ArticleOncoTargets and therapy2018
Integrated omics and gene expression analysis identifies the loss of metabolite-metabolite correlations in small cell lung cancer.
Article in OncoTargets and therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Smoking-Stratified Signal Decomposition and Feature Selection for Never-Smoker Cancer Classification in a Combined Lung-Breast Metabolomics Cohort.International journal of molecular sciences · 2026Article
- Proteogenomic Characterization of High-Grade Lung Neuroendocrine Carcinoma Deciphers Molecular Diversity and Potential Biomarkers of Different Histological Subtypes in Chinese Population.Research (Washington, D.C.) · 2025Article
- Two-Stage Deep-Learning Classifier for Diagnostics of Lung Cancer Using Metabolites.Metabolites · 2023Article
- Review
- Progression and metastasis of small cell lung carcinoma: the role of the PI3K/Akt/mTOR pathway and metabolic alterations.Cancer metastasis reviews · 2021Review
- Path to Clonal Theranostics in Luminal Breast Cancers.Frontiers in oncology · 2021Article
- The MEK5-ERK5 Kinase Axis Controls Lipid Metabolism in Small-Cell Lung Cancer.Cancer research · 2020Article
- Article
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveSmall cell lung cancer (SCLC) is the most aggressive type of lung carcinoma with high metastatic potential and chemoresistance upon relapse. Cancer cells remodel the existing metabolic pathways for their benefits and the perturbations in cellular metabolism are the hallmark of cancer. However, the extent of these changes remains largely unknown for SCLC. MATERIALS AND
methodsWe characterized the metabolic perturbations in SCLC cells (SCLCC) by metabolomics. Large-scale correlation analysis was performed between metabolites. Targeted proteomics and gene expression analysis were employed to investigate the changes of key enzymes and genes in the disturbed pathways.
resultsWe found dramatic decrease of metabolite-metabolite correlations in SCLCC compared with normal control cells and non-small cell lung cancer cells. Pathway analysis revealed that the loss of correlations was associated with the alternations of fatty acid oxidation, urea cycle, and purine salvage pathway in SCLCC. Targeted proteomics and gene expression analysis confirmed significant changes of the expression for the key enzymes and genes in the pathways in SCLCC including the upregulation of carbamoyl phosphate synthase 1 (urea cycle) and carnitine palmitoyltransferase 1A (fatty acid oxidation), and the downregulation of hypoxanthine-guanine phosphoribosyltransferase and adenine phosphoribosyltransferase in purine salvage pathway.
conclusionWe demonstrated the loss of metabolite-metabolite correlations in SCLCC associated with the upregulation of fatty acid oxidation and urea cycle and the downregulation of purine salvage pathways. Our findings provide insights into the metabolic reprogramming in SCLCC and highlight the potential therapeutic targets for the treatment of SCLC.
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