Glycolytic/oxidative metabolic reprogramming in lung cancer: clinical implications for precision oncology

Abstract Glycolytic or oxidative metabolic reprogramming is increasingly recognized as a central driver of lung cancer progression, aggressiveness, immune evasion, therapeutic resistance, and clinical heterogeneity. Lung tumors exhibit a broad metabolic spectrum ranging from highly glycolytic to oxidative phosphorylation (OXPHOS)-dependent phenotypes, largely shaped by oncogenic mutations, tumor suppressor loss, and microenvironmental cues. In this review, we synthesize current knowledge on metabolic alterations in lung cancer and discuss briefly how specific genetic backgrounds – such as KRAS , EGFR , STK11 , and TP53 mutations – shape glycolytic or oxidative programs. We summarize preclinical and clinical evidence on anti-glycolytic and anti-OXPHOS agents, highlighting both promising results and major limitations related to toxicity and lack of biomarker-guided patient selection. Notably, drugs such as 2-deoxyglucose, lonidamine, dichloroacetate, biguanides, and mitochondrial complex I/III inhibitors have shown limited clinical efficacy despite robust preclinical data, underscoring the need for precision metabolic stratification of patients using proposed metabolic biomarkers. We also review emerging metabolic glycolytic/oxidative biomarkers – including 18 F-FDG-PET parameters, GLUT1, PKM2, LDHA, PGC1α, and metabolomic signatures – that may guide therapeutic decisions, identifying patients most likely to benefit from different metabolic interventions. Integrating metabolic profiling with personalized oncology may enhance treatment effectiveness and support the incorporation of anti-metabolic strategies into routine lung cancer care.