Apoptosis culminates in secondary necrosis due to lack of ATP. Cancer stem cells form spheres after apoptosis by evoking the blebbishield emergency program. Hence, determining how blebbishields avoid secondary necrosis is crucial. Here we demonstrate that N-Myc and VEGFR2 control transformation from blebbishields, during which oligomers of K-Ras, p27, BAD, Bax, and Bak boost glycolysis to avoid secondary necrosis. Non-apoptotic cancer cells also utilize oligomers to boost glycolysis, which differentiates the glycolytic function of oligomers from their apoptotic action. Smac mimetic in combination with TNF-α or TRAIL but not in combination with FasL abrogates transformation from blebbishields by inducing secondary necrosis. Thus blebbishield-mediated transformation is dependent on glycolysis, and Smac mimetics represent potential candidates to abrogate the blebbishield emergency program.
To conclude, taxane-containing schemes are valid therapeutic options, but at a very high cost.
Background: Several distinct subtypes of breast cancer (Luminal, Basal-like and Her-2+) have been identified by gene expression profiling of breast cancers and cell lines. Although much is known about the regulation of cell signaling in each breast cancer subtype, little is known about subtype-specific energy metabolism and its regulation. The majority of cancers, including breast cancer, acquire an accelerated metabolic index as part of the transformation process. One of the most studied metabolic changes in cancer, referred to as the Warburg effect, is the increased uptake of glucose and its conversion to lactate; which is released from the cell, thus creating an astringent tumor microenvironment with high lactate and low pH. Accumulation of lactate in the tumor microenvironment presents cancer cells with a potential rich carbon source that could be exploited when the preferred nutrient sources, glucose and glutamine, are not abundant or available. Thus uptake and conversion of lactate to pyruvate and then entry into the TCA cycle and oxidative phosphorylation could generate energy that could potentially allow cancer cells to survive until other nutrients become available or until the cancer cells can invade and migrate toward nutrient rich environments, in other words, until they spread locally and metastasize. Methods and Results: Examination of 59 breast cancer cell lines shows differences in expression of numerous proteins and enzymes involved in cellular metabolism, including the lactate transporters (MCT), the enzyme lactate dehydrogenase (LDH), and glucose transporter proteins (GLUT). We found that MCT1 expression is lost in the Luminal subtype and correlates with loss of LDHB and the regulator and chaperone of MCT1, CD147 (Basigin). Conversely, MCT1 is highly expressed in Basal-like and normal cell lines, along with CD147 and LDHB. While monocarboxylate transporter proteins can transport bi-directionally, MCT1 preferentially transports lactate into the cell, while MCT4 transports lactate out of the cell. The loss of MCT1 in luminal cells suggests a distinct energy metabolism in this subtype versus basal-like cells. The basal-like subtype has been further categorized into Basal and Claudin-low subtypes. Claudin-low cells express stem-like markers such as CD44+/CD24-, EMT markers such as vimentin, and are low expressers of the Claudin proteins. We found that MCT1 and CD147 are highly expressed and differentially regulated in Claudin-low cell lines as compared to normal cells. We have evidence that high lactate (10mM) as a sole energy source delays ATP loss and apoptosis in MCT1 expressing cells, but not in luminal cell lines that lack MCT1. Thus, claudin-low tumors may benefit from local lactate production providing an unexpected energy source. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P4-05-03.
Purpose: Although breast cancers are known to be molecularly heterogeneous, their metabolic heterogeneity is less well understood. This study aimed to identify and evaluate metabolic biomarkers in breast cancers and determine their ability to predict outcomes. Methods: mRNA microarray data from breast cancer cell lines were used to identify bimodal genes, those with the highest potential for robust high/low classification in a clinical setting. Using a panel of breast cancer cell lines, expression and activity of the highest scoring bimodal metabolism gene, lactate dehydrogenase B (LDHB), was quantified and associated with glycolytic phenotype. The contribution of LDHB to glycolysis was evaluated using MDA-MB-231 and HCC1937 cell lines with stable lentiviral knockdown of LDHB. mRNA expression of LDHB was evaluated for association with neoadjuvant chemotherapy response within clinical and PAM50-derived subtypes. Results: LDHB was highly expressed in cell lines with glycolytic, basal-like phenotypes. Knockdown of LDHB in cell lines reduced glycolytic dependence, linking LDHB expression directly to metabolic function. Using four independent patient datasets, LDHB mRNA expression was positively associated with basal subtype and negatively associated with luminal and HER2 subtypes. Furthermore, LDHB predicted basal phenotype independently of hormone-receptor (HR) clinical status (OR = 21.6 for HR-positive/HER2-negative and OR = 18.2 for triple-negative). While LDHB expression could predict basal phenotype, high LDHB expression identified aggressive breast cancer tumors that were primarily but not exclusively basal. Importantly, high LDHB expression predicted pathological complete response to neoadjuvant chemotherapy for both hormone receptor (HR) positive/HER2-negative (OR = 4.0, P = .0002) and triple-negative (OR = 3.0, P = .003) cancers. Consistent with increased response to chemotherapy, LDHB expression in basal cancers within the triple-negative group was associated with the proliferative marker CCNB1 (P < .0001). Conclusion: mRNA expression of LDHB as a single marker predicted glycolytic phenotype in cell lines and response to neoadjuvant chemotherapy in breast cancers independently of HR status. These observations support prospective clinical evaluation of LDHB as a predictive marker of response for breast cancer patients treated with neoadjuvant chemotherapy. Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P3-06-06.
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