Small-molecule protein kinase inhibitors are central tools for elucidating cellular signaling pathways and are promising therapeutic agents. Due to evolutionary conservation of the ATP-binding site, most kinase inhibitors that target this site promiscuously inhibit multiple kinases. Interpretation of experiments utilizing these compounds is confounded by a lack of data on the comprehensive kinase selectivity of most inhibitors. Here we profiled the activity of 178 commercially available kinase inhibitors against a panel of 300 recombinant protein kinases using a functional assay. Quantitative analysis revealed complex and often unexpected kinase-inhibitor interactions, with a wide spectrum of promiscuity. Many off-target interactions occur with seemingly unrelated kinases, revealing how large-scale profiling can be used to identify multi-targeted inhibitors of specific, diverse kinases. The results have significant implications for drug development and provide a resource for selecting compounds to elucidate kinase function and for interpreting the results of experiments that use them.

Summary DNA methylation is a major epigenetic mechanism for gene silencing. While methyltransferases mediate cytosine methylation, it is less clear how unmethylated regions in mammalian genomes are protected from de novo methylation and whether an active demethylating activity is involved. Here we show that either knockout or catalytic inactivation of the DNA repair enzyme Thymine DNA Glycosylase (TDG) leads to embryonic lethality in mice. TDG is necessary for recruiting p300 to retinoic acid (RA)-regulated promoters, protection of CpG islands from hypermethylation, and active demethylation of tissue-specific, developmentally- and hormonally-regulated promoters and enhancers. TDG interacts with the deaminase AID and the damage-response protein GADD45a. These findings highlight a dual role for TDG in promoting proper epigenetic states during development and suggest a two-step mechanism for DNA demethylation in mammals, whereby 5-methylcytosine and 5-hydroxymethylcytosine are first deaminated by AID to thymine and 5-hydroxymethyluracil, respectively, followed by TDG-mediated thymine and 5-hydroxymethyluracil excision repair.

In the last decade, advances in high-throughput technologies such as DNA microarrays have made it possible to simultaneously measure the expression levels of tens of thousands of genes and proteins. This has resulted in large amounts of biological data requiring analysis and interpretation. Nonnegative matrix factorization (NMF) was introduced as an unsupervised, parts-based learning paradigm involving the decomposition of a nonnegative matrix V into two nonnegative matrices, W and H, via a multiplicative updates algorithm. In the context of a p×n gene expression matrix V consisting of observations on p genes from n samples, each column of W defines a metagene, and each column of H represents the metagene expression pattern of the corresponding sample. NMF has been primarily applied in an unsupervised setting in image and natural language processing. More recently, it has been successfully utilized in a variety of applications in computational biology. Examples include molecular pattern discovery, class comparison and prediction, cross-platform and cross-species analysis, functional characterization of genes and biomedical informatics. In this paper, we review this method as a data analytical and interpretive tool in computational biology with an emphasis on these applications.

Desmoplasia, a fibrotic mass including cancer-associated fibroblasts (CAFs) and self-sustaining extracellular matrix (D-ECM), is a puzzling feature of pancreatic ductal adenocarcinoma (PDACs). Conflicting studies have identified tumor-restricting and tumor-promoting roles of PDAC-associated desmoplasia, suggesting that individual CAF/D-ECM protein constituents have distinguishable tumorigenic and tumor-repressive functions. Using 3D culture of normal pancreatic versus PDAC-associated human fibroblasts, we identified a CAF/D-ECM phenotype that correlates with improved patient outcomes, and that includes CAFs enriched in plasma membrane-localized, active α5β1-integrin. Mechanistically, we established that TGFβ is required for D-ECM production but dispensable for D-ECM-induced naïve fibroblast-to-CAF activation, which depends on αvβ5-integrin redistribution of pFAK-independent active α5β1-integrin to assorted endosomes. Importantly, the development of a simultaneous multi-channel immunofluorescence approach and new algorithms for computational batch-analysis and their application to a human PDAC panel, indicated that stromal localization and levels of active SMAD2/3 and α5β1-integrin distinguish patient-protective from patient-detrimental desmoplasia and foretell tumor recurrences, suggesting a useful new prognostic tool.DOI: http://dx.doi.org/10.7554/eLife.20600.001

Intrinsic and acquired cellular resistance factors limit the efficacy of most targeted cancer therapeutics. Synthetic lethal screens in lower eukaryotes suggest that networks of genes closely linked to therapeutic targets would be enriched for determinants of drug resistance. We developed a protein network centered on the epidermal growth factor receptor (EGFR), which is a validated cancer therapeutic target, and used siRNA screening to comparatively probe this network for proteins that regulate the effectiveness of both EGFR-targeted agents and nonspecific cytotoxic agents. We identified subnetworks of proteins influencing resistance, with putative resistance determinants enriched among proteins that interacted with proteins at the core of the network. We found that EGFR antagonists and clinically relevant drugs targeting proteins connected in the EGFR network, such as the kinases protein kinase C or Aurora kinase A, or the transcriptional regulator STAT3, synergized to reduce cell viability and tumor size, suggesting the potential for a direct path to clinical exploitation. Such a focused approach can potentially improve the coherent design of combination cancer therapies.