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Platinum-based chemotherapy, including cisplatin, carboplatin, and oxaliplatin, is prescribed to 10-20% of all cancer patients. Unfortunately, platinum resistance develops in a significant number of patients and is a determinant of clinical outcome. Extensive research has been conducted to understand and overcome platinum resistance, and mechanisms of resistance can be categorized into several broad biological processes, including (1) regulation of drug entry, exit, accumulation, sequestration, and detoxification, (2) enhanced repair and tolerance of platinum-induced DNA damage, (3) alterations in cell survival pathways, (4) alterations in pleiotropic processes and pathways, and (5) changes in the tumor microenvironment. As a resource to the cancer research community, we provide a comprehensive overview accompanied by a manually curated database of the >900 genes/proteins that have been associated with platinum resistance over the last 30 years of literature. The database is annotated with possible pathways through which the curated genes are related to platinum resistance, types of evidence, and hyperlinks to literature sources. The searchable, downloadable database is available online at http://ptrc-ddr.cptac-data-view.org.

Glioblastoma (GBM) is the most aggressive nervous system cancer. Understanding its molecular pathogenesis is crucial to improving diagnosis and treatment. Integrated analysis of genomic, proteomic, post-translational modification and metabolomic data on 99 treatment-naive GBMs provides insights to GBM biology. We identify key phosphorylation events (e.g., phosphorylated PTPN11 and PLCG1) as potential switches mediating oncogenic pathway activation, as well as potential targets for EGFR-, TP53-, and RB1-altered tumors. Immune subtypes with distinct immune cell types are discovered using bulk omics methodologies, validated by snRNA-seq, and correlated with specific expression and histone acetylation patterns. Histone H2B acetylation in classical-like and immune-low GBM is driven largely by BRDs, CREBBP, and EP300. Integrated metabolomic and proteomic data identify specific lipid distributions across subtypes and distinct global metabolic changes in IDH-mutated tumors. This work highlights biological relationships that could contribute to stratification of GBM patients for more effective treatment. Wang et al. perform integrated proteogenomic analysis of adult glioblastoma (GBM), including metabolomics, lipidomics, and single nuclei RNA-Seq, revealing insights into the immune landscape of GBM, cell-specific nature of EMT signatures, histone acetylation in classical GBM, and the existence of signaling hubs which could provide therapeutic vulnerabilities.

Summary Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.

Chimeric antigen receptor (CAR)-modified T cell therapy is effective in treating lymphomas, leukemias, and multiple myeloma in which the tumor cells have high amounts of target antigen. However, achieving durable remission in patients and extending this therapy to patients with solid tumors will require CAR T cells that can eliminate tumors with a low density of target antigen. Although CARs were designed to mimic T cell receptor (TCR) signaling, TCRs are at least 100-fold more sensitive to antigen. To design a CAR with improved antigen sensitivity, we compared TCR and CAR signaling in primary human T cells in response to ROR1, a transmembrane neurotrophic tyrosine kinase that is associated with B-cell chronic lymphocytic leukemia. Phosphoproteomic analysis revealed that key T cell signaling proteins—such as CD3δ, CD3ε, and CD3γ, which comprise a T cell coreceptor, and the TCR adaptor protein LAT—were either not phosphorylated or were only weakly phosphorylated by CAR stimulation. Modifying the CAR sequence to better engage CD3ε and LAT (specifically, BB/ζ CARs containing CD3ε or GRB2 domains) resulted in enhanced T cell activation against tumor cells with a low density of antigen, in both culture and in vivo models of lymphoma, leukemia, and breast cancer. These CARs represent examples of alterations in receptor design that were guided by in-depth interrogation of T cell signaling.

Summary: A primary goal of the US National Cancer Institute's Ras initiative at the Frederick National Laboratory for Cancer Research is to develop methods to quantify RAS signaling to facilitate development of novel cancer therapeutics. We use targeted proteomics technologies to develop a community resource consisting of 256 validated multiple reaction monitoring (MRM)-based, multiplexed assays for quantifying protein expression and phosphorylation through the receptor tyrosine kinase, MAPK, and AKT signaling networks. As proof of concept, we quantify the response of melanoma (A375 and SK-MEL-2) and colorectal cancer (HCT-116 and HT-29) cell lines to BRAF inhibition by PLX4720. These assays replace over 60 western blots with quantitative mass-spectrometry-based assays of high molecular specificity and quantitative precision, showing the value of these methods for pharmacodynamic measurements and mechanism-of-action studies. Methods, fit-for-purpose validation, and results are publicly available as a resource for the community at assays.cancer.gov. Motivation: A lack of quantitative, multiplexable assays for phosphosignaling limits comprehensive investigation of aberrant signaling in cancer and evaluation of novel treatments. To alleviate this limitation, we sought to develop assays by using targeted mass spectrometry for quantifying protein expression and phosphorylation through the receptor tyrosine kinase, MAPK, and AKT signaling networks. The resulting assays provide a resource for replacing over 60 western blots in examining cancer signaling and tumor biology with high molecular specificity and quantitative rigor.

Amongst the pleotropic roles of transforming growth factor β (TGFβ) signaling in cancer, its impact on genomic stability is least understood. Inhibition of TGFβ signaling increases use of alternative end-joining (alt-EJ), an error-prone DNA repair process that typically functions as a ‘backup’ pathway if double strand break repair by homologous recombination or non-homologous end-joining is compromised. However, the consequences of this functional relationship on therapeutic vulnerability in human cancer remain unknown. Here, we show that TGFβ broadly controls the DNA damage response and that it suppresses alt-EJ genes that are associated with genomic instability. Mechanistically-based TGFβ and alt-EJ gene expression signatures were anti-correlated in glioblastoma, squamous cell lung cancer, and serous ovarian cancer. Consistent with error-prone repair, more of the genome was altered in tumors classified as low TGFβ and high alt-EJ, and the corresponding patients had better outcomes. Pan-cancer analysis of solid neoplasms revealed that alt-EJ genes are coordinately expressed and anti-correlated with TGFβ competency in 16 of 17 cancer types tested. Moreover, regardless of cancer type, tumors classified as low TGFβ and high alt-EJ were characterized by an insertion-deletion mutation signature containing short microhomologies and were more sensitive to genotoxic therapy. Collectively, experimental studies revealed that loss or inhibition of TGFβ signaling compromises the DNA damage response, resulting in ineffective repair by alt-EJ. Translation of this mechanistic relationship into gene expression signatures identified a robust anti-correlation that predicts response to genotoxic therapies, thereby expanding the potential therapeutic scope of TGFβ biology. ONE SENTENCE SUMMARY: The impact of TGFβ signaling on DNA repair competency is observed in pan-cancer analysis of survival after treatments that cause DNA damage.

Lung squamous cell carcinoma (LSCC) remains a leading cause of cancer death with few therapeutic options. We characterized the proteogenomic landscape of LSCC, providing a deeper exposition of LSCC biology with potential therapeutic implications. We identify NSD3 as an alternative driver in FGFR1-amplified tumors and low-p63 tumors overexpressing the therapeutic target survivin. SOX2 is considered undruggable, but our analyses provide rationale for exploring chromatin modifiers such as LSD1 and EZH2 to target SOX2-overexpressing tumors. Our data support complex regulation of metabolic pathways by crosstalk between post-translational modifications including ubiquitylation. Numerous immune-related proteogenomic observations suggest directions for further investigation. Proteogenomic dissection of CDKN2A mutations argue for more nuanced assessment of RB1 protein expression and phosphorylation before declaring CDK4/6 inhibition unsuccessful. Finally, triangulation between LSCC, LUAD, and HNSCC identified both unique and common therapeutic vulnerabilities. These observations and proteogenomics data resources may guide research into the biology and treatment of LSCC.

