Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations, and splice variants identified in cancer cells are translated. Herein, we apply a proteogenomic data integration tool (QUILTS) to illustrate protein variant discovery using whole genome, whole transcriptome, and global proteome datasets generated from a pair of luminal and basal-like breast-cancer-patient-derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS sample process replicates defined here as an independent tandem MS experiment using identical sample material. Despite analysis of over 30 sample process replicates, only about 10% of SNVs (somatic and germline) detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNVs without a detectable mRNA transcript were also observed, suggesting that transcriptome coverage was incomplete (ϳ80%). In contrast to germline variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than in the luminal tumor, raising the possibility of differential translation or protein degradation effects. In conclusion, this large-scale proteogenomic integration allowed us to determine the degree to which mutations are translated and identify gaps in sequence coverage, thereby benchmarking current technology and progress toward whole cancer proteome and transcriptome analysis. Massively parallel sequencing (MPS)1 of cancer genomes has demonstrated enormous complexity, and it is often unclear which somatic mutations drive tumor biology and which are nonfunctional passenger mutations that passively accumulate. RNA sequencing is frequently used to determine which nucleotide variants are transcribed and therefore have the potential for biological function. However, many mutations detected at the DNA level are not observed at the mRNA level, and their observation is dependent upon expression of the stability of the mRNA (1). Mutation detection at the peptide level clearly increases the confidence that any given variant is

Findings may help inform the optimal timing for delivery of primary, secondary and tertiary prevention efforts targeting young opioid users.

Background Benzodiazepines are a widely prescribed psychoactive drug; in the U.S., both medical and nonmedical use of benzodiazepines has increased markedly in the past 15 years. Long-term use can lead to tolerance and dependence, and abrupt withdrawal can cause seizures or other life-threatening symptoms. Benzodiazepines are often used nonmedically in conjunction with other drugs, and with opioids in particular a combination that can increase the risk for fatal and non-fatal overdose. This mixed-methods study examines nonmedical use of benzodiazepines among young adults in New York City and its relationship with opioid use. Methods For qualitative analysis, 46 90-minute semi-structured interviews were conducted with young adult opioid users (ages 18–32). Interviews were transcribed and coded for key themes. For quantitative analysis, 464 young adult opioid users (ages 18–29) were recruited using Respondent-Driven Sampling and completed structured interviews. Benzodiazepine use was assessed via a self-report questionnaire that included measures related to nonmedical benzodiazepine and opioid use. Results Participants reported using benzodiazepines nonmedically for a wide variety of reasons, including: to increase the high of other drugs; to lessen withdrawal symptoms; and to come down from other drugs. Benzodiazepines were described as readily available and cheap. There was a high prevalence (93%) of nonmedical benzodiazepine use among nonmedical opioid users, with 57% reporting regular nonmedical use. In bivariate analyses, drug-related risk behaviours such as polysubstance use, drug binging, heroin injection and overdose were strongly associated with regular nonmedical benzodiazepine use. In multivariate analysis, growing up in a middle-income household (earning between $51,000 and $100,000 annually), lifetime overdose experience, having ever used cocaine regularly, having ever been prescribed benzodiazepines, recent drug binging, and encouraging fellow drug users to use benzodiazepines to cope with opioid withdrawal were consistently strong predictors of regular nonmedical benzodiazepine use. Conclusion Nonmedical benzodiazepine use may be common among nonmedical opioid users due to its drug-related multi-functionality. Harm reduction messages should account for the multiple functions benzodiazepines serve in a drug-using context, and encourage drug users to tailor their endorsement of benzodiazepines to peers to include safer alternatives.

Candida albicans maintains both commensal and pathogenic states in humans. Here, we have defined the genomic response to osmotic stress mediated by transcription factor Sko1. We performed microarray analysis of a sko1Δ/Δ mutant strain subjected to osmotic stress, and we utilized gene sequence enrichment analysis and enrichment mapping to identify Sko1-dependent osmotic stress-response genes. We found that Sko1 regulates distinct gene classes with functions in ribosomal synthesis, mitochondrial function, and vacuolar transport. Our in silico analysis suggests that Sko1 may recognize two unique DNA binding motifs. Our C. albicans genomic analyses and complementation studies in Saccharomyces cerevisiae showed that Sko1 is conserved as a regulator of carbohydrate metabolism, redox metabolism, and glycerol synthesis. Further, our real time-qPCR results showed that osmotic stress-response genes that are dependent on the kinase Hog1 also require Sko1 for full expression. Our findings reveal divergent and conserved aspects of Sko1-dependent osmotic stress signaling.