Protein pathway biomarker analysis of human cancer reveals requirement for upfront cellular-enrichment processing

Regulation of EZH2 Expression by INPP4B in Normal Prostate and Primary Prostate Cancer

The phosphatases INPP4B and PTEN are tumor suppressors that are lost in nearly half of advanced metastatic cancers. The loss of PTEN in prostate epithelium initially leads to an upregulation of several tumor suppressors that slow the progression of prostate cancer in mouse models. We tested whether the loss of INPP4B elicits a similar compensatory response in prostate tissue and whether this response is distinct from the one caused by the loss of PTEN. Knockdown of INPP4B but not PTEN in human prostate cancer cell lines caused a decrease in EZH2 expression. In Inpp4b-/- mouse prostate epithelium, EZH2 levels were decreased, as were methylation levels of histone H3. In contrast, Ezh2 levels were increased in the prostates of Pten-/- male mice. Contrary to PTEN, there was a positive correlation between INPP4B and EZH2 expression in normal human prostates and early-stage prostate tumors. Analysis of single-cell transcriptomic data demonstrated that a subset of EZH2-positive cells expresses INPP4B or PTEN, but rarely both, consistent with their opposing correlation with EZH2 expression. Unlike PTEN, INPP4B did not affect the levels of SMAD4 protein expression or Pml mRNA expression. Like PTEN, p53 protein expression and phosphorylation of Akt in Inpp4b-/- murine prostates were elevated. Taken together, the loss of INPP4B in the prostate leads to overlapping and distinct changes in tumor suppressor and oncogenic downstream signaling.

The impact of ultraviolet- and infrared-based laser microdissection technology on phosphoprotein detection in the laser microdissection-reverse phase protein array workflow

Reversible protein phosphorylation represents a key mechanism by which signals are transduced in eukaryotic cells. Dysregulated phosphorylation is also a hallmark of carcinogenesis and represents key drug targets in the precision medicine space. Thus, methods that preserve phosphoprotein integrity in the context of clinical tissue analyses are crucially important in cancer research. Here we investigated the impact of UV laser microdissection (UV LMD) and IR laser capture microdissection (IR LCM) on phosphoprotein abundance of key cancer signaling protein targets assessed by reverse-phase protein microarray (RPPA). Tumor epithelial cells from consecutive thin sections obtained from four high-grade serous ovarian cancers were harvested using either UV LMD or IR LCM methods. Phosphoprotein abundances for ten phosphoproteins that represent important drug targets were assessed by RPPA and revealed no significant differences in phosphoprotein integrity from those obtained using higher-energy UV versus the lower-energy IR laser methods.

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.

Computer-Aided Laser Dissection: A Microdissection Workflow Leveraging Image Analysis Tools

Introduction

The development and application of new molecular diagnostic assays based on next-generation sequencing and proteomics require improved methodologies for procurement of target cells from histological sections. Laser microdissection can successfully isolate distinct cells from tissue specimens based on visual selection for many research and clinical applications. However, this can be a daunting task when a large number of cells are required for molecular analysis or when a sizeable number of specimens need to be evaluated.

Materials and Methods

To improve the efficiency of the cellular identification process, we describe a microdissection workflow that leverages recently developed and open source image analysis algorithms referred to as computer-aided laser dissection (CALD). CALD permits a computer algorithm to identify the cells of interest and drive the dissection process.

Results

We describe several "use cases" that demonstrate the integration of image analytic tools probabilistic pairwise Markov model, ImageJ, spatially invariant vector quantization (SIVQ), and eSeg onto the ThermoFisher Scientific ArcturusXT and Leica LMD7000 microdissection platforms.

Conclusions

The CALD methodology demonstrates the integration of image analysis tools with the microdissection workflow and shows the potential impact to clinical and life science applications.

Protein drug target activation homogeneity in the face of intra-tumor heterogeneity: implications for precision medicine

Introduction: Recent studies indicated tumors may be comprised of heterogeneous molecular subtypes and incongruent molecular portraits may emerge if different areas of the tumor are sampled. This study explored the impact of intra-tumoral heterogeneity in terms of activation/phosphorylation of FDA approved drug targets and downstream kinase substrates.

Material and methods: Two independent sets of liver metastases from colorectal cancer were used to evaluate protein kinase-driven signaling networks within different areas using laser capture microdissection and reverse phase protein array.

Results: Unsupervised hierarchical clustering analysis indicated that the signaling architecture and activation of the MAPK and AKT-mTOR pathways were consistently maintained within different regions of the same biopsy. Intra-patient variability of the MAPK and AKT-mTOR pathway were <1.06 fold change, while inter-patients variability reached fold change values of 5.01.

Conclusions: Protein pathway activation mapping of enriched tumor cells obtained from different regions of the same tumor indicated consistency and robustness independent of the region sampled. This suggests a dominant protein pathway network may be activated in a high percentage of the tumor cell population. Given the genomic intra-tumoral variability, our data suggest that protein/phosphoprotein signaling measurements should be integrated with genomic analysis for precision medicine based analysis.

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 biomarkers for subtyping breast cancer and implications for future research

INTRODUCTION

Breast cancer subtypes are currently defined by a combination of morphologic, genomic, and proteomic characteristics. These subtypes provide a molecular portrait of the tumor that aids diagnosis, prognosis, and treatment escalation/de-escalation options. Gene expression signatures describing intrinsic breast cancer subtypes for predicting risk of recurrence have been rapidly adopted in the clinic. Despite the use of subtype classifications, many patients develop drug resistance, breast cancer recurrence, or therapy failure. Areas covered: This review provides a summary of immunohistochemistry, reverse phase protein array, mass spectrometry, and integrative studies that are revealing differences in biological functions within and between breast cancer subtypes. We conclude with a discussion of rigor and reproducibility for proteomic-based biomarker discovery. Expert commentary: Innovations in proteomics, including implementation of assay guidelines and standards, are facilitating refinement of breast cancer subtypes. Proteomic and phosphoproteomic information distinguish biologically functional subtypes, are predictive of recurrence, and indicate likelihood of drug resistance. Actionable, activated signal transduction pathways can now be quantified and characterized. Proteomic biomarker validation in large, well-designed studies should become a public health priority to capitalize on the wealth of information gleaned from the proteome.

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.

Strategies in functional proteomics: Unveiling the pathways to precision oncology

Personalised strategies in cancer care are required to overcome the therapeutic challenges posed by variability between patients and disease subsets. To this end, enhanced precision tools must be developed to describe the molecular drivers of malignant proliferation. Such tools must also identify druggable targets and biomarkers in order to provide essential information regarding drug development and therapeutic outcome. Here we discuss how proteomics-based approaches provide a set of viable methodologies capable of delivering quantitative information throughout the main stages of personalised oncology and a ratiometric platform that delivers systems-wide methods for drug evaluation.

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.

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.

Subtyping of breast cancer using reverse phase protein arrays

Reverse phase protein arrays (RPPAs) present a robust and sensitive high capacity platform for targeted proteomics that relies on highly specific antibodies to obtain a quantitative readout regarding phosphorylation state and abundance of proteins of interest. This review summarizes the current state of RPPA-based proteomic profiling of breast cancer in the context of existing preanalytical strategies and sample preparation protocols. RPPA-based subtypes identified so far are compared to those obtained by other approaches such as immunohistochemistry, genomics and transcriptomics. Special attention is given to discussing the potential of RPPA for biomarker discovery and biomarker validation.

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.

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.

Spatial normalization of reverse phase protein array data

Reverse phase protein arrays (RPPA) are an efficient, high-throughput, cost-effective method for the quantification of specific proteins in complex biological samples. The quality of RPPA data may be affected by various sources of error. One of these, spatial variation, is caused by uneven exposure of different parts of an RPPA slide to the reagents used in protein detection. We present a method for the determination and correction of systematic spatial variation in RPPA slides using positive control spots printed on each slide. The method uses a simple bi-linear interpolation technique to obtain a surface representing the spatial variation occurring across the dimensions of a slide. This surface is used to calculate correction factors that can normalize the relative protein concentrations of the samples on each slide. The adoption of the method results in increased agreement between technical and biological replicates of various tumor and cell-line derived samples. Further, in data from a study of the melanoma cell-line SKMEL-133, several slides that had previously been rejected because they had a coefficient of variation (CV) greater than 15%, are rescued by reduction of CV below this threshold in each case. The method is implemented in the R statistical programing language. It is compatible with MicroVigene and SuperCurve, packages commonly used in RPPA data analysis. The method is made available, along with suggestions for implementation, at http://bitbucket.org/rppa_preprocess/rppa_preprocess/src.

