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

Enhanced Multiplexing Technology for Proteomics

The identification of thousands of proteins and their relative levels of expression has furthered understanding of biological processes and disease and stimulated new systems biology hypotheses. Quantitative proteomics workflows that rely on analytical assays such as mass spectrometry have facilitated high-throughput measurements of proteins partially due to multiplexing. Multiplexing allows proteome differences across multiple samples to be measured simultaneously, resulting in more accurate quantitation, increased statistical robustness, reduced analysis times, and lower experimental costs. The number of samples that can be multiplexed has evolved from as few as two to more than 50, with studies involving more than 10 samples being denoted as enhanced multiplexing or hyperplexing. In this review, we give an update on emerging multiplexing proteomics techniques and highlight advantages and limitations for enhanced multiplexing strategies.

Toward Practical Integration of Omic and Imaging Data in Co-Clinical Trials

Co-clinical trials are the concurrent or sequential evaluation of therapeutics in both patients clinically and patient-derived xenografts (PDX) pre-clinically, in a manner designed to match the pharmacokinetics and pharmacodynamics of the agent(s) used. The primary goal is to determine the degree to which PDX cohort responses recapitulate patient cohort responses at the phenotypic and molecular levels, such that pre-clinical and clinical trials can inform one another. A major issue is how to manage, integrate, and analyze the abundance of data generated across both spatial and temporal scales, as well as across species. To address this issue, we are developing MIRACCL (molecular and imaging response analysis of co-clinical trials), a web-based analytical tool. For prototyping, we simulated data for a co-clinical trial in "triple-negative" breast cancer (TNBC) by pairing pre- (T0) and on-treatment (T1) magnetic resonance imaging (MRI) from the I-SPY2 trial, as well as PDX-based T0 and T1 MRI. Baseline (T0) and on-treatment (T1) RNA expression data were also simulated for TNBC and PDX. Image features derived from both datasets were cross-referenced to omic data to evaluate MIRACCL functionality for correlating and displaying MRI-based changes in tumor size, vascularity, and cellularity with changes in mRNA expression as a function of treatment.

Recent Developments and Applications of Quantitative Proteomics Strategies for High-Throughput Biomolecular Analyses in Cancer Research

Innovations in medical technology and dedicated focus from the scientific community have inspired numerous treatment strategies for benign and invasive cancers. While these improvements often lend themselves to more positive prognoses and greater patient longevity, means for early detection and severity stratification have failed to keep pace. Detection and validation of cancer-specific biomarkers hinges on the ability to identify subtype-specific phenotypic and proteomic alterations and the systematic screening of diverse patient groups. For this reason, clinical and scientific research settings rely on high throughput and high sensitivity mass spectrometry methods to discover and quantify unique molecular perturbations in cancer patients. Discussed within is an overview of quantitative proteomics strategies and a summary of recent applications that enable revealing potential biomarkers and treatment targets in prostate, ovarian, breast, and pancreatic cancer in a high throughput manner.

Large-scale site-specific mapping of the O-GalNAc glycoproteome

Protein glycosylation is one of the most common protein modifications. A major type of protein glycosylation is O-GalNAcylation, in which GalNAc-type glycans are attached to protein Ser or Thr residues via an O-linked glycosidic bond. O-GalNAcylation is thought to play roles in protein folding, stability, trafficking and protein interactions, and identification of the site-specific O-GalNAc glycoproteome is a crucial step toward understanding the biological significance of the modification. However, lack of suitable methodology, absence of consensus sequon of O-GalNAcylation sites and complex O-GalNAc glycan structures pose analytical challenges. We recently developed a mass spectrometry-based method called extraction of O-linked glycopeptides (EXoO) that enables large-scale mapping of site-specific mucin-type O-GalNAcylation sites. Here we provide a detailed protocol for EXoO, which includes seven stages of: (1) extraction and proteolytic digestion of proteins to peptides, (2) sequential guanidination and de-salting of peptides, (3) enrichment of glycopeptides, (4) solid-phase peptide conjugation and release of O-GalNAc glycopeptides using the OpeRATOR protease, (5) liquid chromatography with tandem mass spectrometry analysis of O-GalNAc glycopeptides, (6) identification of O-GalNAc glycopeptides by database search and (7) quantification of O-GalNAc glycopeptides. Using this protocol, thousands of O-GalNAcylation sites from hundreds of glycoproteins with information regarding site-specific O-GalNAc glycan can be identified and quantified from complex samples. The protocol can be performed by a researcher with basic proteomics skills and takes about 4 d to complete.

