Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma.

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.

Proteogenomic Landscape of Breast Cancer Tumorigenesis and Targeted Therapy.

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.

Integrated Proteogenomic Characterization of Human High-Grade Serous Ovarian Cancer.

To provide a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer, we performed a comprehensive mass-spectrometry-based proteomic characterization of 174 ovarian tumors previously analyzed by The Cancer Genome Atlas (TCGA), of which 169 were high-grade serous carcinomas (HGSCs). Integrating our proteomic measurements with the genomic data yielded a number of insights into disease, such as how different copy-number alternations influence the proteome, the proteins associated with chromosomal instability, the sets of signaling pathways that diverse genome rearrangements converge on, and the ones most associated with short overall survival. Specific protein acetylations associated with homologous recombination deficiency suggest a potential means for stratifying patients for therapy. In addition to providing a valuable resource, these findings provide a view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC. VIDEO ABSTRACT.

Mapping the KRAS proteoform landscape in colorectal cancer identifies truncated KRAS4B that decreases MAPK signaling.

The KRAS gene is one of the most frequently mutated oncogenes in human cancer and gives rise to two isoforms, KRAS4A and KRAS4B. KRAS post-translational modifications (PTMs) have the potential to influence downstream signaling. However, the relationship between KRAS PTMs and oncogenic mutations remains unclear, and the extent of isoform-specific modification is unknown. Here, we present the first top-down proteomics study evaluating both KRAS4A and KRAS4B, resulting in 39 completely characterized proteoforms across colorectal cancer cell lines and primary tumor samples. We determined which KRAS PTMs are present, along with their relative abundance, and that proteoforms of KRAS4A versus KRAS4B are differentially modified. Moreover, we identified a subset of KRAS4B proteoforms lacking the C185 residue and associated C-terminal PTMs. By confocal microscopy, we confirmed that this truncated GFP-KRAS4BC185∗ proteoform is unable to associate with the plasma membrane, resulting in a decrease in mitogen-activated protein kinase signaling pathway activation. Collectively, our study provides a reference set of functionally distinct KRAS proteoforms and the colorectal cancer contexts in which they are present.

Lessons learned: establishing a CLIA-equivalent laboratory for targeted mass spectrometry assays - navigating the transition from research to clinical practice.

Mass spectrometry (MS) assays offer exceptional capabilities in high multiplexity, specificity, and throughput. As proteomics technologies continue advancements to identify new disease biomarkers, transition of these innovations from research settings to clinical applications becomes imperative. To meet the rigorous regulatory standards of clinical laboratories, development of a clinical protein MS assay necessitates adherence to stringent criteria. To illustrate the process, this project focused on using thyroglobulin (Tg) as a biomarker and an immuno-multiple reaction monitoring (iMRM) MS-based assay as a model for establishing a Clinical Laboratory Improvement Amendments (CLIA) compliant laboratory within the Centers of Genomic and Precision Medicine, National Taiwan University. The chosen example also illustrates the clinical utility of MS assays to complement conventional immunoassay-based methods, particularly in cases where the presence of autoantibodies in 10-30% of patients hinders accuracy. The laboratory design entails a comprehensive coordination in spatial layout, workflow organization, equipment selection, ventilation systems, plumbing, electrical infrastructure, documentation procedures, and communication protocols. Practical aspects of the transformation process, including preparing laboratory facilities, testing environments, instrument validation, assay development and validation, quality management, sample testing, and personnel competency, are discussed. Finally, concordant results in proficiency testing demonstrate the harmonization with the University of Washington Medical Center and the quality assurance of the CLIA-equivalent Tg-iMRM MS assay established in Taiwan. The realization of this model protein MS assay in Taiwan highlights the feasibility of international joint development and provides a detailed reference map to expedite the implementation of more MS-based protein assays in clinical laboratories for patient care.

Deep Proteomics Using Two Dimensional Data Independent Acquisition Mass Spectrometry.

