Emanuel F. Petricoin

Preinvasive and invasive ductal pancreatic cancer and its early detection in the mouse

To evaluate the role of oncogenic RAS mutations in pancreatic tumorigenesis, we directed endogenous expression of KRAS(G12D) to progenitor cells of the mouse pancreas. We find that physiological levels of Kras(G12D) induce ductal lesions that recapitulate the full spectrum of human pancreatic intraepithelial neoplasias (PanINs), putative precursors to invasive pancreatic cancer. The PanINs are highly proliferative, show evidence of histological progression, and activate signaling pathways normally quiescent in ductal epithelium, suggesting potential therapeutic and chemopreventive targets for the cognate human condition. At low frequency, these lesions also progress spontaneously to invasive and metastatic adenocarcinomas, establishing PanINs as definitive precursors to the invasive disease. Finally, mice with PanINs have an identifiable serum proteomic signature, suggesting a means of detecting the preinvasive state in patients.

Reverse phase protein microarrays which capture disease progression show activation of pro-survival pathways at the cancer invasion front.

Protein arrays are described for screening of molecular markers and pathway targets in patient matched human tissue during disease progression. In contrast to previous protein arrays that immobilize the probe, our reverse phase protein array immobilizes the whole repertoire of patient proteins that represent the state of individual tissue cell populations undergoing disease transitions. A high degree of sensitivity, precision and linearity was achieved, making it possible to quantify the phosphorylated status of signal proteins in human tissue cell subpopulations. Using this novel protein microarray we have longitudinally analysed the state of pro-survival checkpoint proteins at the microscopic transition stage from patient matched histologically normal prostate epithelium to prostate intraepithelial neoplasia (PIN) and then to invasive prostate cancer. Cancer progression was associated with increased phosphorylation of Akt (P<0.04), suppression of apoptosis pathways (P<0.03), as well as decreased phosphorylation of ERK (P<0.01). At the transition from histologically normal epithelium to PIN we observed a statistically significant surge in phosphorylated Akt (P<0.03) and a concomitant suppression of downstream apoptosis pathways which proceeds the transition into invasive carcinoma.

Laser-capture microdissection

Deciphering the cellular and molecular interactions that drive disease within the tissue microenvironment holds promise for discovering drug targets of the future. In order to recapitulate the in vivo interactions thorough molecular analysis, one must be able to analyze specific cell populations within the context of their heterogeneous tissue microecology. Laser-capture microdissection (LCM) is a method to procure subpopulations of tissue cells under direct microscopic visualization. LCM technology can harvest the cells of interest directly or can isolate specific cells by cutting away unwanted cells to give histologically pure enriched cell populations. A variety of downstream applications exist: DNA genotyping and loss-of-heterozygosity (LOH) analysis, RNA transcript profiling, cDNA library generation, proteomics discovery and signal-pathway profiling. Herein we provide a thorough description of LCM techniques, with an emphasis on tips and troubleshooting advice derived from LCM users. The total time required to carry out this protocol is typically 1–1.5 h.

PROTEOMIC APPLICATIONS FOR THE EARLY DETECTION OF CANCER

The ability of physicians to effectively treat and cure cancer is directly dependent on their ability to detect cancers at their earliest stages. Proteomic analyses of early-stage cancers have provided new insights into the changes that occur in the early phases of tumorigenesis and represent a new resource of candidate biomarkers for early-stage disease. Studies that profile proteomic patterns in body fluids also present new opportunities for the development of novel, highly sensitive diagnostic tools for the early detection of cancer.

Clinical proteomics: translating benchside promise into bedside reality

The ultimate goal of proteomics is to characterize the information flow through protein networks. This information can be a cause, or a consequence, of disease processes. Clinical proteomics is an exciting new subdiscipline of proteomics that involves the application of proteomic technologies at the bedside, and cancer, in particular, is a model disease for studying such applications. Here, we describe proteomic technologies that are being developed to detect cancer earlier, to discover the next generation of targets and imaging biomarkers, and finally to tailor the therapy to the patient.

Proteomic profiling of the NCI-60 cancer cell lines using new high-density reverse-phase lysate microarrays

Because most potential molecular markers and targets are proteins, proteomic profiling is expected to yield more direct answers to functional and pharmacological questions than does transcriptional profiling. To aid in such studies, we have developed a protocol for making reverse-phase protein lysate microarrays with larger numbers of spots than previously feasible. Our first application of these arrays was to profiling of the 60 human cancer cell lines (NCI-60) used by the National Cancer Institute to screen compounds for anticancer activity. Each glass slide microarray included 648 lysate spots representing the NCI-60 cell lines plus controls, each at 10 two-fold serial dilutions to provide a wide dynamic range. Mouse monoclonal antibodies and the catalyzed signal amplification system were used for immunoquantitation. The signal levels from the >30,000 data points for our first 52 antibodies were analyzed by using p-scan and a quantitative dose interpolation method. Clustered image maps revealed biologically interpretable patterns of protein expression. Among the principal early findings from these arrays were two promising pathological markers for distinguishing colon from ovarian adenocarcinomas. When we compared the patterns of protein expression with those we had obtained for the same genes at the mRNA level by using both cDNA and oligonucleotide arrays, a striking regularity appeared: cell-structure-related proteins almost invariably showed a high correlation between mRNA and protein levels across the NCI-60 cell lines, whereas non-cell-structure-related proteins showed poor correlation.

