Development of reverse phase protein microarrays for the validation of clusterin, a mid-abundant blood biomarker

RPPA: Origins, Transition to a Validated Clinical Research Tool, and Next Generations of the Technology

RPPA technology has graduated from a research tool to an essential component of clinical drug discovery research and personalized medicine. Next generations of RPPA technology will be a single clinical instrument that integrates all the steps of the workflow.

High-Density Serum/Plasma Reverse Phase Protein Arrays

In-depth exploration and characterization of human serum and plasma proteomes is an attractive strategy for the identification of potential prognostic or diagnostic biomarkers. The possibility of analyzing larger numbers of samples in a high-throughput fashion has markedly increased with affinity-based microarrays, thus providing higher statistical power to these biomarker studies. Here, we describe a protocol for high-density serum and plasma reverse phase protein arrays (RPPAs). We demonstrate how a biobank of 12,392 samples was immobilized and analyzed on a single microarray slide, allowing high-quality profiling of abundant target proteins across all samples in one assay.

Characterization of protein expression levels with label-free detected reverse phase protein arrays

In reverse-phase protein arrays (RPPA), one immobilizes complex samples (e.g., cellular lysate, tissue lysate or serum etc.) on solid supports and performs parallel reactions of antibodies with immobilized protein targets from the complex samples. In this work, we describe a label-free detection of RPPA that enables quantification of RPPA data and thus facilitates comparison of studies performed on different samples and on different solid supports. We applied this detection platform to characterization of phosphoserine aminotransferase (PSAT) expression levels in Acanthamoeba lysates treated with artemether and the results were confirmed by Western blot studies.

Elucidation of the CHO Super-Ome (CHO-SO) by Proteoinformatics

Chinese hamster ovary (CHO) cells are the preferred host cell line for manufacturing a variety of complex biotherapeutic drugs including monoclonal antibodies. We performed a proteomics and bioinformatics analysis on the spent medium from adherent CHO cells. Supernatant from CHO-K1 culture was collected and subjected to in-solution digestion followed by LC/LC-MS/MS analysis, which allowed the identification of 3281 different host cell proteins (HCPs). To functionally categorize them, we applied multiple bioinformatics tools to the proteins identified in our study including SignalP, TargetP, SecretomeP, TMHMM, WoLF PSORT, and Phobius. This analysis provided information on the presence of signal peptides, transmembrane domains, and cellular localization and showed that both secreted and intracellular proteins were constituents of the supernatant. Identified proteins were shown to be localized to the secretory pathway including ones playing roles in cell growth, proliferation, and folding as well as those involved in protein degradation and removal. After combining proteins predicted to be secreted or having a signal peptide, we identified 1015 proteins, which we termed as CHO supernatant-ome (CHO-SO), or superome. As a part of this effort, we created a publically accessible web-based tool called GO-CHO to functionally categorize proteins found in CHO-SO and identify enriched molecular functions, biological processes, and cellular components. We also used a tool to evaluate the immunogenicity potential of high-abundance HCPs. Among enriched functions were catalytic activity and structural constituents of the cytoskeleton. Various transport related biological processes, such as vesicle mediated transport, were found to be highly enriched. Extracellular space and vesicular exosome associated proteins were found to be the most enriched cellular components. The superome also contained proteins secreted from both classical and nonclassical secretory pathways. The work and database described in our study will enable the CHO community to rapidly identify high-abundance HCPs in their cultures and therefore help assess process and purification methods used in the production of biologic drugs.

An 8 minute colorimetric paper-based reverse phase vertical flow serum microarray for screening of hyper IgE syndrome

A reverse phase serum array with the capacity of simultaneous detection in 113 samples was developed and optimized for a vertical flow 8-minute colorimetric assay detecting IgE.

