Contact spotting of protein microarrays coupled with spike-in of normalizer protein permits time-resolved analysis of ERBB receptor signaling

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.

Modulation of c-kit expression in pancreatic adenocarcinoma: a novel stem cell marker responsible for the progression of the disease

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers because of late symptoms and resistance to chemotherapy and radiation therapy. We have investigated the appearance of c-kit, a stem cell marker, in both normal adult pancreatic tissue and in cancerous tissue. Apart from some very pale staining of islets of Langerhans, normal pancreas was devoid of staining with antibodies to c-kit. In contrast, in cancerous tissue that still preserves the overall integrity of the pancreatic tissue, there was a clear labeling in islets of Langerhans, which seemed to be co-localized with insulin containing β cells. In other cases, where the pancreatic tissue was completely deteriorated, intensive labeling was clearly evident in remnants of both the exocrine and the endocrine tissues. The duct cells of the adenocarcinoma were moderately but clearly labeled with antibodies to c-kit. In contrast, in metastasis of PDAC, very intensive labeling of c-kit was evident. The location of KRAS, which is strongly associated with PDAC, was also analyzed at the initial stages of the disease, when islets of Langerhans still preserve their integrity to a large extent. KRAS was found exclusively in islets of Langerhans and overlapped in its location with insulin and c-kit expressing cells. It is suggested that the modulation of the expression of c-kit, visualized by antibodies to the oncogene molecule, may play an important role in the formation and progression of PDAC. The absence of c-kit in normal pancreas and its appearance in PDAC is probably due to a mutational event, which probably allows conversion of the β cells into cancer stem cells (CSC). Co-expression of both c-kit and KRAS, typical markers for CSC with overlapping with insulin in islets of Langerhans, strongly support the notion that β-cells play a central role in the development of PDAC. The use of specific drugs that can attenuate the kinase activity of c-kit or target KRAS expressing cancer cells should be tested in order to attenuate the progression of this lethal disease.

Facing current quantification challenges in protein microarrays

The proteome is highly variable and differs from cell to cell. The reasons are posttranslational modifications, splice variants, and polymorphisms. Techniques like next-generation sequencing can only give an inadequate picture of the protein status of a cell. Protein microarrays are able to track these changes on the level they occur: the proteomic level. Therefore, protein microarrays are powerful tools for relative protein quantification, to unveil new interaction partners and to track posttranslational modifications. This papers gives an overview on current protein microarray techniques and discusses recent advances in relative protein quantification.

Targeted therapies in cancer - challenges and chances offered by newly developed techniques for protein analysis in clinical tissues

In recent years, new anticancer therapies have accompanied the classical approaches of surgery and radio- and chemotherapy. These new forms of treatment aim to inhibit specific molecular targets namely altered or deregulated proteins, which offer the possibility of individualized therapies.The specificity and efficiency of these new approaches, however, bring about a number of challenges. First of all, it is essential to specifically identify and quantify protein targets in tumor tissues for the reasonable use of such targeted therapies. Additionally, it has become even more obvious in recent years that the presence of a target protein is not always sufficient to predict the outcome of targeted therapies. The deregulation of downstream signaling molecules might also play an important role in the success of such therapeutic approaches. For these reasons, the analysis of tumor-specific protein expression profiles prior to therapy has been suggested as the most effective way to predict possible therapeutic results. To further elucidate signaling networks underlying cancer development and to identify new targets, it is necessary to implement tools that allow the rapid, precise, inexpensive and simultaneous analysis of many network components while requiring only a small amount of clinical material.Reverse phase protein microarray (RPPA) is a promising technology that meets these requirements while enabling the quantitative measurement of proteins. Together with recently developed protocols for the extraction of proteins from formalin-fixed, paraffin-embedded (FFPE) tissues, RPPA may provide the means to quantify therapeutic targets and diagnostic markers in the near future and reliably screen for new protein targets.With the possibility to quantitatively analyze DNA, RNA and protein from a single FFPE tissue sample, the methods are available for integrated patient profiling at all levels of gene expression, thus allowing optimal patient stratification for individualized therapies.

