October 1, 2008 (Vol. 28, No. 17)

Lloyd Dunlap

Successful Programs Are the Result of Various Disciplines Working Together

One of the earliest examples of a vaccine biomarker assay still in use is the polio antibody neutralization assay, which evaluates the immunogenicity of different polio vaccines. This assay is used to support concomitant vaccine clinical trials and developing world implementation studies.

At the just-concluded Cambridge Healthtech “Biomarker Discovery Summit” in Philadelphia, Mark T. Esser, Ph.D., senior research fellow, vaccines and biologics research at Merck, noted that vaccine biomarker assays have been widely used for many years to evaluate both the immunogenicity and the efficacy of vaccines in clinical trials and postmarketing studies.

A successful example of using a vaccine biomarker assay in the development of a vaccine, Dr. Esser said, is the serum bactericidal assay developed for Neisseria meningitidis type C. The results from this biomarker assay were used to license a Meningitis C conjugate vaccine in the U.K., without performing a clinical efficacy study.

Dr. Esser’s talk focused on vaccines, biomarkers, and correlates of protection. Multiplexed antibody biomarker assays use either spotting array technologies or microsphere array technologies to monitor the antibody response to multiple antigens simultaneously.

Merck’s HPV serology assay is based on Luminex’ xMAP technology, which uses multicolored microspheres and the principles of flow cytometry. The technology enables users to perform up to 100 biomarker assays simultaneously on a single sample, Dr. Esser noted. The Merck HPV serology assay simultaneously measures the immune antibody response to neutralizing epitopes on several virus-like particle (VLP) types. Multiplexing an assay allows a generation of more results, quickly and cost effectively compared to running traditional single-test biomarker assays.

Correlates of Protection

The FDA defines a correlate of protection as a laboratory parameter that has been shown, from adequate and well-controlled clinical trials, to be associated with protection from clinical disease, Dr. Esser continued.

Correlates of protection exist for some older vaccines such as Recombivax™ and Energix® for heptatitis B, for which the internationally agreed upon correlate of protection is 10 ml of anti-Hep B surface antigen antibodies. For newer vaccines, such as Gardasil™ for the prevention of cervical cancer, and Rotateq™ for the prevention of rotavirus-induced diarrhea, correlates of protection have not yet been determined, he noted.

Several different biomarker assays were used in the development of Gardisil™. Virus neutralization assays, multiplexed Luminex-based antibody assays, T cell immunology assays, and molecular assays for detecting HPV type-specific infections were all developed to support both pre-clinical animal studies and Phase I–III clinical trials, Dr. Esser explained.

Early in development, serology assays showed that a quadrivalent HPV type 6, 11, 16, and 18 VLP vaccine formulated on Merck’s aluminum adjuvant was immunogenic and elicited T cell responses and both serum and mucosal antibodies in animal models. In clinical development, an HPV 6, 11, 16, and 18 multiplexed, competitive Luminex® Immunoassay was used to select the optimal formulation in dose ranging studies, to show the long-term duration of antibodies following vaccination and the presence of immune memory.

Molecular HPV genotyping assays were also used in clinical development to determine whether cervical or genital lesions were caused by HPV 6, 11, 16, 18, or nonvaccine HPV types. More importantly, the immunology assay was used in an immunobridging study in 9–15 year-old females. The results indicated that Gardasil was safe and immunogenic in this population. The antibody biomarker data were included in the new drug application for Gardasil in adolescent females.

Nongenotoxic Carcinogenicity

In her presentation, Nandini Raghavan, Ph.D., the principal biostatistician in the nonclinical biostatistics department at Johnson & Johnson Pharmaceutical Research & Development, described the development of a gene-expression based signature to predict nongenotoxic carcinogenicity (NGTC) with high accuracy using 24-hour microarray experiments on rats. Dr. Raghavan pointed out that this is especially critical, since short-term assays for nongenotoxic carcinogenicity—which is commonly observed in long-term rodent studies—have proven difficult to develop. Prime objectives of the study were development, validation, and standardization of biomarkers for safety evaluation.

Dr. Raghavan noted that high-throughput genomic technologies are being introduced at a rapid pace, and that these require sophisticated analysis strategies.

“This represents a paradigm shift and data analysis software tools cannot be used,” she stated. “We’re interrogating 35,000 sequences at a time, so the chance of picking up false positives is quite high. Overfitting is a significant problem, leading to nonreproducible results.”

Data Analysis for Predictive Markers

Data analysis must be carefully designed, Dr. Raghavan observed, in order to come up with results that are reproducible and real. Scientists in J&JPRD’s mechanistic toxicology group looked for a small set of genes that can predict NGTC in compounds using 24-hour experiments. The experimental protocol called for high doses of known NGTC and non-NGTC drug compounds to be administered to rats. Subsequent extraction of mRNA from their liver tissue and analysis for gene expression changes were used as predictive markers of changes that might presage NGTC down the road.

