Faculty Bibliography

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.

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.

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.

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.

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.

Bullying is an intentional act that can wreak havoc in the life of an individual. With more than 1 billion users, YouTube^TM 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^TM 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

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.

The goal of this talk is to introduce an integrated quantitative proteogenomic approach to comprehensively map proteomic information back to their encoding genes. We seek evidence from mass spectrometry-based large-scale proteomic data of patient populations in conjunction with patient-centric next-generation sequencing data and unbiased sequencing strategies to study breast cancer (BC) subtypes from a genomic context. We have obtained global and phosphoproteomic data with matching next generation sequencing data for 18 patient-derived xenografts (PDXs) representing the major clinical subtypes of BC. Our workflow starts with the creation of several protein sequence databases that serve as a template for mass spectrometry database identifications. These databases include 1) completely annotated reference protein sequences, 2) patient-specific databases that were created using next generation sequencing data, 3) isoform databases that contain all possible splicing combinations, and 4) amino acid sequence database resulting from a six-frame translation of the entire human reference and customized genomes. All mass spectrometry raw data are searched against the databases for obtaining identifications at the peptide level, and assembly of peptides for quantification using taxonomy-based label-free quantitation (LFQ) that can specifically quantify unique human peptide sequences found in PDXs. The peptides are then mapped to the human genome and visualized using a genome browser. Quantitative changes across PDXs are presented at the protein level or at the isoform level via peptide role-up to specific exons and visualized as a quantitative data track. By combining search results from these databases we obtain a comprehensive view of our PDXs. The complementary nature of the databases enable greater proteomic depth, i.e. databases with complete splicing combinations capture proteomic evidence when patient-specific databases fail due to possible erroneous RNA-seq reads. Similarly, 6-frame translated amino acid databases can capture potentially novel coding regions but are unable to detect splicing. Peptide maps are obtained for individual genes or specific protein isoforms covering both knowledge-driven and novel genomic annotation types. We compile peptides carrying variants, splice junctions, fusions, and new coding regions specific to each PDX or in common with a specific BC subtype. Majority of data is mapped back to the genome loci using unmodified peptides via global proteomics while phosphopeptides that contain variants and splicing are also mapped in a similar manner using phosphoproteomic data. We have currently annotated 455 novel proteogenomic hits covering many examples outlined above for genes related to breast cancer and show how these can be specifically identified and in some instances differentially quantified in the PDX models