Absence of BTK, BCL2, and PLCG2 Mutations in Chronic Lymphocytic Leukemia Relapsing after First-Line Treatment with Fixed-Duration Ibrutinib plus Venetoclax.

PURPOSE: Mutations in BTK, PLCG2, and BCL2 have been reported in patients with progressive disease (PD) on continuous single-agent BTK or BCL2 inhibitor treatment. We tested for these mutations in samples from patients with PD after completion of first-line treatment with fixed-duration ibrutinib plus venetoclax for chronic lymphocytic leukemia (CLL) in the phase II CAPTIVATE study. PATIENTS AND METHODS: A total of 191 patients completed fixed-duration ibrutinib plus venetoclax (three cycles of ibrutinib then 12-13 cycles of ibrutinib plus venetoclax). Genomic risk features [del(11q), del(13q), del(17p), trisomy 12, complex karyotype, unmutated IGHV, TP53 mutated] and mutations in genes recurrently mutated in CLL (ATM, BIRC3, BRAF, CHD2, EZH2, FBXW7, MYD88, NOTCH1, POT1, RPS15, SF3B1, XPO1) were assessed at baseline in patients with and without PD at data cutoff; gene variants and resistance-associated mutations in BTK, PLCG2, or BCL2 were evaluated at PD. RESULTS: Of 191 patients completing fixed-duration ibrutinib plus venetoclax, with median follow-up of 38.9 months, 29 (15%) developed PD. No baseline risk feature or gene mutation was significantly associated with development of PD. No previously reported resistance-associated mutations in BTK, PLCG2, or BCL2 were detected at PD in 25 patients with available samples. Of the 29 patients with PD, 19 have required retreatment (single-agent ibrutinib, n = 16, or ibrutinib plus venetoclax, n = 3); 17 achieved partial response or better, 1 achieved stable disease, and 1 is pending response assessment. CONCLUSIONS: First-line fixed-duration combination treatment with ibrutinib plus venetoclax may mitigate development of resistance mechanisms associated with continuous single-agent targeted therapies, allowing for effective retreatment. See related commentary by Al-Sawaf and Davids, p. 471.

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.

Stability engineering of scFvs for the development of bispecific and multivalent antibodies.

Single-chain Fvs (scFvs) are commonly used building blocks for creating engineered diagnostic and therapeutic antibody molecules. Bispecific antibodies (BsAbs) hold particular interest due to their ability to simultaneously bind and engage two distinct targets. We describe a technology for producing stable, scalable IgG-like bispecific and multivalent antibodies based on methods for rapidly engineering thermally stable scFvs. Focused libraries of mutant scFvs were designed using a combination of sequence-based statistical analyses and structure-, and knowledge-based methods. Libraries encoding these designs were expressed in E. coli and culture supernatants-containing soluble scFvs screened in a high-throughput assay incorporating a thermal challenge prior to an antigen-binding assay. Thermally stable scFvs were identified that retain full antigen-binding affinity. Single mutations were found that increased the measured T(m) of either the V(H) or V(L) domain by as much as 14 degrees C relative to the wild-type scFv. Combinations of mutations further increased the T(m) by as much as an additional 12 degrees C. Introduction of a stability-engineered scFv as part of an IgG-like BsAb enabled scalable production and purification of BsAb with favorable biophysical properties.

Conserved amino acid networks involved in antibody variable domain interactions.

Engineered antibodies are a large and growing class of protein therapeutics comprising both marketed products and many molecules in clinical trials in various disease indications. We investigated naturally conserved networks of amino acids that support antibody V(H) and V(L) function, with the goal of generating information to assist in the engineering of robust antibody or antibody-like therapeutics. We generated a large and diverse sequence alignment of V-class Ig-folds, of which V(H) and V(L) domains are family members. To identify conserved amino acid networks, covariations between residues at all possible position pairs were quantified as correlation coefficients (phi-values). We provide rosters of the key conserved amino acid pairs in antibody V(H) and V(L) domains, for reference and use by the antibody research community. The majority of the most strongly conserved amino acid pairs in V(H) and V(L) are at or adjacent to the V(H)-V(L) interface suggesting that the ability to heterodimerize is a constraining feature of antibody evolution. For the V(H) domain, but not the V(L) domain, residue pairs at the variable-constant domain interface (V(H)-C(H)1 interface) are also strongly conserved. The same network of conserved V(H) positions involved in interactions with both the V(L) and C(H)1 domains is found in camelid V(HH) domains, which have evolved to lack interactions with V(L) and C(H)1 domains in their mature structures; however, the amino acids at these positions are different, reflecting their different function. Overall, the data describe naturally occurring amino acid networks in antibody Fv regions that can be referenced when designing antibodies or antibody-like fragments with the goal of improving their biophysical properties.

The balance of reproducibility, sensitivity, and specificity of lists of differentially expressed genes in microarray studies.

BACKGROUND: Reproducibility is a fundamental requirement in scientific experiments. Some recent publications have claimed that microarrays are unreliable because lists of differentially expressed genes (DEGs) are not reproducible in similar experiments. Meanwhile, new statistical methods for identifying DEGs continue to appear in the scientific literature. The resultant variety of existing and emerging methods exacerbates confusion and continuing debate in the microarray community on the appropriate choice of methods for identifying reliable DEG lists. RESULTS: Using the data sets generated by the MicroArray Quality Control (MAQC) project, we investigated the impact on the reproducibility of DEG lists of a few widely used gene selection procedures. We present comprehensive results from inter-site comparisons using the same microarray platform, cross-platform comparisons using multiple microarray platforms, and comparisons between microarray results and those from TaqMan - the widely regarded "standard" gene expression platform. Our results demonstrate that (1) previously reported discordance between DEG lists could simply result from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion with a non-stringent P-value cutoff filtering, the DEG lists become much more reproducible, especially when fewer genes are selected as differentially expressed, as is the case in most microarray studies; and (3) the instability of short DEG lists solely based on P-value ranking is an expected mathematical consequence of the high variability of the t-values; the more stringent the P-value threshold, the less reproducible the DEG list is. These observations are also consistent with results from extensive simulation calculations. CONCLUSION: We recommend the use of FC-ranking plus a non-stringent P cutoff as a straightforward and baseline practice in order to generate more reproducible DEG lists. Specifically, the P-value cutoff should not be stringent (too small) and FC should be as large as possible. Our results provide practical guidance to choose the appropriate FC and P-value cutoffs when selecting a given number of DEGs. The FC criterion enhances reproducibility, whereas the P criterion balances sensitivity and specificity.

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements.

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings.