Search PubMed⌕ Search

Biomedical subjects

Emanuel F Petricoin

Publications and source records attributed to Emanuel F Petricoin.

At least 19 recordsLinked to original sources
PubMed2006

Nanoparticles: potential biomarker harvesters.

A previously untapped bank of information resides within the low molecular weight proteomic fraction of blood. Intensive efforts are underway to harness this information so that it can be used for early diagnosis of diseases such as cancer. The physicochemical malleability and high surface areas of nanoparticle surfaces make them ideal candidates for developing biomarker harvesting platforms. Given the variety of engineering strategies afforded through nanoparticle technologies, a significant goal is to tailor nanoparticle surfaces to selectively bind a subset of biomarkers, sequestering them for later study using high sensitivity proteomic tests. To date, applications of nanoparticles have largely focused on imaging systems and drug delivery vectors. As such, biomarker harvesting is an underutilized application of nanoparticle technology and is an area of nanotechnology research that will likely undergo substantial growth.

Biomarkers↗
PubMed2006

The amplified peptidome: the new treasure chest of candidate biomarkers.

Mass spectrometric analysis of the low-molecular weight (LMW) range of the serum/plasma proteome is revealing the existence of large numbers of previously unknown peptides and protein fragments predicted to be derived from low-abundance proteins. This raises the question of why such low abundance molecules would be retained at detectable levels in the circulation, instead of being rapidly cleared and excreted. Theoretical models of biomarker production and association with serum carrier proteins have been developed to elucidate the mechanisms governing biomarker half-life in the bloodstream. These models predict that the vast majority of LMW biomarkers exist in association with circulating high molecular mass carrier proteins. Moreover, the total serum/plasma concentration of the biomarker is largely determined by the clearance rate of the carrier protein, not the free-phase biomarker clearance itself. These predictions have been verified experimentally using molecular mass fractionation of human serum before mass spectrometry sequence analysis. These principles have profound implications for biomarker discovery and measurement.

Biomarkers↗
PubMed2006

Selective binding and enrichment for low-molecular weight biomarker molecules in human plasma after exposure to nanoporous silica particles.

The present manuscript describes a biomarker capturing strategy based on nanoporous silica particles. The method is shown to enrich the yield of species in the low-molecular weight proteome (LMWP), allowing detection of small peptides in the low-nanomolar range. Plasma samples were exposed to the silica particles, and the captured molecular species were profiled using MALDI-TOF. Mass spectra of the silica-treated human plasma samples showed a significant enrichment in MALDI-TOF protein profiles in the LMWP. Preliminary results indicated good level of reproducibility in plasma profiles with CVs on peak heights ranging from 6.3 to 14.7%. The MALDI-TOF signature changed significantly when the characteristics of the nanoporous silica were altered. The facile sample pretreatment before MS analysis, coupled to the potential for tailoring the surface properties of silica supports, hold promise for improving the recovery of low-abundance serum biomarkers.

Biomarkers↗
PubMed2006

Nanoporous surfaces as harvesting agents for mass spectrometric analysis of peptides in human plasma.

Silica-based nanoporous surfaces have been developed in order to capture low molecular weight peptides from human plasma. Harvested peptides were subjected to mass spectrometric analysis by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) as a means of detecting and assessing the bound molecules. Peptide profiles consisting of about 70 peaks in the range 800-10,000 m/z were generated. The method could allow detection of small peptides at ng/mL concentration levels, either in standard solutions or in plasma. The same molecular cutoff effect was observed for mixtures of standard proteins and peptides incubated with silicon-based nanoporous surfaces.

Blood Proteins↗
PubMed2006

Technology insight: pharmacoproteomics for cancer--promises of patient-tailored medicine using protein microarrays.

Patient-tailored medicine can be defined as the selection of specific therapeutics to treat disease in a particular individual based on genetic, genomic or proteomic information. While individualized treatments have been used in medicine for years, advances in cancer treatment have now generated a need to more precisely define and identify those patients who will derive the most benefit from new-targeted agents. Cellular signaling pathways are a protein-based network, and the intended drug effect is to disrupt aberrant protein phosphorylation-based enzymatic activity and epigenetic phenomena. Pharmacoproteomics, or the tailoring of therapy based on proteomic knowledge, will begin to take a central role in this process. A new type of protein array platform, the reverse-phase protein microarray, shows potential for providing detailed information about the state of the cellular 'circuitry' from small samples such as patient biopsy specimens. Measurements of hundreds of specific phosphorylated proteins that span large classes of important signaling pathways can be obtained at once from only a few thousand cells. Clinical implementation of these new proteomic tools to aid the clinical, medical and surgical oncologist in making decisions about patient care will now require thoughtful communication between practicing clinicians and research scientists.

Gene Expression Profiling↗
PubMed2006

Serum peptidome for cancer detection: spinning biologic trash into diagnostic gold.

The low molecular weight region of the serum peptidome contains protein fragments derived from 2 sources: (a) high-abundance endogenous circulating proteins and (b) cell and tissue proteins. While some researchers have dismissed the serum peptidome as biological trash, recent work using mass spectrometry-based (MS-based) profiling has indicated that the peptidome may reflect biological events and contain diagnostic biomarkers. In this issue of the JCI, Villanueva et al. report on MS-based peptide profiling of serum samples from patients with advanced prostate, bladder, or breast cancer as well as from healthy controls. Surprisingly, the peptides identified as cancer-type-specific markers proved to be products of enzymatic breakdown generated after patient blood collection. The impact of these results on cancer biomarker discovery efforts is significant because it is widely believed that proteolysis occurring ex vivo should be suppressed because it destroys endogenous biomarkers. Villanueva et al. now suggest that this suppression may in fact be preventing biomarker generation.

Biomarkers↗
PubMed2005

Analysis of mass spectral serum profiles for biomarker selection.

MOTIVATION: Mass spectrometric profiles of peptides and proteins obtained by current technologies are characterized by complex spectra, high dimensionality and substantial noise. These characteristics generate challenges in the discovery of proteins and protein-profiles that distinguish disease states, e.g. cancer patients from healthy individuals. We present low-level methods for the processing of mass spectral data and a machine learning method that combines support vector machines, with particle swarm optimization for biomarker selection. RESULTS: The proposed method identified mass points that achieved high prediction accuracy in distinguishing liver cancer patients from healthy individuals in SELDI-QqTOF profiles of serum. AVAILABILITY: MATLAB scripts to implement the methods described in this paper are available from the HWR's lab website http://lombardi.georgetown.edu/labpage

Algorithms↗
PubMed2005

Analysis of albumin-associated peptides and proteins from ovarian cancer patients.

BACKGROUND: Albumin binds low-molecular-weight molecules, including proteins and peptides, which then acquire its longer half-life, thereby protecting the bound species from kidney clearance. We developed an experimental method to isolate albumin in its native state and to then identify [mass spectrometry (MS) sequencing] the corresponding bound low-molecular-weight molecules. We used this method to analyze pooled sera from a human disease study set (high-risk persons without cancer, n = 40; stage I ovarian cancer, n = 30; stage III ovarian cancer, n = 40) to demonstrate the feasibility of this approach as a discovery method. METHODS: Albumin was isolated by solid-phase affinity capture under native binding and washing conditions. Captured albumin-associated proteins and peptides were separated by gel electrophoresis and subjected to iterative MS sequencing by microcapillary reversed-phase tandem MS. Selected albumin-bound protein fragments were confirmed in human sera by Western blotting and immunocompetition. RESULTS: In total, 1208 individual protein sequences were predicted from all 3 pools. The predicted sequences were largely fragments derived from proteins with diverse biological functions. More than one third of these fragments were identified by multiple peptide sequences, and more than one half of the identified species were in vivo cleavage products of parent proteins. An estimated 700 serum peptides or proteins were predicted that had not been reported in previous serum databases. Several proteolytic fragments of larger molecules that may be cancer-related were confirmed immunologically in blood by Western blotting and peptide immunocompetition. BRCA2, a 390-kDa low-abundance nuclear protein linked to cancer susceptibility, was represented in sera as a series of specific fragments bound to albumin. CONCLUSION: Carrier-protein harvesting provides a rich source of candidate peptides and proteins with potential diverse tissue and cellular origins that may reflect important disease-related information.

Albumins↗
PubMed2005

Mapping molecular networks using proteomics: a vision for patient-tailored combination therapy.

Mapping tumor cell protein networks in vivo will be critical for realizing the promise of patient-tailored molecular therapy. Cancer can be defined as a dysregulation or hyperactivity in the network of intracellular and extracellular signaling cascades. These protein signaling circuits are the ultimate targets of molecular therapy. Each patient's tumor may be driven by a distinct series of molecular pathogenic defects. Thus, for any single molecular targeted therapy, only a subset of cancer patients may respond. Individualization of therapy, which tailors a therapeutic regimen to a tumor molecular portrait, may be the solution to this dilemma. Until recently, the field lacked the technology for molecular profiling at the genomic and proteomic level. Emerging proteomic technology, used concomitantly with genomic analysis, promises to meet this need and bring to reality the clinical adoption of molecular stratification. The activation state of kinase-driven signal networks contains important information relative to cancer pathogenesis and therapeutic target selection. Proteomic technology offers a means to quantify the state of kinase pathways, and provides post-translational phosphorylation data not obtainable by gene arrays. Case studies using clinical research specimens are provided to show the feasibility of generating the critical information needed to individualize therapy. Such technology can reveal potential new pathway interconnections, including differences between primary and metastatic lesions. We provide a vision for individualized combinatorial therapy based on proteomic mapping of phosphorylation end points in clinical tissue material.

