Altered expression of XPO1, the main nuclear export receptor in eukaryotic cells, has been observed in cancer, and XPO1 has been a focus of anticancer drug development. However, mechanistic evidence for cancer-specific alterations in XPO1 function is lacking. Here, genomic analysis of 42,793 cancers identified recurrent and previously unrecognized mutational hotspots in XPO1. XPO1 mutations exhibited striking lineage specificity, with enrichment in a variety of B-cell malignancies, and introduction of single amino acid substitutions in XPO1 initiated clonal, B-cell malignancy in vivo. Proteomic characterization identified that mutant XPO1 altered the nucleocytoplasmic distribution of hundreds of proteins in a sequence-specific manner that promoted oncogenesis. XPO1 mutations preferentially sensitized cells to inhibitors of nuclear export, providing a biomarker of response to this family of drugs. These data reveal a new class of oncogenic alteration based on change-of-function mutations in nuclear export signal recognition and identify therapeutic targets based on altered nucleocytoplasmic trafficking. Significance: Here, we identify that heterozygous mutations in the main nuclear exporter in eukaryotic cells, XPO1, are positively selected in cancer and promote the initiation of clonal B-cell malignancies. XPO1 mutations alter nuclear export signal recognition in a sequence-specific manner and sensitize cells to compounds in clinical development inhibiting XPO1 function. This article is highlighted in the In This Issue feature, p. 1325

Motivation: Leucine-rich nuclear export signals (NESs) are short amino acid motifs that mediate binding of cargo proteins to the nuclear export receptor CRM1, and thus contribute to regulate the localization and function of many cellular proteins. Computational prediction of NES motifs is of great interest, but remains a significant challenge. Results: We have developed a novel approach for amino acid motif searching that can be used for NES prediction. This approach, termed Wregex (weighted regular expression), combines regular expressions with a position-specific scoring matrix (PSSM), and has been implemented in a web-based, freely available, software tool. By making use of a PSSM, Wregex provides a score to prioritize candidates for experimental testing. Key features of Wregex include its flexibility, which makes it useful for searching other types of protein motifs, and its fast execution time, which makes it suitable for large-scale analysis. In comparative tests with previously available prediction tools, Wregex is shown to offer a good rate of true-positive motifs, while keeping a smaller number of potential candidates. Availability: Wregex is free, open-source software available from http://wregex.ehubio.es Contact:gorka.prieto@ehu.es Supplementary information: Supplementary data are available at Bioinformatics online.

Protein inference from peptide identifications in shotgun proteomics must deal with ambiguities that arise due to the presence of peptides shared between different proteins, which is common in higher eukaryotes. Recently data independent acquisition (DIA) approaches have emerged as an alternative to the traditional data dependent acquisition (DDA) in shotgun proteomics experiments. MS E is the term used to name one of the DIA approaches used in QTOF instruments. MS E data require specialized software to process acquired spectra and to perform peptide and protein identifications. However the software available at the moment does not group the identified proteins in a transparent way by taking into account peptide evidence categories. Furthermore the inspection, comparison and report of the obtained results require tedious manual intervention. Here we report a software tool to address these limitations for MS E data.

Inferring which protein species have been detected in bottom‐up proteomics experiments has been a challenging problem for which solutions have been maturing over the past decade. While many inference approaches now function well in isolation, comparing and reconciling the results generated across different tools remains difficult. It presently stands as one of the greatest barriers in collaborative efforts such as the Human Proteome Project and public repositories such as the PRoteomics IDEntifications (PRIDE) database. Here we present a framework for reporting protein identifications that seeks to improve capabilities for comparing results generated by different inference tools. This framework standardizes the terminology for describing protein identification results, associated with the HUPO‐Proteomics Standards Initiative (PSI) mzIdentML standard, while still allowing for differing methodologies to reach that final state. It is proposed that developers of software for reporting identification results will adopt this terminology in their outputs. While the new terminology does not require any changes to the core mzIdentML model, it represents a significant change in practice, and, as such, the rules will be released via a new version of the mzIdentML specification (version 1.2) so that consumers of files are able to determine whether the new guidelines have been adopted by export software.

This paper provides minimum C/N values for correct reception of DVB-T2 signals under fixed reception conditions. The C/N values are obtained after analyzing the results of field and laboratory trials. The field measurements were taken in a middle-sized city, along 33 locations, with MFN and SFN configurations. Both the system configuration options (constellation and code rate, FFT size, pilot pattern, and rotated constellations) and the propagation channel are taken into account to quantify their influence on the reception requirements. DVB-T was also measured and both systems are compared. The final objective is to provide the broadcasters with some guides based on measurements to optimize the DVB-T2 networks by choosing the parameters that best fit their needs.