Evaluation of a Validated Luminex-Based Multiplex Immunoassay for Measuring Immunoglobulin G Antibodies in Serum to Pneumococcal Capsular Polysaccharides.

This article describes the results of a study designed to bridge the World Health Organization (WHO) pneumococcal enzyme-linked immunosorbent assay (ELISA) platform to the validated Luminex-based 13-plex direct immunoassay (dLIA) platform developed by Pfizer, Inc. Both assay platforms quantify serotype-specific serum IgG antibodies (in micrograms per milliliter) against an international reference standard serum. The primary goal of this study was to determine if the dLIA is a suitable replacement for the ELISA to support clinical vaccine studies that include the evaluation of immune responses to serotypes 1, 3, 4, 5, 6A, 6B, 7F, 9V, 14, 18C, 19A, 19F, and 23F. Serum samples were selected from four pivotal 13-valent pneumococcal conjugate vaccine (13vPnC; Prevnar 13) clinical trials on the basis of their serotype-specific IgG concentrations by ELISA. In these studies, subjects were immunized either with 13vPnC or with 7-valent pneumococcal conjugate vaccine (7vPnC; Prevnar). There were 1,528 of 1,574 selected samples with sufficient remaining volume for reanalysis in the dLIA. A comparison of assay results from the dLIA and ELISA platforms showed clear and robust linear quantitative relationships across all 13 serotypes. In addition, lower IgG antibody concentrations in preimmunization samples were measured in the dLIA, thus allowing better differentiation between preimmunization and low-titer postimmunization samples. Overall, the results showed that the established population-level protective threshold IgG concentration, 0.35 µg/ml of serotype-specific serum IgG antibodies, is appropriate for use for data generated using the dLIA platform developed by Pfizer, Inc., for 10 serotypes: serotypes 1, 3, 4, 6A, 7F, 9V, 14, 18C, 19F, and 23F. On the basis of the extensive bridging analyses, however, the use of dLIA cutoff values of 0.23, 0.10, and 0.12 µg/ml is recommended for serotypes 5, 6B, and 19A, respectively. This adjustment will ensure that the consistency of the established population-level protective threshold IgG concentration is maintained when switching from the ELISA to the dLIA platform. The results of this bridging study demonstrate that the 13-plex dLIA platform is a suitable replacement for the WHO reference ELISA platform.IMPORTANCE The pneumococcal enzyme-linked immunosorbent assay (ELISA) measures IgG antibodies in human serum, and it is an important assay that supports licensure of pneumococcal vaccines. The immune correlate of protection, 0.35 µg/ml of IgG antibodies, was determined by the ELISA method. Pfizer has developed a new Luminex-based assay platform to replace the ELISA. These papers describe the important work of (i) validating the Luminex-based assay and (ii) bridging the immune correlate of protection (0.35 µg/ml IgG) to equivalent values reported by the Luminex platform.

The Biomarkers of Lupus Disease Study: A Bold Approach May Mitigate Interference of Background Immunosuppressants in Clinical Trials.

OBJECTIVE: Molecular medicine raised expectations for strategically targeted biologic agents in systemic lupus erythematosus (SLE), but clinical trial results have been disappointing and difficult to interpret. Most studies add investigational agents to various, often effective, standard therapy immunosuppressants used at baseline, with unknown treatment interactions. Eliminating polypharmacy in trials of active lupus remains controversial. We undertook the Biomarkers of Lupus Disease study to test withdrawal of immunosuppressants as a novel approach to rendering SLE trials interpretable. METHODS: In 41 patients with active, non-organ-threatening SLE flare (group A), temporary steroids were given while background immunosuppressants were withdrawn. Time to loss of disease suppression (time to disease flare) and safety were evaluated; standard therapy was immediately resumed when symptoms recurred. Immunologic impacts of standard therapy were studied at baseline by multiplex assay, enzyme-linked immunosorbent assay, and messenger RNA array in group A patients plus 62 additional patients donating a single sample (group B). RESULTS: Patients with lower or higher baseline disease activity had median times to flare of 71 or 45 days, respectively; 40 of 41 patients (98%) had disease flares by 6 months. All flares were treated and resolved within 6 weeks. No serious adverse events occurred from flare or infection. Type I interferon (IFN), Th17, and B lymphocyte stimulator pathways tracked together. Baseline immunosuppressants had distinct impacts on Th17 and B lymphocyte stimulator, depending on IFN signature. CONCLUSION: Trials in active, non-organ-threatening SLE can safely withdraw background treatments if patients who have disease flares are designated nonresponders and returned to standard therapy. Immunologic effects of standard therapy vary between IFN-defined subsets. These findings provide a strategy for minimizing or optimizing treatment combinations in lupus trials and clinical care.