SUMMARY: Many gene products exhibit great structural heterogeneity because of an array of modifications. These modifications are not directly encoded in the genomic template but often affect the functionality of proteins. Protein glycosylation plays a vital role in proper protein functions. However, the analysis of glycoproteins has been challenging compared with other protein modifications, such as phosphorylation. Here, we perform an integrated proteomic and glycoproteomic analysis of 83 prospectively collected high-grade serous ovarian carcinoma (HGSC) and 23 non-tumor tissues. Integration of the expression data from global proteomics and glycoproteomics reveals tumor-specific glycosylation, uncovers different glycosylation associated with three tumor clusters, and identifies glycosylation enzymes that were correlated with the altered glycosylation. In addition to providing a valuable resource, these results provide insights into the potential roles of glycosylation in the pathogenesis of HGSC, with the possibility of distinguishing pathological outcomes of ovarian tumors from non-tumors, as well as classifying tumor clusters. IN BRIEF: Hu et al. provide an integrated proteomic and glycoproteomic characterization of high-grade serous ovarian carcinomas and relevant non-tumor tissues, which reveals tumor-specific glycosylation, uncovers different glycosylation associated with three tumor clusters, and identifies glycosylation enzymes correlated with glycosylation alterations.

AML blasts harbor multiple genomic, epigenomic, and transcriptomic abnormalities. Proteins are responsible for much of the functional biology derived from these transforming events, yet few studies have examined the global proteome in specimens from AML patients. To gain insight into the biology and prognostic biomarkers for AML, we examined the genome, transcriptome and proteome in highly enriched less differentiated, viable leukemic blasts (VLBs) from previously untreated patients with NPM1 mutated (NPM1+) AML. We focused on NPM1+ AML because 1) NPM1 mutations are the most common genomic abnormality used for risk stratifying AML patients; 2) clinical outcomes for NPM1+ patients vary substantially; and 3) restricting studies to VLBs from patients with NPM1+ AMLreduces the molecular diversity and confounding interactions that may impede identification of biological and clinically relevant biomarkers. Cryopreserved specimens from patients with NPM1+ AML were obtained from the SWOG Leukemia and Fred Hutch/University of Washington Hematopoietic Disease Repositories (N=178). All patients were treated with dose intensive induction and consolidation with curative intent. VLBs were isolated from specimens using fluorescence-activated cell sorting (FACS). Fragment analysis was used to identify FLT3-ITDs, while other genomic mutations were identified using targeted next generation sequencing (NGS). RNA sequencing (RNAseq) was used to quantify transcript expression, while protein expression was quantified using tandem mass tag labelling followed by liquid chromatograph with tandem mass spectrometry (TMT-LC-MS/MS). Prognostic significance of biomarkers was examined by univariate and multivariate analyses, with the later adjusting for both age and ELN2017 risk. Adequate analyte from VLBs were available for RNAseq and TMT-LC-MS/MS studies in 131 and 71 patients, respectively. Proteomic profiling identified 6712 expressed proteins. Multivariable analyses adjusting for age and ELN2017 risk identified 211, 218, and 313 proteins were significantly associated with CR, EFS, and OS, respectively, of which 116 and 174 had a HR ≥ 2 or ≤ 0.5 for EFS and OS (Fig 1A). Analyses showed an overall modest correlation between RNA and protein expression for the 6297 genes present in both RNA and protein datasets (Fig 1B, R =0.27). A total of 163 of the 174 proteomic candidates for OS had RNAseq data, but RNA expression was not significantly correlated with OS for most of these genes (Fig 1C). Similarly, the expression correlation between RNA and protein was not improved by restricting the analyses to these 163 genes (Fig 1D, R =0.28). We also compared protein expression between the NPM1+ VLBs and CD34 progenitors from healthy donors (NLCD34=5), which identified 747 proteins with significant expression differences between the two cell populations (FDR ≤ 0.1). Seventy-three of the 747 proteins displayed > 3-fold increased expression in NPM1+ VLBs, some of which activate targetable pathways (HOMER->WNT/CTNNB1) and/or amenable to adoptive immunotherapies (e.g., CT45). Additional analyses identified 401 proteins with significantly increased expression in VLBs harboring a high FLT3-ITD allelic ratio (NPM1+/FLT3-ITD-H), a less favorable population of patients. In these less favorable patients, many of the same proteins remained overexpressed (e.g., CT45 with 7.85-fold increased expression, FDR=0.009), but other targetable proteins also emerged. For example, PKCD had a 3.41-fold increased expression (FDR=0.001) in the NPM1+/FLT3-ITD-H VLBs, and targetable inhibitors against this protein (e.g., Parsaclisib) are already in clinical trials for other cancers. This study examines for the first time the global proteome in a large number of VLBs from patients with AML. As with recent publications examining other cancers, the overall expression correlation between RNA and protein was modest, at best, and most of the informative prognostic proteins for OS were not significant in the transcriptome. In addition, the results show the potential to identify novel proteomic targets in subpopulations of AML patients, which may not be otherwise discovered using other means. Thus, the results demonstrate the need to include proteomic profiling in future multi-omics studies seeking to discover novel prognostic biomarkers and therapeutic targets. Figure 1 Figure 1. Disclosures Erba: AbbVie Inc; Agios Pharmaceuticals Inc; Bristol Myers Squibb; Celgene, a Bristol Myers Squibb company; Incyte Corporation; Jazz Pharmaceuticals Inc; Novartis: Speakers Bureau; AbbVie Inc: Other: Independent review committee; AbbVie Inc; Agios Pharmaceuticals Inc; ALX Oncology; Amgen Inc; Daiichi Sankyo Inc; FORMA Therapeutics; Forty Seven Inc; Gilead Sciences Inc; GlycoMimetics Inc; ImmunoGen Inc; Jazz Pharmaceuticals Inc; MacroGenics Inc; Novartis; PTC Therapeutics: Research Funding; AbbVie Inc; Agios Pharmaceuticals Inc; Astellas; Bristol Myers Squibb; Celgene, a Bristol Myers Squibb company; Daiichi Sankyo Inc; Genentech, a member of the Roche Group; GlycoMimetics Inc; Incyte Corporation; Jazz Pharmaceuticals Inc; Kura Oncology; Nov: Other: Advisory Committee. Moseley: BioSight Ltd: Consultancy. Radich: Novartis: Membership on an entity's Board of Directors or advisory committees; Genentech: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees.

