Jack Pollard

MOTIVATION: Prior biological knowledge greatly facilitates the meaningful interpretation of gene-expression data. Causal networks constructed from individual relationships curated from the literature are particularly suited for this task, since they create mechanistic hypotheses that explain the expression changes observed in datasets. RESULTS: We present and discuss a suite of algorithms and tools for inferring and scoring regulator networks upstream of gene-expression data based on a large-scale causal network derived from the Ingenuity Knowledge Base. We extend the method to predict downstream effects on biological functions and diseases and demonstrate the validity of our approach by applying it to example datasets. AVAILABILITY: The causal analytics tools 'Upstream Regulator Analysis', 'Mechanistic Networks', 'Causal Network Analysis' and 'Downstream Effects Analysis' are implemented and available within Ingenuity Pathway Analysis (IPA, http://www.ingenuity.com). SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online.

Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery and development. New opportunities are emerging in target identification owing to improved disease understanding through cell subtyping, and highly multiplexed functional genomics screens incorporating scRNA-seq are enhancing target credentialling and prioritization. ScRNA-seq is also aiding the selection of relevant preclinical disease models and providing new insights into drug mechanisms of action. In clinical development, scRNA-seq can inform decision-making via improved biomarker identification for patient stratification and more precise monitoring of drug response and disease progression. Here, we illustrate how scRNA-seq methods are being applied in key steps in drug discovery and development, and discuss ongoing challenges for their implementation in the pharmaceutical industry. There have been significant recent advances in the development of single-cell technologies, providing remarkable opportunities for drug discovery and development. Here, Ferran and colleagues discuss how single-cell technologies, primarily single-cell RNA sequencing methods, are being applied in the drug discovery pipeline, from target identification to clinical decision-making. Ongoing challenges and potential future directions are discussed.

T cell infiltration, and formation of immune memory. Antitumor activity extended beyond the treated lesions and inhibited growth of distant tumors and disseminated tumors. Combining the mRNAs with immunomodulatory antibodies enhanced antitumor responses in both injected and uninjected tumors, thus improving survival and tumor regression. Consequently, clinical testing of this cytokine-encoding mRNA mixture is now underway.

Tumor cells display fundamental changes in metabolism and nutrient uptake in order to utilize additional nutrient sources to meet their enhanced bioenergetic requirements. Glutamine (Gln) is one such nutrient that is rapidly taken up by tumor cells to fulfill this increased metabolic demand. A vital step in the catabolism of glutamine is its conversion to glutamate by the mitochondrial enzyme glutaminase (GLS). This study has identified GLS a potential therapeutic target in breast cancer, specifically in the basal subtype that exhibits a deregulated glutaminolysis pathway. Using inducible shRNA mediated gene knockdown, we discovered that loss of GLS function in triple-negative breast cancer (TNBC) cell lines with a deregulated glutaminolysis pathway led to profound tumor growth inhibition in vitro and in vivo. GLS knockdown had no effect on growth and metabolite levels in non-TNBC cell lines. We rescued the anti-tumor effect of GLS knockdown using shRNA resistant cDNAs encoding both GLS isoforms and by addition of an α-ketoglutarate (αKG) analog thus confirming the critical role of GLS in TNBC. Pharmacological inhibition of GLS with the small molecule inhibitor CB-839 reduced cell growth and led to a decrease in mammalian target of rapamycin (mTOR) activity and an increase in the stress response pathway driven by activating transcription factor 4 (ATF4). Finally, we found that GLS inhibition synergizes with mTOR inhibition, which introduces the possibility of a novel therapeutic strategy for TNBC. Our study revealed that GLS is essential for the survival of TNBC with a deregulated glutaminolysis pathway. The synergistic activity of GLS and mTOR inhibitors in TNBC cell lines suggests therapeutic potential of this combination for the treatment of vulnerable subpopulations of TNBC.