Proteomic changes in cerebrospinal fluid of presymptomatic and affected persons carrying familial Alzheimer disease mutations.

OBJECTIVE: To identify cerebrospinal fluid (CSF) protein changes in persons who will develop familial Alzheimer disease (FAD) due to PSEN1 and APP mutations, using unbiased proteomics. DESIGN: We compared proteomic profiles of CSF from individuals with FAD who were mutation carriers (MCs) and related noncarriers (NCs). Abundant proteins were depleted and samples were analyzed using liquid chromatography-electrospray ionization-mass spectrometry on a high-resolution time-of-flight instrument. Tryptic peptides were identified by tandem mass spectrometry. Proteins differing in concentration between the MCs and NCs were identified. SETTING: A tertiary dementia referral center and a proteomic biomarker discovery laboratory. PARTICIPANTS: Fourteen FAD MCs (mean age, 34.2 years; 10 are asymptomatic, 12 have presenilin-1 [PSEN1 ] gene mutations, and 2 have amyloid precursor protein [APP ] gene mutations) and 5 related NCs (mean age, 37.6 years). RESULTS: Fifty-six proteins were identified, represented by multiple tryptic peptides showing significant differences between MCs and NCs (46 upregulated and 10 downregulated); 40 of these proteins differed when the analysis was restricted to asymptomatic individuals. Fourteen proteins have been reported in prior proteomic studies in late-onset AD, including amyloid precursor protein, transferrin, α(1)ß-glycoprotein, complement components, afamin precursor, spondin 1, plasminogen, hemopexin, and neuronal pentraxin receptor. Many other proteins were unique to our study, including calsyntenin 3, AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid) 4 glutamate receptor, CD99 antigen, di- N-acetyl-chitobiase, and secreted phosphoprotein 1. CONCLUSIONS: We found much overlap in CSF protein changes between individuals with presymptomatic and symptomatic FAD and those with late-onset AD. Our results are consistent with inflammation and synaptic loss early in FAD and suggest new presymptomatic biomarkers of potential usefulness in drug development.

Opportunities posed by novel patient selection biomarker approaches in oncology drug development: going beyond the cytotoxics.

An area of unmet medical need in clinical oncology has been optimizing patient selection for a given therapeutic with the goal of getting the right drug to the right patient. Recent studies have developed preclinical approaches to identifying molecular 'signatures of resistance' for cytotoxic therapies and prospective validation of this strategy is ongoing in the clinic. New challenges in this setting include identifying approaches to patient selection for cytostatic compounds such as signaling pathway inhibitors and stem cell targets. Here, we discuss the biomarker methodologies developed using traditional cytotoxic drugs and how these approaches can be adapted to identify biomarkers of patient selection for novel signaling inhibitors and other novel targets. It has become increasingly clear that such biomarker discovery and validation needs to begin early and continue throughout the drug development process.

Molecular classification of Crohn's disease and ulcerative colitis patients using transcriptional profiles in peripheral blood mononuclear cells.

Ulcerative colitis (UC) and Crohn's disease (CD) are common inflammatory bowel diseases producing intestinal inflammation and tissue damage. Although emerging evidence suggests these diseases are distinct, approximately 10% of patients remain classified as indeterminate inflammatory bowel disease even after invasive colonoscopy intended for diagnosis. A molecular diagnostic assay using a clinically accessible tissue would greatly assist in the classification of these diseases. In the present study we assessed transcriptional profiles in peripheral blood mononuclear cells from 42 healthy individuals, 59 CD patients, and 26 UC patients by hybridization to microarrays interrogating more than 22,000 sequences. Supervised analysis identified a set of 12 genes that distinguished UC and CD patient samples with high accuracy. The alterations in transcript levels observed by microarray were verified by real-time polymerase chain reaction. The results suggest that a peripheral blood mononuclear cell-based gene expression signature can provide a molecular biomarker that can complement the standard diagnosis of UC and CD.

Transcriptional profiles in peripheral blood mononuclear cells prognostic of clinical outcomes in patients with advanced renal cell carcinoma.