The methodology—ensemble classification algorithm, based on the well-established algorithm, linear discriminant analysis—was used to generate gene-signatures to predict which class (NGTC or non-NGTC) a compound will fall into.

“Ensemble algorithms such as the well-known random forest,” Dr. Raghavan said, “were used to look for partitions where compounds from each class fall on one side or another.”

The ensemble approach is based on identifying several such partitions and aggregating the results, “which gives you a much more robust classifier,” she noted. Another main thrust of this methodology is the elimination of noisy genes, and a number of strategies developed in-house are used to select genes with high differential expression.

Regulatory agencies are interested in incorporating these screens into their regulations, Dr. Raghavan continued. “This is just a starting point, but it’s a good starting point. We need a lot of validation with vigilance about overfitting at every stage.”

Multiplex Biomarker Assays

Michael Pisano, Ph.D., president and CEO of NextGen Sciences, pointed out that NGS has developed a suite of biomarker mass spectrometry-based services that utilize proprietary methods to significantly decrease timelines and increase success rates traditionally associated with the various stages of biomarker development.

“We can move very rapidly through discovery to assay and into validation without spending lots of time and money,” Dr. Pisano stated.

NGS offers mass spectrometry-based biomarker services that utilize proprietary methods to significantly decrease timelines and increase the success rates traditionally associated with biomarker development. The suite of services, called biomarkerexpress™, includes discovery of protein biomarkers, development of protein biomarker assays, and testing of biological samples to validate putative protein biomarkers and/or determine levels in preclinical and clinical samples. NGS’ emphasis is on protein biomarker assay development and testing of levels in biological and clinical samples.

The company’s peptide multiple reaction monitoring (pMRM) assay is very specific for targeted proteins, Dr. Pisano notes, including post-translational modifications, isoforms and fragments, and provides absolute or relative quantification based on mass spectrometry. The technology directly measures the protein, not the reaction of antigen and antibody, as done in ELISA and immunoassays. pMRM requires small sample sizes and is applicable to biofluids, tissues, cells, and formalin fixed paraffin embedded tissue.

The biomarkerexpress suite includes discoveryexpress™, assayexpress™, testingexpress™, and biomarker library™. The mass spec-based assay platform reduces development time. The multiplexing capability of the pMRM assay easily processes 30–50 proteins simultaneously and can go as high as 100 proteins.

Dr. Pisano commented, “We have disease specific and biofluid specific panels and assays available and continue to develop new panels and assays. The clients also have the ability to customize a panel or assay for their needs.”

He also presented a case study relevant to the discovery and assay development for putative biomarkers of lung cancer progression. The study performed quantitative protein profiling of the conditioned media obtained from A549 lung adenocarcinoma cells undergoing TGFalpha induced epithelial-mesenchymal transition (EMT), which results in changed cell morphology and acquisition of a migratory and invasive phenotype. Cells undergoing EMT would mimic circulating tumor cells or cells in the process of metastasis. Therefore, NGS researchers theorized that secreted proteins from these cells may represent protein secreted by tumor cells in the early stages of metastasis.

pMRM was used to measure all of the proteins on the panel in both conditioned media from A549 cells and subsequently plasma samples from patients with various stages of lung cancer.

A “relative quantitative assay” was developed and tested in a four-week timeframe. Preliminary data from a small patient population shows great potential for this technology, Dr. Pisano reported, with comparable results “from model to patients (sectretome to plasma)”.

Several proteins that were demonstrated to increase in the conditioned media also increased in plasma with progression of disease. Further work is going to verify and validate the panel for use in drug screening in vivo. Dr. Pisano explained that concurrently, testing across a larger population of patients will be performed.


Zhenhao Qi, Ph.D., senior principal scientist, translational sciences, Boehringer Ingelheim Pharmaceuticals, noted an increasing demand for mechanism of action (MOA) biomarkers in Phase I trials to demonstrate that the compound hits the target in vivo and allows better decision making at this early phase.

Biomarker discovery cannot be easily achieved by a single scientist within a single discipline, Dr. Qi observed. “For this program, we have involved scientists from genomics, statistics, molecular biology, bioinformatics/computational biology, therapeutic areas like immunology and inflammation, medical and clinical, and scientists from wet labs to dry labs.

“This core team worked together using a streamlined, iterative process: hypothesis/ experimental design, wet lab experiments, and statistical analysis followed by team discussion, conclusions and recommendations. Then we continued onto the next round of iteration.”

While a genome-wide search may yield ample number of genes that show significant response to stimuli of a biological pathway, this is not sufficient for those genes to be qualified as MOA biomarkers, Dr. Qi noted. To achieve this, the genes need to have functional relevance to the NFKB-IKKbeta pathway.

“Specifically, we need to have literature or publication support showing that those genes are regulated by NFKB (through transcription, gene expression etc.),” he said. “This is where literature/pathway knowledge-base and tools come into play. In addition, those genes’ response to stimuli should be inhibited by IKKbeta inhibitor.”