Array-based proteomic approaches to study signal transduction pathways: prospects, merits and challenges

Very often dysfunctional aspects of various signalling networks are found to be associated with human diseases and disorders. The major characteristics of signal transduction pathways are specificity, amplification of the signal, desensitisation and integration, which is accomplished not solely, but majorly by proteins. Array-based profiling of protein-protein and other biomolecular interactions is a versatile approach, which holds immense potential for multiplex interactome mapping and provides an inclusive representation of the signal transduction pathways and networks. Protein microarrays such as analytical protein microarrays (antigen-antibody interactions, autoantibody screening), RP microarrays (interaction of a particular ligand with all the possible targets in cell), functional protein microarrays (protein-protein or protein-ligand interactions) are implemented for various applications, including analysis of protein interactions and their significance in signalling cascades. Additionally, successful amalgamation of the array-based approaches with different label-free detection techniques allows real-time analysis of interaction kinetics of multiple interaction events simultaneously. This review discusses the prospects, merits and limitations of different variants of array-based techniques and their promising applications for studying the modifications and interactions of biomolecules, and highlights the studies associated with signal transduction pathways and their impact on disease pathobiology.

Proteomic strategies for the discovery of novel diagnostic and therapeutic targets for infectious diseases

Viruses have developed numerous and elegant strategies to manipulate the host cell machinery to establish a productive infectious cycle. The interaction of viral proteins with host proteins plays an important role in infection and pathogenesis, often bypassing traditional host defenses such as the interferon response and apoptosis. Host–viral protein interactions can be studied using a variety of proteomic approaches ranging from genetic and biochemical to large‐scale high‐throughput technologies. Protein interactions between host and viral proteins are greatly influenced by host signal transduction pathways. In this review, we will focus on comparing proteomic information obtained through differing technologies and how their integration can be used to determine the functional aspect of the host response to infection. We will briefly review and evaluate techniques employed to elucidate viral–host interactions with a primary focus on Protein Microarrays (PMA) and Mass Spectrometry (MS) as potential tools in the discovery of novel therapeutic targets. As many potential molecular markers and targets are proteins, proteomic profiling is expected to yield both clearer and more direct answers to functional and pharmacologic questions.

Highly sensitive proximity mediated immunoassay reveals HER2 status conversion in the circulating tumor cells of metastatic breast cancer patients

Background

The clinical benefits associated with targeted oncology agents are generally limited to subsets of patients. Even with favorable biomarker profiles, many patients do not respond or acquire resistance. Existing technologies are ineffective for treatment monitoring as they provide only static and limited information and require substantial amounts of tissue. Therefore, there is an urgent need to develop methods that can profile potential therapeutic targets with limited clinical specimens during the course of treatment.

Methods

We have developed a novel proteomics-based assay, Collaborative Enzyme Enhanced Reactive-immunoassay (CEER) that can be used for analyzing clinical samples. CEER utilizes the formation of unique immuno-complex between capture-antibodies and two additional detector-Abs on a microarray surface. One of the detector-Abs is conjugated to glucose oxidase (GO), and the other is conjugated to Horse Radish Peroxidase (HRP). Target detection requires the presence of both detector-Abs because the enzyme channeling event between GO and HRP will not occur unless both Abs are in close proximity.

Results

CEER was able to detect single-cell level expression and phosphorylation of human epidermal growth factor receptor 2 (HER2) and human epidermal growth factor receptor 1 (HER1) in breast cancer (BCa) systems. The shift in phosphorylation profiles of receptor tyrosine kinases (RTKs) and other signal transduction proteins upon differential ligand stimulation further demonstrated extreme assay specificity in a multiplexed array format. HER2 analysis by CEER in 227 BCa tissues showed superior accuracy when compared to the outcome from immunohistochemistry (IHC) (83% vs. 96%). A significant incidence of HER2 status alteration with recurrent disease was observed via circulating tumor cell (CTC) analysis, suggesting an evolving and dynamic disease progression. HER2-positive CTCs were found in 41% (7/17) while CTCs with significant HER2-activation without apparent over-expression were found in 18% (3/17) of relapsed BCa patients with HER2-negative primary tumors. The apparent 'HER2 status conversion' observed in recurrent BCa may have significant implications on understanding breast cancer metastasis and associated therapeutic development.

