Discovery and validation of a colorectal cancer classifier in a new blood test with improved performance for high-risk subjects.

BACKGROUND: The aim was to improve upon an existing blood-based colorectal cancer (CRC) test directed to high-risk symptomatic patients, by developing a new CRC classifier to be used with a new test embodiment. The new test uses a robust assay format-electrochemiluminescence immunoassays-to quantify protein concentrations. The aim was achieved by building and validating a CRC classifier using concentration measures from a large sample set representing a true intent-to-test (ITT) symptomatic population. METHODS: 4435 patient samples were drawn from the Endoscopy II sample set. Samples were collected at seven hospitals across Denmark between 2010 and 2012 from subjects with symptoms of colorectal neoplasia. Colonoscopies revealed the presence or absence of CRC. 27 blood plasma proteins were selected as candidate biomarkers based on previous studies. Multiplexed electrochemiluminescence assays were used to measure the concentrations of these 27 proteins in all 4435 samples. 3066 patients were randomly assigned to the Discovery set, in which machine learning was used to build candidate classifiers. Some classifiers were refined by allowing up to a 25% indeterminate score range. The classifier with the best Discovery set performance was successfully validated in the separate Validation set, consisting of 1336 samples. RESULTS: The final classifier was a logistic regression using ten predictors: eight proteins (A1AG, CEA, CO9, DPPIV, MIF, PKM2, SAA, TFRC), age, and gender. In validation, the indeterminate rate of the new panel was 23.2%, sensitivity/specificity was 0.80/0.83, PPV was 36.5%, and NPV was 97.1%. CONCLUSIONS: The validated classifier serves as the basis of a new blood-based CRC test for symptomatic patients. The improved performance, resulting from robust concentration measures across a large sample set mirroring the ITT population, renders the new test the best available for this population. Results from a test using this classifier can help assess symptomatic patients' CRC risk, increase their colonoscopy compliance, and manage next steps in their care.

A new in vivo cross-linking mass spectrometry platform to define protein-protein interactions in living cells.

Protein-protein interactions (PPIs) are fundamental to the structure and function of protein complexes. Resolving the physical contacts between proteins as they occur in cells is critical to uncovering the molecular details underlying various cellular activities. To advance the study of PPIs in living cells, we have developed a new in vivo cross-linking mass spectrometry platform that couples a novel membrane-permeable, enrichable, and MS-cleavable cross-linker with multistage tandem mass spectrometry. This strategy permits the effective capture, enrichment, and identification of in vivo cross-linked products from mammalian cells and thus enables the determination of protein interaction interfaces. The utility of the developed method has been demonstrated by profiling PPIs in mammalian cells at the proteome scale and the targeted protein complex level. Our work represents a general approach for studying in vivo PPIs and provides a solid foundation for future studies toward the complete mapping of PPI networks in living systems.

Design of CID-cleavable protein cross-linkers: identical mass modifications for simpler sequence analysis.

The cross-linking Mass Spectrometry (XL-MS) technique has enormous potential for studying the interactions between proteins, and it can provide detailed structural information about the interaction interfaces in large protein complexes. Such information has been difficult to obtain by conventional structural methods. One of the primary impediments to the wider use of the XL-MS technique is the extreme challenge in sequencing cross-linked peptides because of their complex fragmentation patterns in MS. A recent innovation is the development of MS-cleavable cross-linkers, which allows direct sequencing of component peptides for facile identification. Sulfoxides are an intriguing class of thermally-cleavable compounds that have been shown to fragment selectively during low-energy collisional induced dissociation (CID) analysis. Current CID-cleavable cross-linkers create fragmentation patterns in MS(2) of multiple peaks for each cross-linked peptide. Reducing the complexity of the fragmentation pattern in MS(2) facilitates subsequent MS(3) sequencing of the cross-linked peptides. The first authentic identical mass linker (IML) has now been designed, prepared, and evaluated. Multistage tandem mass spectrometry (MS(n)) analysis has demonstrated that the IML cross-linked peptides indeed yield one peak per peptide constituent in MS(2) as predicted, thus allowing effective and sensitive MS(3) analysis for unambiguous identification. Selective fragmentation for IML cross-linked peptides from the 19S proteasome complex was observed, providing a proof-of-concept demonstration for XL-MS studies on protein complexes.

Synthesis of two new enrichable and MS-cleavable cross-linkers to define protein-protein interactions by mass spectrometry.