Acknowledgements: This work was funded by the following NIH/NCI/NCTN grant awards: RO1CA190661, R01CA160872, U10CA180888, U10CA180819, U24CA196175. The authors wish to gratefully acknowledge the importantcontributions of the late Dr. Stephen H. Petersdorf to SWOG and to the study S0106. The authors would like to acknowledge that a portion of the specimens were obtained from the Fred Hutch/University of Washington Hematopoietic Disorder Repository. AML is a molecularly heterogenous disease that harbors multiple genomic, epigenomic, and transcriptomic abnormalities. Despite the use of newer therapeutic agents and identification of multiple prognostic markers, most patients with AML still relapse or succumb to their disease. Understanding biological factors that determine relapse is of major clinical interest in AML. Proteins are responsible for much of the functional biology of the cells. However, few studies have examined the global proteome in AML, and, to our knowledge, studies have not previously examined the proteome in highly enriched undifferentiated AML blasts. Therefore, we have developed an integrated approach utilizing mass spectrometry-based proteomics and leveraging next generation RNA sequencing (RNAseq) to identify novel protein biomarkers associated with clinical outcome in a homogeneous population of undifferentiated viable leukemic blasts (uVLBs) from AML patients. Cryopreserved specimens from previously untreated de novo AML patients (n=27) were obtained from the SWOG Leukemia Repository. Patients were treated with dose intensive induction and consolidation as part of SWOG-9031, SWOG-9333, S0106, and S0112 studies. uVLBs were isolated from specimens using fluorescence-activated cell sorting (FACS). Targeted genome sequencing examined for genomic mutations in uVLBs, while global RNA sequencing (RNAseq) and tandem mass tag labelling followed by liquid chromatograph with tandem mass spectrometry (TMT-LC-MS/MS) were used to quantify transcript and protein expression, respectively. Analyses identified 6761 unique proteins, with 238 and 460 proteins significantly associated with complete response (CR) and overall survival (OS), respectively. There was modest overlap between the prognostically significant transcript and protein biomarkers (Figure 1). We also were able to identify and quantify aberrant proteins arising from genomic mutations . Examples of the "neoproteins" detected included proteins harboring NPM1 mutations (Figure 2a) and those harboring frameshift insertions/deletions in the terminal region of RUNX1 (Figure 2b). For validation of prognostic associations, we examined the proteome in an independent population of de novo AML patients (N=27) treated at the Fred Hutch and University of Washington. As with the SWOG patients, pre-treatment specimens were obtained from patients receiving intensive induction and consolidation with curative intent; however, OS data was not available for many of these patients. As such, the validation studies focused on CR. Patients were randomized by CR response into 9 pools (CR=6 and no CR=3 pools), and specimens were sorted for uVLBs. TMT-based LC-MS/MS quantified protein expression across pools, and analyses examined the prognostic significance of the 238 proteins from the SWOG analyses associated with CR. Thirteen of the most promising candidates were significantly associated with CR prognosis (Table 1), many of which are associated with cancer biology. Together, these studies show the feasibility and biological importance of examining the proteome in uVLBs. Studies examining for biomarkers in the proteome may be a powerful tool to uncover novel prognostic biomarkers that would otherwise not be identified by examining the genome or transcriptome. Furthermore, the multi-omics approach can be used to confirm the translation of potential neoantigens into actionable protein targets, which may lead to more cost-effective mechanisms for the development of innovative adoptive immunotherapies. Figure 1 Figure 1. Disclosures Othus: Biosight: Consultancy; Merck: Consultancy; Celgene: Other: Data safety monitoring board; Glycomimetics: Other: Data safety monitoring board; Daiichi Sankyo: Consultancy. Moseley: BioSight Ltd: Consultancy. Erba: AbbVie Inc; Agios Pharmaceuticals Inc; Bristol Myers Squibb; Celgene, a Bristol Myers Squibb company; Incyte Corporation; Jazz Pharmaceuticals Inc; Novartis: Speakers Bureau; AbbVie Inc; Agios Pharmaceuticals Inc; Astellas; Bristol Myers Squibb; Celgene, a Bristol Myers Squibb company; Daiichi Sankyo Inc; Genentech, a member of the Roche Group; GlycoMimetics Inc; Incyte Corporation; Jazz Pharmaceuticals Inc; Kura Oncology; Nov: Other: Advisory Committee; AbbVie Inc: Other: Independent review committee; AbbVie Inc; Agios Pharmaceuticals Inc; ALX Oncology; Amgen Inc; Daiichi Sankyo Inc; FORMA Therapeutics; Forty Seven Inc; Gilead Sciences Inc; GlycoMimetics Inc; ImmunoGen Inc; Jazz Pharmaceuticals Inc; MacroGenics Inc; Novartis; PTC Therapeutics: Research Funding. Radich: Amgen: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Genentech: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees.

RAS genes are frequently mutated in cancer and have for decades eluded effective therapeutic attack. The National Cancer Institute’s RAS Initiative has a focus on understanding pathways and discovering therapies for RAS-driven cancers. Part of these efforts is the generation of novel reagents to enable the quantification of RAS network proteins. Here we present a dataset describing the development, validation (following consensus principles developed by the broader research community), and distribution of 104 monoclonal antibodies (mAbs) enabling detection of 27 phosphopeptides and 69 unmodified peptides from 20 proteins in the RAS network. The dataset characterizes the utility of the antibodies in a variety of applications, including Western blotting, immunoprecipitation, protein array, immunohistochemistry, and targeted mass spectrometry. All antibodies and characterization data are publicly available through the CPTAC Antibody Portal, Panorama Public Repository, and/or PRIDE databases. These reagents will aid researchers in discerning pathways and measuring expression changes in the RAS signaling network., Design Type(s)disease analysis objectiveMeasurement Type(s)immunocapture • immunoprecipitation • antibody • in situ immunoassay • ex situ immunoassayTechnology Type(s)western blot analysis • liquid chromatography-tandem mass spectrometry • immuno-MRM • immunohistochemistry • RPPA protein profiling assayFactor Type(s)Sample Characteristic(s)Homo sapiens • MCF-10A cell • BxPC-3 cell • NCI cell • breast • ovary • colon • lung • A549 cell • NCI-H1792 cell • HeLa cell • HEK293 Machine-accessible metadata file describing the reported data (ISA-Tab format)

Recent development in high throughput proteomics and genomics profiling enable one to study regulations of genome alterations on protein activities in a systematic manner. In this article, we propose a new statistical method, ProMAP, to systematically characterize the regulatory relationships between proteins and DNA copy number alterations (CNA) in breast and ovarian tumors based on proteogenomic data from the CPTAC-TCGA studies. Because of the dynamic nature of mass spectrometry instruments, proteomics data from labeled mass spectrometry experiments usually have non-ignorable batch effects. Moreover, mass spectrometry based proteomic data often possesses high percentages of missing values and non-ignorable missing-data patterns. Thus, we use a linear mixed effects model to account for the batch structure and explicitly incorporate the abundance-dependent-missing-data mechanism of proteomic data in ProMAP. In addition, we employ a multivariate regression framework to characterize the multiple-to-multiple regulatory relationships between CNA and proteins. Further, we use proper statistical regularization to facilitate the detection of master genetic regulators, which affect the activities of many proteins and often play important roles in genetic regulatory networks. Improved performance of ProMAP over existing methods were illustrated through extensive simulation studies and real data examples. Applying ProMAP to the CPTAC-TCGA breast and ovarian cancer data sets, we identified many genome regions, including a few novel ones, whose CNA were associated with protein and or phosphoprotein abundances. For example, in breast tumors, a small region in 8p11.21 was recognized as the second biggest hub in the CNA-phosphoprotein regulatory map, and further investigation of the regulatory targets suggests the potential role of 8p11.21 CNA in perturbing oxygen binding and transport activities in tumor cells. This and other findings from our analyses help to characterize the impacts of CNAs on protein activity landscapes and cast light on the genetic regulation mechanisms underlying these tumors.

