Background: First-generation molecular profiles for human breast cancers have enabled the identification of features that can predict therapeutic response; however, little is known about how the various data types can best be combined to yield optimal predictors. Collections of breast cancer cell lines mirror many aspects of breast cancer molecular pathobiology, and measurements of their omic and biological therapeutic responses are well-suited for development of strategies to identify the most predictive molecular feature sets. Results: We used least squares-support vector machines and random forest algorithms to identify molecular features associated with responses of a collection of 70 breast cancer cell lines to 90 experimental or approved therapeutic agents. The datasets analyzed included measurements of copy number aberrations, mutations, gene and isoform expression, promoter methylation and protein expression. Transcriptional subtype contributed strongly to response predictors for 25% of compounds, and adding other molecular data types improved prediction for 65%. No single molecular dataset consistently out-performed the others, suggesting that therapeutic response is mediated at multiple levels in the genome. Response predictors were developed and applied to TCGA data, and were found to be present in subsets of those patient samples. Conclusions: These results suggest that matching patients to treatments based on transcriptional subtype will improve response rates, and inclusion of additional features from other profiling data types may provide additional benefit. Further, we suggest a systems biology strategy for guiding clinical trials so that patient cohorts most likely to respond to new therapies may be more efficiently identified.

The genetic basis for the hereditary leiomyomatosis and renal cell cancer syndrome is germ-line inactivating mutation in the gene for the Krebs/tricarboxylic acid cycle enzyme, fumarate hydratase (FH), the enzyme that converts fumarate to malate. These individuals are predisposed to development of leiomyomas of the skin and uterus as well as highly aggressive kidney cancers. Inhibition of FH should result in significant decrease in oxidative phosphorylation necessitating that glycolysis followed by fermentation of pyruvate to lactate will be required to provide adequate ATP as well as to regenerate NAD+. Moreover, FH deficiency is known to up-regulate expression of hypoxia-inducible factor (HIF)-1α by enhancing the stability of HIF transcript. This leads to activation of various HIF-regulated genes including vascular endothelial growth factor and glucose transporter GLUT1 and increased expression of several glycolytic enzymes. Because lactate dehydrogenase-A (LDH-A), also a HIF-1α target, promotes fermentative glycolysis (conversion of pyruvate to lactate), a step essential for regenerating NAD+, we asked whether FH-deficient cells would be exquisitely sensitive to LDH-A blockade. Here, we report that hereditary leiomyomatosis and renal cell cancer tumors indeed overexpress LDH-A, that LDH-A inhibition results in increased apoptosis in a cell with FH deficiency and that this effect is reactive oxygen species mediated, and that LDH-A knockdown in the background of FH knockdown results in significant reduction in tumor growth in a xenograft mouse model. [Mol Cancer Ther 2009;8(3):626–35]

Immunotherapy is a curable treatment for certain cancers, but it is still only effective in a small subset of patients. We have recently reported that programmed cell death protein-1 (PD-1) ligand (PD-L1) expression is regulated by lactate present at high levels in the tumor microenvironment (TME). We hypothesized that the efficacy of anti-PD-1 treatment can be improved by blocking the lactate-generating enzyme, lactate dehydrogenase-A (LDH-A). Anti-PD-1 treatment of mice harboring LDH-A deficient B16-F10 melanoma tumors led to an increase in anti-tumor immune responses compared to mice implanted with tumors expressing LDH-A. Specifically, we observed heightened infiltration of natural killer (NK) cells and CD8⁺ cytotoxic T cells in the LDH-A deficient tumors. These infiltrated cytotoxic cells had an elevated production of interferon-γ (IFN-γ) and granzyme B. Mechanistically, CD8⁺ T cells isolated from the TME of LDH-A deficient B16-F10 melanoma tumors and treated with anti-PD-1 showed enhanced mitochondrial activity and increased reactive oxygen species (ROS) levels. Moreover, infiltration of T regulatory (Treg) cells was diminished in LDH-A deficient tumors treated with anti-PD-1. These altered immune cell profiles were clinically relevant as they were accompanied by significantly reduced tumor growth. Our study suggests that blocking LDH-A in the tumor might improve the efficacy of anti-PD-1 therapy.

Immunometabolism is emerging as a critical determinant of cancer pathophysiology. In this study, we explored the contributions of macrophage-expressed lactate dehydrogenase-A (LDH-A) to tumor formation in a K-Ras murine model of lung carcinoma. Myeloid-specific deletion of LDH-A promoted accumulation of macrophages with a CD86high and MCP-1high M1-like phenotype that suppressed tumor growth. This phenotypic effect was accompanied by reduced VEGF expression and angiogenesis, diminished numbers of PD-L1+ cancer cells, increased numbers of CD3+ T cells, and activation status of CD8+ T cells. Furthermore, it was associated with more pronounced antitumor T-cell immunity via induction of IL17 and IFNγ-producing CD8+ T (Tc17 and Tc1) cells, likely via suppression of lactate-driven PD-L1 expression. Our results suggest that expressions of LDH-A and lactate by macrophage in the tumor microenvironment are major drivers of T-cell immunosuppression, strongly supporting the concept of targeting stromal LDH-A as an effective strategy to blunt tumoral immune escape. Cancer Res; 77(13); 3632–43. ©2017 AACR.

Tumor-induced immune tolerance permits growth and spread of malignant cells. Cancer cells have strong influence on surrounding cells and shape the hypoxic tumor microenvironment (TME) facilitating cancer progression. A dynamic change in glucose metabolism occurring in cancer cells and its influence on the TME are still poorly understood. Indeed, cancer and/or immune cells undergo rapid adaptation in metabolic pathways during cancer progression. Metabolic reprograming affects macrophages, T cells, and myeloid derived suppressor cells (MDSCs) among other immune cells. Their role in the TME depends on a nature and concentration of factors, such as cytokines, reactive oxygen species (ROS), growth factors, and most importantly, diffusible metabolites (i.e., lactate). Further, the amounts of available nutrients and oxygen as well as activity of microbiota may influence metabolic pathways in the TME. The roles of metabolites in regulating of the interaction between immune and cancer cell are highlighted in this review. Targeting metabolic reprogramming or signaling pathways controlling cell metabolism in the TME might be a potential strategy for anti-cancer therapy alone or in combination with current immunotherapies.