The cross-linking Mass Spectrometry (XL-MS) technique extracts structural information from protein complexes without requiring highly purified samples, crystallinity, or large amounts of material. However, there are challenges to applying the technique to protein complexes in vitro, and those challenges become more daunting with in vivo experiments. Issues include effective detection and identification of cross-linked peptides from complex mixtures. While MS-cleavable cross-linkers facilitate the sequencing and identification of cross-linked peptides, enrichable cross-linkers increase their detectability by allowing their separation from non-cross-linked peptides prior to MS analysis. Although a number of cross-linkers with single functionality have been developed in recent years, an ideal reagent would incorporate both capabilities for XL-MS studies. Therefore, two new cross-linkers have been designed and prepared that incorporate an azide (azide-A-DSBSO) or alkyne (alkyne-A-DSBSO) to enable affinity purification strategies based on click chemistry. The integration of an acid cleavage site next to the enrichment handle allows easy recovery of cross-linked products during affinity purification. In addition, these sulfoxide containing cross-linking reagents possess robust MS-cleavable bonds to facilitate fast and easy identification of cross-linked peptides using MS analysis. Optimized, gram-scale syntheses of these cross-linkers have been developed and the azide-A-DSBSO cross-linker has been evaluated with peptides and proteins to demonstrate its utility in XL-MS analysis.

Developing new isotope-coded mass spectrometry-cleavable cross-linkers for elucidating protein structures.

Structural characterization of protein complexes is essential for the understanding of their function and regulation. However, it remains challenging due to limitations in existing tools. With recent technological improvements, cross-linking mass spectrometry (XL-MS) has become a powerful strategy to define protein-protein interactions and elucidate structural topologies of protein complexes. To further advance XL-MS studies, we present here the development of new isotope-coded MS-cleavable homobifunctional cross-linkers: d0- and d10-labeled dimethyl disuccinimidyl sulfoxide (DMDSSO). Detailed characterization of DMDSSO cross-linked peptides further demonstrates that sulfoxide-containing MS-cleavable cross-linkers offer robust and predictable MS2 fragmentation of cross-linked peptides, permitting subsequent MS3 analysis for simplified, unambiguous identification. Concurrent usage of these reagents provides a characteristic doublet pattern of DMDSSO cross-linked peptides, thus aiding in the confidence of cross-link identification by MS(n) analysis. More importantly, the unique isotopic profile permits quantitative analysis of cross-linked peptides and therefore expands the capability of XL-MS strategies to analyze both static and dynamic protein interactions. Together, our work has established a new XL-MS workflow for future studies toward the understanding of structural dynamics of protein complexes.

Mapping the structural topology of the yeast 19S proteasomal regulatory particle using chemical cross-linking and probabilistic modeling.

Structural characterization of proteasome complexes is an essential step toward understanding the ubiquitin-proteasome system. Currently, high resolution structures are not available for the 26S proteasome holocomplex as well as its subcomplex, the 19S regulatory particle (RP). Here we have employed a novel integrated strategy combining chemical cross-linking with multistage tandem mass spectrometry to define the proximity of subunits within the yeast 19S RP to elucidate its topology. This has resulted in the identification of 174 cross-linked peptides of the yeast 19S RP, representing 43 unique lysine-lysine linkages within 24 nonredundant pair-wise subunit interactions. To map the spatial organization of the 19S RP, we have developed and utilized a rigorous probabilistic framework to derive maximum likelihood (ML) topologies based on cross-linked peptides determined from our analysis. Probabilistic modeling of the yeast 19S AAA-ATPase ring (i.e., Rpt1-6) has produced an ML topology that is in excellent agreement with known topologies of its orthologs. In addition, similar analysis was carried out on the 19S lid subcomplex, whose predicted ML topology corroborates recently reported electron microscopy studies. Together, we have demonstrated the effectiveness and potential of probabilistic modeling for unraveling topologies of protein complexes using cross-linking data. This report describes the first study of the 19S RP topology using a new integrated strategy combining chemical cross-linking, mass spectrometry, and probabilistic modeling. Our results have provided a solid foundation to advance our understanding of the 19S RP architecture at peptide level resolution. Furthermore, our methodology developed here is a valuable proteomic tool that can be generalized for elucidating the structures of protein complexes.

Development of a novel cross-linking strategy for fast and accurate identification of cross-linked peptides of protein complexes.