Genomic characterization has allowed for the differentiation of different tumor types based upon the abundance of gene transcripts. However, owing to the many layers of regulation between transcript and the post-translationally modified protein, the functional moiety of the cell, it has been challenging to extrapolate biology from these transcriptional differences. We hypothesized that a comparative analysis of the proteome and phosphoproteome across 7 childhood brain tumors would yield a deeper understanding of the differences in their functional biology. We performed tandem mass tag labeling and triple mass spectrometry of 226 fresh frozen tumor samples collected in a single institution representing the histologic diagnoses of: high grade astrocytoma (27), low grade astrocytoma (97), ganglioglioma (20), ependymoma (32), medulloblastoma (22), atypical teratoid rhabdoid tumor (12), and craniopharyngioma (16). Among these samples were 22 pairs from pre/post recurrence. Across this sample set, we quantified 9155 proteins and 13632 phospho sites. After data preprocessing including normalization, batch correction and missing value imputation, we performed consensus clustering and showed that protein profiles can effectively distinguish major histology types. Additional regression based differential analyses revealed groups of proteins and pathways showing distinct activity patterns across different histologic types. Further leveraging the WGS data, we characterized the functional impact of mutation and fusion features of the glial tumors. Specifically, focusing on the largest cohort, low grade glioma, we analyzed the proteomic ramifications of BRAF status: V600E, BRAF-fusion and wild type. Moreover, from the primary and recurrent tumor pairs, we discovered the upregulation of proteins associated with immune evasion in more advanced LGG tumors. The incorporation of the proteomic dimension into large scale efforts at tumor characterization adds functional insight that can help drive translational efforts.

We present a proteogenomic study of 108 human papilloma virus (HPV)-negative head and neck squamous cell carcinomas (HNSCCs). Proteomic analysis systematically catalogs HNSCC-associated proteins and phosphosites, prioritizes copy number drivers, and highlights an oncogenic role for RNA processing genes. Proteomic investigation of mutual exclusivity between FAT1 truncating mutations and 11q13.3 amplifications reveals dysregulated actin dynamics as a common functional consequence. Phosphoproteomics characterizes two modes of EGFR activation, suggesting a new strategy to stratify HNSCCs based on EGFR ligand abundance for effective treatment with inhibitory EGFR monoclonal antibodies. Widespread deletion of immune modulatory genes accounts for low immune infiltration in immune-cold tumors, whereas concordant upregulation of multiple immune checkpoint proteins may underlie resistance to anti-programmed cell death protein 1 monotherapy in immune-hot tumors. Multi-omic analysis identifies three molecular subtypes with high potential for treatment with CDK inhibitors, anti-EGFR antibody therapy, and immunotherapy, respectively. Altogether, proteogenomics provides a systematic framework to inform HNSCC biology and treatment.

Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies.

Wilson's Disease (WD), a copper transport disorder caused by a genetic defect in the ATP7B gene, has been a long time strong candidate for newborn screening (NBS), since early interventions can give better results by preventing irreversible neurological disability or liver cirrhosis. Several previous pilot studies measuring ceruloplasmin (CP) in infants or children showed that this marker alone was insufficient to meet the universal screening for WD. WD results from mutations that cause absent or markedly diminished levels of ATP7B. Therefore, ATP7B could serve as a marker for the screening of WD, if the protein can be detected from dried blood spots (DBS). This study demonstrates that the immuno-SRM platform can quantify ATP7B in DBS in the picomolar range, and that the assay readily distinguishes affected cases from normal controls (p < 0.0001). The assay precision was

Immunoaffinity enrichment of peptides coupled to multiple reaction monitoring-mass spectrometry (immuno-MRM) enables highly specific, sensitive, and precise quantification of peptides and post-translational modifications. Major obstacles to developing a large number of immuno-MRM assays are the poor availability of monoclonal antibodies (mAbs) validated for immunoaffinity enrichment of peptides and the cost and lead time of developing the antibodies de novo. Although many thousands of mAbs are commercially offered, few have been tested for application to immunoaffinity enrichment of peptides. In this study we tested the success rate of using commercially available mAbs for peptide immuno-MRM assays. We selected 105 commercial mAbs (76 targeting non-modified “pan” epitopes, 29 targeting phosphorylation) to proteins associated with the DNA damage response network. We found that 8 of the 76 pan (11%) and 5 of the 29 phospho-specific mAbs (17%) captured tryptic peptides (detected by LC-MS/MS) of their protein targets from human cell lysates. Seven of these mAbs were successfully used to configure and analytically characterize immuno-MRM assays. By applying selection criteria upfront, the results indicate that a screening success rate of up to 24% is possible, establishing the feasibility of screening a large number of catalog antibodies to provide readily-available assay reagents.

In response to replication stress, a phospho-signaling cascade is activated and required for coordination of DNA repair and replication of damaged templates (intra-S-phase checkpoint) . How phospho-signaling coordinates the DNA replication stress response is largely unknown. We employed state-of-the-art liquid chromatography tandem-mass spectrometry (LC-MS/MS) approaches to generate high-coverage and quantitative proteomic and phospho-proteomic profiles during replication stress in yeast, induced by continuous exposure to the DNA alkylating agent methyl methanesulfonate (MMS) . We identified 32,057 unique peptides representing the products of 4296 genes and 22,061 unique phosphopeptides representing the products of 3183 genes. A total of 542 phosphopeptides (mapping to 339 genes) demonstrated an abundance change of greater than or equal to twofold in response to MMS. The screen enabled detection of nearly all of the proteins known to be involved in the DNA damage response, as well as many novel MMS-induced phosphorylations. We assessed the functional importance of a subset of key phosphosites by engineering a panel of phosphosite mutants in which an amino acid substitution prevents phosphorylation. In total, we successfully mutated 15 MMS-responsive phosphorylation sites in seven representative genes including APN1 (base excision repair); CTF4 and TOF1 (checkpoint and sister-chromatid cohesion); MPH1 (resolution of homologous recombination intermediates); RAD50 and XRS2 (MRX complex); and RAD18 (PRR). All of these phosphorylation site mutants exhibited MMS sensitivity, indicating an important role in protecting cells from DNA damage. In particular, we identified MMS-induced phosphorylation sites on Xrs2 that are required for MMS resistance in the absence of the MRX activator, Sae2, and that affect telomere maintenance.

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.

We report a comprehensive proteogenomics analysis, including whole-genome sequencing, RNA sequencing, and proteomics and phosphoproteomics profiling, of 218 tumors across 7 histological types of childhood brain cancer: low-grade glioma (n = 93), ependymoma (32), high-grade glioma (25), medulloblastoma (22), ganglioglioma (18), craniopharyngioma (16), and atypical teratoid rhabdoid tumor (12). Proteomics data identify common biological themes that span histological boundaries, suggesting that treatments used for one histological type may be applied effectively to other tumors sharing similar proteomics features. Immune landscape characterization reveals diverse tumor microenvironments across and within diagnoses. Proteomics data further reveal functional effects of somatic mutations and copy number variations (CNVs) not evident in transcriptomics data. Kinase-substrate association and co-expression network analysis identify important biological mechanisms of tumorigenesis. This is the first large-scale proteogenomics analysis across traditional histological boundaries to uncover foundational pediatric brain tumor biology and inform rational treatment selection.

