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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↗
PubMed2006

Physicochemically modified silicon as a substrate for protein microarrays.

Reverse phase protein microarrays (RPMA) enable high throughput screening of posttranslational modifications of important signaling proteins within diseased cells. One limitation of protein-based molecular profiling is the lack of a PCR-like intrinsic amplification system for proteins. Enhancement of protein microarray sensitivities is an important goal, especially because many molecular targets within patient tissues are of low abundance. The ideal array substrate will have a high protein-binding affinity and low intrinsic signal. To date, nitrocellulose-coated glass has provided an effective substrate for protein binding in the microarray format when using chromogenic detection systems. As fluorescent systems, such as quantum dots, are explored as potential reporter agents, the intrinsic fluorescent properties of nitrocellulose-coated glass slides limit the ability to image microarrays for extended periods of time where increases in net sensitivity can be attained. Silicon, with low intrinsic autofluorescence, is being explored as a potential microarray surface. Native silicon has low binding potential. Through titrated reactive ion etching (RIE), varying surface areas have been created on silicon in order to enhance protein binding. Further, via chemical modification, reactive groups have been added to the surfaces for comparison of relative protein binding. Using this combinatorial method of surface roughening and surface coating, 3-aminopropyltriethoxysilane (APTES) and mercaptopropyltrimethoxysilane (MPTMS) treatments were shown to transform native silicon into a protein-binding substrate comparable to nitrocellulose.

Adsorption↗
PubMed2006

Proteomic analysis of malignant ovarian cancer effusions as a tool for biologic and prognostic profiling.

PURPOSE: Malignant epithelial ovarian cancer effusions are important in disease dissemination and clinical outcome. The identification of biochemical events active in effusions may improve our identification and application of targeted therapeutics. EXPERIMENTAL DESIGN: Archival effusion samples for which outcome information was known were studied. Clinical variables were comparable between these groups. Two cohorts of patients with malignant effusion were assessed: those with effusion at presentation (Tap1) or at first recurrence (Tap2). Expression and activated fraction of selected signaling proteins were quantitated on serial protein microarrays using validated antibodies. Proteomic results and clinical variables were analyzed by univariate analysis followed by Cox proportional hazards model analysis. RESULTS: Malignant effusions (>80% malignant cells) were distinguished from benign effusions by higher expression of AKT, activated extracellular signal-regulated kinase, activated (P < or = 0.001) and total cAMP-responsive element binding protein (P = 0.01), and JNK (P = 0.03). Malignant pleural effusions could not be differentiated from ascites by signaling profiles. Both had signal expression clusters for survival, proliferation and metastasis, and injury pathways. Cox proportional hazards model analysis revealed high p38 and pEGFR/EGFR ratio as jointly associated with poor survival in Tap1 cases (both P < or = 0.002). Phospho-JNK quantity was associated with worse outcome in Tap2 patients (P = 0.004), when taking other factors into consideration. CONCLUSIONS: Proliferation, survival, and apoptosis signaling dysregulation can be identified in ovarian cancer effusion samples. Biochemical characterization of clinical effusions may provide either predictive and/or correlative information on patient outcome from which to further understand the mechanisms of effusion development and target clinical intervention.

Apoptosis↗
PubMed2006

Laser capture microdissection.

Laser capture microdissection (LCM) is a technique for isolating pure cell populations from a heterogeneous tissue section or cytological preparation via direct visualization of the cells. This technique is applicable to molecular profiling of diseased and disease-free tissue, permitting correlation of cellular molecular signatures with specific cell populations. DNA, RNA, or protein analysis can be performed with the microdissected tissue by any method with adequate sensitivity. The principle components of LCM technology are (1) visualization of the cells of interest via microscopy, (2) transfer of laser energy to a thermolabile polymer with formation of a polymer-cell composite, and (3) removal of the cells of interest from the heterogeneous tissue section. LCM is compatible with a variety of tissue types, cellular staining methods, and tissue-preservation protocols that allow microdissection of fresh or archival specimens. LCM platforms are available as a manual system (PixCell; Arcturus Bioscience) or as an automated system (AutoPix).

