A comparative proteomic study to characterize the vinblastine resistance in human ovarian cancer cells

Drug resistance is a major impediment to the successful treatment of human cancers, including ovarian cancer. Vinblastine (VLB), an antimicrotubule agent, is one of the chemotherapeutic drugs that exhibit resistance in ovarian cancer patients. To determine the protein factors that are involved in vinblastine resistance in human ovarian cancer cells, a combination of sample pre-fractionation and high-resolution 2-DE proteomic analysis was performed. Approximately 1200 proteins were detected and quantitatively compared in both nuclear/membrane and cytosolic fractions. Sixty-nine proteins from the nuclear/membrane fraction showed altered expression levels, whereas 59 were altered in the cytosolic fraction between SKOV3 (vinblastine-sensitive) and SKVLB (vinblastine-resistant) cell lines. These proteins include membrane-associated, chromatin remodeling, cytoskeletal, and microtubule-associated proteins as well as others that regulate signal transduction. This study not only demonstrates a novel understanding of the mechanism of drug resistance but also provides a valuable resource for future studies on drug resistance to vinblastine. In addition, it also represents a good example of how to increase the protein dynamic range and reduce sample complexity using currently available tools.     

Quantitative proteomic analysis of ovarian cancer cells identified mitochondrial proteins associated with Paclitaxel resistance

Paclitaxel has been widely used as an anti-mitotic agent in chemotherapy for a variety of cancers and adds substantial efficacy as the first-line chemotherapeutic regimen for ovarian cancers. However, the frequent occurrence of paclitaxel resistance limits its function in long-term management. Despite abundant clinical and cellular demonstration of paclitaxel resistant tumors, the molecular mechanisms leading to paclitaxel resistance are poorly understood. Using genomic approaches, we have previously identified an association between a BTB/POZ gene, Nac1, and paclitaxel resistance in ovarian cancer. The experiments presented here have applied multiple quantitative proteomic methods to identify protein changes associated with paclitaxel resistance and Nac1 function. The SKOV-3 ovarian serous carcinoma cell line, which has inducible expression of dominant negative Nac1, was used to determine the paclitaxel treatment associated changes in the presence and absence of functional Nac1. Quantitative proteomic analyses were performed using iTRAQ labeling and mass spectrometry. Two label-free quantitative proteomic methods: LC-MS and spectral count were used to increase confidence of proteomic quantification. A total of 1371 proteins were quantified by at least one of the quantitative proteomic methods. Candidate proteins related to paclitaxel and NAC1 function were identified in this study. Go analysis of the protein changes identified upon paclitaxel resistance revealed that cell component enrichment related to mitochondria. Moreover, tubulin and mitochondrial proteins were the major cellular components with changes associated with paclitaxel treatment. This suggests that mitochondria may play a role in paclitaxel resistance.     

Increased expression of annexin I is associated with drug-resistance in nasopharyngeal carcinoma and other solid tumors

Adjuvant chemotherapy alongside radiotherapy is one of the effective therapies in nasopharyngeal carcinoma (NPC) treatment. However, the appearance of drug resistance is a major obstacle for anti-cancer chemotherapy and often causes failure of the chemotherapy. In this study, a drug-resistant gene annexin I (ANX-I) was identified by comparing differentially expressed proteins between a cisplatin (CDDP)-resistant NPC cell line CNE2-CDDP and parental CNE2 cells using 2-DE. When ANX-I was transfected into CNE2 cells, the CDDP resistance of CNE2 cells was dramatically increased. The drug-resistant ability of ANX-I was demonstrated by both in vitro and in vivo assays. The association of ANX-I expression with clinical features was also investigated. Increased expression of ANX-I was significantly associated with disease relapse in NPC (p<0.05). In breast and gastric cancer, increased expression of ANX-I was significantly associated with drug resistance (p<0.001) and poor prognosis (p<0.001), respectively. Taken together, our findings suggest that ANX-I plays an important role in drug resistance.     