Methodologies that facilitate high-throughput proteomic analysis are a key step toward moving proteome investigations into clinical translation. Data independent acquisition (DIA) has potential as a high-throughput analytical method due to the reduced time needed for sample analysis, as well as its highly quantitative accuracy. However, a limiting feature of DIA methods is the sensitivity of detection of low abundant proteins and depth of coverage, which other mass spectrometry approaches address by two-dimensional fractionation (2D) to reduce sample complexity during data acquisition. In this study, we developed a 2D-DIA method intended for rapid- and deeper-proteome analysis compared to conventional 1D-DIA analysis. First, we characterized 96 individual fractions obtained from the protein standard, NCI-7, using a data-dependent approach (DDA), identifying a total of 151,366 unique peptides from 11,273 protein groups. We observed that the majority of the proteins can be identified from just a few selected fractions. By performing an optimization analysis, we identified six fractions with high peptide number and uniqueness that can account for 80% of the proteins identified in the entire experiment. These selected fractions were combined into a single sample which was then subjected to DIA (referred to as 2D-DIA) quantitative analysis. Furthermore, improved DIA quantification was achieved using a hybrid spectral library, obtained by combining peptides identified from DDA data with peptides identified directly from the DIA runs with the help of DIA-Umpire. The optimized 2D-DIA method allowed for improved identification and quantification of low abundant proteins compared to conventional unfractionated DIA analysis (1D-DIA). We then applied the 2D-DIA method to profile the proteomes of two breast cancer patient-derived xenograft (PDX) models, quantifying 6,217 and 6,167 unique proteins in basal- and luminal- tumors, respectively. Overall, this study demonstrates the potential of high-throughput quantitative proteomics using a novel 2D-DIA method.

Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues.

Clinical proteomics requires large-scale analysis of human specimens to achieve statistical significance. We evaluated the long-term reproducibility of an iTRAQ (isobaric tags for relative and absolute quantification)-based quantitative proteomics strategy using one channel for reference across all samples in different iTRAQ sets. A total of 148 liquid chromatography tandem mass spectrometric (LC-MS/MS) analyses were completed, generating six 2D LC-MS/MS data sets for human-in-mouse breast cancer xenograft tissues representative of basal and luminal subtypes. Such large-scale studies require the implementation of robust metrics to assess the contributions of technical and biological variability in the qualitative and quantitative data. Accordingly, we derived a quantification confidence score based on the quality of each peptide-spectrum match to remove quantification outliers from each analysis. After combining confidence score filtering and statistical analysis, reproducible protein identification and quantitative results were achieved from LC-MS/MS data sets collected over a 7-month period. This study provides the first quality assessment on long-term stability and technical considerations for study design of a large-scale clinical proteomics project.

Recommendations for the Generation, Quantification, Storage, and Handling of Peptides Used for Mass Spectrometry-Based Assays.

BACKGROUND: For many years, basic and clinical researchers have taken advantage of the analytical sensitivity and specificity afforded by mass spectrometry in the measurement of proteins. Clinical laboratories are now beginning to deploy these work flows as well. For assays that use proteolysis to generate peptides for protein quantification and characterization, synthetic stable isotope-labeled internal standard peptides are of central importance. No general recommendations are currently available surrounding the use of peptides in protein mass spectrometric assays. CONTENT: The Clinical Proteomic Tumor Analysis Consortium of the National Cancer Institute has collaborated with clinical laboratorians, peptide manufacturers, metrologists, representatives of the pharmaceutical industry, and other professionals to develop a consensus set of recommendations for peptide procurement, characterization, storage, and handling, as well as approaches to the interpretation of the data generated by mass spectrometric protein assays. Additionally, the importance of carefully characterized reference materials-in particular, peptide standards for the improved concordance of amino acid analysis methods across the industry-is highlighted. The alignment of practices around the use of peptides and the transparency of sample preparation protocols should allow for the harmonization of peptide and protein quantification in research and clinical care.

Linking cancer genome to proteome: NCI's investment into proteogenomics.