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.

Novel neoadjuvant therapy paradigms for bladder cancer: results from the National Cancer Center Institute Forum

OBJECTIVE

To bridge gaps in translational science and develop the concepts for 2 novel biomarker-driven clinical trials: one in the presurgical setting and the other in the setting of bladder preservation with chemoradiation.

METHODS AND MATERIALS

The National Cancer Institute sponsored a forum, "Novel Neoadjuvant Therapy for Bladder Cancer," which brought leading clinical and laboratory-based scientists together with the advocacy community.

RESULTS

The group designed a neoadjuvant clinical trial to compare the clinical efficacy of the two frontline chemotherapy regimens (gemcitabine plus cisplatin versus MVAC) and the ability of a gene expression profiling-based algorithm (CoXEN) to predict complete pathological response. The trial was recently opened under the leadership of the Southwest Oncology Group (SWOG, S1314), receiving support for the biomarker studies from the NCI's BISQFP resource. A second clinical trial was planned that will examine the relationship between expression of the DNA repair protein MRE11 and complete response in patients treated with concurrent 5-fluorouracil/mitomycin C plus radiation.

CONCLUSION

The meeting provided a unique opportunity to launch a collective effort to establish molecular-based therapies for muscle-invasive urothelial cancer. The goal is to use this framework to develop comparable trials with immunotherapy in non-muscle invasive cancers and to exploit the neoadjuvant platform to develop targeted therapy in muscle-invasive disease.

SIVQ-LCM protocol for the ArcturusXT instrument

SIVQ-LCM is a new methodology that automates and streamlines the more traditional, user-dependent laser dissection process. It aims to create an advanced, rapidly customizable laser dissection platform technology. In this report, we describe the integration of the image analysis software Spatially Invariant Vector Quantization (SIVQ) onto the ArcturusXT instrument. The ArcturusXT system contains both an infrared (IR) and ultraviolet (UV) laser, allowing for specific cell or large area dissections. The principal goal is to improve the speed, accuracy, and reproducibility of the laser dissection to increase sample throughput. This novel approach facilitates microdissection of both animal and human tissues in research and clinical workflows.

Multiplex quantitative measurement of mRNAs from fixed tissue microarray sections

The development of prognostic and diagnostic biomarkers, such as those from gene expression studies, requires independent validation in clinical specimens. Immunohistochemical analysis on tissue microarrays (TMAs) of formalin-fixed paraffin-embedded tissue is often used to increase the statistical power, and it is used more often than in situ hybridization, which can be technically limiting. Herein, we introduce a method for performing quantitative gene expression analysis across a TMA using an adaptation of 2D-RT-qPCR, a recently developed technology for measuring transcript levels in a histologic section while maintaining 2-dimensional positional information of the tissue sample. As a demonstration of utility, a TMA with tumor and normal human prostate samples was used to validate expression profiles from previous array-based gene discovery studies of prostate cancer. The results show that 2D-RT-qPCR expands the utility of TMAs to include sensitive and accurate gene expression measurements.

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.

Application of molecular technologies for phosphoproteomic analysis of clinical samples

The integration of small kinase inhibitors and monoclonal antibodies into oncological practice has opened a new paradigm for treating cancer patients. As proteins are the direct targets of the new generations of targeted therapeutics, many of which are kinase/enzymatic inhibitors, there is an increasing interest in developing technologies capable of monitoring post-translational changes of the human proteome for the identification of new predictive, prognostic and therapeutic biomarkers. It is well known that the vast majority of the activation/deactivation of these drug targets is driven by phosphorylation. This review provides a description of the main proteomic platforms (planar and bead array, reverse phase protein microarray, phosphoflow, AQUA and mass spectrometry) that have successfully been used for measuring changes in phosphorylation level of drug targets and downstream substrates using clinical specimens. Major emphasis was given to the strengths and weaknesses of the different platforms and to the major barriers that are associated with the analysis of the phosphoproteome. Finally, a number of examples of application of the above-mentioned technologies in the clinical setting are reported.

