The needle in the haystack: application of breast fine-needle aspirate samples to quantitative protein microarray technology

Analysis of neuroendocrine clones in NSCLCs using an immuno-guided laser-capture microdissection-based approach

Clonal evolution and lineage plasticity are key contributors to tumor heterogeneity and response to treatment in cancer. However, capturing signal transduction events in coexisting clones remains challenging from a technical perspective. In this study, we developed and tested a signal-transduction-based workflow to isolate and profile coexisting clones within a complex cellular system like non-small cell lung cancers (NSCLCs). Cooccurring clones were isolated under immunohistochemical guidance using laser-capture microdissection, and cell signaling activation portraits were measured using the reverse-phase protein microarray. To increase the translational potential of this work and capture druggable vulnerabilities within different clones, we measured expression/activation of a panel of key drug targets and downstream substrates of FDA-approved or investigational agents. We isolated intermixed clones, including poorly represented ones (<5% of cells), within the tumor microecology and identified molecular characteristics uniquely attributable to cancer cells that undergo lineage plasticity and neuroendocrine transdifferentiation in NSCLCs.

High-content phenotypic and pathway profiling to advance drug discovery in diseases of unmet need

Conventional thinking in modern drug discovery postulates that the design of highly selective molecules which act on a single disease-associated target will yield safer and more effective drugs. However, high clinical attrition rates and the lack of progress in developing new effective treatments for many important diseases of unmet therapeutic need challenge this hypothesis. This assumption also impinges upon the efficiency of target agnostic phenotypic drug discovery strategies, where early target deconvolution is seen as a critical step to progress phenotypic hits. In this review we provide an overview of how emerging phenotypic and pathway-profiling technologies integrate to deconvolute the mechanism-of-action of phenotypic hits. We propose that such in-depth mechanistic profiling may support more efficient phenotypic drug discovery strategies that are designed to more appropriately address complex heterogeneous diseases of unmet need.

Kinome Profiling of NF1-Related MPNSTs in Response to Kinase Inhibition and Doxorubicin Reveals Therapeutic Vulnerabilities

Neurofibromatosis Type 1 (NF1)-related Malignant Peripheral Nerve Sheath Tumors (MPNST) are highly resistant sarcomas that account for significant mortality. The mechanisms of therapy resistance are not well-understood in MPNSTs, particularly with respect to kinase inhibition strategies. In this study, we aimed to quantify the impact of both the genomic context and targeted therapy on MPNST resistance using reverse phase phosphoproteome array (RPPA) analysis. We treated tumorgrafts from three genetically engineered mouse models using MET (capmatinib) and MEK (trametinib) inhibitors and doxorubicin, and assessed phosphosignaling at 4 h, 2 days, and 21 days. Baseline kinase signaling in our mouse models recapitulated an MET-addicted state (NF1-MET), P53 mutation (NF1-P53), and HGF overexpression (NF1). Following perturbation with the drug, we observed broad and redundant kinome adaptations that extended well beyond canonical RAS/ERK or PI3K/AKT/mTOR signaling. MET and MEK inhibition were both associated with an initial inflammatory response mediated by kinases in the JAK/STAT pathway and NFkB. Growth signaling predominated at the 2-day and 21-day time points as a result of broad RTK and intracellular kinase activation. Interestingly, AXL and NFkB were strongly activated at the 2-day and 21-day time points, and tightly correlated, regardless of the treatment type or genomic context. The degree of kinome adaptation observed in innately resistant tumors was significantly less than the surviving fractions of responsive tumors that exhibited a latency period before reinitiating growth. Lastly, doxorubicin resistance was associated with kinome adaptations that strongly favored growth and survival signaling. These observations confirm that MPNSTs are capable of profound signaling plasticity in the face of kinase inhibition or DNA damaging agent administration. It is possible that by targeting AXL or NFkB, therapy resistance can be mitigated.

The Translational Status of Cancer Liquid Biopsies

Abstract

Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. This can be achieved by leveraging omics information for accurate molecular characterization of tumors. Tumor tissue biopsies are currently the main source of information for molecular profiling. However, biopsies are invasive and limited in resolving spatiotemporal heterogeneity in tumor tissues. Alternative non-invasive liquid biopsies can exploit patient’s body fluids to access multiple layers of tumor-specific biological information (genomes, epigenomes, transcriptomes, proteomes, metabolomes, circulating tumor cells, and exosomes). Analysis and integration of these large and diverse datasets using statistical and machine learning approaches can yield important insights into tumor biology and lead to discovery of new diagnostic, predictive, and prognostic biomarkers. Translation of these new diagnostic tools into standard clinical practice could transform oncology, as demonstrated by a number of liquid biopsy assays already entering clinical use. In this review, we highlight successes and challenges facing the rapidly evolving field of cancer biomarker research.

Lay Summary

Precision oncology aims to tailor clinical decisions specifically to patients with the objective of improving treatment outcomes. The discovery of biomarkers for precision oncology has been accelerated by high-throughput experimental and computational methods, which can inform fine-grained characterization of tumors for clinical decision-making. Moreover, advances in the liquid biopsy field allow non-invasive sampling of patient’s body fluids with the aim of analyzing circulating biomarkers, obviating the need for invasive tumor tissue biopsies. In this review, we highlight successes and challenges facing the rapidly evolving field of liquid biopsy cancer biomarker research.

Utilization of Proteomic Technologies for Precision Oncology Applications

Genomic analysis of tumor specimens has revealed that cancer is fundamentally a proteomic disease at the functional level: driven by genomically defined derangements, but selected for in the proteins that are encoded and the aberrant activation of signaling and biochemical networks. This activation is measured by posttranslational modifications such as phosphorylation and other modifications that modulate cellular signaling, and these events cannot be effectively measured by genomic analysis alone. Moreover, these signaling networks by and large represent the targets for many FDA-approved and experimental molecularly targeted therapeutics. Consequently, it is important that we consider new classification schemas for oncology based not on tumor site of origin or histology under the microscope but on the functional protein signaling architecture. There are numerous proteomic technologies that could be discussed from a purely technological standpoint, but this chapter will concentrate on an overview of the main proteomic technologies available for conducting protein pathway activation analysis of clinical specimens such as multiplex immunoassays, phospho-specific flow cytometry, reverse phase protein microarrays, quantitative immunohistochemistry, and mass spectrometry. This chapter will focus on the application of these technologies to cancer-based clinical studies evaluating prognostic/predictive markers or for stratifying patients to personalized treatments.

Metal enhanced fluorescence biosensing: from ultra-violet towards second near-infrared window

To increase disease survival rates, there is a vital need for diagnosis at very preliminary stages. Then, low concentrations of biomarkers are present which must be effectively detected and quantified for reliable diagnosis. Fluorescent biosensing is commonly enabled through the labelling of these biomarkers with nanostructures and fluorophores. Metal Enhanced Fluorescence (MEF) is a phenomenon whereby the intensity of a fluorescent biosensor signal can be considerably enhanced by placing a metallic nanostructure and fluorophore in close proximity. Importantly, this allows for an even lower detection limit and thus earlier diagnosis. In recent years, extraordinary efforts have been made in the understanding of how the chemical and physical properties of nanomaterials may be exploited advantageously. Via precise nanoscale engineering, it is possible to optimize the optical properties of plasmonic nanomaterials, which now need to be refined and applied in diagnostics. Through MEF, the intensity of this signal can be related in direct proportion to analyte concentration, allowing for diagnosis of disease at an earlier stage than previously. This review paper outlines the potential and recent progress of applied MEF biosensors, highlighting their substantial clinical potential. MEF biosensors are presented both upon assay-based platforms and in solution, with comments on the various metallic nanoparticle morphologies available. This is explored across various emission wavelengths from ultra-violet to the second near infrared window (NIR-II), emphasising their wide applicability. Further to this, the importance of near infrared (NIR-I and NIR-II) biosensing is made clear as it allows for higher penetration in biological media. Finally, by developing multiplexing techniques, multiple and simultaneous analyses of analytes can be achieved. Through the incorporation of metal enhanced fluorescence into biosensing, it will be possible to diagnose disease more rapidly and more reliably than before, with the potential to save countless lives.

An exploratory study examining how nano-liquid chromatography-mass spectrometry and phosphoproteomics can differentiate patients with advanced fibrosis and higher percentage collagen in non-alcoholic fatty liver disease

BACKGROUND

Non-alcoholic steatohepatitis (NASH) is among the leading causes of liver disease worldwide. It is increasingly recognized that the phenotype of NASH may involve a number of different pathways, of which each could become important therapeutic targets. The aim of this study is to use high resolution mass spectrometry (MS) and phosphoproteomics techniques to assess the serum proteome and hepatic phosphoproteome in subjects with NASH-related fibrosis.

METHODS

Sixty-seven biopsy-proven NAFLD subjects with frozen sera and liver tissue were included. Reverse phase protein microarray was used to quantify the phosphorylation of key signaling proteins in liver and nano-liquid chromatography (LC)-MS was used to sequence target biomarkers in the serum. An image analysis algorithm was used to quantify the percentage of collagen (% collagen) using computer-assisted morphometry. Using multiple regression models, serum proteomes and phosphorylated hepatic proteins that were independently (p ≤ 0.05) associated with advanced fibrosis (stage ≥ 2) and higher % collagen were assessed.

RESULTS

Phosphorylated signaling pathways in the liver revealed that apoptosis signal-regulating kinase 1, mitogen-activated protein kinase (ASK1-MAPK pathway involving ASK1 S38 (p < 0.02) and p38 MAPK (p = 0.0002)) activated by the inflammatory cytokine interleukin (IL-10) (p < 0.001), were independently associated with higher % collagen. LC-MS data revealed that serum alpha-2 macroglobulin (α2M) (p = 0.0004) and coagulation factor V (p = 0.0127) were independently associated with higher % hepatic collagen.

CONCLUSIONS

Simultaneous profiling of serum proteome and hepatic phosphoproteome reveals that the activation of ASK1 S38, p38 MAPK in the liver, and serum α2M and coagulation factor V are independently associated with hepatic collagen deposition in patients with NASH. These data suggest the role of these pathways in the pathogenesis of NASH-related fibrosis as a potential therapeutic target.

Reverse Phase Protein Microarrays

While genes and RNA encode information about cellular status, proteins are considered the engine of the cellular machine, as they are the effective elements that drive all cellular functions including proliferation, migration, differentiation, and apoptosis. Consequently, investigations of the cellular protein network are considered a fundamental tool for understanding cellular functions.Alteration of the cellular homeostasis driven by elaborate intra- and extracellular interactions has become one of the most studied fields in the era of personalized medicine and targeted therapy. Increasing interest has been focused on developing and improving proteomic technologies that are suitable for analysis of clinical samples. In this context, reverse-phase protein microarrays (RPPA) is a sensitive, quantitative, high-throughput immunoassay for protein analyses of tissue samples, cells, and body fluids.RPPA is well suited for broad proteomic profiling and is capable of capturing protein activation as well as biochemical reactions such as phosphorylation, glycosylation, ubiquitination, protein cleavage, and conformational alterations across hundreds of samples using a limited amount of biological material. For these reasons, RPPA represents a valid tool for protein analyses and generates data that help elucidate the functional signaling architecture through protein-protein interaction and protein activation mapping for the identification of critical nodes for individualized or combinatorial targeted therapy.

Protein activation mapping of human sun-protected epidermis after an acute dose of erythemic solar simulated light

Ultraviolet radiation is an important etiologic factor in skin cancer and a better understanding of how solar stimulated light (SSL) affects signal transduction pathways in human skin which is needed in further understanding activated networks that could be targeted for skin cancer prevention. We utilized Reverse Phase Protein Microarray Analysis (RPPA), a powerful technology that allows for broad-scale and quantitative measurement of the activation/phosphorylation state of hundreds of key signaling proteins and protein pathways in sun-protected skin after an acute dose of two minimal erythema dose (MED) of SSL. RPPA analysis was used to map the altered cell signaling networks resulting from acute doses of solar simulated radiation (SSL). To that end, we exposed sun-protected skin in volunteers to acute doses of two MED of SSL and collected biopsies pre-SSL and post-SSL irradiation. Frozen biopsies were subjected to laser capture microdissection (LCM) and then assessed by RPPA. The activation/phosphorylation or total levels of 128 key signaling proteins and drug targets were selected for statistical analysis. Coordinate network-based analysis was performed on specific signaling pathways that included the PI3k/Akt/mTOR and Ras/Raf/MEK/ERK pathways. Overall, we found early and sustained activation of the PI3K-AKT-mTOR and MAPK pathways. Cell death and apoptosis-related proteins were activated at 5 and 24 h. Ultimately, expression profile patterns of phosphorylated proteins in the epidermal growth factor receptor(EGFR), AKT, mTOR, and other relevant pathways may be used to determine pharmacodynamic activity of new and selective topical chemoprevention agents administered in a test area exposed to SSL to determine drug-induced attenuation or reversal of skin carcinogenesis pathways.

Skin exposure to ultraviolet radiation leads to the activation of proteins involved in carcinogenic pathways. Janine Einspahr and Clara Curiel-Lewandrowski of the Arizona Cancer Center and colleagues in the US exposed normally ultraviolet protected skin of 12 individuals to two times the dose of solar-simulated light needed to induce redness. Skin biopsies were taken before and after exposure and 128 proteins known to be involved in key cancer signaling pathways were examined using ‘reverse phase protein microarray analysis’. They found early and sustained activation of multiple signaling pathways, in addition to activation of cell death and apoptosis-related proteins. The study may serve as a model for investigating the pathways involved in chronic or ultraviolet-induced carcinogenesis, which may ultimately lead to the development of targeted therapies to attenuate or reverse skin cancer pathways.

[Analysis of contribution of protein phosphorylation in the development of the diseases]

In recent decades, studies in the molecular origins of socially significant diseases have made a big step forward with the development and using of high-performance methods in genomics and proteomics. Numerous studies in the framework of the global program "Human Proteome" were aimed at the identification of all possible proteins in various cell cultures and tissues, including cancer. One of the objectives was to identify biomarkers - proteins with high specificity to certain pathologies. However, in many cases, it is shown that the development of the disease is not associated with the appearance of new proteins, but depends on the level of gene expression or forming of proteoforms - splice variants, single amino acid substitutions (SAP variants), and post-translational modifications (PTM) of proteins. PTM may play a key role in the development of pathology because they activate a variety of regulatory or structural proteins in the majority of cell physiological processes. Phosphorylation is among the most significant of these protein modifications.This review will describe methods for analysis of protein phosphorylation used in the studies of such diseases as cancer and neurodegenerative diseases, as well as examples of cases when the modified proteins are involved directly to their development, and screening such significant PTM is used for the diagnosis and choice of treatment.

Kinase-driven metabolic signalling as a predictor of response to carboplatin-paclitaxel adjuvant treatment in advanced ovarian cancers

BACKGROUND

The biological mechanisms underlying early- and advanced-stage epithelial ovarian cancers (EOCs) are still poorly understood. This study explored kinase-driven metabolic signalling in early and advanced EOCs, and its role in tumour progression and response to carboplatin-paclitaxel treatment.

METHODS

Tumour epithelia were isolated from two independent sets of primary EOC (n=72 and 30 for the discovery and the validation sets, respectively) via laser capture microdissection. Reverse phase protein microarrays were used to broadly profile the kinase-driven metabolic signalling of EOC with particular emphasis on the LBK1-AMPK and AKT-mTOR axes. Signalling activation was compared between early and advanced lesions, and carboplatin-paclitaxel-sensitive and -resistant tumours.

RESULTS

Advanced EOCs were characterised by a heterogeneous kinase-driven metabolic signature and decreased phosphorylation of the AMPK-AKT-mTOR axis compared to early EOC (P<0.05 for AMPKα T172, AMPKα1 S485, AMPKβ1 S108, AKT S473 and T308, mTOR S2448, p70S6 S371, 4EBP1 S65, GSK-3 α/β S21/9, FOXO1 T24/FOXO3 T32, and FOXO1 S256). Advanced tumours with low relative activation of the metabolic signature and increased FOXO1 T24/FOXO3 T32 phosphorylation (P=0.041) were associated with carboplatin-paclitaxel resistance.

CONCLUSIONS

If validated in a larger cohort of patients, the decreased AMPK-AKT-mTOR activation and phosphorylation of FOXO1 T24/FOXO3 T32 may help identify carboplatin-paclitaxel-resistant EOC patients.

Signaling pathway profiling using reverse-phase protein array and its clinical applications

INTRODUCTION

Increased accessibility to next-generation sequencing within the last decade has led to a paradigm shift in cancer treatment from one-size-fits-all medicine to precision medicine providing therapeutic strategies tailored to the requirements of individual patients. However, the effect of even the most successful agent yet tested is only transient, and durable efficacy has yet to be achieved. Genome- and transcriptome-based approaches cannot fully predict the diversity of protein expression patterns or post-translational modifications that directly contribute to cancer pathogenesis and physiology. This underscores the need for concordant proteomic analysis in the next stage of precision medicine. Areas covered: This review begins with an overview of the recent advances and trends in precision medicine that currently rely on genomics, and highlights the utility of antibody-based reverse-phase protein array (RPPA) technology as a proteomic tool in this context. Expert commentary: RPPA is well suited for pharmacodynamics analysis in view of its ability to precisely map signaling status using limited amounts of clinical samples. In addition, the cost-effectiveness and rapid turn-around time of the RPPA platform offer a substantial advantage over existing molecular profiling technologies in clinical settings.

Enrichment of PI3K-AKT-mTOR Pathway Activation in Hepatic Metastases from Breast Cancer

Purpose: Little is known about the molecular signatures associated with specific metastatic sites in breast cancer. Using comprehensive multi-omic molecular profiling, we assessed whether alterations or activation of the PI3K-AKT-mTOR pathway is associated with specific sites of breast cancer metastasis.Experimental Design: Next-generation sequencing-based whole-exome sequencing was coupled with reverse-phase protein microarray (RPPA) functional signaling network analysis to explore the PI3K-AKT-mTOR axis in 32 pretreated breast cancer metastases. RPPA-based signaling data were further validated in an independent cohort of 154 metastatic lesions from breast cancer and 101 unmatched primary breast tumors. The proportion of cases with PI3K-AKT-mTOR genomic alterations or signaling network activation were compared between hepatic and nonhepatic lesions.Results:PIK3CA mutation and activation of AKT (S473) and p70S6K (T389) were detected more frequently among liver metastases than nonhepatic lesions (P < 0.01, P = 0.056, and P = 0.053, respectively). However, PIK3CA mutations alone were insufficient in predicting protein activation (P = 0.32 and P = 0.19 for activated AKT and p70S6K, respectively). RPPA analysis of an independent cohort of 154 tumors confirmed the relationship between pathway activation and hepatic metastasis [AKT (S473), mTOR (S2448), and 4EBP1 (S65); P < 0.01, P = 0.02, and P = 0.01, respectively]. Similar results were also seen between liver metastases and primary breast tumors [AKT (S473) P < 0.01, mTOR (S2448) P < 0.01, 4EBP1 (S65) P = 0.01]. This signature was lost when primary tumors were compared with all metastatic sites combined.Conclusions: Breast cancer patients with liver metastasis may represent a molecularly homogenized cohort with increased incidence of PIK3CA mutations and activation of the PI3K-AKT-mTOR signaling network. Clin Cancer Res; 23(16); 4919-28. ©2017 AACR.

Protein Array-based Approaches for Biomarker Discovery in Cancer

Biomarkers are deemed to be potential tools in early diagnosis, therapeutic monitoring, and prognosis evaluation for cancer, with simplicity as well as economic advantages compared with computed tomography and biopsy. However, most of the current cancer biomarkers present insufficient sensitivity as well as specificity. Therefore, there is urgent requirement for the discovery of biomarkers for cancer. As one of the most exciting emerging technologies, protein array provides a versatile and robust platform in cancer proteomics research because it shows tremendous advantages of miniaturized features, high throughput, and sensitive detections in last decades. Here, we will present a relatively complete picture on the characteristics and advance of different types of protein arrays in application for biomarker discovery in cancer, and give the future perspectives in this area of research.

Functional signaling pathway analysis of lung adenocarcinomas identifies novel therapeutic targets for KRAS mutant tumors

Little is known about the complex signaling architecture of KRAS and the interconnected RAS-driven protein-protein interactions, especially as it occurs in human clinical specimens. This study explored the activated and interconnected signaling network of KRAS mutant lung adenocarcinomas (AD) to identify novel therapeutic targets.Thirty-four KRAS mutant (MT) and twenty-four KRAS wild-type (WT) frozen biospecimens were obtained from surgically treated lung ADs. Samples were subjected to Laser Capture Microdissection and Reverse Phase Protein Microarray analysis to explore the expression/activation levels of 150 signaling proteins along with co-activation concordance mapping. An independent set of 90 non-small cell lung cancers (NSCLC) was used to validate selected findings by immunohistochemistry (IHC).Compared to KRAS WT tumors, the signaling architecture of KRAS MT ADs revealed significant interactions between KRAS downstream substrates, the AKT/mTOR pathway, and a number of Receptor Tyrosine Kinases (RTK). Approximately one-third of the KRAS MT tumors had ERK activation greater than the WT counterpart (p<0.01). Notably 18% of the KRAS MT tumors had elevated activation of the Estrogen Receptor alpha (ER-α) (p=0.02).This finding was verified in an independent population by IHC (p=0.03).KRAS MT lung ADs appear to have a more intricate RAS linked signaling network than WT tumors with linkage to many RTKs and to the AKT-mTOR pathway. Combination therapy targeting different nodes of this network may be necessary to treat this group of patients. In addition, for patients with KRAS MT tumors and activation of the ER-α, anti-estrogen therapy may have important clinical implications.

HE, Lucio C, Douglas CW, Vienna L, B. SM, A. LL, F. PE, Mariaelena P. Impact of upfront cellular enrichment by laser capture microdissection on protein and phosphoprotein drug target signaling activation measurements in human lung cancer: Implications for personalized medicine

PURPOSE

The aim of this study was to evaluate whether upfront cellular enrichment via laser capture microdissection (LCM) is necessary for accurately quantifying predictive biomarkers in nonsmall cell lung cancer tumors.

EXPERIMENTAL DESIGN

Fifteen snap frozen surgical biopsies were analyzed. Whole tissue lysate and matched highly enriched tumor epithelium via LCM were obtained for each patient. The expression and activation/phosphorylation levels of 26 proteins were measured by reverse phase protein microarray. Differences in signaling architecture of dissected and undissected matched pairs were visualized using unsupervised clustering analysis, bar graphs, and scatter plots.

RESULTS

Overall patient matched LCM and undissected material displayed very distinct and differing signaling architectures with 93% of the matched pairs clustering separately. These differences were seen regardless of the amount of starting tumor epithelial content present in the specimen.

CONCLUSIONS AND CLINICAL RELEVANCE

These results indicate that LCM driven upfront cellular enrichment is necessary to accurately determine the expression/activation levels of predictive protein signaling markers although results should be evaluated in larger clinical settings. Upfront cellular enrichment of the target cell appears to be an important part of the workflow needed for the accurate quantification of predictive protein signaling biomarkers. Larger independent studies are warranted.

Functional characterization of epithelial ovarian cancer histotypes by drug target based protein signaling activation mapping: implications for personalized cancer therapy

Epithelial ovarian carcinoma (EOC) is a deadly disease, with a 5-year survival of 30%. The aim of the study was to perform broad-scale protein signaling activation mapping to evaluate if EOC can be redefined based on activated protein signaling network architecture rather than histology. Tumor cells were isolated using laser capture microdissection (LCM) from 72 EOCs. Tumors were classified as serous (n = 38), endometrioid (n = 13), mixed (n = 8), clear cell (CCC; n = 7), and others (n = 6). LCM tumor cells were lysed and subjected to reverse-phase protein microarray to measure the expression/activation level of 117 protein drug targets. Unsupervised hierarchical clustering analysis was utilized to explore the overall signaling network. ANOVA was used to detect significant differences among the groups (p < 0.05). Regardless of histology, unsupervised analysis revealed five pathway-driven clusters. When the EOC histotypes were compared by ANOVA, only CCC showed a distinct signaling network, with activation of EGFR, Syk, HER2/ErbB2, and SHP2 (p = 0.0007, p = 0.0021, p < 0.0001, and p = 0.0410, respectively). The histological classification of EOC fails to adequately describe the underpinning protein signaling network. Nevertheless, CCC presents unique signaling characteristics compared to the other histotypes. EOC may need to be characterized by functional signaling activation mapping rather than pure histology.

Discovering cancer biomarkers from clinical samples by protein microarrays

Cancer biomarkers are of potential use in early cancer diagnosis, anticancer therapy development, and monitoring the responses to treatments. Protein-based cancer biomarkers are major forms in use, as they are much easier to be monitored in body fluids or tissues. For cancer biomarker discovery, high-throughput techniques such as protein microarrays hold great promises, because they are capable of global unbiased monitoring but with a miniaturized format. In doing so, novel and cancer type specific biomarkers can be systematically discovered at an affordable cost. In this review, we give a relatively complete picture on protein microarrays applied to clinical samples for cancer biomarker discovery, and conclude this review with the future perspectives.

Reverse phase protein arrays: mapping the path towards personalized medicine

Reverse phase protein array (RPPA) technology evolved from the advent of miniaturized immunoassays and gene microarray technology. Reverse phase protein arrays provide either a low throughput or high throughput methodology for quantifying proteins and their post-translationally modified forms in both cellular and non-cellular samples. As the demand for patient tailored therapies increases so does the need for precise and sensitive technology to accurately profile the molecular circuitry driving an individual patient's disease. RPPAs are currently utilized in clinical trials for profiling and comparing the functional state of protein signaling pathways, either temporally within tumors, between patients, or within the same patients before/after treatment. RPPAs are generally employed for quantifying large numbers of samples on one array, under identical experimental conditions. However, the goal of personalized cancer medicine is to design therapies based on the molecular portrait of a patient's tumor, which in turn result in more efficacious treatments with less toxicity. Therefore, RPPAs are also being validated for low throughput assays of individual patient samples. This review explores RPPA technology in the cancer research field, concentrating on its role as a fundamental tool for deciphering protein signaling networks and its emerging role in personalized medicine.