Molecular profiling of human cancer

Traditionally, tumours have been categorized on the basis of histology. However, the staining pattern of cancer cells viewed under the microscope is insufficient to reflect the complicated underlying molecular events that drive the neoplastic process. By surveying thousands of genes at once, using DNA arrays, it is now possible to read the molecular signature of an individual patients tumour. When the signature is analysed with clustering algorithms, new classes of cancer emerge that transcend distinctions based on histological appearance alone. Using DNA arrays, protein arrays and appropriate experimental models, the ultimate goal is to move beyond correlation and classification to achieve new insights into disease mechanisms and treatment targets.Key PointsTraditional approaches to cancer classification and diagnosis have been based on histological examination. Extensive genome data and DNA array technology have provided opportunities to monitor gene expression in cancer cells for thousands of genes at once. When preparing tissue samples, tissue fixation procedures must allow preservation of macromolecules. Tissue heterogeneity is another important issue for research on cancerous cells. Approaches to tissue heterogeneity include global sampling, the use of cell lines derived from tumours, and laser capture microdissection. Several studies have reported transcriptional profiling of cancer using DNA arrays. These studies have uncovered classes of cancer that extend traditional classification on the basis of histology and morphology. Clustering of genes by transcriptional profiling is also providing insights into gene function and cancer pathology, such as metastasis. Technologies are being developed that will allow cellular protein and signal pathway profiling. This will further extend our understanding of the molecular pathology of cancer, and can lead to patient-tailored therapies.

Protein microarrays: Meeting analytical challenges for clinical applications

Protein microarrays, one emerging class of proteomic technologies, have broad applications for discovery and quantitative analysis. A rapidly expanding use of this technology is the acquisition of information about the posttranslational modifications of proteins reflecting the activity state of signal pathways and networks, and is now employed for the analysis of biopsy samples in clinical trial research.

2D Differential In-gel Electrophoresis for the Identification of Esophageal Scans Cell Cancer-specific Protein Markers

The reproducibility of conventional two-dimensional (2D) gel electrophoresis can be improved using differential in-gel electrophoresis (DIGE), a new emerging technology for proteomic analysis. In DIGE, two pools of proteins are labeled with 1-(5-carboxypentyl)-1′-propylindocarbocyanine halide (Cy3) N-hydroxy-succinimidyl ester and 1-(5-carboxypentyl)-1′-methylindodi-carbocyanine halide (Cy5) N-hydroxysuccinimidyl ester fluorescent dyes, respectively. The labeled proteins are mixed and separated in the same 2D gel. 2D DIGE was applied to quantify the differences in protein expression between laser capture microdissection-procured esophageal carcinoma cells and normal epithelial cells and to define cancer-specific and normal-specific protein markers. Analysis of the 2D images from protein lysates of ∼ 250,000 cancer cells and normal cells identified 1038 protein spots in cancer cell lysates and 1088 protein spots in normal cell lysates. Of the detected proteins, 58 spots were up-regulated by >3-fold and 107 were down-regulated by >3-fold in cancer cells. In addition to previously identified down-regulated protein annexin I, tumor rejection antigen (gp96) was found up-regulated in esophageal squamous cell cancer. Global quantification of protein expression between laser capture-microdissected patient-matched cancer cells and normal cells using 2D DIGE in combination with mass spectrometry is a powerful tool for the molecular characterization of cancer progression and identification of cancer-specific protein markers.

Use of Reverse Phase Protein Microarrays and Reference Standard Development for Molecular Network Analysis of Metastatic Ovarian Carcinoma

Cancer can be defined as a deregulation or hyperactivity in the ongoing network of intracellular and extracellular signaling events. Reverse phase protein microarray technology may offer a new opportunity to measure and profile these signaling pathways, providing data on post-translational phosphorylation events not obtainable by gene microarray analysis. Treatment of ovarian epithelial carcinoma almost always takes place in a metastatic setting since unfortunately the disease is often not detected until later stages. Thus, in addition to elucidation of the molecular network within a tumor specimen, critical questions are to what extent do signaling changes occur upon metastasis and are there common pathway elements that arise in the metastatic microenvironment. For individualized combinatorial therapy, ideal therapeutic selection based on proteomic mapping of phosphorylation end points may require evaluation of the patient’s metastatic tissue. Extending these findings to the bedside will require the development of optimized protocols and reference standards. We have developed a reference standard based on a mixture of phosphorylated peptides to begin to address this challenge.