Targeting BRAF for patients with melanoma

The prognosis of patients with metastatic melanoma is poor and not influenced by systemic therapy with cytotoxic drugs. New targeted agents directed against the RAS-RAF-MEK-ERK pathway show promising activity in early clinical development and particular interest is focused on selective inhibitors of mutant BRAF, which is present in one half of the cases of metastatic melanoma. The majority of patients on early trials of these drugs develop secondary resistance and subsequent disease progression and it is, therefore, critical to understand the underlying escape mechanisms leading to resistance

A theoretical entropy score as a single value to express inhibitor selectivity

<p>Abstract</p> <p>Background</p> <p>Designing maximally selective ligands that act on individual targets is the dominant paradigm in drug discovery. Poor selectivity can underlie toxicity and side effects in the clinic, and for this reason compound selectivity is increasingly monitored from very early on in the drug discovery process. To make sense of large amounts of profiling data, and to determine when a compound is sufficiently selective, there is a need for a proper quantitative measure of selectivity.</p> <p>Results</p> <p>Here we propose a new theoretical entropy score that can be calculated from a set of IC₅₀data. In contrast to previous measures such as the 'selectivity score', Gini score, or partition index, the entropy score is non-arbitary, fully exploits IC₅₀data, and is not dependent on a reference enzyme. In addition, the entropy score gives the most robust values with data from different sources, because it is less sensitive to errors. We apply the new score to kinase and nuclear receptor profiling data, and to high-throughput screening data. In addition, through analyzing profiles of clinical compounds, we show quantitatively that a more selective kinase inhibitor is not necessarily more drug-like.</p> <p>Conclusions</p> <p>For quantifying selectivity from panel profiling, a theoretical entropy score is the best method. It is valuable for studying the molecular mechanisms of selectivity, and to steer compound progression in drug discovery programs.</p

Exome-wide somatic mutation characterization of small bowel adenocarcinoma

Small bowel adenocarcinoma (SBA) is an aggressive disease with limited treatment options. Despite previous studies, its molecular genetic background has remained somewhat elusive. To comprehensively characterize the mutational landscape of this tumor type, and to identify possible targets of treatment, we conducted the first large exome sequencing study on a population-based set of SBA samples from all three small bowel segments. Archival tissue from 106 primary tumors with appropriate clinical information were available for exome sequencing from a patient series consisting of a majority of confirmed SBA cases diagnosed in Finland between the years 2003-2011. Paired-end exome sequencing was performed using Illumina HiSeq 4000, and OncodriveFML was used to identify driver genes from the exome data. We also defined frequently affected cancer signalling pathways and performed the first extensive allelic imbalance (Al) analysis in SBA. Exome data analysis revealed significantly mutated genes previously linked to SBA (TP53, KRAS, APC, SMAD4, and BRAF), recently reported potential driver genes (SOX9, ATM, and ARID2), as well as novel candidate driver genes, such as ACVR2A, ACVR1B, BRCA2, and SMARCA4. We also identified clear mutation hotspot patterns in ERBB2 and BRAF. No BRAF V600E mutations were observed. Additionally, we present a comprehensive mutation signature analysis of SBA, highlighting established signatures 1A, 6, and 17, as well as U2 which is a previously unvalidated signature. Finally, comparison of the three small bowel segments revealed differences in tumor characteristics. This comprehensive work unveils the mutational landscape and most frequently affected genes and pathways in SBA, providing potential therapeutic targets, and novel and more thorough insights into the genetic background of this tumor type.Peer reviewe

Crystal structure and induction mechanism of AmiC-AmiR: a ligand-regulated transcription antitermination complex.

Inducible expression of the aliphatic amidase operon in Pseudomonas aeruginosa is controlled by an antitermination mechanism which allows production of the full-length transcript only in the presence of small-molecule inducers, such as acetamide. Ligand-regulated antitermination is provided by AmiC, the ligand-sensitive negative regulator, and AmiR, the RNA-binding positive regulator. Under non-inducing or repressing growth conditions, AmiC and AmiR form a complex in which the activity of AmiR is silenced. The crystal structure of the AmiC-AmiR complex identifies AmiR as a new and highly unusual member of the response-regulator family of bacterial signal transduction proteins, regulated by sequestration rather than phosphorylation. Comparison with the structure of free AmiC reveals the subtle mechanism of ligand-induced release of AmiR

Mechanism of activation of the RAF-ERK signaling pathway by oncogenic mutations of B-RAF.

Over 30 mutations of the B-RAF gene associated with human cancers have been identified, the majority of which are located within the kinase domain. Here we show that of 22 B-RAF mutants analyzed, 18 have elevated kinase activity and signal to ERK in vivo. Surprisingly, three mutants have reduced kinase activity towards MEK in vitro but, by activating C-RAF in vivo, signal to ERK in cells. The structures of wild type and oncogenic V599EB-RAF kinase domains in complex with the RAF inhibitor BAY43-9006 show that the activation segment is held in an inactive conformation by association with the P loop. The clustering of most mutations to these two regions suggests that disruption of this interaction converts B-RAF into its active conformation. The high activity mutants signal to ERK by directly phosphorylating MEK, whereas the impaired activity mutants stimulate MEK by activating endogenous C-RAF, possibly via an allosteric or transphosphorylation mechanism