Proteomic analysis of high-molecular-weight protein polymers in a doxorubicin-resistant breast-cancer cell line

We recently reported that increased transglutaminase 2 (TGase 2) expression correlates with increased resistance to the cancer drug doxorubicin in breast-cancer cell lines. Interestingly, high-molecular-weight (HMW) proteins also increased with increased TGase 2 expression in the drug-resistant cell lines. TGase 2 is likely to be responsible for the formation of HMW proteins, because TGase 2 catalyzes cross-linking between proteins. Although the role of the HMW proteins is unclear, we demonstrated that TGase 2 inhibition increases drug sensitivity in breast-cancer cells. Herein we find that TGase 2 inhibition by cystamine dramatically reduces the level of HMW proteins. Identification of the HMW proteins may suggest the mechanism of cancer drug resistance associated with aberrant TGase 2 function. To explore the identities of HMW proteins, we performed in-gel tryptic digestions of unresolved HMW proteins and analyzed the resulting peptides using LC-MALDI-MS/MS. Most of the identified proteins were associated with gene regulation, such as polyadenylate-binding proteins, translation initiation factors, and ribonucleoproteins. This finding suggests that TGase 2 may participate in gene regulation, in addition to its role in cell adhesion.     

A proteomic investigation of isogenic radiation resistant prostate cancer cell lines

To model the problem of radiation resistance in prostate cancer, cell lines mimicking a clinical course of conventionally fractionated or hypofractionated radiotherapy have been generated. Proteomic analysis of radiation resistant and radiosensitive DU145 prostate cancer cells detected 4410 proteins. Over 400 proteins were differentially expressed across both radiation resistant cell lines and pathway analysis revealed enrichment in epithelial to mesenchymal transition, glycolysis and hypoxia. From the radiation resistant protein candidates, the cell surface protein CD44 was identified in the glycolysis and epithelial to mesenchymal transition pathways and may serve as a potential therapeutic target.     

Quantitative mass spectrometry for colorectal cancer proteomics

This review documents the uses of quantitative MS applied to colorectal cancer (CRC) proteomics for biomarker discovery and molecular pathway profiling. Investigators are adopting various labeling and label-free MS approaches to quantitate differential protein levels in cells, tumors, and plasma/serum. We comprehensively review recent uses of this technology to examine mouse models of CRC, CRC cell lines, their secretomes and subcellular fractions, CRC tumors, CRC patient plasma/serum, and stool samples. For biomarker discovery these approaches are uncovering proteins with potential diagnostic and prognostic utility, while in vitro cell culture experiments are characterizing proteomic and phosphoproteomic responses to disrupted signaling pathways due to mutations or to inhibition of drugable enzymes.     

Comparison of membrane-associated proteins in human cholangiocarcinoma and hepatocellular carcinoma cell lines

Cholangiocarcinoma (CCA) and hepatocellular carcinoma (HCC) occur with relatively high incidence in Thailand. Cell line models, originating from Thai patients, are available for both diseases, including the human bile duct epithelial carcinoma cell line (HuCCA-1) and the HCC cell line HCC-S102. Here, we have prepared subproteomes enriched in membrane proteins or in cytosolic proteins from the HuCCA-1 and the HCC-S102 cell lines. Study of differential protein expression by 2-DE and LC/MS/MS showed 195 proteins expressed in the two cell lines, including both membrane-associated and cytosolic proteins. Eighteen proteins were found in both membrane and cytosolic fractions of HuCCA-1, but not in HCC-S102, while nine proteins were found in both membrane and cytosolic fractions of HCC-S102, but not in HuCCA-1. Ten membrane proteins were found in HuCCA-1 but not in HCC-S102, including integrin alpha-6 precursor, ezrin, hippocalcin-like protein 1, mitogen-activated protein kinase kinase kinase 2 (MAPK/ERK kinase kinase 2), and calgizzarin. Proteins showing increased expression in the membrane fraction of HuCCA-1 were mainly cytoskeletal proteins (40.9%), while proteins showing increased expression in the membrane fraction of HCC-S102 were mainly metabolic proteins (39.4%). The subproteomic approach used here facilitates detection of potential biomarkers undetected by regular proteomic methods.     