Capillary nano-immunoassays: advancing quantitative proteomics analysis, biomarker assessment, and molecular diagnostics

There is an emerging demand for the use of molecular profiling to facilitate biomarker identification and development, and to stratify patients for more efficient treatment decisions with reduced adverse effects. In the past decade, great strides have been made to advance genomic, transcriptomic and proteomic approaches to address these demands. While there has been much progress with these large scale approaches, profiling at the protein level still faces challenges due to limitations in clinical sample size, poor reproducibility, unreliable quantitation, and lack of assay robustness. A novel automated capillary nano-immunoassay (CNIA) technology has been developed. This technology offers precise and accurate measurement of proteins and their post-translational modifications using either charge-based or size-based separation formats. The system not only uses ultralow nanogram levels of protein but also allows multi-analyte analysis using a parallel single-analyte format for increased sensitivity and specificity. The high sensitivity and excellent reproducibility of this technology make it particularly powerful for analysis of clinical samples. Furthermore, the system can distinguish and detect specific protein post-translational modifications that conventional Western blot and other immunoassays cannot easily capture. This review will summarize and evaluate the latest progress to optimize the CNIA system for comprehensive, quantitative protein and signaling event characterization. It will also discuss how the technology has been successfully applied in both discovery research and clinical studies, for signaling pathway dissection, proteomic biomarker assessment, targeted treatment evaluation and quantitative proteomic analysis. Lastly, a comparison of this novel system with other conventional immuno-assay platforms is performed.

A Highly Sensitive Porous Silicon (P-Si)-Based Human Kallikrein 2 (hK2) Immunoassay Platform toward Accurate Diagnosis of Prostate Cancer

Levels of total human kallikrein 2 (hK2), a protein involved the pathology of prostate cancer (PCa), could be used as a biomarker to aid in the diagnosis of this disease. In this study, we report on a porous silicon antibody immunoassay platform for the detection of serum levels of total hK2. The surface of porous silicon has a 3-dimensional macro- and nanoporous structure, which offers a large binding capacity for capturing probe molecules. The tailored pore size of the porous silicon also allows efficient immobilization of antibodies by surface adsorption, and does not require chemical immobilization. Monoclonal hK2 capture antibody (6B7) was dispensed onto P-Si chip using a piezoelectric dispenser. In total 13 × 13 arrays (169 spots) were spotted on the chip with its single spot volume of 300 pL. For an optimization of capture antibody condition, we firstly performed an immunoassay of the P-Si microarray under a titration series of hK2 in pure buffer (PBS) at three different antibody densities (75, 100 and 145 µg/mL). The best performance of the microarray platform was seen at 100 µg/mL of the capture antibody concentration (LOD was 100 fg/mL). The platform then was subsequently evaluated for a titration series of serum-spiked hK2 samples. The developed platform utilizes only 15 µL of serum per test and the total assay time is about 3 h, including immobilization of the capture antibody. The detection limit of the hK2 assay was 100 fg/mL in PBS buffer and 1 pg/mL in serum with a dynamic range of 10⁶ (10⁻⁴ to 10² ng/mL).

Reverse Phase Protein Arrays-Quantitative Assessment of Multiple Biomarkers in Biopsies for Clinical Use

Reverse Phase Protein Arrays (RPPA) represent a very promising sensitive and precise high-throughput technology for the quantitative measurement of hundreds of signaling proteins in biological and clinical samples. This array format allows quantification of one protein or phosphoprotein in multiple samples under the same experimental conditions at the same time. Moreover, it is suited for signal transduction profiling of small numbers of cultured cells or cells isolated from human biopsies, including formalin fixed and paraffin embedded (FFPE) tissues. Owing to the much easier sample preparation, as compared to mass spectrometry based technologies, and the extraordinary sensitivity for the detection of low-abundance signaling proteins over a large linear range, RPPA have the potential for characterization of deregulated interconnecting protein pathways and networks in limited amounts of sample material in clinical routine settings. Current aspects of RPPA technology, including dilution curves, spotting, controls, signal detection, antibody validation, and calculation of protein levels are addressed.

Evaluation of optical detection platforms for multiplexed detection of proteins and the need for point-of-care biosensors for clinical use

This review investigates optical sensor platforms for protein multiplexing, the ability to analyze multiple analytes simultaneously. Multiplexing is becoming increasingly important for clinical needs because disease and therapeutic response often involve the interplay between a variety of complex biological networks encompassing multiple, rather than single, proteins. Multiplexing is generally achieved through one of two routes, either through spatial separation on a surface (different wells or spots) or with the use of unique identifiers/labels (such as spectral separation-different colored dyes, or unique beads-size or color). The strengths and weaknesses of conventional platforms such as immunoassays and new platforms involving protein arrays and lab-on-a-chip technology, including commercially-available devices, are discussed. Three major public health concerns are identified whereby detecting medically-relevant markers using Point-of-Care (POC) multiplex assays could potentially allow for a more efficient diagnosis and treatment of diseases.

Signaling pathway profiling by reverse-phase protein array for personalized cancer medicine

Deregulation of intracellular signaling through accumulation of genetic alterations is a hallmark of cancer. In the past few decades, concerted and systematic efforts have been made to identify key genetic alterations and to develop therapeutic agents targeting active signaling molecules. However, the efficacy of molecular therapeutics often varies among individuals, and precise mapping of active molecules in individual patients is now considered an essential for therapy optimization. Reverse-phase protein array or microarray (RPPA or RPPM) is an emerging antibody-based highly quantitative proteomic technology, especially suitable for profiling of expression and modification of signaling proteins in low abundance. Because the supply of clinical materials is often limited, RPPA technology is highly advantageous for clinical proteomics in view of its high sensitivity as well as accurate quantification. RPPA has now begun to be incorporated into various clinical trials employing molecular-targeted therapeutics. In this article we review and discuss the application of RPPA technology in the fields of basic, preclinical, and clinical research. The RPPA Global Workshop was recently launched to accelerate the exchange of rapidly expanding knowledge of this fascinating technology among academic laboratories and industries worldwide. This article is part of a Special Issue entitled: Medical Proteomics.