SUMMARY The integration of mass spectrometry-based proteomics with next-generation DNA and RNA sequencing profiles tumors more comprehensively. Here this “proteogenomics” approach was applied to 122 treatment-naive primary breast cancers accrued to preserve post-translational modifications, including protein phosphorylation and acetylation. Proteogenomics challenged standard breast cancer diagnoses, provided detailed analysis of the ERBB2 amplicon, defined tumor subsets that could benefit from immune checkpoint therapy, and allowed more accurate assessment of Rb status for prediction of CDK4/6 inhibitor responsiveness. Phosphoproteomics profiles uncovered novel associations between tumor suppressor loss and targetable kinases.Acetylproteome analysis highlighted acetylation on key nuclear proteins involved in the DNA damage response and revealed cross-talk between cytoplasmic and mitochondrial acetylation and metabolism. Our results underscore the potential of proteogenomics for clinical investigation of breast cancer through more accurate annotation of targetable pathways and biological features of this remarkably heterogeneous malignancy., In Brief Breast cancer is a highly heterogeneous disease with variable outcomes and subtype-driven treatment approaches, making precision medicine a considerable challenge. Proteogenomic analyses of 122 primary breast cancers provide insights into clinically relevant biology, including cell cycle dysregulation, tumor immunogenicity, aberrant metabolism, and heterogeneity in therapeutic target expression., Graphical Abstract

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.

We undertook a comprehensive proteogenomic characterization of 95 prospectively collected endometrial carcinomas, comprising 83 endometrioid and 12 serous tumors. This analysis revealed possible new consequences of perturbations to the p53 and Wnt/β-catenin pathways, identified a potential role for circRNAs in the epithelial-mesenchymal transition, and provided new information about proteomic markers of clinical and genomic tumor subgroups, including relationships to known druggable pathways. An extensive genome-wide acetylation survey yielded insights into regulatory mechanisms linking Wnt signaling and histone acetylation. We also characterized aspects of the tumor immune landscape, including immunogenic alterations, neoantigens, common cancer/testis antigens, and the immune microenvironment, all of which can inform immunotherapy decisions. Collectively, our multi-omic analyses provide a valuable resource for researchers and clinicians, identify new molecular associations of potential mechanistic significance in the development of endometrial cancers, and suggest novel approaches for identifying potential therapeutic targets.

Background: Primary immunodeficiency disorders (PIDD) comprise a group of life-threatening congenital diseases characterized by absent or impaired immune responses. Despite the fact that effective, curative treatments are available with optimal clinical outcomes when diagnosed early, newborn screening does not exist for the majority of these diseases due to the lack of detectable, specific biomarkers or validated methods for population-based screening. Peptide immunoaffinity enrichment coupled with selected reaction monitoring mass spectrometry (immuno-SRM) is a sensitive proteomic assay, involving antibody-mediated peptide capture, that allows for concurrent quantification of multiple analytes. This assay has promise for use in potential newborn screening of PIDDs that lead to diminished or absent target proteins in the majority of cases. Objective: To determine and evaluate if a multiplex assay based on immuno-SRM is able to reliably and precisely distinguish affected patients with X-linked agammaglobulinemia (XLA), Wiskott-Aldrich Syndrome (WAS), and CD3ϵ-associated severe combined immunodeficiency (SCID) from one another and from unaffected normal control dried blood spot (DBS) samples. Methods: We performed a blinded, multiplexed analysis of proteolytically-generated peptides from WASp, BTK, and CD3ϵ (for WAS, XLA, and SCID, respectively) in DBS samples from 42 PIDD patients, 40 normal adult controls, and 62 normal newborns. The peptide ATPase copper transporting protein (ATP7B) 1056 was simultaneously monitored for quality assurance purposes. Results: The immuno-SRM assays reliably quantified the target peptides in DBS and accurately distinguished affected patients from normal controls. Analysis of signature peptides found statistically significant reduction or absence of peptide levels in affected patients compared to control groups in each case (WASp and BTK: p = 0.0001, SCID: p = 0.05). Intra and inter-assay precision ranged from 11 to 22% and 11 to 43% respectively; linearity (1.39–2000 fmol peptide), and stability (≤ 0.09% difference in 72 h) showed high precision for the multiplexed assay. Inter-laboratory assay comparison showed high concordance for measured peptide concentrations, with R2 linearity ≥ 0.97 for the WASp 274, CD3ϵ 197, BTK 407, and ATP7B 1056 peptides. Conclusion: Immuno-SRM-based quantification of proteotypic peptides from WASp, BTK, and CD3ϵ in DBS distinguishes relevant PIDD cases from one another and from controls, raising the possibility of employing this approach for large-scale multiplexed newborn screening of selective PIDDs.

A lack of analytically robust and multiplexed assays has hampered studies of the large, branched phosphosignaling network responsive to DNA damage. To address this need, we developed and fully analytically characterized a 62-plex assay quantifying protein expression and post-translational modification (phosphorylation and ubiquitination) after induction of DNA damage. The linear range was over 3 orders of magnitude, the median inter-assay variability was 10% CV and the vast majority (∼85%) of assays were stable after extended storage. The multiplexed assay was applied in proof-of-principle studies to quantify signaling after exposure to genotoxic stress (ionizing radiation and 4-nitroquinoline 1-oxide) in immortalized cell lines and primary human cells. The effects of genomic variants and pharmacologic kinase inhibition (ATM/ATR) were profiled using the assay. This study demonstrates the utility of a quantitative multiplexed assay for studying cellular signaling dynamics, and the potential application to studies on inter-individual variation in the radiation response.

The Fanconi anemia pathway is an important coordinator of DNA repair pathways and is particularly relevant to repair of DNA inter-strand crosslinks. Central to the pathway is monoubiquitination of FANCD2, requiring the function of multiple proteins in an upstream Fanconi core complex. We present development and analytical characterization of a novel assay for quantification of unmodified and monoubiquitinated FANCD2 proteoforms, based on peptide immunoaffinity enrichment and targeted multiple reaction monitoring mass spectrometry (immuno-MRM). The immuno-MRM assay is analytically characterized using fit-for-purpose method validation. The assay linear range is >3 orders of magnitude with total repeatability

Immunoaffinity enrichment of peptides coupled to targeted, multiple reaction monitoring mass spectrometry (immuno-MRM) enables precise quantification of peptides. Affinity-purified polyclonal antibodies are routinely used as affinity reagents in immuno-MRM assays, but they are not renewable, limiting the number of experiments that can be performed. In this technical note, we describe a workflow to regenerate anti-peptide polyclonal antibodies coupled to magnetic beads for enrichments in multiplex immuno-MRM assays. A multiplexed panel of 44 antibodies (targeting 60 peptides) is used to show that peptide analytes can be effectively stripped off of antibodies using acid washing without compromising assay performance. The performance of the multiplexed panel (determined by correlation, agreement, and precision of reused assays) is reproducible (R(2) between 0.81 and 0.99) and consistent (median CVs 8-15%) for at least 10 times of washing and reuse. Application of this workflow to immuno-MRM studies greatly reduces per sample assay cost and increases the number of samples that can be interrogated with a limited supply of polyclonal antibody reagent. This allows more characterization for promising and desirable targets prior to committing funds and efforts to conversion to a renewable monoclonal antibody.