Glycoproteomics using fluid-based specimens in the discovery of lung cancer protein biomarkers: Promise and challenge

Lung cancer is the leading cancer in the United States and worldwide. In spite of the rapid progression in personalized treatments, the overall survival rate of lung cancer patients is still suboptimal. Over the past decade, tremendous efforts have been focused on the discovery of protein biomarkers to facilitate the early detection and monitoring of lung cancer progression during treatment. In addition to tumor tissues and cancer cell lines, a variety of biological material has been studied. Particularly in recent years, studies using fluid-based specimen or so-called “fluid-biopsy” specimens have progressed rapidly. Fluid specimens are relatively easier to collect than tumor tissue, and they can be repeatedly sampled during the disease progression. Glycoproteins are the major content of fluid specimens and have long been recognized to play fundamental roles in many physiological and pathological processes. In this review, we focus the discussion on recent advances of glycoproteomics, particularly in the identification of potential glyco protein biomarkers using fluid-based specimens in lung cancer. The purpose of this review is to summarize current strategies, achievements, and perspectives in the field. This insight will highlight the discovery of tumor-associated glycoprotein biomarkers in lung cancer and their potential clinical applications.     

Profiling the potential biomarkers for cell differentiation of pancreatic cancer using iTRAQ and 2-D LC-MS/MS

Pancreatic cancer is a highly lethal disease that is difficult to diagnose at early stage and even more difficult to cure. SW1990 and PANC-1 represent the two cancer cell lines, which are both derived from pancreatic duct, but at different cell differentiation stages. In this study, we applied the iTRAQ-labeling technology and 2-D strong cation exchange/reversed phase liquid chromatography – LC-MS/MS) to profile the secreted proteins of SW1990 and PANC-1 cells in a conditioned cell culture medium. A total of 401 proteins were identified by MS/MS and protein database searching, the percentages of these proteins predicted in the categories of plasma membrane, intracellular and secreted proteins were 29.2, 32.7 and 38.2%, respectively. Fifty six proteins were identified with unknown functions and 19 proteins were quantified with significant level changes between the two cancer cell lines under the specific cell condition with 12 proteins being up-regulated (>1.3-fold change) in PANC-1 (e.g. FLJ31222 protein, 97 kDa protein, type IV collagenase precursor, 38 kDa protein and centaurin) and seven proteins being up-regulated in SW1990 (e.g. fibroblast growth factor receptor substrate 2, putative p150, hypothetical protein LOC 654463 and LOC 55701). The proteins with significant level changes may provide a baseline to investigate mechanisms underlying the differentiation of two cell lines and can be further screened for better protein biomarkers in pancreatic cancer.     

Deep depletion of abundant serum proteins reveals low-abundant proteins as potential biomarkers for human ovarian cancer

Epithelial ovarian cancer (EOC) ranks fifth as a cause of cancer deaths in women. Current diagnostic and monitoring markers have limited reliability for the detection of disease. We have tested the possibility of identifying candidate biomarkers present at low nanogram to picogram levels after removing both the 12 most abundant and 77 moderately abundant proteins from serum samples of EOC patients using antibody affinity columns. We showed that this approach allows the identification of proteins that are expressed at nanogram per liter levels in the serum. Using ICAT/MS/MS analysis, we identified 51 proteins that are differentially expressed by at least twofold. These proteins include leucine-rich α-2-glycoprotein, matrix metalloproteinase-9 (MMP-9), inter-α-trypsin inhibitor heavy chain H1, insulin-like growth factor-binding protein 6, insulin-like growth factor-binding protein 3, isoform 1 of epidermal growth factor receptor, angiopoietin-like protein 3 (ANGPTL3) and phosphatidylcholine-sterol acyltransferase. We confirmed the differential expression of MMP9 and ANGPTL3 in normal and ovarian cancer sera by ELISA assays. Further robust clinical evaluation of the candidate markers identified is necessary.     

Cetuximab inhibits thymidylate synthase in colorectal cells expressing epidermal growth factor receptor

The monoclonal antibody cetuximab directed against the epidermal growth factor receptor (EGFR) is an attractive agent for targeted therapy in advanced colorectal cancer (CRC), especially when combined with 5-fluorouracil (5-FU)-based chemotherapy. However, the mechanisms of cetuximab activity as chemosensitizer remain poorly understood. Using proteome-fluorescence-based technology, we found that cetuximab is able to suppress the expression of thymidylate synthase (TS), which is involved in the mechanism of 5-FU action. Caco-2, HRT-18, HT-29, WiDr and SW-480 CRC cells were found to express EGFR. SW-620 was used as EGFR-negative cell line. Only in EGFR-expressing cells cetuximab is able to inhibit TS expression. Combined treatment with cetuximab and 5-FU revealed a synergistic anti-tumor response that is closely correlated with functional activity of EGFR/mitogen-activated protein kinase (MAPK) pathway. Moreover, no correlation was seen between constitutive TS protein expression, level of cetuximab-induced TS down-regulation and response either to 5-FU alone or in combination with cetuximab. We demonstrated that only EGFR expression with high functional activity of EGFR/MAPK pathway is important for the synergistic effects between cetuximab and 5-FU in the investigated cell lines.     

