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Virginia Espina

Publications and source records attributed to Virginia Espina.

At least 19 recordsLinked to original sources
PubMed2024

Targeted Dynamic Phospho-Proteogenomic Analysis of Gastric Cancer Cells Suggests Host Immunity Provides Survival Benefit.

Despite of massive emergence of molecular targeting drugs, the mainstay of advanced gastric cancer (GC) therapy is DNA-damaging drugs. Using a reverse-phase protein array-based proteogenomic analysis of a panel of 8 GC cell lines, we identified genetic alterations and signaling pathways, potentially associated with resistance to DNA-damaging drugs, including 5-fluorouracil (5FU), cisplatin, and etoposide. Resistance to cisplatin and etoposide, but not 5FU, was negatively associated with global copy number loss, vimentin expression, and caspase activity, which are considered hallmarks of previously established EMT subtype. The segregation of 19,392 protein expression time courses by sensitive and resistant cell lines for the drugs tested revealed that 5FU-resistant cell lines had lower changes in global protein dynamics, suggesting their robust protein level regulation, than their sensitive counterparts, whereas the cell lines that are resistant to other drugs showed increased protein dynamics in response to each drug. Despite faint global protein dynamics, 5FU-resistant cell lines showed increased signal transducer and activator of transcription 1 phosphorylation and PD-L1 expression in response to 5FU. In publicly available cohort data, expression of signal transducer and activator of transcription 1 and NFκB target genes induced by proinflammatory cytokines was associated with prolonged survival in GC. In our validation cohort, total lymphocyte count, rather than PD-L1 positivity, predicted a better relapse-free survival rate in GC patients with 5FU-based adjuvant chemotherapy than those with surgery alone. Moreover, total lymphocyte count+ patients who had no survival benefit from adjuvant chemotherapy were discriminated by expression of IκBα, a potent negative regulator of NFκB. Collectively, our results suggest that 5FU resistance observed in cell lines may be overcome by host immunity or by combination therapy with immune checkpoint blockade.

Stomach Neoplasms↗
PubMed2005

Expression of xeroderma pigmentosum A protein predicts improved outcome in metastatic ovarian carcinoma.

BACKGROUND: The nucleotide excision repair (NER) proteins repair DNA adducts due to xenobiotics and cancer chemotherapy. The authors hypothesized that expression of the NER protein xeroderma pigmentosum A (XPA) would be reduced in a clinically significant fashion in metastatic ovarian carcinoma. METHODS: Malignant effusion specimens were studied so that there was a uniform metastatic ovarian carcinoma population for study. XPA protein expression was analyzed by immunocytochemistry in 142 effusion specimens (109 peritoneal specimens, 33 pleural specimens) from 125 patients. Specimens were obtained at diagnosis (n = 76), and at disease recurrence (n = 66). Patients in the latter group received platinum-based chemotherapy. RESULTS: XPA was expressed in cancer cells in 136 of the 142 (96%) effusion specimens. Strongest expression occurred in leukocytes and reactive mesothelial cells. XPA expression did not correlate with treatment status, effusion site, International Federation of Gynecology and Obstetrics stage, histologic grade, or the extent of residual disease. More effusion tumor cells from patients with a complete response to chemotherapy expressed XPA compared with those with a partial or no response (P = 0.03, chi(2) test). Patients with recurrent disease with XPA expressed in > 25% of tumor cells had better progression-free survival (PFS) by univariate analysis (median = 0 vs. 11 months, P < 0.001; 95% confidence interval [CI], 1-5, 8-14) and overall survival (OS; median = 24 vs. 34 months, P = 0.04; 95% CI, 17-31, 24-44). XPA was the only predictor of PFS outcome by multivariate analysis (P = 0.03). CONCLUSIONS: The results of the current study showed that XPA was widely expressed in metastatic ovarian carcinoma effusion specimens and in the cells of the effusion microenvironment. Paradoxically, XPA expression was associated with better response to chemotherapy and predicted better PFS and OS.

Adenocarcinoma, Clear Cell↗
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

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

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

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↗
PubMed2004

Application of laser capture microdissection and protein microarray technologies in the molecular analysis of airway injury following pollution particle exposure.

