FDA defines a biomarker as a characteristic “objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to therapeutic intervention.” FDA guidance further defines possible, probable, and known biomarker categories depending on the available scientific information on the marker. Biomarkers could be used in clinical medicine for disease diagnosis, indicators of disease status, or to predict and monitor response to treatment.

“Biomarkers could revolutionize both the development and use of therapeutics. The ideal biomarker would be highly predictive of clinical response,” says Richard Scheyer, M.D., executive director, translational medicine, Daiichi Sankyo Pharma Development.

“If the efficacy studies take several years and a large number of patients, a biomarker that could predict clinical response early, or even be a surrogate for the clinical endpoint, would be extremely valuable.”

But does a correlation between a certain biomarker and the health outcome always mean causation, and does biomarker response predict clinical outcome?

“The risk of relying on this hypothesis was underlined by the recent failure of Torcetrapib in clinical trials,” continues Dr. Scheyer, who was a speaker at Cambridge Healthtech’s “Biomarker World Congress” in Philadelphia in May.

Torcetrapib acts by inhibiting cholesteryl ester transfer protein, driving higher HDL and lower LDL cholesterol levels. Historical data shows an unambiguous correlation between high HDL/low LDL and a slower progression of artherosclerosis. However, the drug failed to demonstrate any benefit on carotid artery thickness, a measurement that reflects accumulation of artherosclerotic plaque.

“HDL/LDL is not the only example of biomarkers that correlate with health outcome but demonstrate no causative effects. This means that the intervention itself may have unintended effects on disease progression or that the disease itself may have other parallel processes,” continues Dr. Scheyer.

“Therefore, it is critical to understand what type of biomarker is being measured. Upstream biomarkers may be indicative of the effect on the target, whereas downstream biomarkers capture the convergence of various mechanisms and processes that result in the disease. It is highly unlikely that a biomarker will be found that fully predicts the clinical outcome of novel classes of medications. Nevertheless, even imperfect biomarkers can provide a bridge from nonclinical to clinical efficacy evaluation.”

Other presenters at the “World Biomarker Congress” also described how they used biomarkers in their research.

Automating the Knowledge Base

To understand the significance of each biomarker and its hierarchy in disease development, massive amounts of biological information about each molecule has to be compiled and analyzed.

This information-gathering process still requires manual assembly and analysis. It remains a labor-intensive hurdle for biomarker discovery. Ingenuity Systems addresses the analysis and interpretation bottleneck in biomarker discovery by extracting and systemizing biological and chemical knowledge.

“We provide a hypothesis-generation tool,” says Art Okamoto, product manager. “Ingenuity Pathway Analysis (IPA) delivers known attributes of the targets, maps them to the cellular pathways, and finds direct and indirect molecular relationships.”

Over the past eight years, Ingenuity has built up its knowledge database by systematically combing through publicly available literature and databases for bits of information about biomolecules, their interactions, and their relation to diseases. The data is unified by referencing various gene and protein annotations to NCBI Entrez GeneID.

IPA-Biomarker™ Analysis, within IPA, is used to identify biomarker candidates or compare biomarkers common between several samples, i.e., blood samples of patients with the same disease. Microarray or proteomics output from these samples is then narrowed down using several filters—such as differential levels of expression, species and tissue distribution, disease association, or prevalence in bodily fluids.

The end result is sets of unique and overlapping biomarkers complete with a knowledge summary and links to the original scientific literature.

This biomarker set could be further explored for association with cellular pathways and for mechanistic and functional relationships.

In May the company expanded its licensing agreement with Wyeth, which will utilize IPA in multiple research areas, including novel approaches to identifying biomarkers.

The FDA recognizes biomarkers as a critical element in evidence-based medicine. Absent new markers, advances in targeted therapy will be limited and treatment will remain largely empirical. Thus, it is imperative that biomarker development is accelerated along with the development of new therapies.

Targeted Therapies

“The role of companion diagnostics is changing,” says Walter P. Carney, Ph.D., Siemens Medical Solutions Diagnostics. “Several large pharmaceutical companies are already exhibiting forward thinking toward development of companion diagnostic products. The blockbuster drug model is slowly giving way to more targeted therapeutic options.

“The clinical failure of AstraZeneca’s Iressa®, indicated for the treatment of patients with advanced or metastatic non-small cell lung cancer, was perhaps a major wake-up call. A specific biomarker would increase the success of a drug like Iressa by selecting a smaller population with a higher response to the drug.”

Iressa targets epidermal growth factor (EGFR) in cancer cells. EGFR is a membrane-bound protein; its extracellular domain is shed from the surface of normal and cancer cells and can be detected in blood. Siemens Medical Solutions Diagnostics has developed an FDA-cleared test for the circulating oncoprotein HER-2/neu as well as a research-use only ELISA assay to measure circulating EGFR levels in clinical samples. Changes in serum levels of HER-2/neu or EGFR correlate with disease progression, and thus could be clinically useful in deciding on the course of therapy.

Siemens reports that it is also the first company to introduce a research-use ELISA assay for the circulating extracellular domain of carbonic anhydrase IX (CAIX), a biomarker of hypoxia.

“This biomarker can be measured by immunohistochemistry, ELISA, and imaging, thus presenting opportunities for continuous diagnostics throughout the course of the disease,” continues Dr. Carney. “Changes in CAIX circulating levels, as detected by ELISA, would indicate whether the tumor growth is recurring after the initial biopsy. The goal is to intervene at the earliest possible time and provide patients with a targeted treatment, such as Rencarex®.