Proteomic and other analyses to determine the functional consequences of deregulated kallikrein-related peptidase (KLK) expression in prostate and ovarian cancer

Rapidly developing proteomic tools are improving detection of deregulated kallikrein-related peptidase (KLK) expression, at the protein level, in prostate and ovarian cancer, as well as facilitating the determination of functional consequences downstream. MS-driven proteomics uniquely allows for the detection, identification, and quantification of thousands of proteins in a complex protein pool, and this has served to identify certain KLKs as biomarkers for these diseases. In this review, we describe applications of this technology in KLK biomarker discovery and elucidate MS-based techniques that have been used for unbiased, global screening of KLK substrates within complex protein pools. Although MS-based KLK degradomic studies are limited to date, they helped to discover an array of novel KLK substrates. Substrates identified by MS-based degradomics are reported with improved confidence over those determined by incubating a purified or recombinant substrate and protease of interest, in vitro. We propose that these novel proteomic approaches represent the way forward for KLK research, in order to correlate proteolysis of biological substrates with tissue-related consequences, toward clinical targeting of KLK expression and function for cancer diagnosis, prognosis, and therapies.     

Challenges and opportunities for cell line secretomes in cancer proteomics

Cancer cell lines are the most widely used experimental models in cancer research. Their advantages of easy growth and manipulation are unfortunately paralleled by their limitations derived from long-term growth in isolation from the rest of the tumor, and hence, lack of tumor microenvironment. We are however currently witnessing novel and transformative advances that are making cell lines more reflective of the human biology and therefore, better experimental models for cancer research. Beyond the experimental model used, the choice of cellular proteome is key in proteomics-based biomarker discovery. Over the last decade, cell line secretomes have been proposed as an alternative for tumor biomarker discovery due to the difficulties posed by plasma in terms of complexity and low abundance of tumor-specific biomarkers. Cell line secretomes are enriched with proteins already linked to tumorigenesis, which also have a good chance of being present in biological fluids. In this review, we will provide an overview of the main technical and biological issues related to cell line secretome analysis, and briefly discuss both the challenges and opportunities in its use for tumor biomarker discovery.     

Modulation of cancer cell line differentiation: A neglected proteomic analysis with potential implications in pathophysiology, diagnosis, prognosis, and therapy of cancer

The recent development of compounds that induce cell differentiation in various types of cancer cells has enabled the molecular mechanisms governing this kind of induced cancer regression to be investigated. Moreover, this approach to investigating the pathophysiology of neoplasia represents a promising experimental model for proteomic analysis of cancer cells. Modulating neoplastic cell differentiation grade may reveal cytodifferentiation-related protein expression changes, and doing so in vitro has the advantage of less biological variation. Hence, this analysis brings attention to molecular targets of the so-called differentiating factors (i.e., retinoids, hybrid polar compounds, tyrosine kinase inhibitors, etc.) as well as proteins that are frequently associated with differentiation/dedifferentiation processes. The in vitro study of these proteins and of their pathogenetic roles in cancer may ultimately result in the discovery of cancer biomarkers with diagnostic, prognostic, and therapeutic applications.     

Quantitative proteomics for identification of cancer biomarkers

Quantitative proteomics can be used for the identification of cancer biomarkers that could be used for early detection, serve as therapeutic targets, or monitor response to treatment. Several quantitative proteomics tools are currently available to study differential expression of proteins in samples ranging from cancer cell lines to tissues to body fluids. 2-DE, which was classically used for proteomic profiling, has been coupled to fluorescence labeling for differential proteomics. Isotope labeling methods such as stable isotope labeling with amino acids in cell culture (SILAC), isotope-coded affinity tagging (ICAT), isobaric tags for relative and absolute quantitation (iTRAQ), and (18) O labeling have all been used in quantitative approaches for identification of cancer biomarkers. In addition, heavy isotope labeled peptides can be used to obtain absolute quantitative data. Most recently, label-free methods for quantitative proteomics, which have the potential of replacing isotope-labeling strategies, are becoming popular. Other emerging technologies such as protein microarrays have the potential for providing additional opportunities for biomarker identification. This review highlights commonly used methods for quantitative proteomic analysis and their advantages and limitations for cancer biomarker analysis.     