Advances in both targeted and unbiased MS-based proteomics are now at a mature stage for comprehensively and reproducibly characterizing a large part of the cancer proteome. These developments combined with the extensive genomic characterization of several cancer types by large-scale initiatives such as the International Cancer Genome Consortium and Cancer Genome Atlas Project have paved the way for proteogenomic analysis of omics datasets and integration methods. The advances serve as the basis for the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium and this article highlights its current work and future steps in the area of proteogenomics.

Proteogenomic insights suggest druggable pathways in endometrial carcinoma.

We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of ß-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.

A community standard format for the representation of protein affinity reagents.

Protein affinity reagents (PARs), most commonly antibodies, are essential reagents for protein characterization in basic research, biotechnology, and diagnostics as well as the fastest growing class of therapeutics. Large numbers of PARs are available commercially; however, their quality is often uncertain. In addition, currently available PARs cover only a fraction of the human proteome, and their cost is prohibitive for proteome scale applications. This situation has triggered several initiatives involving large scale generation and validation of antibodies, for example the Swedish Human Protein Atlas and the German Antibody Factory. Antibodies targeting specific subproteomes are being pursued by members of Human Proteome Organisation (plasma and liver proteome projects) and the United States National Cancer Institute (cancer-associated antigens). ProteomeBinders, a European consortium, aims to set up a resource of consistently quality-controlled protein-binding reagents for the whole human proteome. An ultimate PAR database resource would allow consumers to visit one on-line warehouse and find all available affinity reagents from different providers together with documentation that facilitates easy comparison of their cost and quality. However, in contrast to, for example, nucleotide databases among which data are synchronized between the major data providers, current PAR producers, quality control centers, and commercial companies all use incompatible formats, hindering data exchange. Here we propose Proteomics Standards Initiative (PSI)-PAR as a global community standard format for the representation and exchange of protein affinity reagent data. The PSI-PAR format is maintained by the Human Proteome Organisation PSI and was developed within the context of ProteomeBinders by building on a mature proteomics standard format, PSI-molecular interaction, which is a widely accepted and established community standard for molecular interaction data. Further information and documentation are available on the PSI-PAR web site.

Proteogenomic Markers of Chemotherapy Resistance and Response in Triple-Negative Breast Cancer.

Microscaled proteogenomics was deployed to probe the molecular basis for differential response to neoadjuvant carboplatin and docetaxel combination chemotherapy for triple-negative breast cancer (TNBC). Proteomic analyses of pretreatment patient biopsies uniquely revealed metabolic pathways, including oxidative phosphorylation, adipogenesis, and fatty acid metabolism, that were associated with resistance. Both proteomics and transcriptomics revealed that sensitivity was marked by elevation of DNA repair, E2F targets, G2-M checkpoint, interferon-gamma signaling, and immune-checkpoint components. Proteogenomic analyses of somatic copy-number aberrations identified a resistance-associated 19q13.31-33 deletion where LIG1, POLD1, and XRCC1 are located. In orthogonal datasets, LIG1 (DNA ligase I) gene deletion and/or low mRNA expression levels were associated with lack of pathologic complete response, higher chromosomal instability index (CIN), and poor prognosis in TNBC, as well as carboplatin-selective resistance in TNBC preclinical models. Hemizygous loss of LIG1 was also associated with higher CIN and poor prognosis in other cancer types, demonstrating broader clinical implications. SIGNIFICANCE: Proteogenomic analysis of triple-negative breast tumors revealed a complex landscape of chemotherapy response associations, including a 19q13.31-33 somatic deletion encoding genes serving lagging-strand DNA synthesis (LIG1, POLD1, and XRCC1), that correlate with lack of pathologic response, carboplatin-selective resistance, and, in pan-cancer studies, poor prognosis and CIN. This article is highlighted in the In This Issue feature, p. 2483.

Evolution of clinical proteomics and its role in medicine.

Significant progress has been made in characterizing and sequencing genomic alterations of biospecimens from several types of cancer. Understanding the functional changes in the human proteome that arise from the genomic alterations or other factors is the next logical step in the development of high-value protein biomarkers that can be transitioned to clinical studies for biomarker qualification. Linking advances in genomic analysis to proteomic analysis will provide a pathway for qualified biomarkers which can drive the rational development of new diagnostics and therapies. The availability of these multidimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions.

