Antibody array profiling reveals serum TSP-1 as a marker to distinguish benign from malignant prostatic disease

Serum proteome profiling of metastatic breast cancer using recombinant antibody microarrays

The driving force behind oncoproteomics is to identify biomarker signatures associated with a particular malignancy. Here, we have for the first time used large-scale recombinant scFv antibody microarrays in an attempt to classify metastatic breast cancer versus healthy controls, based on differential protein expression profiling of whole serum samples. Using this multiplexed and miniaturised assay set-up providing pM range sensitivities, breast cancer could be classified with a specificity and sensitivity of 85% based on 129 serum analytes. However, by adopting a condensed 11 analyte biomarker signature, composed of nine non-redundant serum proteins, we were able to distinguish cancer versus healthy serum proteomes with a 95% sensitivity and specificity, respectively. When a subgroup of patients, not receiving anti-inflammatory drugs, was analysed, a novel eight analyte biomarker signature with a further improved predictive power was indicated. In a longer perspective, antibody microarray analysis could provide a tool for the development of improved diagnostics and intensified biomarker discovery for breast cancer patients.

Quantitative proteomics for identification of cancer biomarkers

Quantitative proteomics can be used for the identification of cancer biomarkers that could be used for early detection, serve as therapeutic targets, or monitor response to treatment. Several quantitative proteomics tools are currently available to study differential expression of proteins in samples ranging from cancer cell lines to tissues to body fluids. 2-DE, which was classically used for proteomic profiling, has been coupled to fluorescence labeling for differential proteomics. Isotope labeling methods such as stable isotope labeling with amino acids in cell culture (SILAC), isotope-coded affinity tagging (ICAT), isobaric tags for relative and absolute quantitation (iTRAQ), and (18) O labeling have all been used in quantitative approaches for identification of cancer biomarkers. In addition, heavy isotope labeled peptides can be used to obtain absolute quantitative data. Most recently, label-free methods for quantitative proteomics, which have the potential of replacing isotope-labeling strategies, are becoming popular. Other emerging technologies such as protein microarrays have the potential for providing additional opportunities for biomarker identification. This review highlights commonly used methods for quantitative proteomic analysis and their advantages and limitations for cancer biomarker analysis.

Protein microarray platforms for clinical proteomics

Proteomics for clinical applications is presently in a state of transition. It has become clear that the classical approaches based on 2-DE and/or MS need to be complemented by different kinds of technologies. The well-known problems include sample complexity, sensitivity, quantitation, reproducibility, and analysis time. We suggest that the new technologies for clinical proteomics can be supported by antibody-centric protein microarray platforms. These platforms presently include antibody microarrays and lysate, or reverse capture/reverse phase protein microarrays. Other forms of these arrays are in less mature developmental stages, including ORF and self assembling protein microarrays. Bioinformatic support for interpreting these arrays is becoming more available as the whole field of systems biology begins to mature. The present set of applications for these platforms is profoundly focused on certain common cancers, immunology, and cystic fibrosis. However, we predict that many more disease entities will become studied as knowledge of the power and availability of these platforms becomes more widely established. We anticipate that these platforms will eventually evolve to accommodate label-free detection technologies, human genome-scale numbers of analytes, and increases in analytic and bioinformatic speeds.

Antibody arrays--an emerging tool in cancer proteomics

Cancer is a result of complex changes that occur in normal cells as they transform to become malignant and further when they become metastatic. These changes are not a consequence of a single protein but rather involve multiple proteins that function in pathways and networks. Thus, profiling cancer-associated changes requires simultaneous measurement of many proteins in a single sample. Identifying these changes may lead to the discovery of cancer-associated biomarkers that may assist in diagnosis, prognosis, patient monitoring and possibly for therapeutic purposes. Antibody arrays are a relatively new technology that enables one to perform multiplex high-throughput protein expression profiling. This review describes current technologies in antibody array and assay design, and presents a survey of the current literature on the use of these arrays in cancer research.