Faculty Bibliography

Nonmedical prescription opioid use has become widespread. It can lead to heroin use, drug injection and HIV infection. We describe young adult opioid users' sexual risk behavior, partnerships and settings. 464 youth aged 18-29 who reported opioid use in the past 30 days were recruited using Respondent-Driven Sampling. Eligible participants completed a computer-assisted, interviewer-administered risk questionnaire and were tested for STIs and HIV. Participants (33% female; 66% white non-Hispanic) almost all had sex in the prior 90 days; 42% reported more than one partner. Same-sex sex was reported by 3% of men and 10% of women. Consistent condom use was rare. Seven percent reported group sex participation in the last 90 days but lifetime group sex was common among men and women. Young opioid users' unprotected sex, multiple partners and group sex puts them and others at high HIV and STI risk.

Recent advances in mass spectrometry (MS) have enabled extensive analysis of cancer proteomes. Here, we employed quantitative proteomics to profile protein expression across 24 breast cancer patient-derived xenograft (PDX) models. Integrated proteogenomic analysis shows positive correlation between expression measurements from transcriptomic and proteomic analyses; further, gene expression-based intrinsic subtypes are largely re-capitulated using non-stromal protein markers. Proteogenomic analysis also validates a number of predicted genomic targets in multiple receptor tyrosine kinases. However, several protein/phosphoprotein events such as overexpression of AKT proteins and ARAF, BRAF, HSP90AB1 phosphosites are not readily explainable by genomic analysis, suggesting that druggable translational and/or post-translational regulatory events may be uniquely diagnosed by MS. Drug treatment experiments targeting HER2 and components of the PI3K pathway supported proteogenomic response predictions in seven xenograft models. Our study demonstrates that MS-based proteomics can identify therapeutic targets and highlights the potential of PDX drug response evaluation to annotate MS-based pathway activities.

OBJECTIVE: To inform the design of a combination intervention strategy targeting HIV-infected unhealthy alcohol users in Maharashtra, India, that could be tested in future randomized control trials. METHODS: Using probabilistic compartmental simulation modeling we compared intervention strategies targeting HIV-infected unhealthy alcohol users on antiretroviral therapy (ART) in Maharashtra, India. We tested interventions targeting four behaviors (unhealthy alcohol consumption, risky sexual behavior, depression and antiretroviral adherence), in three formats (individual, group based, community) and two durations (shorter versus longer). A total of 5,386 possible intervention combinations were tested across the population for a 20-year time horizon and intervention bundles were narrowed down based on incremental cost-effectiveness analysis using a two-step probabilistic uncertainty analysis approach. RESULTS: Taking into account uncertainty in transmission variables and intervention cost and effectiveness values, we were able to reduce the number of possible intervention combinations to be used in a randomized control trial from over 5,000 to less than 5. The most robust intervention bundle identified was a combination of three interventions: long individual alcohol counseling; weekly Short Message Service (SMS) adherence counseling; and brief sex risk group counseling. CONCLUSIONS: In addition to guiding policy design, simulation modeling of HIV transmission can be used as a preparatory step to trial design, offering a method for intervention pre-selection at a reduced cost.

Inhibition of VLDL secretion reduces plasma levels of atherogenic apolipoprotein B (apoB) lipoproteins but can also cause hepatic steatosis. Approaches targeting apoB synthesis, which lies upstream of VLDL secretion, have potential to effectively reduce dyslipidemia but can also lead to hepatic accumulation of unsecreted triglycerides (TG). Here, we found that treating mice with apoB antisense oligonucleotides (ASOs) for 6 weeks decreased VLDL secretion and plasma cholesterol without causing steatosis. The absence of steatosis was linked to an increase in ER stress in the first 3 weeks of ASO treatment, followed by development of ER autophagy at the end of 6 weeks of treatment. The latter resulted in increased fatty acid (FA) oxidation that was inhibited by both chloroquine and 3-methyl adenine, consistent with trafficking of ER TG through the autophagic pathway before oxidation. These findings support the concept that inhibition of apoB synthesis traps lipids that have been transferred to the ER by microsomal TG transfer protein (MTP), inducing ER stress. ER stress then triggers ER autophagy and subsequent lysosomal lipolysis of TG, followed by mitochondrial oxidation of released FA, leading to prevention of steatosis. The identification of this pathway indicates that inhibition of VLDL secretion remains a viable target for therapies aiming to reduce circulating levels of atherogenic apoB lipoproteins.

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

Every molecular player in the cast of biology's central dogma is being sequenced and quantified with increasing ease and coverage. To bring the resulting genomic, transcriptomic, and proteomic data sets into coherence, tools must be developed that do not constrain data acquisition and analytics in any way but rather provide simple links across previously acquired data sets with minimal preprocessing and hassle. Here we present such a tool: PGx, which supports proteogenomic integration of mass spectrometry proteomics data with next-generation sequencing by mapping identified peptides onto their putative genomic coordinates.

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 thirty 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 (~80%). 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 identified gaps in sequence coverage, thereby benchmarking current technology and progress towards whole cancer proteome and transcriptome analysis.

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal ( http://assays.cancer.gov ) to serve as an open-source repository of well-characterized targeted proteomic assays. The portal is designed to curate and disseminate highly characterized, targeted mass spectrometry (MS)-based assays by providing detailed assay performance characterization data, standard operating procedures, and access to reagents. Assay content is accessed via the portal through queries to find assays targeting proteins associated with specific cellular pathways, protein complexes, or specific chromosomal regions. The position of the peptide analytes for which there are available assays are mapped relative to other features of interest in the protein, such as sequence domains, isoforms, single nucleotide polymorphisms, and posttranslational modifications. The overarching goals are to enable robust quantification of all human proteins and to standardize the quantification of targeted MS-based assays to ultimately enable harmonization of results over time and across laboratories.

The field of proteogenomics has been driven by combined advances in next-generation sequencing (NGS) and proteomic methods. NGS technologies are now both rapid and affordable, making it feasible to include sequencing in the clinic and academic research setting. Alongside the improvements in sequencing technologies, methods in high throughput proteomics have increased the depth of coverage and the speed of analysis. The integration of these data types using continuously evolving bioinformatics methods allows for improvements in gene and protein annotation, and a more comprehensive understanding of biological systems.

Bullying is an intentional act that can wreak havoc in the life of an individual. With more than 1 billion users, YouTube is a powerful medium for disseminating information. The purpose of this study was to describe the extent to which content related to bullying is present on YouTube with respect to source, content, number of views, length, and year uploaded. Collectively, the videos in this sample were viewed more than half a billion times. The source of the most widely viewed videos was consumers, and none of the most widely viewed videos was posted by a governmental agency or a professional organization. The most common content in the videos was describing or depicting violence (n=89). Over one-half addressed getting help (n=56). Suicide was mentioned in 38 of the videos. Additional investment by professional agencies is warranted to improve understanding about ways to increase the dissemination of positive messages about bullying prevention, and about helping adolescents who are bullied on social media.