Statistical Analysis

The in vitro liposaccharide stimulant (LPS) whole blood assay is the major assay for this biomarker hunting, Dr. Qi noted. Two of the big challenges of biomarker discovery are a high degree of interindividual variability and sensitivity that is responsiveness to low concentration of inhibitor (compound).

“The statistics play an important role here,” he said. “We have to do iterative experiments with a certain number of donors. The statistical analysis guides us toward optimal LPS concentration for in vitro stimulation, that is the optimal inhibition window for an IKKbeta inhibitor.”

Two genes were identified as high potential biomarkers—IL6 and IL1b as mRNA biomarkers—then subsequently as protein biomarkers. In both cases, responses were statistically significant at their EC50 concentrations in the gene (Taqman) and protein (ELISA) expression experiments with a full dose range of inhibitor. These two genes will serve as ex vivo predictive MOA biomarkers in the Phase I trial.

The Phase I trial ex vivo study protocol will: 1) Dose volunteers with compound/ inhibitors, 2) take blood at estimated Cmax and Cmin, and 3) stimulate cells from blood with LPS and look for downstream readouts—ELISAs for IL-6, IL1b.

Metabolic Syndrome

Jin Sam You, Ph.D., of Monarch LifeSciences noted that cardiovascular disease (CVD) and atherosclerosis is the leading cause of death in the U.S.

CVD is greatly exacerbated by metabolic syndrome which is characterized by a group of risk factors including obesity, dyslipidemia, glucose intolerance, insulin resistance, and hypertension. Many studies have linked high saturated fat and fructose diets to insulin resistance and diabetes, Dr. You said. Ossabaw swine fed an excess calorie, high trans-fat/cholesterol diet develop all components of MetS.

Pigs provide a good research model in translational research because they have anatomy, physiology, and pathophysiology comparable to humans, You continued. They develop similar vascular disease and have similar lipid profiles. Additionally, their vessel size is similar to that of humans, which allows for clinically relevant interventions to be assessed. The Ossabaw miniature swine is unique among pig animal models in that the Ossabaw pig mimics humans by developing metabolic syndrome and atherosclerosis when maintained sedentary on an excess calorie atherogenic diet.

Differential Expression Analysis

In the discovery phase, differential expression proteomic analysis was obtained using an LC/MS-based label-free protein quantification method to profile the global protein expression.

Subsequent statistical modeling was utilized to select proteins for a predictive or diagnostic biomarker panel, Dr. You added. Candidate biomarkers will be validated by developing and using targeted MRM/SRM mass spec assays (LifeMarker™ assays) and testing the candidate biomarkers in new, larger sample sets. This panel of biomarkers will then be used in the development of clinically useful diagnostic tools that are more predictive than those currently available.

Atherosclerosis in Ossabaw swine was demonstrated to increase with severity of MetS as confirmed grossly and by angiography and intravascular ultrasound. The label-free LC/MS-based quantitative proteomic analysis method of protein expression profiles was validated in this model by reproducing known correlations to atherosclerosis and metabolic syndrome, Dr. You concluded. The many proteins identified provide a great opportunity to find biomarkers and predictive panels of biomarkers for cardiovascular disease.

Mass Spec Platforms

Critical to using mass spectrometry platforms for biomarker development is the need to progress from the general profiling of proteins to the targeting of specific protein panels, Randall W. Nelson, Ph.D., research professor and director of the molecular biosignatures analysis unit at The Biodesign Institute, Arizona State University.

The value of such a targeted approach, Dr. Nelson observed, lies in the ability to differentiate microheterogeneity in the proteins under investigation—variation in the chemical structure of the amino acid sequence of a protein that does not produce a major change in its properties such as gene, translational, and posttranslational modifications—and to generate data on only the specific molecular determinants relevant to disease. His talk focused on using targeted mass spectrometric immunoassays to investigate human plasma and urinary proteins in healthy and disease cohorts.

Dr. Nelson’s group uses mass spectrometry to identify biomarkers by looking for specific variances in proteins, characterizing them one by one. Plasma protein is increasingly their area of interest.

While Dr. Nelson served as the president, CEO, and founder at Intrinsic Bioprobes, the company adopted a strategy by looking at routine proteins in more detail and identified post-translational modifications, point mutations, variants, and truncations that defined the proteome. These variants, in turn, provide information that can be used to design targeted diagnostic assays, stratify patients in clinical trials, monitor patients more effectively, and facilitate pharmacokinetic studies by following in vivo changes of therapeutic proteins.

Dr. Nelson shared results with the conference illustrating the ability to detect low level protein variants relevant to type 2 diabetes, and how these findings are subsequently used to develop advanced assays for disease diagnosis and monitoring. Currently, these assays are out of R&D and being used in CLIA labs. Dr. Nelson forsees diagnostic use within the next 5–10 years.

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