Editorial: Targeted cancer therapy through metabolic pathways

Metabolic reprogramming is widely recognized as a hallmark of cancer, playing a pivotal role in tumor progression, therapeutic resistance, immune evasion, and metastasis (Liu et al., 2025a). Aberrant metabolic pathways not only support the rapid proliferation of cancer cells but also create vulnerabilities that can be therapeutically targeted. As cancer cells adapt their metabolic networks to meet increased bioenergetic and biosynthetic demands, these pathways present actionable vulnerabilities for targeted therapeutic intervention (Punnasseril et al., 2025). Recent advances in both experimental and computational approaches, including highthroughput omics technologies, systems biology, and bioinformatics, have greatly expanded our understanding of the metabolic landscape in cancer (Catalano et al., 2025). Integrating mechanistic insights with data-driven discovery holds the key to identifying novel therapeutic targets, predicting treatment response, and designing effective metabolism-based therapies. Huang et al., examined LDH isoenzymes, especially LDHA, which is elevated in ovarian, endometrial, and cervical cancers to enable Warburg-effect glycolysis under hypoxia, fueling invasion and acidosis that hampers T cells. Elevated LDH level also correlates with advanced disease stage, metastasis, and chemotherapy resistance, positioning it as a prognostic marker.LDHA blockade inhibits growth preclinically, yet context-specific ferroptosis risks in cervical cases complicate translation (Huang et al., 2026).He at al., used integrated multi-omics to define bladder cancer subtypes via 144 dysregulated amino acid genes, revealing a poor-prognosis cluster with glutamine/tryptophan hyperdrive, proliferation signals, and inflamed-yet-suppressed immunity. Their 16-gene risk model demonstrate improved performance compared to existing approaches, predicts PI3K/mTOR and immunotherapy responses, and localizes to malignant epithelia, validated by PSPH knockdown curbing invasion (He et al., 2026). Liu et al.,revealed CELF1, an RNA-binding protein overexpressed in luminal A (ERpositive) breast cancers, as a driver of aggressive phenotypes through GLUT1-mediated aerobic glycolysis. High CELF1 correlates with poor survival and ESR1 expression, while its knockdown inhibits proliferation, colony formation, migration, and xenograft growth by downregulating glycolytic enzymes HK2 and G6PD alongside cyclin D1. Overexpression in HER2 cells yields opposite effects, while combining CELF1 knockout with GLUT1 inhibitor BAY-876 synergistically suppresses tumors, suggesting this axis as a potential therapeutic target for luminal subtype (Li et al., 2025).Liu et al., unveiled the role of FBXO39, a ubiquitin ligase in degrading p53 to unleash LDHA-mediated glycolysis, promoting colorectal cancer aggressiveness. FBXO39 upregulation correlates with poor outcomes, and its silencing stabilizes p53, reduces lactate production, cell viability, and EMT-associated features in HCT116 cells. Rescue experiments tie effects to LDHA; patient cohorts link high FBXO39/LDHA to advanced TNM, proposing FBXO39-p53-LDHA axis for glycolytic tumors (Liu et al., 2025b). Wang et al., applied WGCNA and machine learning to TCGA-LIHC, pinpointing a glycolysis/lipid module yielding hub genes (e.g., PKM, ACAT2) via LASSO-Cox signatures.High-risk profile predicts recurrence, sorafenib response, and in vitro knockdown validates proliferation inhibition. Multi-omics nomogram integrates hubs for prognosis, advocating metabolic panels for hepatocellular therapy stratification (Wang et al., 2025). Han et al., integrated multi-omics that unveils GABARAP-mediated mitophagy sustaining pyruvate metabolism as osteosarcoma progression drivers. This work also positions mitophagy-pyruvate inhibition, potentially via ATG modulators or PDK blockers as novel metabolic therapies. They also revealed that GABARAP links mitophagy-driven metabolic adaptation with immune evasion, representing a key regulator and potential therapeutic target in osteosarcoma (Han et al., 2025).Altogether, the articles in this Research Topic reflect the crucial importance of metabolic reprogramming in cancer development, which refers to glycolysis as well as lipids metabolism, use of amino acids and mitophagy, and interactions between immunometabolism. Such studies highlight the role of increasing significance of multi-omics techniques and stratification based on biomarkers to define actionable metabolic targets. Nonetheless, issues including metabolic plasticity, heterogeneity of tumors and its potential toxicity to normal tissues are also a significant obstacle to clinical translation. The next step in the research should be investigating ways of combining metabolic intervention with immunotherapy and precision medicine approaches to increase the effectiveness and sustainability of therapy.