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|Advancing Beyond the Genome with Affinity Proteomics|
Advancing Beyond the Genome with Affinity Proteomics
Until recently, the field of disease proteomics was focused on separation techniques coupled with mass-spectrometric identification of proteins. However, technological limitations due to patient-to-patient variability and loss of signal from low-abundance proteins have lead researchers to a different technique: affinity proteomics.
Based on the use of capture reagents such as antibodies, affinity proteomics has emerged as a tool capable of gathering information on the global level in a high-throughput format. In the last 10 years, antibody microarray technology rapidly evolved from proof-of-concept to state-of-the-art technology capable of targeting complex, nonfractionated protein samples.
Multiple versions of affinity reagents are deployed in this space, including full-length antibodies, aptamers, affibody molecules, and single-chain variable fragments of antibodies. Various capture formats are also being explored, ranging from planar arrays (similar to commonly used printed DNA arrays) to beads, to direct synthesis of antibodies in the array format.
Affinity arrays are rapidly emerging as powerful biomarker discovery tools and have become key topics for discussion at biotech conferences worldwide. Antibody-based proteomics has already delivered multiple specific biomarker candidates, and many of those are being translated into clinical practice.
“The field of disease proteomics is in agreement that a clinical state is more likely to be described by a complex protein signature rather than a single biomarker,” says Christer Wingren, Ph.D., associate professor, CREATE Health and department of immunology, Lund University.
“Under the assumption that the immune system is highly sensitive to changes in health, like a sensor, we decided to focus on inflammatory and immunoregulatory proteins,” continues Dr. Wingren, who spoke at the Select Biosciences Advances in Microarray Technology meeting in March in Edinburgh.
“Our arrays combine molecules commonly associated with immune system regulations, but their combinations, or signatures, are unique to each disease. Moreover, these signatures seem to be robust enough to cope with population biological variability.”
Dr. Wingren’s team worked closely with clinicians to determine unmet clinical needs that could be addressed by serum proteomics. Systemic lupus erythromatosis (SLE) is a severe autoimmune disease, diagnosed on the basis of multiple clinical criteria. A more precise diagnosis of SLE, including classifying it in categories and predicting the onset of flare, would enable rheumatologists to optimize therapy accordingly.
“We also had to adapt our technology to a common clinical format, which means using crude unfractionated blood samples,” continues Dr. Wingren. “Our cross-disciplinary approach led to simultaneous optimization of all major array parameters, including antibody design, array surface, sample handling, array detection, and bioinformatic analysis, which has turned out to be essential in our efforts to design a state-of-the-art antibody array platform.”
The team used well-characterized single-chain antibody fragments directed against a few hundred key analytes involved in immunoregulation. Serum proteome profiles revealed SLE-specific inflammatory portraits. Moreover, the signatures were able to differentiate between phenotypic subsets of SLE, as well as between states of flare and remission.
Immunovia, a Lund University spin-off, will continue to validate and commercialize diagnostic tests based on the immune signatures. Notably, Dr. Wingren says he and his team have also made significant progress in defining cancer-associated biomarker signatures using the same technology platform.
Inflammatory Signaling Pathways
“RayBiotech Quantibody?7000 sandwich-based array offers global profiling of 320 unique proteins related to cytokine signaling. Our targeted arrays help to narrow down specific signaling pathways. Even more focused arrays, such as the T-helper array, allows researchers to identify cell functions via cytokine expression profiles.”
RayBiotech’s Quantibody Multiplex ELISA Antibody Arrays provide quadruplicate data points to accurately measure the concentrations of up to 40 proteins simultaneously in 100 µL of sample. The array map depicted here is for the Human Quantibody Th1/Th2 Cytokine Array.
RayBiotech antibody arrays are used for probing disease processes, particularly when only a few details are known. For example, use of a broad screening array confirmed the long-suspected role of inflammation in autism by detecting high expression of inflammatory cytokines in brains of autistic patients.
“We are committed to making our technology valuable for biomarker discovery and validation,” Burkholder continues. “In a benchmark study, RayBiotech’s C-1000 120-cytokine screening array was used to profile plasma from patients with the confirmed Alzheimer disease diagnosis and from matched controls.”
Prediction analysis and cross-validation established an 18-marker signature, which was able to correctly predict clinical diagnosis of Alzheimer disease with 89% accuracy, Burkholder claims. “Cytokine biology is exceedingly complex, and we are yet to exhaust discovery opportunities in this space,” he says.
“We are not just a supplier for biomarker discovery, we are a partner,” he adds. The company supports biomarker discovery efforts on its platform through a grant program. RayBiotech also offers biostatistics and bioinformatics support, and provides comprehensive testing and validation services.
RayBiotech, which was on the program at the St. John’s University Biotechnology Colloquium last month, has even published its own biomarker research, in which human proteins were screened simultaneously in samples of patients with ovarian cancer and of normal subjects. The five-marker cytokine signature identified via the screen is now being validated by quantitative antibody arrays. The firm believes that this and other affinity signatures hold a promise of early diagnosis of cancer, when the treatment is most effective.
Larger Profiling Studies
The goal of the Human Protein Atlas is to systematically explore the human proteome using an affinity-based approach. At the time this article was written, the Atlas contained 15,598 antibodies targeting 12,238 genes. Antibodies are developed in a high-throughput manner against recombinant protein epitope signature tags, selected based on their low homology to other proteins.