Cell Separation↗
PubMed2006

Accurate diagnosis of acute graft-versus-host disease using serum proteomic pattern analysis.

OBJECTIVE: The rapid diagnosis of acute graft-versus-host disease (GVHD) following allogeneic hematopoietic cell transplantation (HCT) is important for optimizing the management of this life-threatening complication. Current diagnostic techniques are time-consuming and require invasive tissue sampling. We investigated serum protein pattern analysis using surface-enhanced laser desorption ionization time-of-flight (SELDI-TOF) mass spectrometry as a tool to diagnose GVHD. PATIENTS AND METHODS: Eighty-eight serum samples were obtained from 34 patients undergoing HCT either pretransplant (n = 28 samples) or at various time points posttransplant (n = 60 samples), including 22 samples obtained on the day of onset of acute GVHD symptoms. Serum proteomic spectra generated from a "training set" of known samples were used to identify distinct proteomic patterns that best categorized a sample as either pretransplant, posttransplant non-GVHD, or GVHD; these distinct proteomic signatures were subsequently used to classify samples from a masked "test" sample set into the appropriate diagnostic category. RESULTS: Proteomic pattern analysis accurately distinguished GVHD samples from both posttransplant non-GVHD samples and pretransplant samples (100% specificity and 100% sensitivity in both cases). Furthermore, distinct serum proteomic signatures were identified that distinguished pretransplant from posttransplant non-GVHD samples (100% specificity and 94% sensitivity). CONCLUSION: These preliminary data suggest a potential application of SELDI-TOF-based proteomic analysis as a rapid and accurate method to diagnose acute GVHD.

Adult↗
PubMed2005

Manual exfoliation of fresh tissue obviates the need for frozen sections for molecular profiling.

BACKGROUND: Simple, rapid tissue processing that preserves macromolecules will enhance translational research capabilities. Traditional fixative-based approaches for specimen preservation are ideal for histologic evaluation but are not conducive to molecular studies of nucleic acids and protein. Tissue cryosections preserve macromolecule integrity, but the process is labor intensive and technically challenging. To the authors' knowledge to date, an alternative method capable of retrieving cells while providing adequate histologic detail yet preserving macromolecule integrity has been lacking. In the current study, the authors evaluated the utility of using manual exfoliation of clinical tissue samples as a means of obtaining cells for molecular analysis. This technique possesses the advantages of fixed and frozen tissue sections without their drawbacks. This simple, rapid, nonfixative based technique is capable of preparing cells from human clinical material for further isolation without compromising the preservation of macromolecules in the tissue. METHODS: Cells from a variety of clinical resection specimens from solid tumors were directly scraped from the tissue samples using the edge of a glass microscope slide and smeared onto another slide for cytologic evaluation. The manually exfoliated cells were evaluated microscopically for cytologic quality and cellular quantity. Pure cell populations were procured by laser capture microdissection (LCM) with subsequent extraction of nucleic acids and proteins. The integrity and suitability of the recovered nucleic acids and proteins for molecular analysis were evaluated using the polymerase chain reaction (PCR), reverse transcriptase-PCR, and reverse-phase protein microarray, respectively. RESULTS: Manual exfoliation permits the selection of homogeneous cell populations by LCM based on well established cytologic characteristics. DNA and mRNA, of comparable quality to frozen sections, can be amplified from the manual exfoliation cells. Proteins of similar quality can be recovered using this technique and quantitated via reverse-phase protein microarray. CONCLUSIONS: Molecular macromolecules of high quality and sufficient quantity can be retrieved from human clinical samples using manual exfoliation and LCM to procure specific cell populations. The manual exfoliation technique does not destroy the original tissue source, thereby allowing subsequent formalin tissue fixation. The technique of manual exfoliation in conjunction with LCM can enable the molecular profiling of a sampled selected cell population. Because it does not destroy the original tissue, histologic correlation can be combined with molecular profiling.

