Dataset Information

Metabolic landscapes in sarcomas.

ABSTRACT: Metabolic rewiring offers novel therapeutic opportunities in cancer. Until recently, there was scant information regarding soft tissue sarcomas, due to their heterogeneous tissue origin, histological definition and underlying genetic history. Novel large-scale genomic and metabolomics approaches are now helping stratify their physiopathology. In this review, we show how various genetic alterations skew activation pathways and orient metabolic rewiring in sarcomas. We provide an update on the contribution of newly described mechanisms of metabolic regulation. We underscore mechanisms that are relevant to sarcomagenesis or shared with other cancers. We then discuss how diverse metabolic landscapes condition the tumor microenvironment, anti-sarcoma immune responses and prognosis. Finally, we review current attempts to control sarcoma growth using metabolite-targeting drugs.

SUBMITTER: Miallot R

PROVIDER: S-EPMC8296645 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Publications

Metabolic landscapes in sarcomas.

Miallot Richard R Galland Franck F Millet Virginie V Blay Jean-Yves JY Naquet Philippe P

Journal of hematology & oncology 20210722 1

Metabolic rewiring offers novel therapeutic opportunities in cancer. Until recently, there was scant information regarding soft tissue sarcomas, due to their heterogeneous tissue origin, histological definition and underlying genetic history. Novel large-scale genomic and metabolomics approaches are now helping stratify their physiopathology. In this review, we show how various genetic alterations skew activation pathways and orient metabolic rewiring in sarcomas. We provide an update on the con ...[more]

PMID: 34294128

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Project description:Metabolic deregulation is an emergent hallmark of cancer. Altered patterns of metabolic pathways result in exacerbated synthesis of macromolecules, increased proliferation, and resistance to treatment via alteration of drug processing. In addition, molecular heterogeneity creates a barrier to therapeutic options. In breast cancer, this broad variation in molecular metabolism constitutes, simultaneously, a source of prognostic and therapeutic challenges and a doorway to novel interventions. In this work, we investigated the metabolic deregulation landscapes in breast cancer molecular subtypes. Such landscapes are the regulatory signatures behind subtype-specific metabolic features. n = 735 breast cancer samples of the Luminal A, Luminal B, Her2+, and Basal subtypes, as well as n = 113 healthy breast tissue samples were analyzed. By means of a single-sample-based algorithm, deregulation for all metabolic pathways in every sample was determined. Deregulation levels match almost perfectly with the molecular classification, indicating that metabolic anomalies are closely associated with gene-expression signatures. Luminal B tumors are the most deregulated but are also the ones with higher within-subtype variance. We argued that this variation may underlie the fact that Luminal B tumors usually present the worst prognosis, a high rate of recurrence, and the lowest response to treatment in the long term. Finally, we designed a therapeutic scheme to regulate purine metabolism in breast cancer, independently of the molecular subtype. This scheme is founded on a computational tool that provides a set of FDA-approved drugs to target pathway-specific differentially expressed genes. By providing metabolic deregulation patterns at the single-sample level in breast cancer subtypes, we have been able to further characterize tumor behavior. This approach, together with targeted therapy, may open novel avenues for the design of personalized diagnostic, prognostic, and therapeutic strategies.

Project description:Metabolic reprogramming, due in part to the overexpression of metabolic enzymes, is a key hallmark of cancer cells. Lactate dehydrogenase (LDHA), a metabolic enzyme that catalyzes the interconversion of lactate and pyruvate, is overexpressed in a wide variety of cancer types, including pancreatic ductal adenocarcinoma (PDAC). Furthermore, the genetic or pharmacological inhibition of LDHA suppresses cancer growth, demonstrating a cancer-promoting role for this enzyme. Therefore, several pharmacological LDHA inhibitors are being developed and tested as potential anti-cancer therapeutic agents. Because cancer cells are known to rapidly adapt and become resistant to anti-cancer therapies, in this study, we modeled the adaptation of cancer cells to LDHA inhibition. Using PDAC as a model system, we studied the molecular aspects of cells resistant to the competitive LDHA inhibitor sodium oxamate. We performed unbiased RNA-sequencing (RNA-seq), assay for transposase-accessible chromatin with sequencing (ATAC-seq), and metabolomics analyses of parental and oxamate-resistant PDAC cells treated with and without oxamate to identify the transcriptional, chromatin, and metabolic landscapes of these cells. We found that oxamate-resistant PDAC cells were significantly different from parental cells at the levels of mRNA expression, chromatin accessibility, and metabolites. Additionally, an integrative analysis combining the RNA-seq and ATAC-seq datasets identified a subset of differentially expressed mRNAs that directly correlated with changes in chromatin accessibility. Finally, functional analysis of differentially expressed metabolic genes in parental and oxamate-resistant PDAC cells treated with and without oxamate, together with an integrative analysis of RNA-seq and metabolomics data, revealed changes in metabolic enzymes that might explain the changes in metabolite levels observed in these cells. Collectively, these studies identify the transcriptional, chromatin, and metabolic landscapes of LDHA inhibitor resistance in PDAC cells. Future functional studies related to these changes remain necessary to reveal the direct roles played by these changes in the development of LDHA inhibitor resistance and uncover approaches for more effective use of LDHA inhibitors in cancer therapy.

Dataset Information

Metabolic landscapes in sarcomas.

Publications

Metabolic landscapes in sarcomas.

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