Anti-Cancer Activity of PAK4/NAMPT Inhibitor and Programmed Cell Death Protein-1 Antibody in Kidney Cancer.

BACKGROUND: Kidney cancer (or renal cell carcinoma, RCC) is the sixth most common malignancy in the United States and is increasing in incidence. Despite new therapies, including targeted therapies and immunotherapies, most RCCs are resistant to treatment. Thus, several laboratories have been evaluating new approaches to therapy, both with single agents as well as combinations. Although we have previously shown efficacy of the dual PAK4/nicotinamide phosphoribosyltransferase (NAMPT) inhibitor KPT-9274, and the immune checkpoint inhibitors (CPI) have shown utility in the clinic, there has been no evaluation of this combination either clinically or in an immunocompetent animal model of kidney cancer. METHODS: In this study, we use the renal cell adenocarcinoma (RENCA) model of spontaneous murine kidney cancer. Male BALB/cJ mice were injected subcutaneously with RENCA cells and, after tumors were palpable, they were treated with KPT-9274 and/or anti-programmed cell death 1 (PDCD1; PD1) antibody for 21 days. Tumors were measured and then removed at animal euthanasia for subsequent studies. RESULTS: We demonstrate a significant decrease in allograft growth with the combination treatment of KPT-9274 and anti-PD1 antibody without significant weight loss by the animals. This is associated with decreased (MOUSE) Naprt expression, indicating dependence of these tumors on NAMPT in parallel to what we have observed in human RCC. Histology of the tumors showed substantial necrosis regardless of treatment condition, and flow cytometry of antibody-stained tumor cells revealed that the enhanced therapeutic effect of KPT-9274 and anti-PD1 antibody was not driven by infiltration of T cells into tumors. CONCLUSIONS: This study highlights the potential of the RENCA model for evaluating immunologic responses to KPT-9274 and checkpoint inhibitor (CPI) and suggests that therapy with this combination could improve efficacy in RCC beyond what is achievable with CPI alone.

Metabolic reprogramming in clear cell renal cell carcinoma.

Research in many cancers has uncovered changes in metabolic pathways that control tumour energetics and biosynthesis, so-called metabolic reprogramming. Studies in clear cell renal cell carcinoma (ccRCC) have been particularly revealing, leading to the concept that ccRCC is a metabolic disease. ccRCC is generally accompanied by reprogramming of glucose and fatty acid metabolism and of the tricarboxylic acid cycle. Metabolism of tryptophan, arginine and glutamine is also reprogrammed in many ccRCCs, and these changes provide opportunities for new therapeutic strategies, biomarkers and imaging modalities. In particular, metabolic reprogramming facilitates the identification of novel and repurposed drugs that could potentially be used to treat ccRCC, which when metastatic has currently limited long-term treatment options. Further research and dissemination of these concepts to nephrologists and oncologists will lead to clinical trials of therapeutics specifically targeted to tumour metabolism, rather than generally toxic to all proliferating cells. Such novel agents are highly likely to be more effective and to have far fewer adverse effects than existing drugs.

Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis.

Kidney cancer [or renal cell carcinoma (RCC)] is known as "the internist's tumor" because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel-Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburg effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the ß-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Together, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC.

New opportunities from the cancer metabolome.

BACKGROUND: Metabolomics, the study of all metabolites produced in the body, which often includes flora and drug metabolites, is the omics approach that can be considered most closely related to a patient's phenotype. Metabolomics has a great and largely untapped potential in the field of oncology, and the analysis of the cancer metabolome to identify biofluid markers and novel druggable targets can now be undertaken in many research laboratories. CONTENT: The cancer metabolome has been used to identify and begin to evaluate potential biomarkers and therapeutic targets in a variety of malignancies, including breast, prostate, and kidney cancer. We discuss the several standard techniques for metabolite separation and identification, with their potential problems and drawbacks. Validation of biomarkers and targets may entail intensive use of labor and technology and generally requires a large number of study participants as well as laboratory validation studies. The field of pharmacometabolomics, in which specific therapies are chosen on the basis of a patient's metabolomic profile, has shown some promise in the translation of metabolomics into the arena of personalized medicine. SUMMARY: The relatively new approach using metabolomics has just begun to enter the mainstream of cancer diagnostics and therapeutics. As this field advances, metabolomics will take its well-deserved place next to genomics, transcriptomics, and proteomics in both clinical and basic research in oncology.