Understanding the mechanisms by which various types of air pollution particles (particulate matter, PM) mediate adverse health effects would provide biological plausibility to epidemiological associations of increased rates of morbidity and mortality. The majority of information regarding the means by which PM generates lung injury has been derived from in vitro studies. However, it is unclear as to what extent these mechanisms can be extrapolated to the in vivo situation. Current methods to assess mechanisms of PM-induced lung injury make it difficult to obtain site-specific, sensitive, and comprehensive determinations of cellular and molecular pathology associated with PM-induced injury. In the present study, the ability of laser capture microdissection (LCM) and protein microarray technologies were assessed to examine the effect of residual oil fly ash (ROFA) exposure on airway intracellular signaling pathways and transcription factor activation. Sprague-Dawley rats were intratracheally instilled with 0.5 mg/rat of ROFA. LCM was used to recover airway cells and protein extracts derived from the microdissected airways were analyzed by protein microarray. ROFA exposure increased p-ERK:ERK and p-I kappa B:I kappa B, suggesting changes in cell growth, transformation, and inflammation within the airway. These results are consistent with previously reported in vitro findings, demonstrating for the first time the credibility of applying LCM and protein microarray technologies to assess acute lung injury induced by environmental air pollutants.

Air Pollutants↗
PubMed2004

Genomic and proteomic technologies for individualisation and improvement of cancer treatment.

The development of microarray-based technologies for characterising tumours, both at the genomic and proteomic levels, has had a significant impact on the field of oncology. Gene expression profiling of various human tumour tissues has led to the identification of expression patterns related to disease outcome and drug resistance, as well as to the discovery of new therapeutic targets and insights into disease pathogenesis. Protein microarray technologies, such as reverse-phase protein arrays, provide the unique opportunity to profile tissues and assess the activity of signalling pathways within isolated cell populations. This technology can be used to identify patients likely to benefit from specific treatment modalities and also to monitor therapeutic response in samples obtained during and after treatment. Routine application of genomic and proteomic microarray technologies in clinical practice will require significant efforts to standardise the techniques, controls and reference standards, and analytical tools used. Extensive, independent validation using large, statistically-powered datasets will also be necessary. Inclusion of concomitant genomic and proteomic-based molecular profiling techniques into clinical trial protocols will bring us closer to the reality of patient-tailored therapy.

Gene Expression Profiling↗
PubMed2004

Biomarkers of ovarian tumours.

Ovarian cancer is one of the most aggressive gynaecological malignancies and most often the high mortality is a direct result of delays in diagnosis. The development of an ovarian cancer-specific biomarker for the early detection of disease has the capacity to improve the dismal survival rate. Currently, there are multiple investigations that are utilising both genomic and proteomic technologies to identify genes, gene products and proteins that may potentially identify diagnostic ovarian cancer biomarkers. Here, we review the studies that are involved in biomarker development for the detection of ovarian cancer.

Biomarkers, Tumor↗
PubMed2004

Protein microarray detection strategies: focus on direct detection technologies.

Protein microarrays are being utilized for functional proteomic analysis, providing information not obtainable by gene arrays. Microarray technology is applicable for studying protein-protein, protein-ligand, kinase activity and posttranslational modifications of proteins. A precise and sensitive protein microarray, the direct detection or reverse-phase microarray, has been applied to ongoing clinical trials at the National Cancer Institute for studying phosphorylation events in EGF-receptor-mediated cell signaling pathways. The variety of microarray applications allows for multiple, creative microarray designs and detection strategies. Herein, we discuss detection strategies and challenges for protein microarray technology, focusing on direct detection of protein microarrays.

Animals↗
PubMed2004

Serum proteomics in cancer diagnosis and management.

Mass spectrometry-based diagnostics has the potential to revolutionize molecular medicine. Using modern mass-spectrometer technologies, clinical tests can be developed that are practical, robust, accurate, and inexpensive. Serum proteomic pattern profiling couples mass spectrometry with adaptive artificial-intelligence-based bioinformatics, which can now be employed to detect pathological states reflected in the serum proteome. With this approach, rapid and cost-effective tests with exquisite clinical sensitivity and specificity are emerging. These tools may dramatically change how disease is detected, monitored, and managed.