Orthogonal Proteomic Platforms and Their Implications for the Stable Classification of High-Grade Serous Ovarian Cancer Subtypes

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) established a harmonized method for large-scale clinical proteomic studies. SWATH-MS, an instance of data-independent acquisition (DIA) proteomic methods, is an alternate proteomic approach. In this study, we used SWATH-MS to analyze remnant peptides from the original retrospective TCGA samples generated for the CPTAC ovarian cancer proteogenomic study. The SWATH-MS results recapitulated the confident identification of differentially expressed proteins in enriched pathways associated with the robust Mesenchymal high-grade serous ovarian cancer subtype and the homologous recombination deficient tumors. Hence, SWATH/DIA-MS presents a promising complementary or orthogonal alternative to the CPTAC proteomic workflow, with the advantages of simpler and faster workflows and lower sample consumption, albeit with shallower proteome coverage. In summary, both analytical methods are suitable to characterize clinical samples, providing proteomic workflow alternatives for cancer researchers depending on the context-specific goals of the studies.

•

SWATH-MS and iTRAQ-DDA are used to classify 103 high-grade serous ovarian cancer

•

SWATH-MS re-capitulates differentially expressed proteins in ovarian cancer subtypes

•

SWATH-MS is a robust proteomic approach for large-scale clinical proteomic studies

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.

Developing Workflow for Simultaneous Analyses of Phosphopeptides and Glycopeptides

Enrichment of modified peptides from global peptides is inevitable in mass spectrometric analysis protein modifications because of their importance in the study of cellular functions and low abundance in the global proteomic analysis. Recent advances in enrichment methods for modified peptides such as phosphopeptides and intact glycopeptides (IGPs) show that the methods for proteomic analyses of both protein modifications are robust. We have recently observed and reported a large number of IGPs from phosphoproteomic analysis using IMAC-based phosphopeptides enrichment procedure. To determine whether phosphorylated peptides could be specifically isolated from coenriched IGPs in IMAC experiments with different pH, IMAC procedures were performed at different pH conditions, and we found that the enrichment of phosphopeptides at pH 2.0 was the optimal condition for having the highest number of phosphopeptide identifications; however, coenrichment of phosphopeptides and glycopeptides was inevitable in the entire pH range. The hydrophilic enrichments of IGPs performed before or after IMAC enrichment were evaluated subsequently to determine the optimal workflow for simultaneous analyses of phosphopeptides and glycopeptides, and IMAC enrichment followed by hydrophilic enrichment was chosen as the optimized workflow. Applying the workflow to the TMT-labeled peptides from luminal and basal-like type of breast cancer patient-derived xenograft (PDX) models allowed quantitative analyses of phospho- and glycoproteomics with 17582 phosphopeptides and 3468 glycopeptides identified, and 1237 phosphopeptides and 236 glycopeptides showed significant expression differences between luminal and basal-like, respectively. This method allows simultaneous analyses of phosphoprotein and glycoprotein modifications, extending our understanding of roles of glycosylation and phosphorylation in biology and diseases.

SWATH Mass Spectrometry Applied to Cerebrospinal Fluid Differential Proteomics: Establishment of a Sample-Specific Method

Mass spectrometry (MS) has become the gold standard method for proteomics by allowing the simultaneous identification and/or quantification of thousands of proteins of a given sample. Over time, mass spectrometry has evolved into newer quantitative approaches with increased sensitivity and accuracy, such as the sequential windows acquisition of all theoretical fragment-ion spectra (SWATH)-MS approach. Moreover, in the past few years, some improvements were made in the SWATH-acquisition algorithm, allowing the design of sample-customized acquisition methods by adjusting the Q1 windows' width in order to reduce it in the most populated m/z regions. This customization results in an increase in the specificity and a reduction in the interferences, ultimately leading to an improvement in the amount of quantitative data extracted to eventually increase the proteome coverage. These improvements are especially relevant for clinical neuroproteomics, which is mainly based on the analysis of circulatory biofluids, in particular the cerebrospinal fluid (CSF) due to its close connection with the brain.In the present chapter, a detailed description of the methodologies necessary to perform a whole-proteome relative quantification of CSF samples by SWATH-MS is presented, starting with the isolation of the protein fraction, its preparation for MS analysis, with all the necessary information for the design of a SWATH-MS method specific for each sample batch, and finally providing different methodologies for the analysis of the quantitative data obtained.

Quantitative proteomics using SILAC-MS identifies N-acetylcysteine-solution-triggered reversal response of renal cell carcinoma cell lines

N-acetylcysteine (NAC), a precursor for glutathione (GSH), causes permeable antioxidation protecting normal cells and disrupting cancer cells. In the present study, we found that a NAC-based medium can trigger a reversal response of human clear cell renal cell carcinoma (ccRCC). To further investigate the action of a NAC-based solution in ccRCC cell lines, 786-O and SN12C were incubated in a serum-free acid medium (low pH) in the presence of 2 mM NAC for 24 hours or in a serum-free medium (normal pH) as the control, and then a phenotypic and proteomic analyses were performed. To determine the reversal occurrence, we tested the phenotypic features associated with cancer cells. Under this premise, a systematic and in-depth analysis of NAC-solution-triggered protein alterations was carried out by quantitative proteomics in both cell lines. Among the paramount protein signature, we identified a large number of proteins associated with cancer features were downregulated, but other proteins in the KEGG pathways associated with recovery of the missing tumorigenicity, such as the p53 pathway and repair pathway, were significantly upregulated. Quantification of notable proteins was validated by messenger RNA (mRNA) and protein levels in the ccRCC cell line. Collectively, our data indicate that the NAC-based solution inhibits human ccRCC cell growth by decreasing cell proliferation and inducing apoptosis, limiting their migration by limiting cell motility and completely changing their metabolic mode. Thus, NAC-based solutions could be used for the prevention or treatment of ccRCC.