Preparation and use of reverse protein microarrays

Reverse-phase protein array (RPPA) is a multiplex, high-throughput proteomic technique for profiling the activation status of signal transduction pathways involved in cancer survival and progression, potentially allowing for identification of new biomarkers and drug targets. On RPPA, the entire patient proteome is immobilized on a spot and single proteins can be quantified across a set of samples, spotted on the same array, with high specificity and sensitivity. Array immunostaining and signal amplification systems are used to generate a signal proportional to the concentration of the analyte. Dedicated scanners and software are used to detect spots, measure intensity, subtract background, normalize signal, and generate a numeric value as output. The generated output file is then analyzed using several different bioinformatic and biostatistical tools. In this unit, the RPPA procedure is described in depth, from sample handling and preparation to data analysis, with particular emphasis on tissue sample analysis.

Glioblastoma cell enrichment is critical for analysis of phosphorylated drug targets and proteomic-genomic correlations

The quality of cancer genomic and proteomic data relies upon the quality of the clinical specimens examined. Here, we show that data derived from non-microdissected glioblastoma multiforme tumor tissue is either masked or not accurate, producing correlations between genomic and proteomic data that lead to false classifications for therapeutic stratification. We analyzed the level of 133 key signaling proteins and phosphoproteins in laser capture microdissected (LCM) primary tumors from a study set of tissues used for the Cancer Genome Atlas (TCGA) profiling efforts, comparing the results to tissue-matched, nontumor cell-enriched lysates from adjacent sections. Among the analytes, 44%, including targets for clinically important inhibitors, such as phosphorylated mTOR, AKT, STAT1, VEGFR2, or BCL2, differed between matched tumor cell-enriched and nonenriched specimens (even in tumor sections with 90% tumor cell content). While total EGFR protein levels were higher in tumors with EGFR mutations, regardless of tumor cell enrichment, EGFR phosphorylation was increased only in LCM-enriched tumor specimens carrying EGFR mutations. Phosphorylated and total PTEN, which is highly expressed in normal brain, was reduced only in LCM-enriched tumor specimens with either PTEN mutation or loss in PTEN copy number, with no differences observed in non-microdissected samples. These results were confirmed in an independent, non-microdissected, publicly available protein data set from the TCGA database. Our findings highlight the necessity for careful upfront cellular enrichment in biospecimens that form the basis for targeted therapy selection and for molecular characterization efforts such as TCGA.

Laser capture microdissection for the investigative pathologist

An important step in translational research is the validation of molecular findings from in vitro experiments using tissue specimens. However, tissue specimens are complex and contain a multitude of diverse cell populations that interfere with the molecular profiling data of a specific cell type. Laser capture microdissection (LCM) alleviates this issue by providing a valuable tool for the enrichment of a specific cell type within complex tissue samples. However, LCM and molecular analysis from tissue specimens can be complex and challenging due to numerous issues related with the tissue processing and its impact on the integrity of biomolecules in the specimen. The intricate nature of this application highlights the essential role a pathologist plays in translational research by contributing an expertise in histopathology, tissue handling, tissue analysis techniques, and clinical correlation of biological findings. The present review examines key practical aspects in tissue handling, specimen selection, quality control, and sample preparation for LCM and downstream molecular analyses that are a primary objective of the investigative pathologist.

Analysis of transcription factor mRNAs in identified oxytocin and vasopressin magnocellular neurons isolated by laser capture microdissection

The oxytocin (Oxt) and vasopressin (Avp) magnocellular neurons (MCNs) in the hypothalamus are the only neuronal phenotypes that are present in the supraoptic nucleus (SON), and are characterized by their robust and selective expression of either the Oxt or Avp genes. In this paper, we take advantage of the differential expression of these neuropeptide genes to identify and isolate these two individual phenotypes from the rat SON by laser capture microdissection (LCM), and to analyze the differential expression of several of their transcription factor mRNAs by qRT-PCR. We identify these neuronal phenotypes by stereotaxically injecting recombinant Adeno-Associated Viral (rAAV) vectors which contain cell-type specific Oxt or Avp promoters that drive expression of EGFP selectively in either the Oxt or Avp MCNs into the SON. The fluorescent MCNs are then dissected by LCM using a novel Cap Road Map protocol described in this paper, and the purified MCNs are extracted for their RNAs. qRT-PCR of these RNAs show that some transcription factors (RORA and c-jun) are differentially expressed in the Oxt and Avp MCNs.

