New Treatment Target Identified for Key Prostate Cancer Driver

Researchers have identified a potential alternative approach to blocking the activity of a key molecular driver of an advanced form of prostate cancer, called androgen-independent or castration-resistant prostate cancer.

In prostate cancer cell lines and in several mouse models of prostate cancer, treatment with drug-like small molecules that target a protein called ROR-γ disrupted the activity of the androgen receptor (AR), the researchers showed. Signaling through AR is the chief means by which prostate cancer cells grow and spread.

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Bridging the gap between non-targeted stable isotope labeling and metabolic flux analysis

Abstract

Background

Metabolism gained increasing interest for the understanding of diseases and to pinpoint therapeutic intervention points. However, classical metabolomics techniques only provide a very static view on metabolism. Metabolic flux analysis methods, on the other hand, are highly targeted and require detailed knowledge on metabolism beforehand.

Results

We present a novel workflow to analyze non-targeted metabolome-wide stable isotope labeling data to detect metabolic flux changes in a non-targeted manner. Furthermore, we show how similarity-analysis of isotopic enrichment patterns can be used for pathway contextualization of unidentified compounds. We illustrate our approach with the analysis of changes in cellular metabolism of human adenocarcinoma cells in response to decreased oxygen availability. Starting without a priori knowledge, we detect metabolic flux changes, leading to an increased glutamine contribution to acetyl-CoA production, reveal biosynthesis of N-acetylaspartate by N-acetyltransferase 8-like (NAT8L) in lung cancer cells and show that NAT8L silencing inhibits proliferation of A549, JHH-4, PH5CH8, and BEAS-2B cells.

Conclusions

Differential stable isotope labeling analysis provides qualitative metabolic flux information in a non-targeted manner. Furthermore, similarity analysis of enrichment patterns provides information on metabolically closely related compounds. N-acetylaspartate and NAT8L are important players in cancer cell metabolism, a context in which they have not received much attention yet.

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