Blood Proteins↗
PubMed2004

Use of proteomic analysis to monitor responses to biological therapies.

Proteomics has the potential to revolutionise diagnosis and disease management. Serum protein pattern profiling by surface-enhanced laser desorption/ionisation time of flight (SELDI-TOF) mass spectrometry is emerging as a novel approach to discover protein patterns capable of distinguishing disease and disease-free states with high sensitivity and specificity. This method has shown great promise for early diagnosis of ovarian cancer and is being applied to a range of pathological states. Protein microarray technology is being evaluated as a new means to track biological responses to therapy. Through the measurement of key protein phosphorylation sites at different stages of disease progression or before and after treatment, protein signal pathways can be mapped and thus become the starting point for individualised therapy. Laser capture microdissection (LCM) coupled with immunostaining of protein microarrays allows isolation of pure cell populations and relative quantitation of phosphorylated and non-phosphorylated forms of the cell's key signalling proteins. This technology is currently in use at the National Institutes of Health in Phase II clinical trials of metastatic breast and ovarian cancer. Cell survival and apoptotic protein pathways are monitored as biological markers of disease progression in these clinical trials. Proteomic technologies, such as serum protein pattern profiling, combined with protein microarray technologies, constitute a new paradigm for detecting disease and monitoring disease response to therapy. Ultimately, proteomics and genomics will become integrated into cancer patient management through the design and tracking of individualised therapy.

Animals↗
PubMed2003

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.

Blotting, Western↗
PubMed2003

Protein microarrays: molecular profiling technologies for clinical specimens.

Proteomics, the study of protein function within biologic systems, will further our understanding of cancer pathogenesis. Coupled with transcript profiling, proteomics can herald the advent of molecular therapy tailored to the individual patient's neoplasm. Protein microarrays, one emerging class of proteomic technologies, have broad applications for discovery and quantitative analysis. This technology is uniquely suited to gather information about the post-translational modifications of proteins reflecting the activity state of signal pathways and networks. Protein microarrays now make it feasible to conduct signal network profiling within cellular samples. Nevertheless, to be successful, design and use of protein microarrays must take into consideration enormous analytical challenges. A subclass of protein microarrays, Reverse Phase Arrays, created to meet these challenges, has been optimized for use with tissue specimens, and is now in use for the analysis of biopsy samples for clinical trial research.

Antibodies↗
PubMed2003

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.

Animals↗
PubMed2003

Molecular diagnostics.

It is increasingly evident that molecular diagnostics, that is, the use of diagnostic testing to understand the molecular mechanisms of an individual patient's disease, will be pivotal in the delivery of safe and effective therapy for many diseases in the future. A huge body of new information on the genetic, genomic and proteomic profiles of different hematopoietic diseases is accumulating. This chapter focuses on new technologies and advancements in understanding the molecular basis of hematologic disorders, providing an overview of new information and its significance to patient care. In Section I, Dr. Braziel discusses the impact of new genetic information and research technologies on the actual practice of diagnostic molecular hematopathology. Recent and projected changes in methodologies and analytical strategies used by clinical molecular diagnostics laboratories for the evaluation of hematologic disorders will be discussed, and some of the challenges to clinical implementation of new molecular information and techniques will be highlighted. In Section II, Dr. Shipp provides an update on current scientific knowledge in the genomic profiling of malignant lymphomas, and describes some of the technical aspects of gene expression profiling. Analysis methods and the actual and potential clinical and therapeutic applications of information obtained from genomic profiling of malignant lymphomas are discussed. In Section III, Dr. Liotta presents an update on proteomic analysis, a new and very active area of research in hematopoietic malignancies. He describes new technologies for rapid identification of different important proteins and protein networks, and the potential therapeutic and prognostic value of the elucidation of these proteins and protein pathways in the clinical care of patients with malignant lymphomas.

Cytogenetic Analysis↗