Individualized therapy for metastatic colorectal cancer

Systemic therapeutic efficacy is central to determining the outcome of patients with metastatic colorectal cancer (CRC). In these patients, there is a critical need for predictive biomarkers to optimize efficacy whilst minimizing toxicity. The integration of a new generation of molecularly targeted drugs into the treatment of CRC, coupled with the development of sophisticated technologies for individual tumours as well as patient molecular profiling, underlines the potential for personalized medicine. In this review, we focus on the latest progress made within the genomic and proteomic fields, concerning predictive biomarkers for individualized therapy in metastatic CRC.

A pilot characterization of human lung NSCLC by protein pathway activation mapping

BACKGROUND

An understanding of the activated protein signaling architecture in non-small-cell lung cancer (NSCLC) is of critical importance to the development of new therapeutic approaches and identification of predictive and prognostic biomarkers for patient stratification.

METHODS

We used reverse-phase protein microarrays to map the activated protein signaling networks of 47 NSCLC tumors, 28 of which were node negative, which were subjected to tumor cellular enrichment using laser capture microdissection. The phosphorylation/cleavage levels of 111 key signaling proteins and total levels of 17 proteins were measured for broadscale signaling analysis.

RESULTS

Pathway activation mapping of NSCLC revealed distinct subgroups composed of epidermal growth factor receptor (ERBB1), v-erb-b2 erythroblastic leukemia viral oncogene homolog 2 (ERBB2), v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (ERBB3), v-erb-a erythroblastic leukemia viral oncogene homolog 4 (ERBB4), v-akt murine thymoma viral oncogene homolog 1- mammalian target of rapamycin (AKT-mTOR), protein kinase, AMP-activated, alpha 2 catalytic subunit (AMPK), and autophagy-related signaling, along with transforming growth factor-beta-signaling protein 1 (SMAD), insulin-line growth factor receptor (IGFR), rearranged during transfection proto-oncogene (RET), and activated CDC42-associated kinase (ACK) activation. Investigation of epidermal growth factor receptor (EGFR)-driven signaling identified a unique cohort of tumors with low EGFR protein expression yet high relative levels of phosphorylated EGFR and high EGFR total protein with low relative levels of phosphorylation. Last, mapping analysis of patients with NSCLC with N0 disease revealed a pilot pathway activation signature composed of linked epidermal growth factor receptor family (HER)-AMPK-AKT-mTOR signaling network along with focal adhesion kinase- LIM domain kinase-1 (FAK-LIMK) and janus kinase (JAK)-signal transducers and activators of transcription (STAT) pathways that correlated with short-term survival and aggressive disease.

CONCLUSIONS

Functional protein pathway activation mapping of NSCLC reveals distinct activation subgroups that are underpinned by important therapeutic targets and that patients with early-stage node negative disease and poor prognosis may be identified by activation of defined, biochemically linked protein signaling events. Such findings, if confirmed in larger study sets, could help select and stratify patients for personalized targeted therapies.

Optimal molecular profiling of tissue and tissue components: defining the best processing and microdissection methods for biomedical applications

Isolation of well-preserved pure cell populations is a prerequisite for sound studies of the molecular basis of any tissue-based biological phenomenon. This updated chapter reviews current methods for obtaining anatomically specific signals from molecules isolated from tissues, a basic requirement for productive linking of phenotype and genotype. The quality of samples isolated from tissue and used for molecular analysis is often glossed over or omitted from publications, making interpretation and replication of data difficult or impossible. Fortunately, recently developed techniques allow life scientists to better document and control the quality of samples used for a given assay, creating a foundation for improvement in this area. Tissue processing for molecular studies usually involves some or all of the following steps: tissue collection, gross dissection/identification, fixation, processing/embedding, storage/archiving, sectioning, staining, microdissection/annotation, and pure analyte labeling/identification and quantification. We provide a detailed comparison of some current tissue microdissection technologies and provide detailed example protocols for tissue component handling upstream and downstream from microdissection. We also discuss some of the physical and chemical issues related to optimal tissue processing and include methods specific to cytology specimens. We encourage each laboratory to use these as a starting point for optimization of their overall process of moving from collected tissue to high-quality, appropriately anatomically tagged scientific results. Improvement in this area will significantly increase life science quality and productivity. The chapter is divided into introduction, materials, protocols, and notes subheadings. Because many protocols are covered in each of these sections, information relating to a single protocol is not contiguous. To get the greatest benefit from this chapter, readers are advised to read through the entire chapter first, identify protocols appropriate to their laboratory for each step in their workflow, and then reread entries in each section pertaining to each of these single protocols.