Rencarex, a CAIX-specific antibody developed by Wilex, is currently in Phase III trials for treatment of nonmetastatic renal cell carcinoma. CAIX ELISA could also assist in predicting therapy outcome and in monitoring efficacy of Rencarex-mediated treatment.

Wilex has an imaging-diagnostic agreement with the nuclear medicine service department of Memorial Sloan Kettering Cancer Center. In the collaboration, G250, a CAIX-specific antibody conjugated with a contrast agent, is injected into renal cell carcinoma (RCC) patients and accumulation of the radioactive label is monitored by PET/CT imaging. The initial studies demonstrated a high degree of correlation between the label accumulation and RCC diagnosis.

“Targeted therapies are the way of the future. They result in fewer side effects and higher efficacy,” adds Dr. Carney.

“The advances in this space go hand-in-hand with the development of companion diagnostics, and circulating biomarkers fit perfectly with our vision at Siemens of combining circulating biomarkers (DNA, RNA, proteins or autoantibodies) with in vivo imaging. Circulating biomarkers provide real-time information about disease progression, and at some point our biomarker-based tests will be sensitive enough to deliver a long-term prognosis.”

Solving Analytical Hurdles

Analytical challenges in biomarker discovery seem rather daunting. Protein biomarkers are never completely present or absent, and sometimes a small change in concentration may correlate with a biological effect. In fact, biomarkers present in low concentrations may be the most clinically relevant. Biomarker variability between individuals is based not only on a genotype but also on the subject’s environment on the day of the sample collection. Therefore, setting a numerical value for a particular biomarker is difficult. In addition, well-annotated clinical samples are rarely available for biomarker research, as most pharmaceutical companies in possession of such samples are not engaged in biomarker discovery.

“Lastly, the experimental work flow of biomarker research stalls at the transition point between high-throughput untargeted biomarker identification and laborious low-throughput biomarker validation.

“There should be an intermediate step of relatively high-throughput target attrition, with the ultimate goal to reduce the number of targets chosen for final validation by at least a factor of ten,” comments Mark Garner, Ph.D., senior manager, translational sciences, Applied Biosystems (ABI). “We designed our workflow as a continuum between discovery and validation.”

For the untargeted discovery stage, ABI utilizes LC MALDI analysis of protein samples each labeled with a particular iTRAQ® labeling reagent. These isobaric labels consist of a reporter part and a balance part.

The reporter parts of the iTRAQ labels are different from each other by 1 atomic mass. This differential is balanced by the corresponding increase in the atomic mass of the balance parts, resulting in labels with identical m/z ratios.

When labeled samples are separated in a 4800 MALDI TOF/TOF analyzer, the label parts break off. Quantities of each label correlate with quantities of peptides in each sample. The ratio between labels indicates alterations in relative abundance of peptides between the samples. According to the company, up to eight samples can be multiplexed and quantified using this method.

Multiple Reaction Monitoring

For targeted analysis and verification of selected hits, ABI suggests the use of multiple reaction monitoring (MRM). “This is a standard analysis method for small molecule drugs,” continues Dr. Garner. “It has high specificity and sensitivity for detecting compounds in complex mixtures. We are the first to apply it to proteomics.”

MRM is done on a triple quadrupole mass spectrometer coupled with liquid chromatography. A peptide is identified based on the mass ratio of one of its fragments to the whole peptide. Over 150 MRMs (or peptides) could be detected in a single run.

“We have designed the 4000 Q TRAP® MS/MS system as a hybrid instrument, where the mass analyzer portion of the quad is also a linear ion trap. This is a critical distinction for proteomics analysis. It is likely that in a complex mixture of peptides several will have the same mass ratio. Our hybrid instrument not only quantifies peptides but also confirms their sequence by MS/MS.”

“Real-time PCR will remain a leading technology for comparing levels of expression of target genes,” says Mike Lucero, executive vp at Fluidigm. “Microarrays cover only three orders of magnitude. The power of real-time PCR is the ability to cover the dynamic range of six orders of magnitude, which translates into 1 to 100,000 gene copies per cell. This is a biological range that microarrays could not address. Real-time PCR demonstrates extreme sensitivity, allowing the detection of less than five copies of a target sequence. Real-time PCR enables the analysis of small samples like clinical biopsies or samples generated by laser capture microdissection.”

Despite these advantages, real-time PCR has not made a significant foray into biomarker validation because of major logistical barriers. Preparation and set-up of reactions require multiple mixing and loading steps, often times done manually. The cost of reagents for typical 10-µL reactions quickly becomes prohibitive. But probably the most significant limitation of real-time PCR is its low throughput.

“In a 384-well plate you can analyze 48 genes in only eight samples. Most of us got used to living with this limitation, but the ability to analyze more samples in parallel would open the doors for innovative experiments that are simply not possible right now,” continues Lucero.

Fluidigm developed BioMark 48.48 dynamic arrays for simultaneous real-time PCR analysis of 2,304 reactions, i.e., 48 genes in 48 samples. The set-up is limited to loading primers, samples, and the reaction master-mix. Next, the samples and reagents are automatically propelled into the corresponding chambers of the array. Sample chambers (9 nL) and assay chambers (1 nL) are linked by channels and regulated by integrated NanoFlex™ valves. A valve is also a channel embedded into elastomeric rubber, crosswise and directly above a liquid-carrying channel.

When 10-psi pressure is applied to the upper valve-channel, it balloons into the flow channel below. This “balloon” hermetically seals the flow channel and stops the flow of fluids. A 48.48 array contains 5,000 of these valves that pass fluids into chambers without cross mixing and with zero dead volume.

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