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Background A variety of oncogenic and environmental factors alter tumor metabolism to serve the distinct cellular biosynthetic and bioenergetic needs present during oncogenesis. Extracellular acidosis is a common microenvironmental stress in solid tumors, but little is known about its metabolic influence, particularly when present in the absence of hypoxia. In order to characterize the extent of tumor cell metabolic adaptations to acidosis, we employed stable isotope tracers to examine how acidosis impacts glucose, glutamine, and palmitate metabolism in breast cancer cells exposed to extracellular acidosis. Results Acidosis increased both glutaminolysis and fatty acid β-oxidation, which contribute metabolic intermediates to drive the tricarboxylic acid cycle (TCA cycle) and ATP generation. Acidosis also led to a decoupling of glutaminolysis and novel glutathione (GSH) synthesis by repressing GCLC/GCLM expression. We further found that acidosis redirects glucose away from lactate production and towards the oxidative branch of the pentose phosphate pathway (PPP). These changes all serve to increase nicotinamide adenine dinucleotide phosphate (NADPH) production and counter the increase in reactive oxygen species (ROS) present under acidosis. The reduced novel GSH synthesis under acidosis may explain the increased demand for NADPH to recycle existing pools of GSH. Interestingly, acidosis also disconnected novel ribose synthesis from the oxidative PPP, seemingly to reroute PPP metabolites to the TCA cycle. Finally, we found that acidosis activates p53, which contributes to both the enhanced PPP and increased glutaminolysis, at least in part, through the induction of G6PD and GLS2 genes. Conclusions Acidosis alters the cellular metabolism of several major metabolites, which induces a significant degree of metabolic inflexibility. Cells exposed to acidosis largely rely upon mitochondrial metabolism for energy generation to the extent that metabolic intermediates are redirected away from several other critical metabolic processes, including ribose and glutathione synthesis. These alterations lead to both a decrease in cellular proliferation and increased sensitivity to ROS. Collectively, these data reveal a role for p53 in cellular metabolic reprogramming under acidosis, in order to permit increased bioenergetic capacity and ROS neutralization. Understanding the metabolic adaptations that cancer cells make under acidosis may present opportunities to generate anti-tumor therapeutic agents that are more tumor-specific.

Abstract Within solid tumor microenvironments, lactic acidosis, and hypoxia each have powerful effects on cancer pathophysiology. However, the influence that these processes exert on each other is unknown. Here, we report that a significant portion of the transcriptional response to hypoxia elicited in cancer cells is abolished by simultaneous exposure to lactic acidosis. In particular, lactic acidosis abolished stabilization of HIF-1α protein which occurs normally under hypoxic conditions. In contrast, lactic acidosis strongly synergized with hypoxia to activate the unfolded protein response (UPR) and an inflammatory response, displaying a strong similarity to ATF4-driven amino acid deprivation responses (AAR). In certain breast tumors and breast tumor cells examined, an integrative analysis of gene expression and array CGH data revealed DNA copy number alterations at the ATF4 locus, an important activator of the UPR/AAR pathway. In this setting, varying ATF4 levels influenced the survival of cells after exposure to hypoxia and lactic acidosis. Our findings reveal that the condition of lactic acidosis present in solid tumors inhibits canonical hypoxia responses and activates UPR and inflammation responses. Furthermore, these data suggest that ATF4 status may be a critical determinant of the ability of cancer cells to adapt to oxygen and acidity fluctuations in the tumor microenvironment, perhaps linking short-term transcriptional responses to long-term selection for copy number alterations in cancer cells. Cancer Res; 72(2); 491–502. ©2011 AACR.

Although lactic acidosis is a prominent feature of solid tumors, we still have limited understanding of the mechanisms by which lactic acidosis influences metabolic phenotypes of cancer cells. We compared global transcriptional responses of breast cancer cells in response to three distinct tumor microenvironmental stresses: lactic acidosis, glucose deprivation, and hypoxia. We found that lactic acidosis and glucose deprivation trigger highly similar transcriptional responses, each inducing features of starvation response. In contrast to their comparable effects on gene expression, lactic acidosis and glucose deprivation have opposing effects on glucose uptake. This divergence of metabolic responses in the context of highly similar transcriptional responses allows the identification of a small subset of genes that are regulated in opposite directions by these two conditions. Among these selected genes, TXNIP and its paralogue ARRDC4 are both induced under lactic acidosis and repressed with glucose deprivation. This induction of TXNIP under lactic acidosis is caused by the activation of the glucose-sensing helix-loop-helix transcriptional complex MondoA:Mlx, which is usually triggered upon glucose exposure. Therefore, the upregulation of TXNIP significantly contributes to inhibition of tumor glycolytic phenotypes under lactic acidosis. Expression levels of TXNIP and ARRDC4 in human cancers are also highly correlated with predicted lactic acidosis pathway activities and associated with favorable clinical outcomes. Lactic acidosis triggers features of starvation response while activating the glucose-sensing MondoA-TXNIP pathways and contributing to the “anti-Warburg” metabolic effects and anti-tumor properties of cancer cells. These results stem from integrative analysis of transcriptome and metabolic response data under various tumor microenvironmental stresses and open new paths to explore how these stresses influence phenotypic and metabolic adaptations in human cancers.