Antibodies are used in multiple cell biology applications, but there are no standardized methods to assess antibody quality-an absence that risks data integrity and reproducibility. We describe a mass spectrometry-based standard operating procedure for scoring immunoprecipitation antibody quality. We quantified the abundance of all the proteins in immunoprecipitates of 1,124 new recombinant antibodies for 152 chromatin-related human proteins by comparing normalized spectral abundance factors from the target antigen with those of all other proteins. We validated the performance of the standard operating procedure in blinded studies in five independent laboratories. Antibodies for which the target antigen or a member of its known protein complex was the most abundant protein were classified as 'IP gold standard'. This method generates quantitative outputs that can be stored and archived in public databases, and it represents a step toward a platform for community benchmarking of antibody quality.

SUMMARY To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology., Graphical Abstract, In Brief Comprehensive proteogenomic characterization in 103 treatment-naive clear cell renal cell carcinoma patient samples highlights tumor-specific alterations at the proteomic level that are unrevealed by transcriptomic profiling and proposes a revised subtyping scheme based on integrated omics analysis.

Extensive genomic characterization of human cancers presents the problem of inference from genomic abnormalities to cancer phenotypes. To address this problem, we analysed proteomes of colon and rectal tumours characterized previously by The Cancer Genome Atlas (TCGA) and perform integrated proteogenomic analyses. Somatic variants displayed reduced protein abundance compared to germline variants. Messenger RNA transcript abundance did not reliably predict protein abundance differences between tumours. Proteomics identified five proteomic subtypes in the TCGA cohort, two of which overlapped with the TCGA 'microsatellite instability/CpG island methylation phenotype' transcriptomic subtype, but had distinct mutation, methylation and protein expression patterns associated with different clinical outcomes. Although copy number alterations showed strong cis- and trans-effects on mRNA abundance, relatively few of these extend to the protein level. Thus, proteomics data enabled prioritization of candidate driver genes. The chromosome 20q amplicon was associated with the largest global changes at both mRNA and protein levels; proteomics data highlighted potential 20q candidates, including HNF4A (hepatocyte nuclear factor 4, alpha), TOMM34 (translocase of outer mitochondrial membrane 34) and SRC (SRC proto-oncogene, non-receptor tyrosine kinase). Integrated proteogenomic analysis provides functional context to interpret genomic abnormalities and affords a new paradigm for understanding cancer biology.

Adoption of targeted mass spectrometry (MS) approaches such as multiple reaction monitoring (MRM) to study biological and biomedical questions is well underway in the proteomics community. Successful application depends on the ability to generate reliable assays that uniquely and confidently identify target peptides in a sample. Unfortunately, there is a wide range of criteria being applied to say that an assay has been successfully developed. There is no consensus on what criteria are acceptable and little understanding of the impact of variable criteria on the quality of the results generated. Publications describing targeted MS assays for peptides frequently do not contain sufficient information for readers to establish confidence that the tests work as intended or to be able to apply the tests described in their own labs. Guidance must be developed so that targeted MS assays with established performance can be made widely distributed and applied by many labs worldwide. To begin to address the problems and their solutions, a workshop was held at the National Institutes of Health with representatives from the multiple communities developing and employing targeted MS assays. Participants discussed the analytical goals of their experiments and the experimental evidence needed to establish that the assays they develop work as intended and are achieving the required levels of performance. Using this “fit-for-purpose” approach, the group defined three tiers of assays distinguished by their performance and extent of analytical characterization. Computational and statistical tools useful for the analysis of targeted MS results were described. Participants also detailed the information that authors need to provide in their manuscripts to enable reviewers and readers to clearly understand what procedures were performed and to evaluate the reliability of the peptide or protein quantification measurements reported. This paper presents a summary of the meeting and recommendations.

High-affinity antibodies binding to linear peptides in solution are a prerequisite for performing immuno-MRM, an emerging technology for protein quantitation with high precision and specificity using peptide immunoaffinity enrichment coupled to stable isotope dilution and targeted mass spectrometry. Recombinant antibodies can be generated from appropriate libraries in high-throughput in an automated laboratory and thus may offer advantages over conventional monoclonal antibodies. However, recombinant antibodies are typically obtained as fragments (Fab or scFv) expressed from E. coli, and it is not known whether these antibody formats are compatible with the established protocols and whether the affinities necessary for immunocapture of small linear peptides can be achieved with this technology. Hence, we performed a feasibility study to ask: (a) whether it is feasible to isolate high-affinity Fabs to small linear antigens and (b) whether it is feasible to incorporate antibody fragments into robust, quantitative immuno-MRM assays. We describe successful isolation of high-affinity Fab fragments against short (tryptic) peptides from a human combinatorial Fab library. We analytically characterize three immuno-MRM assays using recombinant Fabs, full-length IgGs constructed from these Fabs, or traditional monoclonals. We show that the antibody fragments show similar performance compared with traditional mouse- or rabbit-derived monoclonal antibodies. The data establish feasibility of isolating and incorporating high-affinity Fabs into peptide immuno-MRM assays.

We performed the first proteogenomic study on a prospectively collected colon cancer cohort. Comparative proteomic and phosphoproteomic analysis of paired tumor and normal adjacent tissues produced a catalog of colon cancer-associated proteins and phosphosites, including known and putative new biomarkers, drug targets, and cancer/testis antigens. Proteogenomic integration not only prioritized genomically inferred targets, such as copy-number drivers and mutation-derived neoantigens, but also yielded novel findings. Phosphoproteomics data associated Rb phosphorylation with increased proliferation and decreased apoptosis in colon cancer, which explains why this classical tumor suppressor is amplified in colon tumors and suggests a rationale for targeting Rb phosphorylation in colon cancer. Proteomics identified an association between decreased CD8 T cell infiltration and increased glycolysis in microsatellite instability-high (MSI-H) tumors, suggesting glycolysis as a potential target to overcome the resistance of MSI-H tumors to immune checkpoint blockade. Proteogenomics presents new avenues for biological discoveries and therapeutic development.

Multiple reaction monitoring (MRM) mass spectrometry has been successfully applied to monitor targeted proteins in biological specimens, raising the possibility that assays could be configured to measure all human proteins. We report the results of a pilot study designed to test the feasibility of a large-scale, international effort for MRM assay generation. We have configured, validated across three laboratories and made publicly available as a resource to the community 645 novel MRM assays representing 319 proteins expressed in human breast cancer. Assays were multiplexed in groups of >150 peptides and deployed to quantify endogenous analytes in a panel of breast cancer-related cell lines. The median assay precision was 5.4%, with high interlaboratory correlation (R(2) > 0.96). Peptide measurements in breast cancer cell lines were able to discriminate among molecular subtypes and identify genome-driven changes in the cancer proteome. These results establish the feasibility of a large-scale effort to develop an MRM assay resource.

