Multi-omics of Metabolic Reprogramming in Cancer: Mechanisms, Diagnostics, and Therapy

Metabolic reprogramming is a hallmark of cancer, enabling tumor cells to sustain uncontrolled proliferation, survive stress, evade immune surveillance, and adapt to therapy. Beyond the classical Warburg effect, tumors frequently rewire multiple metabolic circuits, including glucose utilization, amino acid dependency (e.g., glutamine, serine/glycine), lipid synthesis and oxidation, and nucleotide metabolism. These alterations arise from coordinated changes across genetic lesions, transcriptional and epigenetic regulation, protein signaling, and metabolite availability, often shaped by the tumor microenvironment. While metabolomics provides a direct readout of metabolic states, integrating metabolomics with genomics, transcriptomics, proteomics, epigenomics, and single-cell is essential to uncover causal mechanisms and actionable vulnerabilities. Rigorous multi-omics integration and clinically interpretable models are increasingly needed to translate metabolic insights into diagnostic biomarkers and metabolism-targeted therapies.This Research Topic aims to showcase cutting-edge multi-omics studies and integrative analytical methods focused on cancer metabolic reprogramming and its translational implications. We seek contributions that combine metabolomics with other omics layers to (i) dissect metabolic mechanisms driving tumor initiation, progression, metastasis, immune modulation, and therapy resistance; (ii) identify robust metabolic biomarkers for early detection, prognosis, and treatment stratification; and (iii) discover and validate metabolism-related therapeutic targets and combination strategies. We particularly encourage studies that connect metabolic phenotypes to clinical outcomes and that provide mechanistic validation (e.g., isotope tracing, functional perturbation, orthogonal assays) or external cohort validation. By integrating multi-omics evidence across pathways such as glucose, amino acid, lipid, and nucleotide metabolism, this Topic aims to accelerate the development of metabolically informed precision oncology.This Research Topic welcomes Original Research, Reviews, Methods, and Brief Research Reports on integrative multi-omics analyses of tumor metabolic reprogramming, including but not limited to: • Multi-omics integration to characterize glucose, amino acid, lipid, and nucleotide metabolic rewiring across cancer types. • Metabolomics combined with genomics, transcriptomics, proteomics, and epigenomics to infer regulatory drivers and pathway activity.• Tumor–microenvironment metabolic interactions (hypoxia, acidosis, nutrient competition, immune cell metabolism; stromal–tumor crosstalk). • Metabolism-driven biomarker discovery for diagnosis, prognosis, minimal residual disease, and therapy response prediction (blood, tissue, urine, imaging-linked metabolites). • Identification of metabolic liabilities and targets (e.g., glycolysis, glutaminolysis, one-carbon metabolism, FA synthesis/oxidation, nucleotide synthesis), and multi-omics-guided drug combination strategies. • Single-cell/spatial multi-omics and metabolic heterogeneity. • Computational methods for data integration, interpretability, and reproducibility. Authors should clearly state translational relevance and provide appropriate validation (independent cohorts, orthogonal assays, or functional experiments). Topic editors: Bo Chen, Xin He, Zhiyuan Bo Source: https://www.frontiersin.org/research-topics/77629/multi-omics-of-metabolic-reprogramming-in-cancer-mechanisms-diagnostics-and-therapy