Knowledge of elaborate structures of protein complexes is fundamental for understanding their functions and regulations. Although cross-linking coupled with mass spectrometry (MS) has been presented as a feasible strategy for structural elucidation of large multisubunit protein complexes, this method has proven challenging because of technical difficulties in unambiguous identification of cross-linked peptides and determination of cross-linked sites by MS analysis. In this work, we developed a novel cross-linking strategy using a newly designed MS-cleavable cross-linker, disuccinimidyl sulfoxide (DSSO). DSSO contains two symmetric collision-induced dissociation (CID)-cleavable sites that allow effective identification of DSSO-cross-linked peptides based on their distinct fragmentation patterns unique to cross-linking types (i.e. interlink, intralink, and dead end). The CID-induced separation of interlinked peptides in MS/MS permits MS(3) analysis of single peptide chain fragment ions with defined modifications (due to DSSO remnants) for easy interpretation and unambiguous identification using existing database searching tools. Integration of data analyses from three generated data sets (MS, MS/MS, and MS(3)) allows high confidence identification of DSSO cross-linked peptides. The efficacy of the newly developed DSSO-based cross-linking strategy was demonstrated using model peptides and proteins. In addition, this method was successfully used for structural characterization of the yeast 20 S proteasome complex. In total, 13 non-redundant interlinked peptides of the 20 S proteasome were identified, representing the first application of an MS-cleavable cross-linker for the characterization of a multisubunit protein complex. Given its effectiveness and simplicity, this cross-linking strategy can find a broad range of applications in elucidating the structural topology of proteins and protein complexes.

A large-scale and robust dynamic MRM study of colorectal cancer biomarkers.

Over the past 20 years, mass spectrometry (MS) has emerged as a dynamic tool for proteomics biomarker discovery. However, published MS biomarker candidates often do not translate to the clinic, failing during attempts at independent replication. The cause can be shortcomings in study design, sample quality, assay quantitation, and/or quality/process control. To address these shortcomings, we developed an MS workflow in accordance with Tier 2 measurement requirements for targeted peptides, defined by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) "fit-for-purpose" approach, using dynamic multiple reaction monitoring (dMRM), which measures specific peptide transitions during predefined retention time (RT) windows. We describe the development of a robust multipex dMRM assay measuring 641 proteotypic peptides from 392 colorectal cancer (CRC) related proteins, and the procedures to track and handle sample processing and instrument variation over a four-month study, during which the assay measured blood samples from 1045 patients with CRC symptoms. After data collection, transitions were filtered by signal quality metrics before entering receiver operating characteristic (ROC) analysis. The results demonstrated CRC signal carried by 127 proteins in the symptomatic population. The workflow might be further developed to build Tier 1 assays for clinical tests identifying symptomatic individuals at elevated risk of CRC. SIGNIFICANCE: We developed a dMRM MS method with the rigor of a Tier 2 assay as defined by the CPTAC 'fit for purpose approach' [1]. Using quality and process control procedures, the assay was used to quantify 641 proteotypic peptides representing 392 CRC-related proteins in plasma from 1045 CRC-symptomatic patients. To our knowledge, this is the largest MRM method applied to the largest study to date. The results showed that 127 of the proteins carried univariate CRC signal in the symptomatic population. This large number of single biomarkers bodes well for future development of multivariate classifiers to distinguish CRC in the symptomatic population.

Discovery and Validation of Plasma-Protein Biomarker Panels for the Detection of Colorectal Cancer and Advanced Adenoma in a Danish Collection of Samples from Patients Referred for Diagnostic Colonoscopy.

BACKGROUND: Well-collected and well-documented sample repositories are necessary for disease biomarker development. The availability of significant numbers of samples with the associated patient information enables biomarker validation to proceed with maximum efficacy and minimum bias. The creation and utilization of such a resource is an important step in the development of blood-based biomarker tests for colorectal cancer. METHODS: We have created a subject data and biological sample resource, Endoscopy II, which is based on 4698 individuals referred for diagnostic colonoscopy in Denmark between May 2010 and November 2012. Of the patients referred based on 1 or more clinical symptoms of colorectal neoplasia, 512 were confirmed by pathology to have colorectal cancer and 399 were confirmed to have advanced adenoma. Using subsets of these sample groups in case-control study designs (300 patients for colorectal cancer, 302 patients for advanced adenoma), 2 panels of plasma-based proteins for colorectal cancer and 1 panel for advanced adenoma were identified and validated based on ELISA data obtained for 28 proteins from the samples. RESULTS: One of the validated colorectal cancer panels was comprised of 8 proteins (CATD, CEA, CO3, CO9, SEPR, AACT, MIF, and PSGL) and had a validation ROC curve area under the curve (AUC) of 0.82 (CI 0.75-0.88). There was no significant difference in the performance between early- and late-stage cancer. The advanced adenoma panel was comprised of 4 proteins (CATD, CLUS, GDF15, SAA1) and had a validation ROC curve AUC of 0.65 (CI 0.56-0.74). CONCLUSIONS: These results suggest that the development of blood-based aids to colorectal cancer detection and diagnosis is feasible.

A Plasma-Based Protein Marker Panel for Colorectal Cancer Detection Identified by Multiplex Targeted Mass Spectrometry.

