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Targeting metabolic dependencies in pediatric cancer.

ABSTRACT: PURPOSE OF REVIEW:In an attempt to identify potential new therapeutic targets, efforts to describe the metabolic features unique to cancer cells are increasingly being reported. Although current standard of care regimens for several pediatric malignancies incorporate agents that target tumor metabolism, these drugs have been part of the therapeutic landscape for decades. More recent research has focused on the identification and targeting of new metabolic vulnerabilities in pediatric cancers. The purpose of this review is to describe the most recent translational findings in the metabolic targeting of pediatric malignancies. RECENT FINDINGS:Across multiple pediatric cancer types, dependencies on a number of key metabolic pathways have emerged through study of patient tissue samples and preclinical modeling. Among the potentially targetable vulnerabilities are glucose metabolism via glycolysis, oxidative phosphorylation, amino acid and polyamine metabolism, and NAD metabolism. Although few agents have yet to move forward into clinical trials for pediatric cancer patients, the robust and promising preclinical data that have been generated suggest that future clinical trials should rationally test metabolically targeted agents for relevant disease populations. SUMMARY:Recent advances in our understanding of the metabolic dependencies of pediatric cancers represent a source of potential new therapeutic opportunities for these diseases.

SUBMITTER: Issaq SH

PROVIDER: S-EPMC7263318 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Targeting metabolic dependencies in pediatric cancer.

Issaq Sameer H SH Heske Christine M CM

Current opinion in pediatrics 20200201 1

<h4>Purpose of review</h4>In an attempt to identify potential new therapeutic targets, efforts to describe the metabolic features unique to cancer cells are increasingly being reported. Although current standard of care regimens for several pediatric malignancies incorporate agents that target tumor metabolism, these drugs have been part of the therapeutic landscape for decades. More recent research has focused on the identification and targeting of new metabolic vulnerabilities in pediatric can ...[more]

PMID: 31789976

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Project description:Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest types of cancer. A factor that contributes to the poor prognosis of the disease is the complex tumor microenvironment (TME). The PDAC TME is composed of excessive fibrosis and desmoplasia, which creates a harsh environment resulting in hypoxia and altered nutrient availability. To promote survival and proliferation in this environment, PDAC cells can reprogram glutamine (Gln) metabolism. Previous studies have demonstrated that PDAC cells use Gln to support proliferation and redox balance. However, earlier attempts to inhibit Gln metabolism using glutaminase inhibitors resulted in rapid metabolic reprogramming and ultimately therapeutic resistance. Here, we hypothesized that using a Gln analogue, such as 6-Diazo-5-oxo-L-norleucine (DON), could broadly target Gln metabolism in PDAC and prevent rapid adaptation. Indeed, DON treatment led to a significant decrease in PDAC proliferation in a dose-dependent manner, as well as a profound reduction of various metabolites involved in central carbon and nucleotide metabolism, suggesting that DON creates a metabolic crisis. In addition, we observed a significant decrease in tumor growth in various in vivo models (syngeneic, immunodeficient) using DRP-104 (sirpiglenastat), a novel pro-drug version of DON that was designed to circumvent DON associated GI toxicity and allow the therapeutic exploration of broad Gln antagonism. Mechanistically, we found that ERK signaling is increased as a compensatory mechanism through the increased activity of receptor tyrosine kinases (RTKs). Combinatorial treatment of DRP-104 and Trametinib (MEK1/2) inhibitor led to a significant increase in survival in a syngeneic model PDAC. Taken together, these pre-clinical results suggest that broadly targeting Gln metabolism could provide a new therapeutic avenue for PDAC and that the combination with an ERK signaling pathway inhibitor could further improve the therapeutic outcome.

Project description:BACKGROUND:Cancer cells reprogram their metabolism to survive and propagate. Thus, targeting metabolic rewiring in tumors is a promising therapeutic strategy. Genome-wide RNAi and CRISPR screens are powerful tools for identifying genes essential for cancer cell proliferation and survival. Integrating loss-of-function genetic screens with genomics and transcriptomics datasets reveals molecular mechanisms that underlie cancer cell dependence on specific genes; though explaining cell line-specific essentiality of metabolic genes was recently shown to be especially challenging. RESULTS:We find that variability in tissue culture medium between cell lines in a genetic screen is a major confounding factor affecting cell line-specific essentiality of metabolic genes-while, quite surprisingly, not being previously accounted for. Additionally, we find that altered expression level of a metabolic gene in a certain cell line is less indicative of its essentiality than for other genes. However, cell line-specific essentiality of metabolic genes is significantly correlated with changes in the expression of neighboring enzymes in the metabolic network. Utilizing a machine learning method that accounts for tissue culture media and functional association between neighboring enzymes, we generated predictive models for cancer cell line-specific dependence on 162 metabolic genes (representing a ~?2.2-fold increase compared to previous studies). The generated predictive models reveal numerous novel associations between molecular features and cell line-specific dependency on metabolic genes. Specifically, we demonstrate how cancer cell dependence on one-carbon metabolic enzymes is explained based on cancer lineage, oncogenic mutations, and RNA expression of neighboring enzymes. CONCLUSIONS:Considering culture media as well as accounting for molecular features of functionally related metabolic enzymes in a metabolic network significantly improves our understanding of cancer cell line-specific dependence on metabolic genes. We expect our approach and predictive models of metabolic gene essentiality to be a useful tool for investigating metabolic abnormalities in cancer.

Dataset Information

Targeting metabolic dependencies in pediatric cancer.

Publications

Targeting metabolic dependencies in pediatric cancer.

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