Realizing the promise of reverse phase protein arrays for clinical, translational, and basic research: a workshop report: the RPPA (Reverse Phase Protein Array) society

Reverse phase protein array (RPPA) technology introduced a miniaturized "antigen-down" or "dot-blot" immunoassay suitable for quantifying the relative, semi-quantitative or quantitative (if a well-accepted reference standard exists) abundance of total protein levels and post-translational modifications across a variety of biological samples including cultured cells, tissues, and body fluids. The recent evolution of RPPA combined with more sophisticated sample handling, optical detection, quality control, and better quality affinity reagents provides exquisite sensitivity and high sample throughput at a reasonable cost per sample. This facilitates large-scale multiplex analysis of multiple post-translational markers across samples from in vitro, preclinical, or clinical samples. The technical power of RPPA is stimulating the application and widespread adoption of RPPA methods within academic, clinical, and industrial research laboratories. Advances in RPPA technology now offer scientists the opportunity to quantify protein analytes with high precision, sensitivity, throughput, and robustness. As a result, adopters of RPPA technology have recognized critical success factors for useful and maximum exploitation of RPPA technologies, including the following: preservation and optimization of pre-analytical sample quality, application of validated high-affinity and specific antibody (or other protein affinity) detection reagents, dedicated informatics solutions to ensure accurate and robust quantification of protein analytes, and quality-assured procedures and data analysis workflows compatible with application within regulated clinical environments. In 2011, 2012, and 2013, the first three Global RPPA workshops were held in the United States, Europe, and Japan, respectively. These workshops provided an opportunity for RPPA laboratories, vendors, and users to share and discuss results, the latest technology platforms, best practices, and future challenges and opportunities. The outcomes of the workshops included a number of key opportunities to advance the RPPA field and provide added benefit to existing and future participants in the RPPA research community. The purpose of this report is to share and disseminate, as a community, current knowledge and future directions of the RPPA technology.

Implications of functional proteomics in breast cancer

Breast cancer is one of the major public health problems of the Western world. Recent advances in genomics and gene expression-profiling approaches have enriched our understanding of this heterogeneous disease. However, progress in functional proteomics in breast cancer research has been relatively slow. Allied with genomics, the functional proteomics approach will be important in improving diagnosis through better classification of breast cancer and in predicting prognosis and response to different therapies, including chemotherapy, hormonal therapy, and targeted therapy. In this review, we will present functional proteomic approaches with a focus on the recent clinical implications of utilizing the reverse-phase protein array platform in breast cancer research.

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.

Improved porous silicon microarray based prostate specific antigen immunoassay by optimized surface density of the capture antibody

Enriching the surface density of immobilized capture antibodies enhances the detection signal of antibody sandwich microarrays. In this study, we improved the detection sensitivity of our previously developed P-Si (porous silicon) antibody microarray by optimizing concentrations of the capturing antibody. We investigated immunoassays using a P-Si microarray at three different capture antibody (PSA - prostate specific antigen) concentrations, analyzing the influence of the antibody density on the assay detection sensitivity. The LOD (limit of detection) for PSA was 2.5 ng mL(-1), 80 pg mL(-1), and 800 fg mL(-1) when arraying the PSA antibody, H117 at the concentration 15 μg mL(-1), 35 μg mL(-1), and 154 μg mL(-1), respectively. We further investigated PSA spiked into human female serum in the range of 800 fg mL(-1) to 500 ng mL(-1). The microarray showed a LOD of 800 fg mL(-1) and a dynamic range of 800 fg mL(-1) to 80 ng mL(-1) in serum spiked samples.

Dynamic protein pathway activation mapping of adipose-derived stem cell differentiation implicates novel regulators of adipocyte differentiation

Next to embryonic stem cell research, adult stem cell research is providing a promising alternative for enhanced tissue regeneration and transplantation. The key biochemical networks controlling the differentiation processes regulating stem cell biology remain largely disputed and or undefined, contributing to a lack of knowledge of the principle phosphoregulatory events propagating signal transduction. To effectively monitor these events relative to adipocyte differentiation, this study utilized a high throughput reverse phase protein microarray platform and characterized adult adipose-derived stem cell (ASC) differentiation through the monitoring of ∼100 phosphospecific endpoints with 33 distinct time points examined across 14 days. This kinetic-based analysis showed time ordered signal transduction ultimately implicating pathways correlated with adipogenic differentiation. To further validate the causal significance of these network activations, pharmacological targeting was implemented to include the chemical inhibitors MAPK inhibitor PD169316, rapamycin, and HNMPA-(AM)3 yielding partial or complete disruption of adipocytic differentiation, as noted by a decrease or lack of lipid formation within the mature adipocytes. Based on this analysis, v-crk sarcoma virus CT10 oncogene homolog (CRKII) and c-abl oncogene 1, non-receptor tyrosine kinase (c-ABL) were implicated as novel key regulators of adipocyte differentiation, with v-akt murine thymoma viral oncogene (AKT), mammalian target of rapamycin (mTOR), and SMAD family member (SMAD) pathways being implicated as secondary regulators. This dynamic molecular profiling provides a novel insight into the signaling architecture of mesenchymal stem cell differentiation and may be useful in the development of therapeutic modulators for clinical applications; in addition to advancing the collective understanding of key cellular processes, ultimately contributing to more confident stem cell manipulation.

Stochastic profiling of transcriptional regulatory heterogeneities in tissues, tumors and cultured cells

Single-cell variations in gene and protein expression are important during development and disease. Such cell-to-cell heterogeneities can be directly inspected one cell at a time, but global methods are usually not sensitive enough to work with the starting material of a single cell. Here we provide a detailed protocol for stochastic profiling, a method that infers single-cell regulatory heterogeneities by repeatedly sampling small collections of cells selected at random. Repeated stochastic sampling is performed by laser-capture microdissection or limiting dilution, followed by careful exponential cDNA amplification, hybridization to microarrays and statistical analysis. Stochastic profiling surveys the transcriptome for programs that are heterogeneously regulated among cellular subpopulations in their native tissue context. The protocol is readily optimized for specific biological applications and takes about 1 week to complete.

