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Query: UMLS:C0598934 (tumor growth)
 58,965 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Previously, we showed that high-energy metabolites (lactate and ketones) "fuel" tumor growth and experimental metastasis in an in vivo xenograft model, most likely by driving oxidative mitochondrial metabolism in breast cancer cells. To mechanistically understand how these metabolites affect tumor cell behavior, here we used genome-wide transcriptional profiling. Briefly, human breast cancer cells (MCF7) were cultured with lactate or ketones, and then subjected to transcriptional analysis (exon-array). Interestingly, our results show that treatment with these high-energy metabolites increases the transcriptional expression of gene profiles normally associated with "stemness," including genes upregulated in embryonic stem (ES) cells. Similarly, we observe that lactate and ketones promote the growth of bonafide ES cells, providing functional validation. The lactate- and ketone-induced "gene signatures" were able to predict poor clinical outcome (including recurrence and metastasis) in a cohort of human breast cancer patients. Taken together, our results are consistent with the idea that lactate and ketone utilization in cancer cells promotes the "cancer stem cell" phenotype, resulting in significant decreases in patient survival. One possible mechanism by which these high-energy metabolites might induce stemness is by increasing the pool of Acetyl-CoA, leading to increased histone acetylation, and elevated gene expression. Thus, our results mechanistically imply that clinical outcome in breast cancer could simply be determined by epigenetics and energy metabolism, rather than by the accumulation of specific "classical" gene mutations. We also suggest that high-risk cancer patients (identified by the lactate/ketone gene signatures) could be treated with new therapeutics that target oxidative mitochondrial metabolism, such as the anti-oxidant and "mitochondrial poison" metformin. Finally, we propose that this new approach to personalized cancer medicine be termed "Metabolo-Genomics," which incorporates features of both 1) cell metabolism and 2) gene transcriptional profiling. Importantly, this powerful new approach directly links cancer cell metabolism with clinical outcome, and new therapeutic strategies for inhibiting the TCA cycle and mitochondrial oxidative phosphorylation in cancer cells.
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PMID:Ketones and lactate increase cancer cell "stemness," driving recurrence, metastasis and poor clinical outcome in breast cancer: achieving personalized medicine via Metabolo-Genomics. 2151 13

We have recently proposed a new model of cancer metabolism to explain the role of aerobic glycolysis and L-lactate production in fueling tumor growth and metastasis. In this model, cancer cells secrete hydrogen peroxide (H2O2), initiating oxidative stress and aerobic glycolysis in the tumor stroma. This, in turn, drives L-lactate secretion from cancer-associated fibroblasts. Secreted L-lactate then fuels oxidative mitochondrial metabolism (OXPHOS) in epithelial cancer cells, by acting as a paracrine onco-metabolite. We have previously termed this type of two-compartment tumor metabolism the "Reverse Warburg Effect," as aerobic glycolysis takes place in stromal fibroblasts, rather than epithelial cancer cells. Here, we used MCT4 immuno-staining of human breast cancer tissue microarrays (TMAs; > 180 triple-negative patients) to directly assess the prognostic value of the "Reverse Warburg Effect." MCT4 expression is a functional marker of hypoxia, oxidative stress, aerobic glycolysis, and L-lactate efflux. Remarkably, high stromal MCT4 levels (score = 2) were specifically associated with decreased overall survival (< 18% survival at 10 y post-diagnosis). In contrast, patients with absent stromal MCT4 expression (score = 0), had 10-y survival rates of ~97% (p-value < 10 (-32) ). High stromal levels of MCT4 were strictly correlated with a loss of stromal Cav-1 (p-value < 10 (-14) ), a known marker of early tumor recurrence and metastasis. In fact, the combined use of stromal Cav-1 and stromal MCT4 allowed us to more precisely identify high-risk triple-negative breast cancer patients, consistent with the goal of individualized risk-assessment and personalized cancer treatment. However, epithelial MCT4 staining had no prognostic value, indicating that the "conventional" Warburg effect does not predict clinical outcome. Thus, the "Reverse Warburg Effect" or "parasitic" energy-transfer is a key determinant of poor overall patient survival. As MCT4 is a druggable-target, MCT4 inhibitors should be developed for the treatment of aggressive breast cancers, and possibly other types of human cancers. Similarly, we discuss how stromal MCT4 could be used as a biomarker for identifying high-risk cancer patients that could likely benefit from treatment with FDA-approved drugs or existing MCT-inhibitors (such as, AR-C155858, AR-C117977, and AZD-3965).
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PMID:Using the "reverse Warburg effect" to identify high-risk breast cancer patients: stromal MCT4 predicts poor clinical outcome in triple-negative breast cancers. 2254 77