The Warburg effect, characterized by the preferential conversion of glucose to lactate even in the presence of oxygen and functional mitochondria, is a prominent metabolic hallmark of cancer cells and has emerged as a promising therapeutic target for cancer therapy. Elevated lactate levels and acidic pH within the tumor microenvironment (TME) resulting from glycolytic profoundly impact various cellular populations, including macrophage reprogramming and impairment of T-cell functionality. Altogether, the Warburg effect has been shown to promote tumor progression and immunosuppression through multiple mechanisms. This review provides an overview of the current understanding of the Warburg effect in cancer and its implications. We summarize recent pharmacological strategies aimed at targeting glycolytic enzymes, highlighting the challenges encountered in achieving therapeutic efficacy. Additionally, we examine the utility of the Warburg effect as an early diagnostic tool. Finally, we discuss the multifaceted roles of lactate within the TME, emphasizing its potential as a therapeutic target to disrupt metabolic interactions between tumor and immune cells, thereby enhancing anti-tumor immunity.

Previous studies demonstrated that pre-treatment with malonate, a reversible inhibitor of succinate dehydrogenase, given before ischaemia, reduces infarct size. However, it is unknown whether administration of malonate may reduce reperfusion injury. Isolated mice hearts were treated, under normoxic conditions, with increasing concentrations of disodium malonate (0.03–30 mmol/L, n = 4). Malonate induced a concentration-dependent decrease in left ventricular developed pressure (LVdevP) (EC50 = 8.05 ± 2.11 mmol/L). In isolated hearts submitted to global ischaemia (35 min) followed by reperfusion (60 min), malonate 3 mmol/L given only during the first 15 min of reperfusion reduced lactate dehydrogenase release (125.41 ± 16.82 vs. 189.20 ± 13.74 U/g dry tissue/15 min in controls, P = 0.015) and infarct size (24.57 ± 2.32 vs. 39.84 ± 2.78%, P = 0.001, n = 7–8 per group) and improved recovery of LVdevP (20.06 ± 3.82 vs 7.76 ± 2.53% of baseline LVdevP, P = 0.017). ¹H NMR spectroscopy demonstrated marked changes in the metabolic profile of malonate-treated hearts, including increased accumulation of succinate. Furthermore, malonate reduced reactive oxygen species (ROS) production, as measured by MitoSOX staining in myocardial samples obtained after 5 min of reperfusion and in mitochondrial preparations from these samples, preserved mitochondrial respiration, and reduced mitochondrial permeabilization, assessed by calcein retention. Treatment with malonate did not result in activation of RISK or SAFE signalling pathways in tissue extracts obtained 5 min after reperfusion. Succinate dehydrogenase inhibition with malonate at the onset of reperfusion reduces infarct size in isolated mice hearts through reduction in ROS production and mitochondrial permeability transition pore opening.

Purpose. To explore the metabolic profile of vitreous fluid of patients with proliferative diabetic retinopathy (PDR) using ¹H-NMR–based metabonomic analysis. Methods. ¹H-NMR spectra were acquired from vitreous samples obtained during vitrectomy from 22 patients with type 1 diabetes with PDR and from 22 nondiabetic patients with macular hole (control group). Data analysis included a principal component analysis and partial least squares discriminant analysis (PLS-DA). In addition, ¹H-¹H and ¹H-¹³C HMQC correlation spectra were acquired for the identification of metabolites. Furthermore, the main metabolites accounting for the differences in metabolic profile were assessed by current biochemical methods. Results. Lactate was the most abundant metabolite, and it was present at higher levels in samples from PDR patients than from nondiabetic patients (P = 0.02). Glucose was significantly higher in samples from PDR patients than nondiabetic patients (P = 0.03). After removing the lactate peak at 1.35 ppm and with the use of PLS-DA, a model was obtained that was able to correctly classify 19 of 22 patients with PDR and 18 of 22 controls, resulting in a sensitivity of 86% and a specificity of 81%. The main metabolites involved in this specific pattern recognition were galactitol and ascorbic acid (AA); levels of both were significantly lower in PDR patients. Conclusions. ¹H-NMR–based metabonomic analysis of vitreous fluid permits the obtainment of a metabolic signature of PDR. Apart from the higher abundance of lactate and glucose, significant deficits of galactitol and AA are the main metabolic fingerprints of vitreous fluid from PDR patients.