Quantitative analysis of the mitochondrial proteome in human ovarian carcinomas

Mitochondria play important roles in growth, signal transduction, division, tumorigenesis and energy metabolism in epithelial ovarian carcinomas (EOCs) without an effective biomarker. To investigate the proteomic profile of EOC mitochondrial proteins, a 6-plex isobaric tag for relative and absolute quantification (iTRAQ) proteomics was used to identify mitochondrial expressed proteins (mtEPs) in EOCs relative to controls, followed by an integrative analysis of the identified mtEPs and the Cancer Genome Atlas (TCGA) data from 419 patients. A total of 5115 quantified proteins were identified from purified mitochondrial samples, and 262 proteins were significantly related to overall survival in EOC patients. Furthermore, 63 proteins were identified as potential biomarkers for the development of an EOC, and our findings were consistent with previous reports on a certain extent. Pathway network analysis identified 70 signaling pathways. Interestingly, the results demonstrated that cancer cells exhibited an increased dependence on mitophagy, such as peroxisome, phagosome, lysosome, valine, leucine and isoleucine degradation and fatty acid degradation pathways, which might play an important role in EOC invasion and metastasis. Five proteins (GLDC, PCK2, IDH2, CPT2 and HMGCS2) located in the mitochondrion and enriched pathways were selected for further analysis in an EOC cell line and tissues, and the results confirmed reliability of iTRAQ proteomics. These findings provide a large-scale mitochondrial proteomic profiling with quantitative information, a certain number of potential protein biomarkers and a novel vision in the mitophagy bio-mechanism of a human ovarian carcinoma.

Surfactant and Chaotropic Agent Assisted Sequential Extraction/On-Pellet Digestion (SCAD) for Enhanced Proteomics

As a popular sample preparation approach, filter-aided sample preparation (FASP) has been widely used in proteomic analysis. However, several limitations have been noted, including sample loss during filtration, repetitive centrifugation steps, and the possibility of breakage of filtration membrane. Extraction bias among different sample preparation strategies presents another challenge. To overcome these limitations and address remaining challenges, we developed a novel surfactant and chaotropic agent assisted sequential extraction/on-pellet digestion (SCAD) protocol. The new strategy resulted in higher protein yield and improved peptide recovery and protein coverage compared to two conventional sample preparation methods (FASP and urea). In combination of three strategies, more than 10,000 distinct protein groups were identified with 1% FDR from MDA-MB-231 cells without any prefractionation. This in-depth proteome analysis was accomplished by optimization of protein extraction, enzymatic digestion, LC gradient, and peptide sequencing method. Ingenuity Pathways Analysis (IPA) of proteins exclusively identified in SCAD revealed several crucial signaling pathways that regulate breast cancer progression. SCAD also enabled an unbiased extraction of different categories of proteins (membrane, intracellular, nuclear) associated with tumorigenesis, which integrates the advantages of FASP and urea extraction. This novel strategy expedites comprehensive protein identification, which is applicable for biomarker discovery in various types of cancers.

Evaluation of NCI-7 Cell Line Panel as a Reference Material for Clinical Proteomics

Reference materials are vital to benchmarking the reproducibility of clinical tests and essential for monitoring laboratory performance for clinical proteomics. The reference material utilized for mass spectrometric analysis of the human proteome would ideally contain enough proteins to be suitably representative of the human proteome, as well as exhibit a stable protein composition in different batches of sample regeneration. Previously, The Clinical Proteomic Tumor Analysis Consortium (CPTAC) utilized a PDX-derived comparative reference (CompRef) materials for the longitudinal assessment of proteomic performance; however, inherent drawbacks of PDX-derived material, including extended time needed to grow tumors and high level of expertise needed, have resulted in efforts to identify a new source of CompRef material. In this study, we examined the utility of using a panel of seven cancer cell lines, NCI-7 Cell Line Panel, as a reference material for mass spectrometric analysis of human proteome. Our results showed that not only is the NCI-7 material suitable for benchmarking laboratory sample preparation methods, but also NCI-7 sample generation is highly reproducible at both the global and phosphoprotein levels. In addition, the predicted genomic and experimental coverage of the NCI-7 proteome suggests the NCI-7 material may also have applications as a universal standard proteomic reference.