Abstract Although lactic acidosis and other tumor microenvironmental stresses are prominent features in solid tumors, how they influence the phenotypes of cancer cells are not well understood. We compared the transcriptional response of breast cancer cells under three distinct tumor microenvironmental stresses – lactic acidosis, glucose deprivation and hypoxia. We found that lactic acidosis induced gene expression highly similar to glucose deprivation and triggered features of starvation response. In spite of their similar transcriptional response, lactic acidosis had opposite effects on the glucose uptake to glucose deprivation. This discrepancy guided the supervised analysis of expression data to identify TXNIP as the potential regulator for such divergent metabolic effects. TXNIP and its paralogue ARRDC4 were both induced under lactic acidosis and repressed with glucose deprivation. Their expression was also highly correlated with predicted lactic acidosis pathway activities and associated with favorable clinical outcomes in human cancers. These findings are due to the ability of TXNIP to inhibit the tumor glycolytic phenotypes and redirect energy generation toward aerobic respiration. The induction of TXNIP under lactic acidosis is caused by the activation of the glucose-sensing helix-loop-helix transcriptional complex MondoA: Mlx. Lactic acidosis activates the MondoA-TXNIP pathways and contributes to its “anti-Warburg” metabolic effects and anti-tumor properties of cancer cells. These findings illustrate the value of such integrative analysis of transcriptome and metabolic response under various tumor microenvironmental stresses and may lead to important insights on how they influence the phenotypic and metabolic adaptations in human cancers. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2340.

Human disease studies using DNA microarrays in both clinical/observational and experimental/controlled studies are having increasing impact on our understanding of the complexity of human diseases. A fundamental concept is the use of gene expression as a "common currency" that links the results of in vitro controlled experiments to in vivo observational human studies. Many studies--in cancer and other diseases--have shown promise in using in vitro cell manipulations to improve understanding of in vivo biology, but experiments often simply fail to reflect the enormous phenotypic variation seen in human diseases. We address this with a framework and methods to dissect, enhance and extend the in vivo utility of in vitro derived gene expression signatures. From an experimentally defined gene expression signature we use statistical factor analysis to generate multiple quantitative factors in human cancer gene expression data. These factors retain their relationship to the original, one-dimensional in vitro signature but better describe the diversity of in vivo biology. In a breast cancer analysis, we show that factors can reflect fundamentally different biological processes linked to molecular and clinical features of human cancers, and that in combination they can improve prediction of clinical outcomes.

We present an applied study in cancer genomics for integrating data and inferences from laboratory experiments on cancer cell lines with observational data obtained from human breast cancer studies. The biological focus is on improving understanding of transcriptional responses of tumors to changes in the pH level of the cellular microenvironment. The statistical focus is on connecting experimentally defined biomarkers of such responses to clinical outcome in observational studies of breast cancer patients. Our analysis exemplifies a general strategy for accomplishing this kind of integration across contexts. The statistical methodologies employed here draw heavily on Bayesian sparse factor models for identifying, modularizing and correlating with clinical outcome these signatures of aggregate changes in gene expression. By projecting patterns of biological response linked to specific experimental interventions into observational studies where such responses may be evidenced via variation in gene expression across samples, we are able to define biomarkers of clinically relevant physiological states and outcomes that are rooted in the biology of the original experiment. Through this approach we identify microenvironment-related prognostic factors capable of predicting long term survival in two independent breast cancer datasets. These results suggest possible directions for future laboratory studies, as well as indicate the potential for therapeutic advances though targeted disruption of specific pathway components.

2054 The tumor microenvironment has a significant impact on tumor development. Two important determinants of this environment are hypoxia and lactic acidosis. We developed genome-scale gene expression studies aiming to dissect transcriptional responses of HMEC cells to lactic acidosis and hypoxia in vitro , and explore how they are linked to tumor clinical phenotypes in vivo . Statistical methods were applied to derive experimental signatures for these phenotypes and analyze their associations to heterogeneous sets of published breast cancer datasets. We find lactic acidosis elicits expression responses dominated by acidosis which are unrelated to hypoxia and it serves as an independent biomarker of good prognosis in tumor progression. Additionally, we identified an inverse relationship between the lactic acidosis response and Akt pathways and showed that lactic acidosis could inhibit Akt activation and glycolytic phenotypes of cancer cells. These observations suggest mechanisms to rationalize the association between lactic acidosis responses with favorable clinical outcomes in human cancers. This reciprocal information acquired from in vitro perturbations and in vivo clinical phenotypes via microarray led to novel findings of roles played by key characteristics of the tumor microenvironment and the distinction between physiological parameters and cellular responses.