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.

Molecular analysis of HER2 signaling in human breast cancer by functional protein pathway activation mapping

PURPOSE

Targeting of the HER2 protein in human breast cancer represents a major advance in oncology but relies on measurements of total HER2 protein and not HER2 signaling network activation. We used reverse-phase protein microarrays (RPMA) to measure total and phosphorylated HER2 in the context of HER family signaling to understand correlations between phosphorylated and total levels of HER2 and downstream signaling activity.

EXPERIMENTAL DESIGN

Three independent study sets, comprising a total of 415 individual patient samples from flash-frozen core biopsy samples and formalin-fixed and paraffin-embedded (FFPE) surgical and core samples, were analyzed via RPMA. The phosphorylation and total levels of the HER receptor family proteins and downstream signaling molecules were measured in laser capture microdissected (LCM) enriched tumor epithelium from 127 frozen pretreatment core biopsy samples and whole-tissue lysates from 288 FFPE samples and these results were compared with FISH and immunohistochemistry (IHC).

RESULTS

RPMA measurements of total HER2 were highly concordant (>90% all sets) with FISH and/or IHC data, as was phosphorylation of HER2 in the FISH/IHC(+) population. Phosphorylation analysis of HER family signaling identified HER2 activation in some FISH/IHC(-) tumors and, identical to that seen with FISH/IHC(+) tumors, the HER2 activation was concordant with EGF receptor (EGFR) and HER3 phosphorylation and downstream signaling endpoint activation.

CONCLUSIONS

Molecular profiling of HER2 signaling of a large cohort of human breast cancer specimens using a quantitative and sensitive functional pathway activation mapping technique reveals IHC(-)/FISH(-)/pHER2(+) tumors with HER2 pathway activation independent of total HER2 levels and functional signaling through HER3 and EGFR.

An efficient procedure for protein extraction from formalin-fixed, paraffin-embedded tissues for reverse phase protein arrays

INTRODUCTION

Protein extraction from formalin-fixed paraffin-embedded (FFPE) tissues is challenging due to extensive molecular crosslinking that occurs upon formalin fixation. Reverse-phase protein array (RPPA) is a high-throughput technology, which can detect changes in protein levels and protein functionality in numerous tissue and cell sources. It has been used to evaluate protein expression mainly in frozen preparations or FFPE-based studies of limited scope. Reproducibility and reliability of the technique in FFPE samples has not yet been demonstrated extensively. We developed and optimized an efficient and reproducible procedure for extraction of proteins from FFPE cells and xenografts, and then applied the method to FFPE patient tissues and evaluated its performance on RPPA.

RESULTS

Fresh frozen and FFPE preparations from cell lines, xenografts and breast cancer and renal tissues were included in the study. Serial FFPE cell or xenograft sections were deparaffinized and extracted by six different protein extraction protocols. The yield and level of protein degradation were evaluated by SDS-PAGE and Western Blots. The most efficient protocol was used to prepare protein lysates from breast cancer and renal tissues, which were subsequently subjected to RPPA. Reproducibility was evaluated and Spearman correlation was calculated between matching fresh frozen and FFPE samples.The most effective approach from six protein extraction protocols tested enabled efficient extraction of immunoreactive protein from cell line, breast cancer and renal tissue sample sets. 85% of the total of 169 markers tested on RPPA demonstrated significant correlation between FFPE and frozen preparations (p < 0.05) in at least one cell or tissue type, with only 23 markers common in all three sample sets. In addition, FFPE preparations yielded biologically meaningful observations related to pathway signaling status in cell lines, and classification of renal tissues.

CONCLUSIONS

With optimized protein extraction methods, FFPE tissues can be a valuable source in generating reproducible and biologically relevant proteomic profiles using RPPA, with specific marker performance varying according to tissue type.

