The clinical proteomic technology centers.

The use of mass spectrometry for clinical diagnostic applications for biomarkers of cancer is promising. Yet the challenges remain enormous. One of the biggest challenges is separating, measuring and analyzing the relevant proteins and peptides from human biological samples. Another prominent challenge is developing and applying the rigorous standards, protocols and metrics associated with clinical diagnostics to proteomic technologies and experiments. A new National Cancer Institute program seeks to address the second challenge.

In late September, the National Cancer Institute (NCI) announced $35.5 million in funding over five years for five Clinical Proteomic Technology Centers for Cancer Research (CPTAC). The Initiative will assess the use of current mass spectrometry and affinity capture platforms for applied clinical proteomics. In addition, CPTAC aims to develop standardized technologies, methods and protocols for each stage of the process, from sample collection through data analysis and storage.

The CPTAC is part of the Clinical Proteomic Technologies Initiative for Cancer (CPTI). Launched in 2005, the five-year, $104 million CPTI is comprised of three programs: CPTAC, the Advanced Proteomic Platforms and Computational Sciences, and the Clinical Proteomics Reagents Resource. The Advanced Proteomic Platforms and Computational Sciences program, for which funding estimates are put at $56 million over five years, will further the development of peptide measurement tools as well as computational methods. Funding for the Clinical Proteomics Reagents Resource, estimated at $12.5 million, will be a central source for reagents and will develop standard reagents. Award announcements for both programs will be made later this year.

In describing CPTAC, Dr. Henry Rodriguez, program director of the CPTI, told IBO, "The overall purpose of this program is to accelerate the implementation of proteomic analysis technology in identifying, validating and monitoring cancer-relevant proteins and peptides in clinical samples. Specifically, the CPTAC program is designed to develop multidisciplinary approaches to the evaluation and implementation of high-throughput mass spectrometry [MS] and affinity-based proteomics platforms pertinent to clinical cancer research."

The five Technology Centers (see table, page 6) and their collaborators will evaluate and compare proteomic platforms and develop standardized approaches and resources to analyze proteomic changes indicative of cancer in human clinical samples. According to Dr. Rodriguez, "The reviews identified superior institutions with outstanding expertise in technology assessment and development and team building. The selected multidisciplinary team adequately represents a broad range of commercially available MS proteomic platforms and analysis software and provides the most comprehensive approach to assess intra-platform and inter-laboratory variability and subsequent impact on eventual technology applications."

As specified in a pre-application meeting document, each CPTAC team will develop a proteomic analysis platform, and the teams will share materials, protocols, data, samples, algorithms and resources. Data, standards and samples and other resources will be publicly available. For measurement assessment materials, the NCI, in coordination with the National Institute of Standards and Technology, will provide Centers with "protein mixtures and prepared sample biological fluids."

In the paper "Clinical Proteomics: In Pursuit of 'True Biomarker Discovery,'" published in October 2005 in the journal Cancer Epidemiology Biomarkers and Prevention, Drs. Zhen Zhang and Daniel W. Chan highlight how variabilities in samples, techniques and experimental design of clinical proteomic studies have cast doubt on the validity of such studies' results. Specifically, the authors cite biological variability, preanalytical variability and analytical variability as issues that must be addressed. Biological variabilities include variations in protein expression across human populations and variations in disease classification. Preanalytical variations include variations in sample collection, handling and processing. Analytical variables include variations introduced by fractionation and protein depletion techniques as well as variations among mass spectrometry technologies.

The paper is an example of the types of critiques that CPTAC's efforts can address. "If proteomics technologies are to successfully be incorporated into clinical diagnostics, universally accepted metrics will be needed at many steps to clarify and compare experimental results and protocols. In addition, knowing sources of measurement variability, bias, and how to best address them is also important. This program aims to address each of these challenges," said Dr. Rodriguez.

Another issue addressed by Drs. Zhen Zhang and Daniel W. Chan is the complexity of the human proteome, including the wide dynamic range of proteins found in a clinical specimen. As Dr. Rodriguez put it, "One of the profound challenges in applied clinical proteomics is the need to handle complex biological mixtures, which are typical of clinical specimens. Moreover, method development is further complicated by a broad variability in protein concentrations that may exceed 10 orders of magnitude ('dynamic range').