Targeted mass spectrometry-based assays enable multiplex quantification of receptor tyrosine kinase, MAP Kinase, and AKT 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 PLX-4720. 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 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.

Targeted Mass Spectrometry Enables Multiplexed Quantification of Immunomodulatory Proteins in Clinical Biospecimens.

Immunotherapies are revolutionizing cancer care, producing durable responses and potentially cures in a subset of patients. However, response rates are low for most tumors, grade 3/4 toxicities are not uncommon, and our current understanding of tumor immunobiology is incomplete. While hundreds of immunomodulatory proteins in the tumor microenvironment shape the anti-tumor response, few of them can be reliably quantified. To address this need, we developed a multiplex panel of targeted proteomic assays targeting 52 peptides representing 46 proteins using peptide immunoaffinity enrichment coupled to multiple reaction monitoring-mass spectrometry. We validated the assays in tissue and plasma matrices, where performance figures of merit showed over 3 orders of dynamic range and median inter-day CVs of 5.2% (tissue) and 21% (plasma). A feasibility study in clinical biospecimens showed detection of 48/52 peptides in frozen tissue and 38/52 peptides in plasma. The assays are publicly available as a resource for the research community.

Targeted Mass Spectrometry Enables Quantification of Novel Pharmacodynamic Biomarkers of ATM Kinase Inhibition.

The ATM serine/threonine kinase (HGNC: ATM) is involved in initiation of repair of DNA double-stranded breaks, and ATM inhibitors are currently being tested as anti-cancer agents in clinical trials, where pharmacodynamic (PD) assays are crucial to help guide dose and scheduling and support mechanism of action studies. To identify and quantify PD biomarkers of ATM inhibition, we developed and analytically validated a 51-plex assay (DDR-2) quantifying protein expression and DNA damage-responsive phosphorylation. The median lower limit of quantification was 1.28 fmol, the linear range was over 3 orders of magnitude, the median inter-assay variability was 11% CV, and 86% of peptides were stable for storage prior to analysis. Use of the assay was demonstrated to quantify signaling following ionizing radiation-induced DNA damage in both immortalized lymphoblast cell lines and primary human peripheral blood mononuclear cells, identifying PD biomarkers for ATM inhibition to support preclinical and clinical studies.

Proteogenomic insights into the biology and treatment of HPV-negative head and neck squamous cell carcinoma.

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.

A synopsis of the 3rd annual Cancer Proteomics Conference.

The 3rd annual 'Cancer Proteomics Conference', organized by Select Biosciences (Sudbury, UK), was held in Berlin, Germany, 8-9 June 2010. With the aim of strengthening the links between scientists from Europe, as well as international investigators worldwide, more than 200 delegates attended, representing various countries. The Conference covered many topics in proteomics, including the use of proteomics for cancer therapeutic development, diagnostic applications, biomarker discovery, post-translational modifications and clinical proteomics, as well as new proteomic technologies, which may facilitate future progress. One distinct feature of this meeting was that the Conference was co-located with the 'Advances in Antibody and Peptide Therapeutics' meeting. Delegates had access to both meetings, allowing for enhanced interaction among investigators from the closely linked fields of research.

Analytical validation of protein-based multiplex assays: a workshop report by the NCI-FDA interagency oncology task force on molecular diagnostics.

Clinical proteomics has the potential to enable the early detection of cancer through the development of multiplex assays that can inform clinical decisions. However, there has been some uncertainty among translational researchers and developers as to the specific analytical measurement criteria needed to validate protein-based multiplex assays. To begin to address the causes of this uncertainty, a day-long workshop titled "Interagency Oncology Task Force Molecular Diagnostics Workshop" was held in which members of the proteomics and regulatory communities discussed many of the analytical evaluation issues that the field should address in development of protein-based multiplex assays for clinical use. This meeting report explores the issues raised at the workshop and details the recommendations that came out of the day's discussions, such as a workshop summary discussing the analytical evaluation issues that specific proteomic technologies should address when seeking US Food and Drug Administration approval.