Cell Separation↗
PubMed2005

Proteomic analysis of apoptotic pathways reveals prognostic factors in follicular lymphoma.

Follicular lymphoma (FL) is the second most common non-Hodgkin's lymphoma and generally is incurable. Reliable prognostic markers to differentiate patients who progress rapidly from those who survive for years with indolent disease have not been established. Most cases overexpress Bcl-2, but the pathogenesis of FL remains incompletely understood. To determine whether a proteomic approach could help overcome these obstacles, we procured lymphoid follicles from 20 cases of FL and 15 cases of benign follicular hyperplasia (FH) using laser capture microdissection. Lysates were spotted on reverse-phase protein microarrays and probed with 21 antibodies to proteins in the intrinsic apoptotic pathway, including those specific for posttranslational modifications such as phosphorylation. A panel of three antibodies [phospho-Akt(Ser473), Bcl-2, and cleaved poly(ADP-ribose) polymerase] segregated most cases of FL from FH. Phospho-Akt(Ser473) and Bcl-2 were significantly increased in FL (P = 0.001 and P < 0.0001, respectively). Additionally, the Bcl-2/Bak ratio completely segregated FL from FH. High ratios of Bcl-2/Bak and Bcl-2/Bax were associated with early death from disease with differences in median survival times of 7.3 years (P = 0.0085) and 3.8 years (P = 0.018), respectively. Using protein microarrays, we identified candidate proteins that may signify clinically relevant molecular events in FL. This approach showed significant changes at the posttranslational level, including Akt phosphorylation, and suggested new prognostic markers, including the Bcl-2/Bak and Bcl-2/Bax ratios. Proteomic end points should be incorporated in larger, multicenter trials to validate the clinical utility of these protein microarray findings.

Adult↗
PubMed2005

A transforming growth factor-beta receptor-interacting protein frequently mutated in human ovarian cancer.

Ovarian carcinomas, particularly recurrent forms, are frequently resistant to transforming growth factor-beta (TGF-beta)-mediated growth inhibition. However, mutations in the TGF-beta receptor I and receptor II (TbetaR-I and TbetaR-II) genes have only been reported in a minority of ovarian carcinomas, suggesting that alterations in TGF-beta-signaling components may play an important role in the loss of TGF-beta responsiveness. Using laser-capture microdissection and nested reverse-transcription-PCR, we found that km23, which interacts with the TGF-beta receptor complex, is altered at a high frequency in human ovarian cancer patients. A novel form of km23, missing exon 3 (Deltaexon3-km23), was found in 2 of 19 tumor tissues from patients with ovarian cancer. In addition to this alteration, a stop codon mutation (TAA --> CAC) was detected in two patients. This alteration results in an elongated protein, encoding 107-amino-acid residues (Delta107km23), instead of the wild-type 96-amino-acid form of km23. Furthermore, five missense mutations (T38I, S55G, T56S, I89V, and V90A) were detected in four patients, providing a total alteration rate of 42.1% (8 of 19 cases) in ovarian cancer. No km23 alterations were detected in 15 normal tissues. Such a high alteration rate in ovarian cancer suggests that km23 may play an important role in either TGF-beta resistance or tumor progression in this disease. In keeping with these findings, the functional studies described herein indicate that both the Deltaexon3-km23 and S55G/I89V-km23 mutants displayed a disruption in binding to the dynein intermediate chain in vivo, suggesting a defect in cargo recruitment to the dynein motor complex. In addition, the Deltaexon3-km23 resulted in an inhibition of TGF-beta-dependent transcriptional activation of both the p3TP-lux and activin responsive element reporters. Collectively, our results suggest that km23 alterations found in ovarian cancer patients result in altered dynein motor complex formation and/or aberrant transcriptional regulation by TGF-beta.

Aged↗
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↗