INTRODUCTION: Colorectal cancer (CRC) testing programs reduce mortality; however, approximately 40% of the recommended population who should undergo CRC testing does not. Early colon cancer detection in patient populations ineligible for testing, such as the elderly or those with significant comorbidities, could have clinical benefit. Despite many attempts to identify individual protein markers of this disease, little progress has been made. Targeted mass spectrometry, using multiple reaction monitoring (MRM) technology, enables the simultaneous assessment of groups of candidates for improved detection performance. MATERIALS AND METHODS: A multiplex assay was developed for 187 candidate marker proteins, using 337 peptides monitored through 674 simultaneously measured MRM transitions in a 30-minute liquid chromatography-mass spectrometry analysis of immunodepleted blood plasma. To evaluate the combined candidate marker performance, the present study used 274 individual patient blood plasma samples, 137 with biopsy-confirmed colorectal cancer and 137 age- and gender-matched controls. Using 2 well-matched platforms running 5 days each week, all 274 samples were analyzed in 52 days. RESULTS: Using one half of the data as a discovery set (69 disease cases and 69 control cases), the elastic net feature selection and random forest classifier assembly were used in cross-validation to identify a 15-transition classifier. The mean training receiver operating characteristic area under the curve was 0.82. After final classifier assembly using the entire discovery set, the 136-sample (68 disease cases and 68 control cases) validation set was evaluated. The validation area under the curve was 0.91. At the point of maximum accuracy (84%), the sensitivity was 87% and the specificity was 81%. CONCLUSION: These results have demonstrated the ability of simultaneous assessment of candidate marker proteins using high-multiplex, targeted-mass spectrometry to identify a subset group of CRC markers with significant and meaningful performance.

Characterizing the dynamics of proteasome complexes by proteomics approaches.

SIGNIFICANCE: The proteasome is the degradation machine of the ubiquitin-proteasome system, which is critical in controlling many essential biological processes. Aberrant regulation of proteasome-dependent protein degradation can lead to various human diseases, and general proteasome inhibitors have shown efficacy for cancer treatments. Though clinically effective, current proteasome inhibitors have detrimental side effects and, thus, better therapeutic strategies targeting proteasomes are needed. Therefore, a comprehensive characterization of proteasome complexes will provide the molecular details that are essential for developing new and improved drugs. RECENT ADVANCES: New mass spectrometry (MS)-based proteomics approaches have been developed to study protein interaction networks and structural topologies of proteasome complexes. The results have helped define the dynamic proteomes of proteasome complexes, thus providing new insights into the mechanisms underlying proteasome function and regulation. CRITICAL ISSUES: The proteasome exists as heterogeneous populations in tissues/cells, and its proteome is highly dynamic and complex. In addition, proteasome complexes are regulated by various mechanisms under different physiological conditions. Consequently, complete proteomic profiling of proteasome complexes remains a major challenge for the field. FUTURE DIRECTIONS: We expect that proteomic methodologies enabling full characterization of proteasome complexes will continue to evolve. Further advances in MS instrumentation and protein separation techniques will be needed to facilitate the detailed proteomic analysis of low-abundance components and subpopulations of proteasome complexes. The results will help us understand proteasome biology as well as provide new therapeutic targets for disease diagnostics and treatment.

Selective enrichment and identification of azide-tagged cross-linked peptides using chemical ligation and mass spectrometry.

Protein-protein interaction is one of the key regulatory mechanisms for controlling protein function in various cellular processes. Chemical cross-linking coupled with mass spectrometry has proven to be a powerful method not only for mapping protein-protein interactions of all natures, including weak and transient ones, but also for determining their interaction interfaces. One critical challenge remaining in this approach is how to effectively isolate and identify cross-linked products from a complex peptide mixture. In this work, we have developed a novel strategy using conjugation chemistry for selective enrichment of cross-linked products. An azide-tagged cross-linker along with two biotinylated conjugation reagents were designed and synthesized. Cross-linking of model peptides and cytochrome c as well as enrichment of the resulting cross-linked peptides has been assessed. Selective conjugation of azide-tagged cross-linked peptides has been demonstrated using two strategies: copper catalyzed cycloaddition and Staudinger ligation. While both methods are effective, Staudinger ligation is better suited for enriching the cross-linked peptides since there are fewer issues with sample handling. LC MS(n) analysis coupled with database searching using the Protein Prospector software package allowed identification of 58 cytochrome c cross-linked peptides after enrichment and affinity purification. The new enrichment strategy developed in this work provides useful tools for facilitating identification of cross-linked peptides in a peptide mixture by MS, thus presenting a step forward in future studies of protein-protein interactions of protein complexes by cross-linking and mass spectrometry.