Targeting metabolism represents a possible successful approach to treat cancer. Dichloroacetate (DCA) is a drug known to divert metabolism from anaerobic glycolysis to mitochondrial oxidative phosphorylation by stimulation of PDH. In this study, we investigated the response of two pancreatic cancer cell lines to DCA, in two-dimensional and three-dimension cell cultures, as well as in a mouse model. PANC-1 and BXPC-3 treated with DCA showed a marked decrease in cell proliferation and migration which did not correlate with enhanced apoptosis indicating a cytostatic rather than a cytotoxic effect. Despite PDH activation, DCA treatment resulted in reduced mitochondrial oxygen consumption without affecting glycolysis. Moreover, DCA caused enhancement of ROS production, mtDNA, and of the mitophagy-marker LC3B-II in both cell lines but reduced mitochondrial fusion markers only in BXPC-3. Notably, DCA downregulated the expression of the cancer stem cells markers CD24/CD44/EPCAM only in PANC-1 but inhibited spheroid formation/viability in both cell lines. In a xenograft pancreatic cancer mouse-model DCA treatment resulted in retarding cancer progression. Collectively, our results clearly indicate that the efficacy of DCA in inhibiting cancer growth mechanistically depends on the cell phenotype and on multiple off-target pathways. In this context, the novelty that DCA might affect the cancer stem cell compartment is therapeutically relevant.

Dichloroacetate, a selective mitochondria-targeting drug for oral squamous cell carcinoma: a metabolic perspective of treatment Dichloroacetate, a selective mitochondria-targeting drug for oral squamous cell carcinoma: a metabolic perspective of treatment

Despite the significant recent advances in clinical practice, gastric cancer (GC) represents a leading cause of cancer-related deaths in the world. In fact, occurrence of chemo-resistance still remains a daunting hindrance to effectiveness of the current approach to GC therapy. There is accumulating evidence that a plethora of cellular and molecular factors is implicated in drug-induced phenotypical switching of GC cells. Among them, epithelial-mesenchymal transition (EMT), autophagy, drug detoxification, DNA damage response and drug target alterations, have been reported as major determinants. Intriguingly, resistant GC phenotype may be the result of GC cell-induced tumor microenvironment (TME) remodeling, which is currently emerging as a key player in promoting drug resistance and overcoming cytotoxic effects of drugs. In this review, we discuss the possible mechanisms of drug resistance and their involvement in determining current GC therapies failure.

Gastric cancer (GC) is a leading cause of cancer-related deaths in the world. Molecular heterogeneity is a major determinant for the clinical outcomes and an exhaustive tumor classification is currently missing. Histologically normal tissue adjacent to the tumor (NAT) is commonly used as a control in cancer studies, nevertheless a recently published paper described the unique characteristics of the NAT in several tumor types. Little is known about the global gene expression profile of gastric NAT (gNAT) which could be an effective tool for a more realistic definition of GC molecular signature. Here, we integrated data of 512 samples from the Genotype-Tissue Expression project (GETx) and The Cancer Genome Atlas (TCGA) to analyze the transcriptome of healthy gastric tissues, gNAT, and GC samples. We validated TCGA-GETx data mining through inHouse gNAT and GC expression dataset. Differential gene expression together with pathway enrichment analyses, indeed, led to different results when using the gNAT or the healthy tissue as control. Based on our analyses, gNAT showed a peculiar gene signature and biological features, like the estrogen receptor pathways activation, suggesting a molecular behavior partially different from both healthy and GC tissues. Therefore, using gNAT as healthy control tissue in the characterization of tumor associated biological processes and pathways could lead to suboptimal results.