EGFR and KRAS mutation analysis in cytologic samples of lung adenocarcinoma enabled by laser capture microdissection

The discovery of activating mutations in EGFR and KRAS in a subset of lung adenocarcinomas was a major advance in our understanding of lung adenocarcinoma biology, and has led to groundbreaking studies that have demonstrated the efficacy of tyrosine kinase inhibitor therapy. Fine-needle aspirates and other cytologic procedures have become increasingly popular for obtaining diagnostic material in lung carcinomas. However, frequently the small amount of material or sparseness of tumor cells obtained from cytologic preparations limit the number of specialized studies, such as mutation analysis, that can be performed. In this study we used laser capture microdissection to isolate small numbers of tumor cells to assess for EGFR and KRAS mutations from cell block sections of 19 cytology samples from patients with known lung adenocarcinomas. We compared our results with previous molecular assays that had been performed on either surgical or cytology specimens as part of the patient's initial clinical work-up. Not only were we able to detect the identical EGFR or KRAS mutation that was present in the patient's prior molecular assay in every case, but we were also able to consistently detect the mutation from as few as 50 microdissected tumor cells. Furthermore, isolating a more pure population of tumor cells resulted in increased sensitivity of mutation detection as we were able to detect mutations from laser capture microdissection-enriched cases where the tumor load was low and traditional methods of whole slide scraping failed. Therefore, this method can not only significantly increase the number of lung adenocarcinoma patients that can be screened for EGFR and KRAS mutations, but can also facilitate the use of cytologic samples in the newly emerging field of molecular-based personalized therapies.

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.

Construction and hyperspectral imaging of quantum dot lysate arrays

The emerging field of proteomic molecular profiling will be driven by new technologies that can measure dozens to hundreds of proteins from a small sample input from a patient's biopsy. Lysate arrays, or reverse-phase protein microarrays, provide a platform for complex mixtures of proteins extracted from cells and tissues to be directly immobilized onto a solid support (such as a biochip with protein binding capacity) in diminutive volumes (picoliter-to-nanoliter). The proteins are spotted using precision robotics and then quantitatively assayed using primary antibodies; important posttranslational modifications, such as phosphorylations that are important for protein activation, may also be assayed to provide an estimate of the regulation of cellular signaling. Until recently, chromogenic signals and fluorescence (using organic fluorophores) detection were two strategies relied upon for signal detection. Emerging regents such as quantum dots (Qdot® nanocrystals; QD) are now employed for improved performance. QD embody a more versatile detection system because the robust signals may be time averaged and the narrow spectral emissions enable many protein targets to be quantified within the same lysate spot. Previously, we found that commercially available pegylated, streptavidin-conjugated QD were effective detection agents, with low-background affinities to spurious components within heterogeneous protein mixtures. Hyperspectral imaging allows the simultaneous detection of the different colored QD reagents within a single lysate spot. Here, we described the construction and imaging of QD lysate arrays. This technology is an emerging, enabling tool within the exciting, clinically oriented field of clinical tissue proteomics.

Protein expression signatures for inhibition of epidermal growth factor receptor-mediated signaling

Analysis of cellular signaling networks typically involves targeted measurements of phosphorylated protein intermediates. However, phosphoproteomic analyses usually require affinity enrichment of phosphopeptides and can be complicated by artifactual changes in phosphorylation caused by uncontrolled preanalytical variables, particularly in the analysis of tissue specimens. We asked whether changes in protein expression, which are more stable and easily analyzed, could reflect network stimulation and inhibition. We employed this approach to analyze stimulation and inhibition of the epidermal growth factor receptor (EGFR) by EGF and selective EGFR inhibitors. Shotgun analysis of proteomes from proliferating A431 cells, EGF-stimulated cells, and cells co-treated with the EGFR inhibitors cetuximab or gefitinib identified groups of differentially expressed proteins. Comparisons of these protein groups identified 13 proteins whose EGF-induced expression changes were reversed by both EGFR inhibitors. Targeted multiple reaction monitoring analysis verified differential expression of 12 of these proteins, which comprise a candidate EGFR inhibition signature. We then tested these 12 proteins by multiple reaction monitoring analysis in three other models: 1) a comparison of DiFi (EGFR inhibitor-sensitive) and HCT116 (EGFR-insensitive) cell lines, 2) in formalin-fixed, paraffin-embedded mouse xenograft DiFi and HCT116 tumors, and 3) in tissue biopsies from a patient with the gastric hyperproliferative disorder Ménétrier's disease who was treated with cetuximab. Of the proteins in the candidate signature, a core group, including c-Jun, Jagged-1, and Claudin 4, were decreased by EGFR inhibitors in all three models. Although the goal of these studies was not to validate a clinically useful EGFR inhibition signature, the results confirm the hypothesis that clinically used EGFR inhibitors generate characteristic protein expression changes. This work further outlines a prototypical approach to derive and test protein expression signatures for drug action on signaling networks.