The CPTAC request for applications (RFA) cited specific MS platforms, specifically, time-of-flight (TOF) MS, Fourier transform ion cyclotron resonance (FTICR) MS, tandem MS/MS and liquid chromatography (LC)-MS, as well as MALDI matrix-assisted laser desorption-ionization (MALDI) and electrospray-ionization (ESI) ionization sources. Ineligible for funding under this program were surface enhanced laser desorption ionization (SELDI) MS. In excluding SELDI, the program's Request for Application (RFA) stated, "Surface enhanced laser desorption ionization (SELDI) MS will not be considered for this RFA due to its limited ability to comprehensively measure and identify low abundance proteins in serum or plasma considered to be within the dynamic range of proteins released from cancer cells." Two-dimensional gel electrophoresis approaches were also ineligible for funding "because of the limited sample throughput inherent to the current implementations of that technology."

Specific affinity-based capture technologies, which include two-dimensional formats, such as protein slides, and three-dimensional formats, or bead-based techniques, were not specified in the RFA. Challenges for such platforms cited by Dr. Rodriguez in a May 2006 presentation are stability, specificity, sensitivity and selectivity.

For both MS and affinity capture technologies, the RFA explained, "Examples of relevant endpoints to address include, but are not limited to: reproducibility, dynamic range of measurable protein/peptide concentrations, the accuracy of molecular mass determination (in MS-based applications), sample throughput, detection specificity, peptide/protein identification and quantification, and unit cost per assay." Technical criteria for platform evaluation include resolution, accuracy, dynamic range, sensitivity and reproducibility. A presentation to technology vendors explained that the goal is the "assurance that protein measurement results are due to changes in the sample and not changes or variability due to: instrument; assay performance; reagents; operator; or site."

CPTAC could mark an important advancement in the development of MS for the diagnosis of cancer. As Dr. Rodriguez emphasized, "The existing proteomic platforms, such as those based on MS and protein affinity microarrays, have the potential to serve as clinical tools to interrogate the proteome. However, current implementations of these technologies suffer from inadequate methodologies for experimental calibration and standardization, reproducible assessment, and rigorous validation and comparison of results across institutions."

CPTAC Awardees

Broad Institute of MIT and Harvard Focus:

* Multiple reaction monitoring assays for the quantification of candidate-based protein markers in plasma.

* Use of a workflow involving strong cation exchange chromatographic fractionation of peptides and immunoaffinity enrichment on specific anti-peptide antibodies (stable isotope standards and capture by anti-peptide antibodies).

Memorial Sloan-Kettering Cancer Center 

Focus:

* Automated sample processing technology (robotics).

* The coupling of novel sample fractionation using magnetic beads for the capture of peptides prior to MS analysis.

Purdue University

Focus:

* New high-throughput immunoaffinity and other separations technologies and MS instrumentation, biofabrication expense, and well-conceived analysis methods for integrating and comparing proteomics data from different platforms.

* The development of a microarray platform employing interferometric analysis that offers the potential for label-free very high-throughput and sensitive analysis of small amounts of biological fluids.

University of California, San Francisco/Lawrence Berkeley National Laboratory/Buck Institute

Focus:

* The development of a new workflow for plasma protein analysis, and the development of novel methods to monitor the degree of degradation of banked biological samples.

* Posttranslational modifications, extensive technological platforms and sophisticated informatics infrastructure.

Vanderbilt School ef Medicine

Focus

* The use of multiple state-of-the-art MS instruments and front-end separation techniques, robust data handling and development of new algorithms to enable cross-platform and cross-database comparisons, and innovative approaches to undertake quantitative MS analyses of biological samples.

* Extensive comparison of shotgun-based techniques.

* Integration of different technologies for sample preparation, MS analysis, multiplex affinity arrays (reverse phase protein arrays and antibody arrays), data acquisition and analysis, and bioinformatics approaches.