Tel1 is the budding yeast ortholog of the mammalian tumor suppressor and DNA damage response (DDR) kinase ATM. However, tel1-Δ cells, unlike ATM-deficient cells, do not exhibit sensitivity to DNA-damaging agents, but do display shortened (but stably maintained) telomere lengths. Neither the extent to which Tel1p functions in the DDR nor the mechanism by which Tel1 contributes to telomere metabolism is well understood. To address the first question, we present the results from a comprehensive genome-wide screen for genetic interactions with tel1-Δ that cause sensitivity to methyl methanesulfonate (MMS) and/or ionizing radiation, along with follow-up characterizations of the 13 interactions yielded by this screen. Surprisingly, many of the tel1-Δ interactions that confer DNA damage sensitivity also exacerbate the short telomere phenotype, suggesting a connection between these two phenomena. Restoration of normal telomere length in the tel1-Δ xxx-Δ mutants results in only minor suppression of the DNA damage sensitivity, demonstrating that the sensitivity of these mutants must also involve mechanisms independent of telomere length. In support of a model for increased replication stress in the tel1-Δ xxx-Δ mutants, we show that depletion of dNTP pools through pretreatment with hydroxyurea renders tel1-Δ cells (but not wild type) MMS-sensitive, demonstrating that, under certain conditions, Tel1p does indeed play a critical role in the DDR.

Cells employ error-free or error-prone postreplication repair (PRR) processes to tolerate DNA damage. Here, we present a genome-wide screen for sensitivity to 0.001% methyl methanesulfonate (MMS). This relatively low dose is of particular interest because wild-type cells exhibit no discernible phenotypes in response to treatment, yet PRR mutants are unique among repair mutants in their exquisite sensitivity to 0.001% MMS; thus, low-dose MMS treatment provides a distinctive opportunity to study postreplication repair processes. We show that upon exposure to low-dose MMS, a PRR-defective rad18Δ mutant stalls into a lengthy G2 arrest associated with the accumulation of single-stranded DNA (ssDNA) gaps. Consistent with previous results following UV-induced damage, reactivation of Rad18, even after prolonged G2 arrest, restores viability and genome integrity. We further show that PRR pathway preference in 0.001% MMS depends on timing and context; cells preferentially employ the error-free pathway in S phase and do not require MEC1-dependent checkpoint activation for survival. However, when PRR is restricted to the G2 phase, cells utilize REV3-dependent translesion synthesis, which requires a MEC1-dependent delay and results in significant hypermutability.

The fast growth of celiac disease diagnosis has sparked the production of gluten-free food and the search for reliable methods to detect gluten in foodstuff. In this paper, we report on a microfluidic electronic tongue (e-tongue) capable of detecting trace amounts of gliadin, a protein of gluten, down to 0.005 mg kg–1 in ethanol solutions, and distinguishing between gluten-free and gluten-containing foodstuff. In some cases, it is even possible to determine whether gluten-free foodstuff has been contaminated with gliadin. That was made possible with an e-tongue comprising four sensing units, three of which made of layer-by-layer (LbL) films of semiconducting polymers deposited onto gold interdigitated electrodes placed inside microchannels. Impedance spectroscopy was employed as the principle of detection, and the electrical capacitance data collected with the e-tongue were treated with information visualization techniques with feature selection for optimizing performance. The sensing units are disposable...

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 post-translational 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.

In this paper we discuss the detection of glucose and triglycerides using information visualization methods to process impedance spectroscopy data. The sensing units contained either lipase or glucose oxidase immobilized in layer-by-layer (LbL) films deposited onto interdigitated electrodes. The optimization consisted in identifying which part of the electrical response and combination of sensing units yielded the best distinguishing ability. It is shown that complete separation can be obtained for a range of concentrations of glucose and triglyceride when the interactive document map (IDMAP) technique is used to project the data into a two-dimensional plot. Most importantly, the optimization procedure can be extended to other types of biosensors, thus increasing the versatility of analysis provided by tailored molecular architectures exploited with various detection principles.

High-throughput technologies can now identify hundreds of candidate protein biomarkers for any disease with relative ease. However, because there are no assays for the majority of proteins and de novo immunoassay development is prohibitively expensive, few candidate biomarkers are tested in clinical studies. We tested whether the analytical performance of a biomarker identification pipeline based on targeted mass spectrometry would be sufficient for data-dependent prioritization of candidate biomarkers, de novo development of assays and multiplexed biomarker verification. We used a data-dependent triage process to prioritize a subset of putative plasma biomarkers from >1,000 candidates previously identified using a mouse model of breast cancer. Eighty-eight novel quantitative assays based on selected reaction monitoring mass spectrometry were developed, multiplexed and evaluated in 80 plasma samples. Thirty-six proteins were verified as being elevated in the plasma of tumor-bearing animals. The analytical performance of this pipeline suggests that it should support the use of an analogous approach with human samples.

The lymphatic circulation mediates drainage of fluid and cells from the periphery through lymph nodes, facilitating immune detection of lymph-borne foreign Ags. The 10.1.1 mAb recognizes a lymphatic endothelial Ag, in this study purified by Ab-affinity chromatography. SDS-PAGE and mass spectrometry identified murine chloride channel calcium-activated 1 (mCLCA1) as the 10.1.1 Ag, a 90-kDa cell-surface protein expressed in lymphatic endothelium and stromal cells of spleen and thymus. The 10.1.1 Ab-affinity chromatography also purified LFA-1, an integrin that mediates leukocyte adhesion to endothelium. This mCLCA1–LFA-1 interaction has functional consequences, as lymphocyte adhesion to lymphatic endothelium was blocked by 10.1.1 Ab bound to endotheliumor by LFA-1 Ab bound to lymphocytes. Lymphocyte adhesion was increased by cytokine treatment of lymphatic endothelium in association with increased expression of ICAM-1, an endothelial surface protein that is also a ligand for LFA-1. By contrast, mCLCA1 expression and the relative contribution of mCLCA1 to lymphocyte adhesion were unaffected by cytokine activation, demonstrating that mCLCA1 and ICAM-1 interactions with LFA-1 are differentially regulated. mCLCA1 also bound to the LFA-1–related Mac-1 integrin that is preferentially expressed on leukocytes. mCLCA1-mediated adhesion of Mac-1– or LFA-1–expressing leukocytes to lymphatic vessels and lymph node lymphatic sinuses provides a target for investigation of lymphatic involvement in leukocyte adhesion and trafficking during the immune response.

Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA) utilizes antibodies to enrich peptides from complex matrices for quantitation by stable isotope dilution mass spectrometry. SISCAPA improves sensitivity and limits the sample handling required for plasma-based analysis. Thus far, SISCAPA assays have been performed using polyclonal antibodies, yet monoclonal antibodies are an attractive alternative since they provide exquisite specificity, a renewable resource, and the potential for isolation of clones with very high affinities (10−9 M or better). The selection of a good monoclonal antibody out of hundreds-to-thousands of clones presents a challenge, since the screening assay should ideally be in the format of the final SISCAPA assay, but performing the assays manually is labor- and time-intensive. In this manuscript, we demonstrate that monoclonal antibodies can be used in SISCAPA assays, and we describe an automated high-throughput SISCAPA method that makes screening of large numbers of hybridomas feasible while conserving time and resources.

