The term "proteome" refers to the entire complement of proteins, including the modifications made to a particular set of proteins, produced by an organism or a cellular system. This will vary with time and distinct requirements, such as stresses, that a cell or organism undergoes. The term "proteomics" is a large-scale comprehensive study of a specific proteome, including information on protein abundances, their variations and modifications, along with their interacting partners and networks, in order to understand cellular processes. “Clinical proteomics” is a sub-discipline of proteomics that involves the application of proteomic technologies on clinical specimens such as blood. Cancer, in particular, is a model disease for applying such technologies to identify unique biosignatures and biomarkers responsible for the diagnosis, prognosis and therapeutic prediction of such disease. Biomarkers are biological molecules found in blood, other body fluids, or tissues that are a sign of a normal or abnormal process, or of a condition or disease. They may also be used to see how well the body responds to a treatment for a disease or condition.
The greatest promise for the detection and treatment of cancer lies in the deep understanding of molecular basis for disease initiation, progression and efficacious treatment based on the discovery of unique biomarkers. Although progress in cancer genomics has been rapid during the past few years, it only provides us with a glimpse of what may occur as dictated by the genetic code. In reality, we still need to measure what is happening in a patient in real time, which means finding tell-tale proteins that provide insight into the biological processes of cancer development. This is because genes are only the "recipes" of the cell, while the proteins encoded by the genes are ultimately the functional players that drive both normal and disease physiology.
The accessibility of cancer-related proteins in tissues and bodily fluids has triggered extensive protein-focused research for the hunt of “biomarkers.” Proteomics has the ability to interrogate a variety of biospecimens for their protein contents and accurately measure the concentrations of these proteins. This can provide scientists and clinicians with a powerful tool to understand the different processes involved in cancer development and progression in hope to identify biomarkers specific for these cellular processes along with those indicating efficacious therapeutic intervention.
The biggest conceptual challenge inherent in proteomics lies in the proteome's increased degree of complexity compared to the genome. For example:
In order to better understand cancer biology and to accelerate the development of both cancer diagnostics and therapeutics, biological insight from genomic analysis is being integrated with the analysis of protein content in tumor cells. By understanding the protein components resulting from genetic aberrations in cancer, scientists can begin to piece together what changes are occurring in a cancer proteome. Based upon the progress made in the reproducibility and transferability of proteomic workflows and methodology in the Clinical Proteomic Technologies for Cancer initiative launched in 2006, Clinical Proteomic Tumor Analysis Consortium (CPTAC), is to link cancer genome to proteome by systematically analyzing the protein content of tumors of which there is comprehensive genomic characterization from initiatives such as The Cancer Genome Atlas. This integrative approach will produce a deeper understanding of cancer biology, with high-quality datasets, reagents, and analytically validated quantitative assays to be made publicly available.
Described below are some of the main technologies being used to advance our understanding of protein biochemistry.
Mass spectrometry (MS) is an evolving technology that allows scientists to detect and quantify proteins in a complex biological matrix. Such methods are very precise, distinguishing proteins that differ in composition by a single hydrogen atom, the smallest atom. Despite its potential, MS technologies are not yet capable of separating the complex protein mixtures from unprocessed human biospecimens. Additional technologies such as organelle or protein fractionation or affinity capture have been developed to reduce the complexity of proteins in biospecimens by enriching for a subset of proteins of interest, in addition to improving the sensitivity of instrumentation for detection and quantification of proteins.
Protein microarrays are powerful tools for capturing and measuring proteins from biospecimen in a high throughput fashion. A protein microarray typically consists of a small piece of glass or plastic coated with thousands of "capture reagents" (molecules that can "grab" specific proteins). This technology allows scientists to isolate and study many potential biomarker proteins. Protein microarrays can be miniaturized to contain tens of thousands of capture features arranged in a grid, each specific for a given protein, therefore, they are considered a multiplexed device – for example, they can test for multiple biomarkers simultaneously, which is essential for clinical use.
Nanotechnology is the creation of manufacturing devices and components that range from 1 to 100 nanometers. A nanometer is one billionth of a meter, or 1/80,000 the width of a human hair. Nanotechnology devices have the potential to greatly expand the capabilities of proteomics, addressing current limitations in selectively reaching a target protein in vivo through physical and biological barriers, detecting low abundance targets, and providing a "toolbox" to translate the discovery of protein biomarkers to novel therapeutic and diagnostic tests. Typical nano-devices include nanoparticles used for the targeted delivery of anticancer drugs, energy-based therapeutics (including heat and radiation) and imaging contrast reagents. Nanowires and nanocantilever arrays can be used in biosensors that measure minute quantities of biomarkers in biological fluids.
For more information, see the NCI Alliance for Nanotechnology in Cancer
Major areas of focus in bioinformatics research include data modeling and database design, data interoperability and comparison, gene and protein expression analysis, structural predictions, vocabularies and ontologies, as well as modeling for systems biology. In the second phase of the CPTC program, the development of new bioinformatic tools for integrative analysis of genomic and proteomic data is necessary to drive the collaborative, multidisciplinary effort required to drive discovery from the laboratory to clinical practice.
Cancer research has come to rely heavily on the quality of biospecimens for the measurement of genetic and protein expression, and the linkage of that information with clinical status and disease pathways such as tumor growth, migration, metastasis, angiogenesis, and apoptosis (cell death). Since cancer diagnosis and treatment often begin with diagnostic biopsies followed by surgical resection of the tumor, there are many opportunities to collect valuable biospecimens for research. The NCI has recognized the critical need for research access to large numbers of high-quality biospecimens annotated with clinical data. NCI is addressing this critical need through its Office of Biorepositories and Biospecimen Research.
There is a growing need in the field of proteomics for high-quality, well-characterized standard reagents that can improve the specificity and reproducibility of proteomic technologies. One widely used reagent in proteomic research is an antibody, a naturally occurring serum protein whose biological role requires high-antigen specificity. They have long been useful as the capture and detection reagents in proteomics.
Alternative affinity reagents such as aptamers have recently shown great promise as an adjunct to antibodies. These nucleic acid-based molecules possess protein-binding specificity, similar to antibodies that make them useful as protein capture and detection reagents.
Standard proteomic reagents will be useful for many applications in cancer research, including: