ArticleJournal of proteome research2024
Metabolomic Profiling of Tumor Tissues Unveils Metabolic Shifts in Non-Small Cell Lung Cancer Patients with Concurrent Diabetes Mellitus.
Article in Journal of proteome research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- The obesity paradox effect of triglyceride-glucose-body mass index (TyG-BMI) on all-cause mortality in patients with malignant tumors: a machine learning-driven cohort study.Translational cancer research · 2026Article
- Development and validation of a plasma-urine metabolism diagnostic model for renal cell carcinoma using machine learning.World journal of urology · 2025Article
- Development and validation of models based on clinical and CT features: multivariate analysis for predicting vascular invasion in non-small cell lung cancer.Quantitative imaging in medicine and surgery · 2025Article
- Effect of type 2 diabetes mellitus on systemic treatment for advanced non-small cell lung cancer.Translational lung cancer research · 2025Article
- Methods and Guidelines for Metabolism Studies: Applications to Cancer Research.International journal of molecular sciences · 2025Review
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Authors and funding
6 authors.
Funding
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Abstract
A comprehensive understanding of the exact influence of type 2 diabetes mellitus (T2DM) on the metabolic status of non-small cell lung cancer (NSCLC) is still lacking. This study explores metabolic alterations in tumor tissues among patients with coexisting NSCLC and T2DM in comparison with NSCLC patients. A combined approach of clinical analysis and metabolomics was employed, including 20 NSCLC patients and 20 NSCLC+T2DM patients. Targeted metabolomics analysis was performed on tumor tissues using the liquid chromatography-mass spectrometry (LC-MS) approach. A clear segregation was observed between NSCLC+T2DM and matched NSCLC tissue samples in Orthogonal Partial Least Squares Discrimination Analysis (OPLS-DA). Furthermore, the levels of 7 metabolites are found to be significantly different between diabetes/nondiabetes tumor tissue samples. The related pathways included arginine biosynthesis, glutathione metabolism, arginine and proline metabolism, purine metabolism, biotin metabolism, and histidine metabolism. 3-Phenyllactic acid, carnitine-C5, carnitine-C12, and serotonin showed a positive linear correlation with fasting blood glucose levels in NSCLC patients. Uridine, pipecolic acid, cytosine, and fasting blood glucose levels were found to have a negative correlation. Our results suggest that NSCLC patients with concurrent T2DM exhibit distinct metabolic shifts in tumor tissues compared to those of solely NSCLC patients.
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