Reverse phase protein microarrays and their utility in drug development

The majority of human diseases, including cancer, are characterized by abnormal protein function. Proteins regulate virtually every cellular process and exhibit multiple kinds of post-translational modification that modulate expression levels and activation states, such as phosphorylation by protein kinases. Additionally proteins interact with each other in complex regulatory networks and signal transduction pathways modulated by feedback mechanisms. These pathways are disrupted in disease and altered by therapeutic drugs. Reverse phase protein microarray (RPMA) technology allows simultaneous measurement of numerous phosphorylated, glycosylated, cleaved, or total cellular proteins from complex mixtures in many samples at once. Therefore, RPMAs can provide a portrait of a cell's signaling pathways in diseased states, before and after treatment with drugs, and allows comparison of changes in drug-resistant and sensitive cells. Furthermore, the technology offers a means of connecting genomic abnormalities in cancer to targetable alterations in protein signaling pathways, even for genetic events that seem otherwise undruggable. Consequently, the RPMA platform has great utility in many steps of drug development including target identification, validation of a pharmaceutical agent's efficacy, understanding mechanisms of action, and discovery of biomarkers that predict or guide therapeutic response. RPMAs have become a powerful tool for drug development and are now being integrated into human clinical cancer trials, where they are being used to personalize therapy.

Proteomic approaches to the discovery of cancer biomarkers for early detection and personalized medicine

Cancer biomarkers for the early detection of malignancies and selection of therapeutic strategies have been requested in the clinical field. Accurate and informative cancer biomarkers hold significant promise for improvements in the early detection of disease and in the selection of the most effective therapeutic strategies. Recently, significant progress in the comprehensive analysis of the human genome, epigenome, transcriptome, proteome and metabolome has led to revolutionary changes in the discovery of cancer biomarkers. The Human Proteome Organization has launched a global Human Proteome Project to map the entire human protein set. The Human Proteome Project research group has focused on three working proteomic pillars-mass spectrometry-based, antibody-based and knowledge-based proteomics-and each of these technologies is advancing rapidly. In this review, we introduce the proteomic platforms that are currently being used for cancer biomarker discovery, and describe examples of novel cancer biomarkers that were identified with each proteomic technology.

Phosphoproteomics: A possible route to novel biomarkers of breast cancer

Proteomics is rapidly transforming the way that cancer and other pathologies are investigated. The ability to identify hundreds of proteins and to compare their abundance in different clinical samples presents a unique opportunity for direct identification of novel disease markers. Furthermore, recent advances allow us to analyse and compare PTMs. This gives an additional dimension for defining a new class of protein biomarker based not only on abundance and expression but also on the occurrence of covalent modifications specific to a disease state or therapy response. Such modifications are often a consequence of the activation/inactivation of a particular disease related pathway. In this review we evaluate the available information on breast cancer related protein-phosphorylation events, illustrating the rationale for investigating this PTM as a target for breast cancer research with eventual clinical relevance. We present a critical survey of the published experimental strategies to study protein phosphorylation on a system wide scale and highlight recent specific advances in breast cancer phosphoproteomics. Finally we discuss the feasibility of establishing novel biomarkers for breast cancer based on the detection of patterns of specific protein phosphorylation events.

Functional protein pathway activation mapping of the progression of normal skin to squamous cell carcinoma

Reverse phase protein microarray analysis was used to identify cell signaling derangements in squamous cell carcinoma (SCC) compared with actinic keratosis (AK) and upper inner arm (UIA). We analyzed two independent tissue sets with isolation and enrichment of epithelial cells by laser capture microdissection. Set 1 served as a pilot and a means to identify protein pathway activation alterations that could be further validated in a second independent set. Set 1 was comprised of 4 AK, 13 SCC, and 20 UIA. Set 2 included 15 AK, 9 SCCs, and 20 UIAs. Activation of 51 signaling proteins, known to be involved in tumorigenesis, were assessed for set 1 and showed that the MEK-ERK [mitogen-activated protein (MAP)/extracellular signal-regulated (ERK; MEK)] pathway was activated in SCC compared with AK and UIA, and that epidermal growth factor receptor (EGFR) and mTOR pathways were aberrantly activated in SCC. Unsupervised two-way hierarchical clustering revealed that AK and UIA shared a common signaling network activation architecture while SCC was dramatically different. Statistical analysis found that prosurvival signaling through phosphorylation of ASK and 4EBP1 as well as increased Bax and Bak expression was higher in AK compared with UIA. We expanded pathway network activation mapping in set 2 to 101 key signaling proteins, which corroborated activation of MEK-ERK, EGFR, and mTOR pathways through discovery of a number of upstream and downstream signaling molecules within these pathways to conclude that SCC is indeed a pathway activation-driven disease. Pathway activation mapping of SCC compared with AK revealed several interconnected networks that could be targeted with drug therapy for potential chemoprevention and therapeutic applications.

Reverse-phase protein microarrays

Cancer is the consequence of intra- and extracellular signaling network deregulation that derives from alteration of genetic and proteomic cellular homeostasis. Mapping the individual molecular circuitry of a patient's tumor cells is the starting point for rational personalized therapy.While genes and RNA encode information about cellular status, proteins are considered the engine of the cellular machine, as they are the effective elements that drive cellular functions, such as proliferation, migration, differentiation, and apoptosis. Consequently, investigations of the cellular protein network are considered a fundamental tool to understand cellular functions. In the last decades, increasing interest has been focused on the improvement of new technologies for proteomic analysis. In this context, reverse-phase protein microarrays (RPMAs) have been developed to study and analyze posttranslational modifications that are responsible for principal cell functions and activities. This innovative technology allows the investigation of protein activation as a consequence of protein-protein interaction or biochemical reactions, such as phosphorylation, glycosylation, ubiquitination, protein cleavage, and conformational alterations.Intracellular balance is carefully conserved by constant rearrangements of proteins through the activity of a series of kinases and phosphatases. Therefore, knowledge of the key cellular signaling cascades reveal information regarding the cellular processes driving a tumor's growth (such as cellular survival, proliferation, invasion, and cell death) and response to treatment.Alteration to cellular homeostasis, driven by elaborate intra- and extracellular interactions, has become one of the most studied fields in the era of personalized medicine and targeted therapy. RPMA technology is a valid tool that can be applied to protein analysis of several diseases for the potential to generate protein interaction and activation maps that lead to the identification of critical nodes for individualized or combinatorial target therapy.

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.