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.

Increasing the sensitivity of reverse phase protein arrays by antibody-mediated signal amplification

Background

Reverse phase protein arrays (RPPA) emerged as a useful experimental platform to analyze biological samples in a high-throughput format. Different signal detection methods have been described to generate a quantitative readout on RPPA including the use of fluorescently labeled antibodies. Increasing the sensitivity of RPPA approaches is important since many signaling proteins or posttranslational modifications are present at a low level.

Results

A new antibody-mediated signal amplification (AMSA) strategy relying on sequential incubation steps with fluorescently-labeled secondary antibodies reactive against each other is introduced here. The signal quantification is performed in the near-infrared range. The RPPA-based analysis of 14 endogenous proteins in seven different cell lines demonstrated a strong correlation (r = 0.89) between AMSA and standard NIR detection. Probing serial dilutions of human cancer cell lines with different primary antibodies demonstrated that the new amplification approach improved the limit of detection especially for low abundant target proteins.

Conclusions

Antibody-mediated signal amplification is a convenient and cost-effective approach for the robust and specific quantification of low abundant proteins on RPPAs. Contrasting other amplification approaches it allows target protein detection over a large linear range.

Molecular profiling of signalling pathways in formalin-fixed and paraffin-embedded cancer tissues

In most hospitals word-wide, histopathological cancer diagnosis is currently based on formalin-fixed and paraffin-embedded (FFPE) tissues. In the last few years new approaches and developments in patient-tailored cancer therapy have raised the need to select more precisely those patients, who will respond to personalised treatments. The most efficient way for optimal therapy and patient selection is probably to provide a tumour-specific protein network portrait prior to treatment. The discovery and characterisation of deregulated signalling molecules (e.g. human epidermal growth factor receptor 2, mitogen-activated protein kinases) are very promising candidates for the identification of new suitable therapy targets and for the selection of those patients who will receive the greatest benefit from individualised treatments. The reverse phase protein array (RPPA) is a promising new technology that allows quick, precise and simultaneous analysis of many components of a network. Importantly it requires only limited amounts of routine clinical material (e.g. FFPE biopsies) and can be used for absolute protein measurements. We and other research groups have described successful protein extraction from routine FFPE tissues. In this manuscript we show how these recent developments might facilitate the implementation of RPPA in clinical trials and routine settings.

Biomarker discovery and clinical proteomics

New biomarkers are urgently needed to accelerate efforts in developing new drugs and treatments of known diseases. New clinical and translational proteomics studies emerge almost every day. However, discovery of new diagnostic biomarkers lags behind because of variability at every step in proteomics studies (e.g., assembly of a cohort of patients, sample preparation and the nature of body fluids, selection of a profiling method and uniform protocols for data analysis).Quite often, the validation step that follows the discovery phase does not reach desired levels of sensitivity and specificity or reproducibility between laboratories. Mass spectrometry and gel-based methods do not provide enough throughput for screening thousands of clinical samples. Further development of protein arrays may address this issue.Despite many obstacles, proteomics delivers vast amounts of information useful for understanding the molecular mechanisms underlying diseases.

Antibody microarrays as an experimental platform for the analysis of signal transduction networks

A significant bottleneck for the time-resolved and quantitative description of signaling networks is the limited sample capacity and sensitivity of existing methods. Recently, antibody microarrays have emerged as a promising experimental platform for the quantitative and comprehensive determination of protein abundance and protein phosphorylation. This review summarizes the development of microarray applications involving antibody-based capture of target proteins with a focus on quantitative applications. Technical aspects regarding the production of antibody microarrays, identification of suitable detection and capture antibody pairs, signal detection methods, detection limit, and data analysis are discussed in detail.