Conclusion

CEER can be multiplexed to analyze pathway proteins in a comprehensive manner with extreme specificity and sensitivity. This format is ideal for analyzing clinical samples with limited availability.

Proteomic technologies for the identification of disease biomarkers in serum: advances and challenges ahead

Serum is an ideal biological sample that contains an archive of information due to the presence of a variety of proteins released by diseased tissue, and serum proteomics has gained considerable interest for the disease biomarker discovery. Easy accessibility and rapid protein changes in response to disease pathogenesis makes serum an attractive sample for clinical research. Despite these advantages, the analysis of serum proteome is very challenging due to the wide dynamic range of proteins, difficulty in finding low-abundance target analytes due to the presence of high-abundance serum proteins, high levels of salts and other interfering compounds, variations among individuals and paucity of reproducibility. Sample preparation introduces pre-analytical variations and poses major challenges to analyze the serum proteome. The label-free detection techniques such as surface plasmon resonance, microcantilever, few nanotechniques and different resonators are rapidly emerging for the analysis of serum proteome and they have exhibited potential to overcome few limitations of the conventional techniques. In this article, we will discuss the current status of serum proteome analysis for the biomarker discovery and address key technological advancements, with a focus on challenges and amenable solutions.

Reverse phase protein microarrays advance to use in clinical trials

Individualizing cancer therapy for molecular targeted inhibitors requires a new class of molecular profiling technology that can map the functional state of the cancer cell signal pathways containing the drug targets. Reverse phase protein microarrays (RPMA) are a technology platform designed for quantitative, multiplexed analysis of specific phosphorylated, cleaved, or total (phosphorylated and non-phosphorylated) forms of cellular proteins from a limited amount of sample. This class of microarray can be used to interrogate tissue samples, cells, serum, or body fluids. RPMA were previously a research tool; now this technology has graduated to use in research clinical trials with clinical grade sensitivity and precision. In this review we describe the application of RPMA for multiplexed signal pathway analysis in therapeutic monitoring, biomarker discovery, and evaluation of pharmaceutical targets, and conclude with a summary of the technical aspects of RPMA construction and analysis.

Serum S100A6 concentration predicts peritoneal tumor burden in mice with epithelial ovarian cancer and is associated with advanced stage in patients

BACKGROUND

Ovarian cancer is the 5th leading cause of cancer related deaths in women. Five-year survival rates for early stage disease are greater than 94%, however most women are diagnosed in advanced stage with 5 year survival less than 28%. Improved means for early detection and reliable patient monitoring are needed to increase survival.

METHODOLOGY AND PRINCIPAL FINDINGS

Applying mass spectrometry-based proteomics, we sought to elucidate an unanswered biomarker research question regarding ability to determine tumor burden detectable by an ovarian cancer biomarker protein emanating directly from the tumor cells. Since aggressive serous epithelial ovarian cancers account for most mortality, a xenograft model using human SKOV-3 serous ovarian cancer cells was established to model progression to disseminated carcinomatosis. Using a method for low molecular weight protein enrichment, followed by liquid chromatography and mass spectrometry analysis, a human-specific peptide sequence of S100A6 was identified in sera from mice with advanced-stage experimental ovarian carcinoma. S100A6 expression was documented in cancer xenografts as well as from ovarian cancer patient tissues. Longitudinal study revealed that serum S100A6 concentration is directly related to tumor burden predictions from an inverse regression calibration analysis of data obtained from a detergent-supplemented antigen capture immunoassay and whole-animal bioluminescent optical imaging. The result from the animal model was confirmed in human clinical material as S100A6 was found to be significantly elevated in the sera from women with advanced stage ovarian cancer compared to those with early stage disease.

CONCLUSIONS

S100A6 is expressed in ovarian and other cancer tissues, but has not been documented previously in ovarian cancer disease sera. S100A6 is found in serum in concentrations that correlate with experimental tumor burden and with clinical disease stage. The data signify that S100A6 may prove useful in detecting and/or monitoring ovarian cancer, when used in concert with other biomarkers.