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.

Analytical validation of a novel multiplex test for detection of advanced adenoma and colorectal cancer in symptomatic patients.

Early detection of colorectal cancer (CRC) is key to reducing associated mortality. Despite the importance of early detection, approximately 40% of individuals in the United States between the ages of 50-75 have never been screened for CRC. The low compliance with colonoscopy and fecal-based screening may be addressed with a non-invasive alternative such as a blood-based test. We describe here the analytical validation of a multiplexed blood-based assay that measures the plasma concentrations of 15 proteins to assess advanced adenoma (AA) and CRC risk in symptomatic patients. The test was developed on an electrochemiluminescent immunoassay platform employing four multi-marker panels, to be implemented in the clinic as a laboratory developed test (LDT). Under the Clinical Laboratory Improvement Amendments (CLIA) and College of American Pathologists (CAP) regulations, a United States-based clinical laboratory utilizing an LDT must establish performance characteristics relating to analytical validity prior to releasing patient test results. This report describes a series of studies demonstrating the precision, accuracy, analytical sensitivity, and analytical specificity for each of the 15 assays, as required by CLIA/CAP. In addition, the report describes studies characterizing each of the assays' dynamic range, parallelism, tolerance to common interfering substances, spike recovery, and stability to sample freeze-thaw cycles. Upon completion of the analytical characterization, a clinical accuracy study was performed to evaluate concordance of AA and CRC classifier model calls using the analytical method intended for use in the clinic. Of 434 symptomatic patient samples tested, the percent agreement with original CRC and AA calls was 87% and 92% respectively. All studies followed CLSI guidelines and met the regulatory requirements for implementation of a new LDT. The results provide the analytical evidence to support the implementation of the novel multi-marker test as a clinical test for evaluating CRC and AA risk in symptomatic individuals.

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 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.

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.

Discovery of a novel B-Raf fusion protein related to c-Met drug resistance.

In recent years, there have been notable advances with the development of anticancer drugs including those targeting protein tyrosine kinases such as the c-Met receptor, which has been implicated in the development and progression of several cancers. However, despite such progress, drug resistance continues to be the single most important cause of cancer treatment failure, and understanding the mechanisms of drug resistance remains a major hurdle in treating patients with recurrent disease. PF-04217903 is a small-molecule c-Met kinase inhibitor that potently inhibits c-Met-driven processes such as cell growth (proliferation and survival), motility, invasion, and morphology of a variety of tumor cells. Resistance to PF-04217903 was observed in GTL-16, a gastric carcinoma cell line with a constitutively activated c-Met receptor. In this report, mass spectrometry (MS) based quantitative phosphoproteomic analysis was used to determine changes in signaling pathways in the parental cells in response to c-Met inhibition and to investigate the changes in protein levels and related canonical pathways in both parental and PF-04217903 resistant (R3) clones in response to c-Met inhibition. The quantitative MS workflow included phosphoprotein enrichment of cell lysates from six treatment conditions: in-solution digestion, chemical labeling of peptides with a set of 6-plex isobaric tandem mass tags (TMT), HILIC fractionation, phosphopeptide enrichment, and nano LC-MS/MS on a LTQ-Orbitrap mass spectrometer. An investigation of these quantitative datasets using Ingenuity Pathways Analysis (IPA) revealed pathway changes in the various treatments that were consistent with previously observed transcriptomic and phenotypic changes. Proteomic analysis also revealed an increase in B-Raf expression in R3 clones. Expression profiling confirmed that B-Raf gene copy number was up-regulated and also indicated the presence of a mutated form of B-Raf. Using a bottom-up MS approach, SND-1 was identified as the B-Raf fusion partner. The discovery of this novel B-Raf fusion protein presents a novel target with potential clinical implications in the treatment of patients resistant to c-Met inhibitors.

Quantitative phosphoproteomic analysis of the STAT3/IL-6/HIF1alpha signaling network: an initial study in GSC11 glioblastoma stem cells.

Initiation and maintenance of several cancers including glioblastoma (GBM) may be driven by a small subset of cells called cancer stem cells (CSCs). CSCs may provide a repository of cells in tumor cell populations that are refractory to chemotherapeutic agents developed for the treatment of tumors. STAT3 is a key transcription factor associated with regulation of multiple stem cell types. Recently, a novel autocrine loop (IL-6/STAT3/HIF1alpha) has been observed in multiple tumor types (pancreatic, prostate, lung, and colon). The objective of this study was to probe perturbations of this loop in a glioblastoma cancer stem cell line (GSC11) derived from a human tumor by use of a JAK2/STAT3 phosphorylation inhibitor (WP1193), IL-6 stimulation, and hypoxia. A quantitative phosphoproteomic approach that employed phosphoprotein enrichment, chemical tagging with isobaric tags, phosphopeptide enrichment, and tandem mass spectrometry in a high-resolution instrument was applied. A total of 3414 proteins were identified in this study. A rapid Western blotting technique (<1 h) was used to confirm alterations in key protein expression and phosphorylation levels observed in the mass spectrometric experiments. About 10% of the phosphoproteins were linked to the IL-6 pathway, and the majority of remaining proteins could be assigned to other interlinked networks. By multiple comparisons between the sample conditions, we observed expected changes and gained novel insights into the contribution of each factor to the IL6/STAT3/HIF1alpha autocrine loop and the CSC response to perturbations by hypoxia, inhibition of STAT3 phosphorylation, and IL-6 stimulation.

Development of a novel LC/MS method to quantitate cellular stearoyl-CoA desaturase activity.

Stearoyl-CoA desaturase 1 (SCD1) is an enzyme that catalyzes the rate-limiting step in de novo synthesis of monounsaturated fatty acids--mainly oleate and palmitoleate from stearoyl-CoA and palmitoyl-Co A, respectively. These products are the most abundant monounsaturated fatty acids in membrane phospholipids, triglycerides, cholesterol esters. Reports on mice with a targeted disruption of SCD1 gene (SCD1-/-) exhibit improved glucose tolerance and insulin sensitivity compared to wild-type suggesting SCD1 could be a therapeutic target for diabetes and related metabolic diseases. Measurement of SCD1 activity is technically challenging and traditional cell-based SCD1 assay procedure is labor intensive with low throughput. We describe here a novel medium-throughput LC/MS cell-based assay for determining cellular SCD1 activity, facilitating screening of potential SCD1 inhibitor compounds. Confluent HepG2 cells were grown in 24-well plates and incubated with vehicle or an inhibitor followed by incubation with deuterium labeled saturated fatty acid substrates. Total cell lipids were extracted and the conversion of stearate to oleate was measured by liquid chromatography-mass spectrometry. Sterculate, a known inhibitor of SCD1, inhibited the enzyme activity in a dose dependent manner in this assay with a calculated EC(50) of 247 nM. The medium-throughput method described here is an important step towards identifying an inhibitor of SCD1 to treat diabetes and related metabolic diseases.