ArticleCancer medicine2023
Integrative metabolomics and transcriptomics analysis reveals novel therapeutic vulnerabilities in lung cancer.
Article in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 18 citations in OpenAlex.
- Single-cell transcriptomic analysis identifies a tumor-enriched GIMAP7⁺ CD4⁺ naïve T cell population with a unique immunoregulatory state in lung adenocarcinoma.Functional & integrative genomics · 2026Article
- Serum Metabolomics Study Reveals a Diagnostic Model for Lung Cancer Brain Metastasis.The clinical respiratory journal · 2026Article
- Leveraging untargeted metabolomics in combination with machine learning to uncover novel insights into bladder cancer.Cancer & metabolism · 2026Article
- The identification of RNA splicing aberrations and their potential regulatory network in Chinese non-small cell lung cancer.Respiratory research · 2026Article
- Promotion of lung cancer growth via glutamate ionotropic receptor N-methyl-D-aspartate-type subunit 2D (Journal of thoracic disease · 2026Article
- Bioinformatics Identification and Experimental Validation of a Prognostic Model for the Survival of Lung Squamous Cell Carcinoma Patients.Biochemical genetics · 2025Article
- Multi-tissue metabolomics reveal mtDNA- and diet-specific metabolite profiles in a mouse model of cardiometabolic disease.Redox biology · 2025Article
- Immune inflammatory regulation in Anti-NMDAR encephalitis: insights from transcriptome analysis.Frontiers in neurology · 2025Article
- Fuel for thought: targeting metabolism in lung cancer.Translational lung cancer research · 2024Review
- Metabolomic Profiling of Tumor Tissues Unveils Metabolic Shifts in Non-Small Cell Lung Cancer Patients with Concurrent Diabetes Mellitus.Journal of proteome research · 2024Article
- Efficacy and safety of anlotinib in combination with immune checkpoint inhibitors or not as advanced non-small cell lung cancer treatment: a systematic review and network meta-analysis.Translational cancer research · 2024Article
- Cross-omics strategies and personalised options for lung cancer immunotherapy.Frontiers in immunology · 2024Review
- Integrative Omics Analysis Reveals Metabolic Features of Ground-Glass Opacity-Associated Lung Cancer.Journal of Cancer · 2024Article
- Multiomic Investigations into Lung Health and Disease.Microorganisms · 2023Review
- Depiction of neuroendocrine features associated with immunotherapy response using a novel one-class predictor in lung adenocarcinoma.Discover oncology · 2023Article
- Integrative metabolomics and transcriptomics analysis reveals novel therapeutic vulnerabilities in lung cancer.Cancer medicine · 2023Article
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Authors and funding
15 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundNon-small cell lung cancer (NSCLC) comprises the majority (~85%) of all lung tumors, with lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) being the most frequently diagnosed histological subtypes. Multi-modal omics profiling has been carried out in NSCLC, but no studies have yet reported a unique metabolite-related gene signature and altered metabolic pathways associated with LUAD and LUSC.
methodsWe integrated transcriptomics and metabolomics to analyze 30 human lung tumors and adjacent noncancerous tissues. Differential co-expression was used to identify modules of metabolites that were altered between normal and tumor.
resultsWe identified unique metabolite-related gene signatures specific for LUAD and LUSC and key pathways aberrantly regulated at both transcriptional and metabolic levels. Differential co-expression analysis revealed that loss of coherence between metabolites in tumors is a major characteristic in both LUAD and LUSC. We identified one metabolic onco-module gained in LUAD, characterized by nine metabolites and 57 metabolic genes. Multi-omics integrative analysis revealed a 28 metabolic gene signature associated with poor survival in LUAD, with six metabolite-related genes as individual prognostic markers.
conclusionsWe demonstrated the clinical utility of this integrated metabolic gene signature in LUAD by using it to guide repurposing of AZD-6482, a PI3Kβ inhibitor which significantly inhibited three genes from the 28-gene signature. Overall, we have integrated metabolomics and transcriptomics analyses to show that LUAD and LUSC have distinct profiles, inferred gene signatures with prognostic value for patient survival, and identified therapeutic targets and repurposed drugs for potential use in NSCLC treatment.
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