Development of a novel proteomic approach for mitochondrial proteomics from cardiac tissue from patients with atrial fibrillation

Atrial fibrillation (AF) is the most common cardiac arrhythmia affecting approximately 2.2 million Americans. Because several studies have suggested that changes in mitochondrial function and morphology may contribute to AF, we developed a novel proteomic workflow focused on the identification of differentially expressed mitochondrial proteins in AF patients. Right human atrial tissue was collected from 20 patients, 10 with and 10 without AF, and the tissue was subjected to hydrostatic pressure cycling-based lysis followed by label-free mass spectrometric (MS) analysis of mitochondrial enriched isolates. Approximately 5% of the 700 proteins identified by MS analysis were differentially expressed between the AF and non-AF samples. We chose four differentially abundant proteins for further verification using reverse phase protein microarray analysis based on their known importance in energy production and regulatory association with atrial ion channels: four and a half LIM, destrin, heat shock protein 2, and chaperonin-containing TCP1. These initial study results provide evidence that a workflow to identify AF-related proteins that combines a powerful upfront tissue cell lysis with high resolution MS for discovery and protein array technology for verification may be an effective strategy for discovering candidate markers in highly fibrous tissue samples.

Pilot and feasibility study: prospective proteomic profiling of mammary epithelial cells from high-risk women provides evidence of activation of pro-survival pathways

Normal mammary gland homeostasis requires the coordinated regulation of protein signaling networks. However, we have little prospective information on whether activation of protein signaling occurs in premalignant mammary epithelial cells, as represented by cells with cytological atypia from women who are at high risk for breast cancer. This information is critical for understanding the role of deregulated signaling pathways in the initiation of breast cancer and for developing targeted prevention and/or treatment strategies for breast cancer in the future. In this pilot and feasibility study, we examined the expression of 52 phosphorylated, total, and cleaved proteins in 31 microdissected Random Periareolar Fine Needle Aspiration (RPFNA) samples by high-throughput Reverse Phase Protein Microarray. Unsupervised hierarchical clustering analysis indicated the presence of four clusters of proteins that represent the following signaling pathways: (1) receptor tyrosine kinase/Akt/mammalian target of rapamycin (RTK/Akt/mTOR), (2) RTK/Akt/extracellular signal-regulated kinase (RTK/Akt/ERK), (3) mitochondrial apoptosis, and (4) indeterminate. Clusters 1 through 3 comprised moderately to highly expressed proteins, while Cluster 4 comprised proteins that are lowly expressed in a majority of RPFNA samples. Our exploratory study showed that the interlinked components of mitochondrial apoptosis pathway are highly expressed in all mammary epithelial cells obtained from high-risk women. In particular, the expression levels of anti-apoptotic Bcl-xL and pro-apoptotic Bad are positively correlated in both non-atypical and atypical samples (unadjusted P < 0.0001), suggesting a delicate balance between the pro-apoptotic and anti-apoptotic regulation of cell proliferation during the early steps of mammary carcinogenesis. Our feasibility study suggests that the activation of key proteins along the RTK/Akt pathway may tip this balance to cell survival. Taken together, our results demonstrate the feasibility of mapping proteomic signaling networks in limited RPFNA samples obtained from high-risk women and the promise of developing rational drug targets or preventative strategies for breast cancer in future proteomic studies with a larger cohort of high-risk women.

Fine-needle aspiration for proteomic study of tumour tissues

Fine-needle aspiration (FNA) is a technique largely applied in the diagnosis of tumours. FNA is a safe diagnostic procedure that is widely employed in the examination of masses at relatively low cost and minimal risk to the patient. In this review, we report on the state-of-the-art and the potential role of FNA to search for protein biomarkers by the proteomic approach.

Reverse phase protein microarrays for clinical applications

Phosphorylated proteins represent one of the most important constituents of the proteome and are under intense analysis by the biotechnology and pharmaceutical industry because of their central role for cellular signal transduction. Indeed, alterations in cellular signaling and control mechanisms that modulate signal transduction, functionally underpin most human cancers today. Beyond their central role as the causative components of tumorigenesis, these proteins have become an important research focus for discovery of predictive and prognostic biomarkers. Consequently, these pathway constituents comprise a powerful biomarker subclass whereby the same analyte that provides prediction and/or prognosis is also the drug target itself: a theranostic marker. Reverse phase protein microarrays have been developed to generate a functional patient-specific circuit "map" of the cell signaling networks based directly on cellular analysis of a biopsy specimen. This patient-specific circuit diagram provides key information that identifies critical nodes within aberrantly activated signaling that may serve as drug targets for individualized or combinatorial therapy. The protein arrays provide a portrait of the activated signaling network by the quantitative analysis of the phosphorylated, or activated, state of cell signaling proteins. Based on the growing realization that each patient's tumor is different at the molecular level, the ability to measure and profile the ongoing phosphoprotein biomarker repertoire provides a new opportunity to personalize therapy based on the patient-specific alterations.

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.

Application of proteomic technologies for prostate cancer detection, prognosis, and tailored therapy

Prostate cancer affects 3 in 10 men over the age of 50 years, and, unfortunately, the clinical course of the disease is poorly predicted. At present, there is no means that can distinguish indolent from aggressive/metastatic tumors. Thus, a personalized clinical approach could be helpful in diagnosing clinically relevant disease and guiding appropriate patient therapy. Individualized medicine requires a deep knowledge of the molecular mechanisms underpinning prostate cancer carcinogenesis. Proteomics may be the most powerful way to uncover biomarkers of detection, prognosis, and prediction, as proteins do the work of the cell and represent the majority of the diagnostic markers and drug targets today. Proteomic technologies are rapidly advancing beyond the two-dimensional gel separation techniques of the past to new types of mass spectrometry and protein microarray analyses. Biological fluids and tissue-cell proteomes from men with prostate cancer are being explored to identify diagnostic and prognostic biomarkers and therapeutic targets using these new proteomic approaches. Traditional and novel proteomic technology and their application to prostate cancer studies in translational research will be presented and discussed in this review. Proteomics coupled with powerful nanotechnology-based biomarker discovery approaches may provide a new and exciting opportunity for body fluid-borne biomarker discovery and characterization. While innovative mass spectrometry technology and nanotrap could be applied to improve the discovery and measurement of biomarkers for the early detection of prostate cancer, the use of tissue proteomic tools such as the reverse-phase protein microarray may provide new approaches for personalization of therapies tailored to each tumor's unique pathway activation network.

Antibody-based proteomics: analysis of signaling networks using reverse protein arrays

Protein kinases drive the cellular signal transduction networks that underlie the regulation of growth, survival and differentiation. To repair the deregulations of signaling cascades that are associated with numerous disease states, therapeutic strategies, based on controlling aberrant protein kinase activity, are emerging. To develop such therapies it is crucial to have knowledge of the full complexity of signaling networks at a molecular level in order to understand the information flow through signaling cascades and their cell and tissue specificity. Antibody-based proteomic approaches (such as reverse-phase protein microarrays) are a powerful tool for using to obtain those signaling maps, through the study of phosphorylation states of pathway components using antibodies that specifically recognize the phosphorylated form of kinase substrates.