An on-chip cell culturing and combinatorial drug screening system

A low-cost, convenient and precise drug combination screening microfluidic platform is developed, in which cell culture chambers designed with micropillars integrate with three laminar flow diffusion channels. This platform has several distinct features, including minimum shear stress on cells, biocompatibility, optimum concentration distribution and automatic combinatorial gradient generation, which can potentially speed up the discovery of an effective drug combination for cancer ablations. The presented device can generate two-drug combination gradients at the optimum flow rate of 90 μL/h and can be applied to identify the optimal combination of two clinically relevant chemotherapy drugs. For demonstration, paclitaxel at 0.77 × 10^?3 mg/mL and cisplatin at 0.23 × 10^?4 mg/mL were studied against lung cancer cells (A549). This microfluidic device has the potential to provide a precise and robust screening for anticancer combinational drugs practiced in clinics.     

Generation of artificial neural networks models in anticancer study

Artificial neural networks (ANNs) have several applications; one of them is the prediction of biological activity. Here, ANNs were applied to a set of 32 compounds with anticancer activity assayed experimentally against two cancer cell lines (A2780 and T-47D). Using training and test sets, the obtained correlation coefficients between experimental and calculated values of activity, for A2780, were 0.804 and 0.829, respectively, and for T-47D, we got 0.820 for the training set and 0.927 for the test set. Comparing multiple linear regression and ANN models, the latter were better suited in establishing relationships between compounds’ structure and their anticancer activity.     

Proneurotensin/neuromedin N secreted from small cell lung carcinoma cell lines as a potential tumor marker

Proteins secreted from specific cancer cells have a high potential for use as tumor markers. We identified secreted proteins produced by 15 different carcinoma cell lines grown in serum-free medium using MS/MS. Proneurotensin/neuromedin N (proNT/NMN) was found in conditioned medium from four of seven small cell lung carcinoma cell lines but not from eight nonsmall cell lung carcinoma cell lines. These results indicate proNT/NMN has potential as a specific tumor marker of small cell lung carcinoma.     

Proteomic approaches to the study of malignant lymphoma: Analyses on patient samples

We describe the application of proteomic techniques for protein profiling and biomarker discovery in malignant lymphoma. Hematologic malignancies are primarily characterized by their clinical, morphological, immunophenotypical, and molecular-genetic features. However, when based on these parameters, apparently identical lymphomas may show distinct clinical courses, suggesting underlying biological heterogeneity. Recent proteomic analyses have identified differences in protein expression both with regard to subclassification of the malignant lymphoma entities, as well as in correlation with clinical outcome. In this review, studies on quantification of differential protein expression in and between malignant lymphoma entities are included. Studies are included that are based on patient samples, that is, serum/plasma or cytological specimens, as well as intact tumor tissues, together with studies that focus on tumor cells alone, or in conjunction with the tumor microenvironment. For biomarker discovery in malignant lymphoma, these approaches are used to uncover the underlying biological mechanisms and identify proteins with potential diagnostic and prognostic utility, either as predictive biomarkers or as novel future treatment targets.     

Proteomic profiling of 13 paired ductal infiltrating breast carcinomas and non-tumoral adjacent counterparts

According to recent statistics, breast cancer remains one of the leading causes of death among women in Western countries. Breast cancer is a complex and heterogeneous disease, presently classified into several subtypes according to their cellular origin. Among breast cancer histotypes, infiltrating ductal carcinoma represents the most common and potentially aggressive form. Despite the current progress achieved in early cancer detection and treatment, including the new generation of molecular therapies, there is still need for identification of multiparametric biomarkers capable of discriminating between cancer subtypes and predicting cancer progression for personalized therapies. One established step in this direction is the proteomic strategy, expected to provide enough information on breast cancer profiling. To this aim, in the present study we analyzed 13 breast cancer tissues and their matched non-tumoral tissues by 2-DE. Collectively, we identified 51 protein spots, corresponding to 34 differentially expressed proteins, which may represent promising candidate biomarkers for molecular-based diagnosis of breast cancer and for pattern discovery. The relevance of these proteins as factors contributing to breast carcinogenesis is discussed.