PURPOSE: Given their accessibility, surrogate tissues, such as peripheral blood mononuclear cells (PBMC), may provide potential predictive biomarkers in clinical pharmacogenomic studies. In leukemias and lymphomas, the prognostic value of peripheral blast expression profiles is clear; however, it is unclear whether circulating mononuclear cells of patients with solid tumors might yield profiles with similar prognostic associations. EXPERIMENTAL DESIGN: In this study, we evaluated the association of expression profiles in PBMCs with clinical outcomes in patients with advanced renal cell cancer. Transcriptional patterns in PBMCs of 45 renal cell cancer patients were compared with clinical outcome data at the conclusion of a phase II study of the mTOR kinase inhibitor CCI-779 to determine whether pretreatment transcriptional patterns in PBMCs were correlated with eventual patient outcomes. RESULTS: Unsupervised hierarchical clustering of the PBMC profiles using all expressed genes identified clusters of patients with significant differences in survival. Cox proportional hazards modeling showed that the expression levels of many PBMC transcripts were predictors for the patient outcomes of time to progression and overall survival (time to death). Supervised class prediction approaches identified multivariate expression patterns in PBMCs capable of assigning favorable outcomes of time to death and time to progression in a test set of renal cancer patients, with overall performance accuracies of 72% and 85%, respectively. CONCLUSIONS: The present study provides the first example of gene expression profiling in peripheral blood, a clinically accessible surrogate tissue, for identifying patterns of gene expression associated with higher likelihoods of positive outcome in patients with a solid tumor.

Population pharmacokinetics of CCI-779: correlations to safety and pharmacogenomic responses in patients with advanced renal cancer.

OBJECTIVE: Our objective was to estimate the pharmacokinetic parameters of CCI-779 and its metabolite, sirolimus, and evaluate associations of exposure parameters with safety and clinical activity. Exposure parameters were also correlated with pharmacogenomic responses in peripheral blood mononuclear cells (PBMCs). METHODS: In this randomized, double-blind, multicenter trial, once-weekly intravenous doses of 25, 75, or 250 mg CCI-779 were administered to patients with advanced renal cancer. Whole blood for CCI-779 and sirolimus concentrations was drawn. Population pharmacokinetic analyses yielded Bayesian-predicted exposure metrics that were correlated with severity and duration of adverse events and survival. PBMC samples taken before and after treatment were examined for pharmacogenomic responses. Ribonucleic acid samples were converted to labeled probes and hybridized to oligonucleotide arrays containing more than 12,600 human sequences. RESULTS: The final population pharmacokinetic models of CCI-779 and sirolimus included 235 and 305 observations, respectively, from 50 patients. For CCI-779, dose, single versus multiple dose, and body surface area were significant pharmacokinetic covariates. For sirolimus, dose and hematocrit were significant covariates. Age, sex, or race did not influence drug disposition. CCI-779 area under the curve correlated with adverse event severity for thrombocytopenia (P = .007), pruritus (P = .011), and hyperlipemia (P = .040). Exposure (CCI-779 cumulative area under the curve) correlated with a specific subset of gene transcripts in PBMCs following 16 weeks after therapy (P < .001, Spearman correlation). CONCLUSIONS: Concentrations of CCI-779 and sirolimus were adequately described with a population model incorporating factors for dose, attenuated exposure of multiple doses, body surface area, and hematocrit. Correlations with adverse event severity and duration profiles were provided to aid in the detection of treatment-emergent effects. Pharmacogenomic profiling of PBMCs identified altered ribonucleic acid transcript expression levels that correlate with exposure. These transcripts represent potential biomarkers of CCI-779 exposure in peripheral blood.

A novel approach to combinatorial library design.

We address the problem of designing a general-purpose combinatorial library to screen for pharmaceutical leads. Conventional approaches focus on diversity as the primary factor in designing such libraries. We suggest making screening libraries out of a set of pharmaceutically relevant scaffolds, with multiple analogs per scaffold. The rationale for this rests on the fact that even though the hit-rate in active series is much higher than in the database as a whole, often a large fraction of the compounds in active series are inactive. This is especially true when the series has not been optimized for the target under study. We introduce the concept of hit-rate within a series and use historic screening data to arrive at a crude estimate for it. We then use simple probability arguments to show that 50-100 compounds are required in each series in order to be nearly certain of finding at least one active compound in each true active series for any given target.