Antineoplastic Combined Chemotherapy Protocols↗
PubMed2005

Supra-additive growth inhibition by a celecoxib analogue and carboxyamido-triazole is primarily mediated through apoptosis.

Combination studies of celecoxib and chemotherapeutic agents suggest that combining cyclooxygenase-2 inhibitors with other agents may have supra-additive or synergistic effects on tumor growth inhibition. Carboxyamido-triazole (CAI), a voltage-independent calcium channel inhibitor, has been shown to induce growth inhibition and apoptosis in cancer cells. We found that continuous exposure to cytostatic doses of CAI and LM-1685, a celecoxib analogue, reduced the proliferation and survival of seven human cancer cell lines by at least one log (P < or = 0.001) over either agent alone. To explore the mechanism of action of this combination, we further studied the effects of LM-1685/CAI on CCL-250 colorectal carcinoma cells. We found that the supra-additive antiproliferative effects occurred throughout a range of LM-1685 doses (5-25 micromol/L) and paralleled a decrease in COX-2 activity as measured by prostaglandin E2 production. In these cells, treatment with LM-1685/CAI suppressed the extracellular signal-regulated kinase pathway within the first hour but ultimately results in high, sustained activation of ERK over a 9-day period (P = 0.0005). Suppression of cyclin D1 and phospho-AKT, and cleavage of caspase-3 and PARP were concomitant with persistent ERK activation. Addition of PD98059, a MEK-1 inhibitor, suppressed ERK activation and significantly but incompletely reversed these signaling events and apoptosis. Flow cytometry experiments revealed that the CAI/LM-1685 combination induced a 3-fold increase in apoptosis over control (P = 0.005) in 3 days. We show that the combination of CAI and LM-1685 produces a cytotoxic effect by suppressing proliferation and triggering apoptosis.

Antineoplastic Combined Chemotherapy Protocols↗
PubMed2005

Adipocyte-derived collagen VI affects early mammary tumor progression in vivo, demonstrating a critical interaction in the tumor/stroma microenvironment.

The interactions of transformed cells with the surrounding stromal cells are of importance for tumor progression and metastasis. The relevance of adipocyte-derived factors to breast cancer cell survival and growth is well established. However, it remains unknown which specific adipocyte-derived factors are most critical in this process. Collagen VI is abundantly expressed in adipocytes. Collagen(-/-) mice in the background of the mouse mammary tumor virus/polyoma virus middle T oncogene (MMTV-PyMT) mammary cancer model demonstrate dramatically reduced rates of early hyperplasia and primary tumor growth. Collagen VI promotes its growth-stimulatory and pro-survival effects in part by signaling through the NG2/chondroitin sulfate proteoglycan receptor expressed on the surface of malignant ductal epithelial cells to sequentially activate Akt and beta-catenin and stabilize cyclin D1. Levels of the carboxyterminal domain of collagen VIalpha3, a proteolytic product of the full-length molecule, are dramatically upregulated in murine and human breast cancer lesions. The same fragment exerts potent growth-stimulatory effects on MCF-7 cells in vitro. Therefore, adipocytes play a vital role in defining the ECM environment for normal and tumor-derived ductal epithelial cells and contribute significantly to tumor growth at early stages through secretion and processing of collagen VI.

Adipocytes↗
PubMed2005

Importance of communication between producers and consumers of publicly available experimental data.

The application of mass spectrometry to discover new cancer biomarkers is in its infancy. Many of these new markers are low-abundance proteins that exist as fragments associated with carrier proteins. Although reproducibility is key to the use of mass spectrometry for ion fingerprint analysis, the scientific community has yet to establish a common platform or standardized operating procedures that are necessary for intra- and inter-laboratory comparison. In an effort to assist others who are perfecting mass spectrometry platforms for profiling, ongoing experimental data were posted for public consumption. An unintended consequence of unrestricted access to experimental data is the risk of inappropriate conclusions drawn and publicly disseminated that could have been avoided by communication between the producers and consumers of the data. Such disputes, however, should not divert us from the validation of this promising new approach.

Biomarkers, Tumor↗
PubMed2005

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.

Carcinoma↗
PubMed2005

A serum proteomic approach to gauging the state of remission in Wegener's granulomatosis.

