Ba-alawi, W. | bioRxiv Science

bioRxiv2018

Metabolic adaptations underlie epigenetic vulnerabilities in chemoresistant breast cancer.

Cancer cell survival upon cytotoxic drug exposure leads to changes in cell identity, dictated by the epigenome. Several metabolites serve as substrates or co-factors to chromatin-modifying enzymes, suggesting that metabolic changes can underlie change in cell fate. Here, we show that progression of triple-negative breast cancer (TNBC) to taxane-resistance is characterized by altered methionine metabolism and S-adenosylmethionine (SAM) availability, giving rise to DNA hypomethylation in regions enriched for transposable elements (TE). Compensatory redistribution of H3K27me3 forming Large Organized Chromatin domains of lysine (K) modification (LOCK) prevents expression of TE in taxane-resistant cells. Pharmacological inhibition of EZH2, the H3K27me3 methyltransferase, alleviates TE repression, leading to the accumulation of dsRNA and activation of the interferon viral mimicry-response, specifically inhibiting the growth of taxane-resistant TNBC. Together, our work delineates a role for metabolic adaptations in redefining the epigenome of taxane-resistant TNBC cells and underlies an epigenetic vulnerability toward pharmacological inhibition of EZH2.

genomics↗

bioRxiv2017

PharmacoDB: an integrative database for mining in vitro anticancer drug screening studies

Recent pharmacogenomic studies profiled large panels of cancer cell lines against hundreds of approved drugs and experimental chemical compounds. The overarching goal of these screens is to measure sensitivity of cell lines to chemical perturbation, correlate these measures to genomic features, and thereby develop novel predictors of drug response. However, leveraging this valuable data is challenging due to the lack of standards for annotating cell lines and chemical compounds, and quantifying drug response. Moreover, it has been recently shown that the complexity and complementarity of the experimental protocols used in the field result in high levels of technical and biological variation in the in vitro pharmacological profiles. There is therefore a need for new tools to facilitate rigorous comparison and integrative analysis of large-scale drug screening datasets. To address this issue, we have developed PharmacoDB (pharmacodb.pmgenomics.ca), a database integrating the largest pharmacogenomic studies published to date. Here, we describe how the curation of cell line and chemical compound identifiers maximizes the overlap between datasets and how users can leverage such data to compare and extract robust drug phenotypes. PharmacoDB provides a unique resource to mine a compendium of curated pharmacogenomic datasets that are otherwise disparate and difficult to integrate.\n\nKey pointsO_LICuration of cell line and drug identifiers in the largest pharmacogenomic studies published to date\nC_LIO_LIUniform processing of drug sensitivity data to reduce heterogeneity across studies\nC_LIO_LIMultiple drug response summary metrics enabling visual comparison and integrative analysis\nC_LI

bioinformatics↗