Probing Folate-Responsive and Stage-Sensitive Metabolomics and Transcriptional Co-Expression Network Markers to Predict Prognosis of Non-Small Cell Lung Cancer Patients

Tumour metabolomics and transcriptomics co-expression network as related to biological folate alteration and cancer malignancy remains unexplored in human non-small cell lung cancers (NSCLC). To probe the diagnostic biomarkers, tumour and pair lung tissue samples (n = 56) from 97 NSCLC patients were profiled for ultra-performance liquid chromatography tandem mass spectrometry (UPLC/MS/MS)-analysed metabolomics, targeted transcriptionomics, and clinical folate traits. Weighted Gene Co-expression Network Analysis (WGCNA) was performed. Tumour lactate was identified as the top VIP marker to predict advance NSCLC (AUC = 0.765, Sig = 0.017, CI 0.58-0.95). Low folate (LF)-tumours vs. adjacent lungs displayed higher glycolytic index of lactate and glutamine-associated amino acids in enriched biological pathways of amino sugar and glutathione metabolism specific to advance NSCLCs. WGCNA classified the green module for hub serine-navigated glutamine metabolites inversely associated with tumour and RBC folate, which module metabolites co-expressed with a predominant up-regulation of LF-responsive metabolic genes in glucose transport (GLUT1), de no serine synthesis (PHGDH, PSPH, and PSAT1), folate cycle (SHMT1/2 and PCFR), and down-regulation in glutaminolysis (SLC1A5, SLC7A5, GLS, and GLUD1). The LF-responsive WGCNA markers predicted poor survival rates in lung cancer patients, which could aid in optimizing folate intervention for better prognosis of NSCLCs susceptible to folate malnutrition.

Automated summary

This study investigates the co-expression network of tumour metabolomics and transcriptomics in relation to biological folate alteration and cancer malignancy in non-small cell lung cancers (NSCLC). Tumour lactate is identified as a top marker for predicting advanced NSCLC. Low folate (LF) tumours show higher glycolytic index and enrichment of specific biological pathways associated with amino sugar and glutathione metabolism. The co-expression network analysis reveals the involvement of LF-responsive metabolic genes in glucose transport, serine synthesis, folate cycle, and glutaminolysis. LF-responsive markers are also associated with poor survival rates in lung cancer patients.