OBJECTIVE: To identify serum ion patterns that distinguish remission from active disease in patients with Wegener's granulomatosis (WG). METHODS: Using sera collected in the WG Etanercept Trial, we selected samples from patients who either were undergoing a period of extended disease remission or had recent flares of active WG. Unfractionated samples were randomized into sets for training and testing, such that remission sera and active disease sera could be analyzed without batch bias. Molecular species within the sera were ionized by high-resolution, matrix-assisted laser desorption ionization time-of-flight mass spectrometry. We then used a bioinformatics pattern-recognition tool to identify optimal combinations of ions. During the training stage, the clinical data (remission versus active disease) were provided in association with the spectral data from each sample. In the testing stage, we performed blinded testing on a previously unexamined set of samples. RESULTS: The most robust model, trained on a total of 82 samples (42 remission, 40 active disease), included 7 key ions with mass:charge ratios of 803.239, 2,171.672, 2,790.574, 3,085.237, 5,051.726, 5,833.989, and 6,630.465. The combined relative amplitudes of these 7 ions identified 5 distinct clusters of either remission or active disease samples during the training stage. In the testing stage, this model segregated 72 samples into the same 5 clusters, including 1 large remission cluster (n = 28) and another large active disease cluster (n = 32). Three smaller clusters of active disease or remission samples were also identified, with remission clusters populated by 2 samples in one cluster and 8 in another, and an active disease cluster populated by 2 samples. The model categorized 35 of 37 remission samples correctly (sensitivity 95%, 95% confidence interval [95% CI] 82.1-99.4) and 32 of 35 active disease samples correctly (specificity 91%, 95% CI 78.1-98.1). CONCLUSION: This serum proteomic profiling approach appears to be useful in distinguishing between states of stable clinical remission and active disease. Further validation and refinement of this strategy may help clinicians apply immunosuppressive therapies more judiciously among their patients, thereby avoiding morbidity and mortality from excessive treatment. Identification of the most robust and clinically useful combinations of ions will permit the rational selection of molecules for sequencing and analysis.

Antirheumatic Agents↗
PubMed2005

CSF proteome: a protein repository for potential biomarker identification.

Proteomic analysis is not limited to the analysis of serum or tissues. Synovial, peritoneal, pericardial and cerebrospinal fluid represent unique proteomes for disease diagnosis and prognosis. In particular, cerebrospinal fluid serves as a rich source of putative biomarkers that are not solely limited to neurologic disorders. Peptides, proteolytic fragments and antibodies are capable of crossing the blood-brain barrier, thus providing a repository of pathologic information. Proteomic technologies such as immunoblotting, isoelectric focusing, 2D gel electrophoresis and mass spectrometry have proven useful for deciphering this unique proteome. Cerebrospinal fluid proteins are generally less abundant than their corresponding serum counterparts, necessitating the development and use of sensitive analytical techniques. This review highlights some of the promising areas of cerebrospinal fluid proteomic research and their clinical applications.

Alzheimer Disease↗
PubMed2005

Pathology of the future: molecular profiling for targeted therapy.

Recent evidence suggests that each patient's cancer has a unique subset of molecular pathogenetic derangements. These derangements may both genetic and proteomic alterations. Genomic and proteomic research tools enable genome-wide assessment of gene expression as well as kinase driven cell signaling events. These tools are illuminating the molecular derangements of individual tumors, even if these tumors have similar morphological characteristics. A combination of laser capture microdissection with multiplexed phosphoproteomic analysis using reverse phase protein microarray technology is being used to identify protein molecular signatures of individual tumors. The in vivo state of multiple kinase driven signal pathways may be evaluated by reverse phase protein microarray with a panel of specific antibodies developed based upon our knowledge of biological processes. Molecular profiling of individual patient's tumors is currently being evaluated in clinical trials at the National Institutes of Health, National Cancer Institute for monitoring Epidermal Growth Factor (EGF) cell signaling events for patients with breast and ovarian cancer.

Forecasting↗
PubMed2005

Reverse-phase protein microarrays for tissue-based analysis.

The deciphering of the human genome has elucidated our biological structural design and has generated insights into disease development and pathogenesis. At the same time, knowledge of genetic changes during disease processes has demonstrated the need to move beyond genomics towards proteomics and a systems biology approach to science. Analyzing the proteome comprises more than just a numeration of proteins. In fact, it characterizes proteins within cells in the context of their functional status and interactions in their physiological micro- and macroenvironments. As dysregulated signaling often underpins most human diseases, an overarching goal of proteomics is to profile the working state of signaling pathways, to develop 'circuit maps' of normal and diseased protein networks and identify hyperactive, defective or inoperable transduction pathways. Reverse-phase protein microarrays represent a new technology that can generate a multiplex readout of dozens of phosphorylated events simultaneously to profile the state of a signaling pathway target even after the cell is lyzed and the contents denatured.

Animals↗