Integrative Omics Analysis Reveals Metabolic Features of Ground-Glass Opacity-Associated Lung Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38434969", "kind": "science-record", "revision": 3, "content_hash": "sha256:9c09854b187a1987e60099b052ccb92b360d3a4a5720abaad8df4b7e537496c3", "created_at": "2026-11-01T19:20:22Z", "updated_at": "2026-11-01T22:11:22Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Integrative Omics Analysis Reveals Metabolic Features of Ground-Glass Opacity-Associated Lung Cancer.", "doi": "10.7150/jca.92437", "pmid": "38434969", "authors": ["Shuai Shi", "Dayuan Luo", "Yanyi Yang", "Xiang Wang"], "journal": "Journal of Cancer", "year": 2024, "abstract": "Background: Ground-glass opacity (GGO)-associated cancers are increasingly prevalent, exhibiting unique clinical and molecular features that suggest the need for a distinct treatment strategy. However, the metabolic characteristics and vulnerabilities of GGO-associated lung cancers remain unexplored. Methods: We conducted metabolomic and transcriptomic analyses on 40 pairs of GGO-associated lung cancer tissues and adjacent normal tissues. By integrating data from TCGA database and single-cell RNA sequencing, we aimed to identify aberrant metabolic pathways, establish a metabolite-associated gene signature, and pinpoint key metabolic genes. The physiological effect of key genes was detected in vitro and vivo assays. Results: We identified a 30-gene metabolite-associated signature and discovered aberrant metabolic pathways for GGO-associated lung cancer at both metabolic and transcriptional levels. Patients with this signature displayed specific prognostic and molecular features. Cox regression analysis, based on the Cancer Genome Atlas Program (TCGA) data, further narrowed down the metabolite-related gene signature, resulting in a 5-gene signature. Confirmed by single-cell RNA sequencing (GSE203360), the 5-gene signature was mainly expressed in cancer cells of GGO tissue. Real-time quantitative PCR (RT-qPCR) further validated the differential expression of these genes between GGO and adjacent normal tissue obtained from pulmonary surgery. Finally, our integrative analysis unveiled aberrant histidine metabolism at both the multi-omics and single-cell levels. Moreover, we identified MAOB as a key metabolic gene, demonstrating its ability to suppress cell proliferation, migration, and invasion in LUAD cell lines, both in vitro and in vivo. Conclusions: We identified a specific metabolite-associated gene signature and identified aberrant histidine metabolism in GGO-associated lung cancer from multiple perspectives. Notably, MAOB, a crucial component in histidine metabolism, demonstrated a significant inhibitory effect on the proliferation and metastasis of LUAD, indicating its potential significance in pathogenesis and therapeutic interventions.", "claims": [{"id": "claim-method", "statement": "According to stepwise Cox regression, we ultimately identified 5 genes as a metabolite- associated risk signature in the Cox proportional hazard model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38434969", "locator": "sections[26] \"Screening for metabolic genes with prognostic value\" paragraph 2", "quote": "According to stepwise Cox regression, we ultimately identified 5 genes as a metabolite- associated risk signature in the Cox proportional hazard model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Based on the 30-gene multi-omics signature, we conducted k-means consensus clustering analysis on 503 LUAD samples from TCGA.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38434969", "locator": "sections[25] \"Clusters based on metabolite-associated gene signature have distinct prognostic and physiological features\" paragraph 2", "quote": "Based on the 30-gene multi-omics signature, we conducted k-means consensus clustering analysis on 503 LUAD samples from TCGA."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Stepwise Cox regression identified a five-gene metabolite-associated risk signature comprising NT5E, SULT2B1, CYP3A5, MAOB, and PLD4, and TCGA LUAD patients in the high-risk group had a worse prognosis (P < 0.001).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38434969", "locator": "sections[26] \"Screening for metabolic genes with prognostic value\" paragraph 2", "quote": "According to stepwise Cox regression, we ultimately identified 5 genes as a metabolite- associated risk signature in the Cox proportional hazard model. The 5 risk genes are NT5E, SULT2B1, CYP3A5, MAOB and PLD4 (Figure 4B)."}, {"asset": "source:pmid:38434969", "locator": "sections[26] \"Screening for metabolic genes with prognostic value\" paragraph 2", "quote": "LUAD patients deriving from TCGA were divided into high and low-risk groups according to the median of risk score, and patients in the high-risk group had a worse prognosis with a P-value less than 0.001 (Figure 4C)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Stepwise Cox regression identified a five-gene metabolite-associated risk signature comprising NT5E, SULT2B1, CYP3A5, MAOB, and PLD4, and TCGA LUAD patients in the high-risk group had a worse prognosis (P < 0.001).", "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:38434969"], "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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Real-time quantitative PCR (RT-qPCR) further validated the differential expressi", "f GGO tissue. Real-time quantitative PCR (RT-qPCR) further validated the differential expressi", "nly expressed in cancer cells of GGO tissue. Real-time quantitative PCR (RT-qPCR) further validated the differential"], "order_basis": "paper_text_order:1349", "id": "assay:1"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.77, "evidence": ["vasion in LUAD cell lines, both in vitro and in vivo. 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