Protein pathway activation mapping of brain metastasis from lung and breast cancers reveals organ type specific drug target activation

Brain metastases are the most common fatal complication of systemic cancer, especially of lung (40-50%) and breast (20-30%) cancers. In this era of personalized therapy, there is a critical need to uncover the signaling architecture of brain metastases; however, little is known about what signaling pathways are activated in the context of the brain microenvironment. Using a unique study set of 42 brain metastases from patients with breast or nonsmall cell lung cancer (NSCLC), the phosphorylation/activation states of 128 key signaling proteins involved in cancer signaling were measured in laser capture microdissected tumor epithelium using reverse phase protein microarray (RPMA) technology. Distinct pathway activation subgroups from both breast and lung metastases were underpinned by, among others, ERBB2, AKT, mTOR, EGFR, SMAD, and ERK-p38 signaling. Breast cancer metastases showed significantly (p < 0.05) higher activation of the c-ERBB2/IGFR-AKT pathway network compared to NSCLC metastases, whereas NSCLC metastases to the brain exhibited higher relative levels of many members of the EGFR-ERK signaling network. Protein pathway activation mapping using RPMA revealed both the heterogeneity of signaling networks in brain metastases that would require a prior stratification to targeted therapies as well as the requirement of direct analysis of the metastatic lesion.

Why is it crucial to reintegrate pathology into cancer research?

The integration of pathology with molecular biology is vital if we are to enhance the translational value of cancer research. Pathology represents a bridge between medicine and basic biology, it remains the gold standard for cancer diagnosis, and it plays an important role in discovery studies. In the past, pathology and cancer research were closely associated; however, the molecular biology revolution has shifted the focus of investigators toward the molecular alterations of tumors. The reductionist approach taken in molecular studies is producing great insight into the inner workings of neoplasia, but it can also minimize the importance of histopathology and of understanding the disease as a whole. In turn, pathologists can underestimate the role of molecular studies in developing new ancillary techniques for clinical diagnosis. A multidisciplinary approach that integrates pathology and molecular biology within a translational research system is needed. This process will require overcoming cultural barriers and can be achieved through education, a more effective incorporation of pathology into biological research, and conversely an integration of biological research into the pathology laboratory.

SIVQ-aided laser capture microdissection: A tool for high-throughput expression profiling

Introduction:

Laser capture microdissection (LCM) facilitates procurement of defined cell populations for study in the context of histopathology. The morphologic assessment step in the LCM procedure is time consuming and tedious, thus restricting the utility of the technology for large applications.

Results:

Here, we describe the use of Spatially Invariant Vector Quantization (SIVQ) for histological analysis and LCM. Using SIVQ, we selected vectors as morphologic predicates that were representative of normal epithelial or cancer cells and then searched for phenotypically similar cells across entire tissue sections. The selected cells were subsequently auto-microdissected and the recovered RNA was analyzed by expression microarray. Gene expression profiles from SIVQ–LCM and standard LCM–derived samples demonstrated highly congruous signatures, confirming the equivalence of the differing microdissection methods.

Conclusion:

SIVQ–LCM improves the work-flow of microdissection in two significant ways. First, the process is transformative in that it shifts the pathologist's role from technical execution of the entire microdissection to a limited-contact supervisory role, enabling large-scale extraction of tissue by expediting subsequent semi-autonomous identification of target cell populations. Second, this work-flow model provides an opportunity to systematically identify highly constrained cell populations and morphologically consistent regions within tissue sections. Integrating SIVQ with LCM in a single environment provides advanced capabilities for efficient and high-throughput histological-based molecular studies.

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.