Verification of candidate biomarkers relies upon specific, quantitative assays optimized for selective detection of target proteins, and is increasingly viewed as a critical step in the discovery pipeline that bridges unbiased biomarker discovery to preclinical validation. Although individual laboratories have demonstrated that multiple reaction monitoring (MRM) coupled with isotope dilution mass spectrometry can quantify candidate protein biomarkers in plasma, reproducibility and transferability of these assays between laboratories have not been demonstrated. We describe a multilaboratory study to assess reproducibility, recovery, linear dynamic range and limits of detection and quantification of multiplexed, MRM-based assays, conducted by NCI-CPTAC. Using common materials and standardized protocols, we demonstrate that these assays can be highly reproducible within and across laboratories and instrument platforms, and are sensitive to low mug/ml protein concentrations in unfractionated plasma. We provide data and benchmarks against which individual laboratories can compare their performance and evaluate new technologies for biomarker verification in plasma.

Although the field of mass spectrometry-based proteomics is still in its infancy, recent developments in targeted proteomic techniques have left the field poised to impact the clinical protein biomarker pipeline now more than at any other time in history. for proteomics to meet its potential for finding biomarkers, clinicians, statisticians, epidemiologists and chemists must work together in an interdisciplinary approach. These interdisciplinary efforts will have the greatest chance for success if participants from each discipline have a basic working knowledge of the other disciplines. To that end, the purpose of this review is to provide a nontechnical overview of the emerging/evolving roles that mass spectrometry (especially targeted modes of mass spectrometry) can play in the biomarker pipeline, in hope of making the technology more accessible to the broader community for biomarker discovery efforts. Additionally, the technologies discussed are broadly applicable to proteomic studies, and are not restricted to biomarker discovery.

Activation of the DNA damage response pathway is a hallmark for early tumorigenesis, while loss of pathway activity is associated with disease progression. Thus we hypothesized that a gene expression signature associated with the DNA damage response may serve as a prognostic signature for outcome in cancer patients. We identified ionizing radiation-responsive transcripts in human lymphoblast cells derived from 12 individuals and used this signature to screen a panel of cancer data sets for the ability to predict long-term survival of cancer patients. We demonstrate that gene sets induced or repressed by ionizing radiation can predict clinical outcome in two independent breast cancer data sets, and we compare the radiation signature to previously described gene expression-based outcome predictors. While genes repressed in response to radiation likely represent the well-characterized proliferation signature predictive of breast cancer outcome, genes induced by radiation likely encode additional information representing other deregulated biological properties of tumors such as checkpoint or apoptotic responses.

Despite their potential to impact diagnosis and treatment of cancer, few protein biomarkers are in clinical use. Biomarker discovery is plagued with difficulties ranging from technological (inability to globally interrogate proteomes) to biological (genetic and environmental differences among patients and their tumors). We urgently need paradigms for biomarker discovery. To minimize biological variation and facilitate testing of proteomic approaches, we employed a mouse model of breast cancer. Specifically, we performed LC-MS/MS of tumor and normal mammary tissue from a conditional HER2/Neu-driven mouse model of breast cancer, identifying 6758 peptides representing >700 proteins. We developed a novel statistical approach (SASPECT) for prioritizing proteins differentially represented in LC-MS/MS datasets and identified proteins over- or under-represented in tumors. Using a combination of antibody-based approaches and multiple reaction monitoring-mass spectrometry (MRM-MS), we confirmed the overproduction of multiple proteins at the tissue level, identified fibulin-2 as a plasma biomarker, and extensively characterized osteopontin as a plasma biomarker capable of early disease detection in the mouse. Our results show that a staged pipeline employing shotgun-based comparative proteomics for biomarker discovery and multiple reaction monitoring for confirmation of biomarker candidates is capable of finding novel tissue and plasma biomarkers in a mouse model of breast cancer. Furthermore, the approach can be extended to find biomarkers relevant to human disease.

In most cell signaling experiments, analytes are measured one Western blot lane at a time in a semiquantitative and often poorly specific manner, limiting our understanding of network biology and hindering the translation of novel therapeutics and diagnostics. We show the feasibility of using multiplex immuno-MRM for phospho-pharmacodynamic measurements, establishing the potential for rapid and precise quantification of cell signaling networks. A 69-plex immuno-MRM assay targeting the DNA damage response network was developed and characterized by response curves and determinations of intra- and inter-assay repeatability. The linear range was ≥ 3 orders of magnitude, the median limit of quantification was 2.0 fmol/mg, the median intra-assay variability was 10% CV, and the median interassay variability was 16% CV. The assay was applied in proof-of-concept studies to immortalized and primary human cells and surgically excised cancer tissues to quantify exposure-response relationships and the effects of a genomic variant (ATM kinase mutation) or pharmacologic (kinase) inhibitor. The study shows the utility of multiplex immuno-MRM for simultaneous quantification of phosphorylated and nonmodified peptides, showing feasibility for development of targeted assay panels to cell signaling networks.

Multiple approaches for simplifying the serum proteome have been described. These techniques are generally developed across different laboratories, samples, mass spectrometry platforms, and analysis tools. Hence, comparing the available schemes is impossible from the existing literature because of confounding variables. We describe a head-to-head comparison of several serum fractionation schemes, including N-linked glycopeptide enrichment, cysteinyl-peptide enrichment, magnetic bead separation (C3, C8, and WCX), size fractionation, protein A/G depletion, and immunoaffinity column depletion of abundant serum proteins. Each technique was compared to results obtained from unfractionated human serum. The results show immunoaffinity subtraction is the most effective means for simplifying the serum proteome while maintaining reasonable sample throughput. The reported dataset is publicly available and provides a standard against which emergent technologies can be compared and evaluated for their contribution to serum-based biomarker discovery.

Immunoaffinity enrichment of peptides coupled to targeted, multiple reaction monitoring-mass spectrometry (immuno-MRM) has recently been developed for quantitative analysis of peptide and protein expression. As part of this technology, antibodies are generated to short, linear, tryptic peptides that are well-suited for detection by mass spectrometry. Despite its favorable analytical performance, a major obstacle to widespread adoption of immuno-MRM is a lack of validated affinity reagents because commercial antibody suppliers are reluctant to commit resources to producing anti-peptide antibodies for immuno-MRM while the market is much larger for conventional technologies, especially Western blotting and ELISA. Part of this reluctance has been the concern that affinity reagents generated to short, linear, tryptic peptide sequences may not perform well in traditional assays that detect full-length proteins. In this study, we test the feasibility and success rates of generating immuno-MRM monoclonal antibodies (mAbs) (targeting tryptic peptide antigens) that are also compatible with conventional, protein-based immuno-affinity technologies. We generated 40 novel, peptide immuno-MRM assays and determined that the cross-over success rates for using immuno-MRM monoclonals for Western blotting is 58% and for ELISA is 43%, which compare favorably to cross-over success rates amongst conventional immunoassay technologies. These success rates could most likely be increased if conventional and immuno-MRM antigen design strategies were combined, and we suggest a workflow for such a comprehensive approach. Additionally, the 40 novel immuno-MRM assays underwent fit-for-purpose analytical validation, and all mAbs and assays have been made available as a resource to the community via the Clinical Proteomic Tumor Analysis Consortium's (CPTAC) Antibody (http://antibodies.cancer.gov) and Assay Portals (http://assays.cancer.gov), respectively. This study also represents the first determination of the success rate (92%) for generating mAbs for immuno-MRM using a recombinant B cell cloning approach, which is considerably faster than the traditional hybridoma approach.