30:53Z", "updated_at": "2026-11-01T21:35:37Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Multi-omics-based construction of a palmitoylation-driven prognostic model reveals tumor immune phenotypes in osteosarcoma.", "doi": "10.1007/s12672-025-03364-8", "pmid": "40802135", "authors": ["Jingyu Chen", "Feihu Chen", "Haiping Zhang", "Yuanlong Hu", "Xingyu Zhou", "Xijia Weng", "Guofeng Bao", "Xiaomin Ding"], "journal": "Discover oncology", "year": 2025, "abstract": "BACKGROUND: Osteosarcoma (OS), the leading primary malignancy of bone in adolescents, is known for its aggressive metastatic behavior and poor responsiveness to conventional therapies. As a lipid-mediated post-translational modification, protein palmitoylation has gained attention for its pivotal role in modulating oncogenic signaling pathways and facilitating tumor immune escape. However, its prognostic value and functional role in OS remain unclear.\nMETHODS: Transcriptomic and clinical data from the TARGET and GEO cohorts were used to identify palmitoylation-related prognostic genes. The palmitoylation-related prognostic signature (PPS) was constructed using univariate Cox and LASSO regression. The model was validated by GSE39058 and assessed via survival analysis, ROC curves, and nomogram construction. Functional enrichment (GO, KEGG, GSVA) and immune infiltration analyses were performed. Single-cell expression profiles were explored using the TISCH2 database, and the predictive value of PPS for immunotherapy response was evaluated in the IMvigor210 cohort.\nRESULTS: A three-gene PPS (ZDHHC3, ZDHHC21, ZDHHC23) was identified and shown to independently predict survival in OS. Elevated PPS levels correlated with unfavorable clinical outcomes, diminished immune cell presence, and suppressed immune checkpoint molecule levels. Functional analysis revealed enrichment of oncogenic and immunosuppressive pathways in the high-PPS group. Single-cell analysis confirmed PPS gene expression in malignant and immune cells. In the IMvigor210 cohort, high PPS predicted worse response to anti-PD-L1 immunotherapy.\nCONCLUSIONS: This study establishes a novel palmitoylation-related prognostic signature in osteosarcoma, which reflects tumor aggressiveness and immune evasion. PPS holds promise as both a stratification indicator and an intervention point for osteosarcoma treatment.", "claims": [{"id": "claim-method", "statement": "To identify candidate prognostic markers among palmitoylation-related genes, univariate Cox analysis was first performed. Subsequently, the LASSO algorithm was employed to establish the prognostic model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40802135", "locator": "sections[4] \"Construction of palmitoylation-related prognostic signature\" paragraph 2", "quote": "To identify candidate prognostic markers among palmitoylation-related genes, univariate Cox analysis was first performed. Subsequently, the LASSO algorithm was employed to establish the prognostic model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets analyzed in this study are publicly available. Bulk transcriptomic and clinical data for osteosarcoma were obtained from the TARGET database (https://ocg.cancer.gov/programs/target) and the Gene Expression Omnibus (GEO, accession number: GSE39058). Single-cell RNA-seq data (GSE162454) were accessed via the TISCH2 database (http://tisch.comp-genomics.org/). Immunotherapy response data were retrieved from the IMvigor210 cohort, available at http://research-pub.gene.com/IMvigor210CoreBiologies.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40802135", "locator": "sections[25] \"Data availability\" paragraph 2", "quote": "The datasets analyzed in this study are publicly available. Bulk transcriptomic and clinical data for osteosarcoma were obtained from the TARGET database (https://ocg.cancer.gov/programs/target) and the Gene Expression Omnibus (GEO, accession number: GSE39058). Single-cell RNA-seq data (GSE162454) were accessed via the TISCH2 database (http://tisch.comp-genomics.org/). Immunotherapy response data were retrieved from the IMvigor210 cohort, available at http://research-pub.gene.com/IMvigor210CoreBiologies."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A three-gene PPS (ZDHHC3, ZDHHC21, ZDHHC23) was identified and shown to independently predict survival in OS.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40802135", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A three-gene PPS (ZDHHC3, ZDHHC21, ZDHHC23) was identified and shown to independently predict survival in OS."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A three-gene PPS (ZDHHC3, ZDHHC21, ZDHHC23) was identified and shown to independently predict survival in OS.", "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:40802135"], "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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Bulk transcriptomic and clinical data for osteosarcoma were obtained from the TARGET database (https://ocg.cancer.gov/programs/target) and the Gene Expression Omnibus (GEO, accession number: GSE39058). Single-cell RNA-seq data (GSE162454) were accessed via the TISCH2 database (http://tisch.comp-genomics.org/). Immunotherapy response data were retrieved from the IMvigor210 cohort, available at http://research-pub.gene.com/IMvigor210CoreBiologies.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets analyzed in this study are publicly available. Bulk transcriptomic and clinical data for osteosarcoma were obtained from the TARGET database (https://ocg.cancer.gov/programs/target) and the Gene Expression Omnibus (GEO, accession number: GSE39058). Single-cell RNA-seq data (GSE162454) were accessed via the TISCH2 database (http://tisch.comp-genomics.org/). 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