“To retrieve these epitopes for protein profiling, we heat-denature biological samples in a controlled manner. The heat treatment exposes the epitopes that may be otherwise hidden by native protein conformations. This makes recognition of some protein targets more efficient,” says Dr. Schwenk, who also gave a presentation at the Select Biosciences conference in Edinburgh. “This feature enables us to use crude unfractionated blood and urine samples for biomarker discovery.
“We generally utilize bead arrays, where antibodies are coupled onto beads with distinctive color codes. Bead arrays have notable advantages over planar arrays. Beads can be mixed to achieve any desired combination of antibodies. The capture process can be analyzed by flow cytometry with dual laser, where one of the lasers reads the bead identity, and another analyzes interaction with captured protein target.”
This format proved to be highly sensitive, with only 10 µL of plasma required for analysis of 10,000 target proteins, according to Dr. Schwenk. The process lends itself well to larger-scaled profiling studies within disease proteomics, with hundreds of thousands of assays performed in a single day.
The team recently described human fibulin-1 as a candidate marker for renal impairment. High-throughput profiling of samples from patients with renal impairment and from controls revealed significant differences in levels of fibulin-1. The team is validating this marker using other clinical assays.
OncoMark is focused on tissue-based biomarkers as targets for drug development. Starting with primary tumor resections represented in an array format, Dr. Gallagher’s academic group developed a signature consisting of three proteins that predict the probability of cancer recurrence.
Use of IHC-MARK to quantify differential expression of a nuclear biomarker in tumor tissue. Images on the top represent a highly biomarker-positive tumor sample, while images on the bottom row represent a mostly biomarker-negative tumor sample. Images on the left are the original IHC-stained tissues, while equivalent regions with mark-up showing biomarker expression are on the right. Red indicates biomarker-positive nuclei, while blue indicates biomarker-negative nuclei. [University College Dublin]
“As we can analyze hundreds of tissue samples at the same time, we can fast-track development of biomarkers,” continues Dr. Gallagher, who provided a detailed deion of his research at the Edinburgh meeting.
“For example, we found that patients’ outcome, and potentially their response to chemotherapy, is regulated in a significant way by immune cell infiltration into tumors. Moreover, we were able to identify specific macrophage populations that may present novel targets for antitumor therapies.”
The key enabling technology is OncoMark’s IHC-MARK software, which can recognize the specific morphological features of tumor cells and automatically quantify levels of biomarkers in these malignant cells. OncoMark used this approach to investigate the roles of novel candidate biomarkers in the progression of malignant melanoma for a European Union-funded program, Target-Melanoma.
The technology has also proven to be valuable in a more traditional diagnostic application. The single most important assessment for any breast cancer patient is the hormone receptor levels, determined by immunocytochemistry. The response to tamoxifen therapy is predicted by the percentage of cells positive for the estrogen receptor. Actual scoring of positive cells is very subjective and can lead to a large number of false positives and false negatives.
IHC-MARK’s objective scoring accurately predicted response to hormonal therapy in a randomized controlled trial involving over 500 patients, Dr. Gallagher reports. OncoMark is currently combining the detection capabilities of IHC-MARK with novel biomarker content, particularly indicators of response to both classical chemotherapy and molecularly targeted agents.
Due to the complexity of the human proteome, large dynamic range in protein concentrations, and changes of protein abundance due to minor physiological stimuli, processing of samples for proteomic analysis is a challenging task.
“Over a period of 10 years, we have systematically developed methods for protein extraction from tissues that provide maximum protein solubilization and preserve protein native conformation,” says Joerg Hoheisel, Ph.D., head of functional genome analysis, German Cancer Research Center.
Protein analyses on an array of some 800 antibodies that target cancer-related proteins. Left, the origin of the antibodies was determined with two fluorescence-labeled anti-IgG antibodies (green: mouse; red: rabbit). The other panels show the result of two-color analyses of protein extracts from human serum (middle) and pancreatic cancer tissue (right)
“We found that depletion of high-abundance proteins and other types of fractionation led to co-depletion of minor proteins and, therefore, introduced a strong bias in protein representation,” explains Dr. Hoheisel, one of the key presenters at the U.S. HUPO Conference on the Future of Proteomics in March in San Francisco.
“Our goal was to create a set of reproducible conditions for protein analysis by antibody arrays using unfractionated body liquids and tissue samples. An entirely new protein purification and hybridization strategy had to be worked out for the antibody arrays.”
Once the appropriate conditions were optimized, Dr. Hoheisel’s group was able to establish distinct pancreatic cancer signatures by analyzing nearly 900 samples. Another signature forecasts the recurrence of bladder cancer.
Similar to cDNA microarrays, antibody arrays are analyzed by two-color fluorescent assay. Moreover, in certain conditions only one dye molecule binds one protein molecule. The team adapted already existing single-molecule detection techniques to visualize individual affinity capture events.
Selective illumination excites fluorophores only in a small region of the specimen immediately adjacent to the glass-water interface. Such a readout allows for easier discrimination between fluorescence arising from captured molecules and background caused by light scattering at the surface.
Using this approach, as few as 600 molecules per spot could be detected and counted. The team applied this method to develop a proof-of-concept diagnosis of tuberculosis based on capture and detection of lipoarabinomannan, a polysaccharide marker of tuberculosis. Current tuberculosis diagnosis is not sensitive enough to detect the infection at early stages when the treatment may be the most effective.
With the rapid re-emergence of tuberculosis worldwide, a reliable and sensitive diagnosis is of critical importance for disease control. Antibody capture combined with fluorescence detection seems to be well positioned to address this growing need.
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