Proteomic phenotyping: metastatic and invasive breast cancer

Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer

Introduction

Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC). This study used surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) to identify differentially expressed proteins in sera from BC and healthy volunteers (HV), with the goal of developing a new prognostic biomarker panel.

Methods

Training set serum samples from 99 BC and 51 HV subjects were applied to four adsorptive chip surfaces (anion-exchange, cation-exchange, hydrophobic, and metal affinity) and analyzed by time-of-flight MS. For validation, 100 independent BC serum samples and 70 HV samples were analyzed similarly. Cluster analysis of protein spectra was performed to identify protein patterns related to BC and HV groups. Univariate and multivariate statistical analyses were used to develop a protein panel to distinguish breast cancer sera from healthy sera, and its prognostic potential was evaluated.

Results

From 51 protein peaks that were significantly up- or downregulated in BC patients by univariate analysis, binary logistic regression yielded five protein peaks that together classified BC and HV with a receiver operating characteristic (ROC) area-under-the-curve value of 0.961. Validation on an independent patient cohort confirmed the five-protein parameter (ROC value 0.939). The five-protein parameter showed positive association with large tumor size (P = 0.018) and lymph node involvement (P = 0.016). By matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS, immunoprecipitation and western blotting the proteins were identified as a fragment of apolipoprotein H (ApoH), ApoCI, complement C3a, transthyretin, and ApoAI. Kaplan-Meier analysis on 181 subjects after median follow-up of >5 years demonstrated that the panel significantly predicted disease-free survival (P = 0.005), its efficacy apparently greater in women with estrogen receptor (ER)-negative tumors (n = 50, P = 0.003) compared to ER-positive (n = 131, P = 0.161), although the influence of ER status needs to be confirmed after longer follow-up.

Conclusions

Protein mass profiling by MS has revealed five serum proteins which, in combination, can distinguish between serum from women with breast cancer and healthy control subjects with high sensitivity and specificity. The five-protein panel significantly predicts recurrence-free survival in women with ER-negative tumors and may have value in the management of these patients.

Identification of CD44 as a surface biomarker for drug resistance by surface proteome signature technology

We developed surface proteome signatures (SPS) for identification of new biomarkers playing a role in cancer drug resistance. SPS compares surface antigen expression of different cell lines by immunocytochemistry of a phage display antibody library directed to surface antigens of HT1080 fibrosarcoma cells. We applied SPS to compare the surface proteomes of two epithelial derived cancer cell lines, MCF7 and NCI/ADR-RES, which is drug resistant because of overexpression of the P-glycoprotein (P-gp) drug efflux pump. Surface proteomic profiling identified CD44 as an additional biomarker that distinguishes between these two cell lines. CD44 immunohistochemistry can distinguish between tumors derived from these lines and predict tumor response to doxorubicin in vivo. We further show that CD44 plays a role in drug resistance, independently of P-gp, in NCI/ADR-RES cells and increases expression of the antiapoptotic protein Bcl-xL. Our findings illustrate the utility of SPS to distinguish between cancer cell lines and their derived tumors and identify novel biomarkers involved in drug resistance.

MCF-7/ADR cells (re-designated NCI/ADR-RES) are not derived from MCF-7 breast cancer cells: a loss for breast cancer multidrug-resistant research

MCF-7/ADR cells have been widely used as a multidrug-resistant breast cancer cell model in cancer research. The origin of MCF-7/ADR has been a matter of debate since MCF-7/ADR cells were re-designated NCI/ADR-RES in 1998. Many recent studies still describe MCF-7/ADR cells as originating from the breast cancer cell line MCF-7. Thus, the real origin of MCF-7/ADR cells remains more unclear. In this study, a new adriamycin (ADR)-resistant cell line MCF-7/ADR' was reproduced using the same procedure employed during the initial establishment of MCF-7/ADR. Since the MCF-7/ADR' cell line was definitely derived from parental MCF-7 cells, we were able to directly compare these cell lines together with MCF-7/ADR using immunocytochemical, morphological, and consecutive DNA fingerprinting analyses to determine the true origin of MCF-7/ADR. Both ADR-resistant cell lines displayed some similar phenotypic characteristics, such as high levels of P-glycoprotein (P-gp) expression, increased vacuolation, abundant filamentous material, and irregular pseudopodia. With increasing concentrations of ADR, the DNA fingerprints of MCF-7/ADR' cells were always identical to the parental MCF-7 cells. However, the DNA fingerprints of MCF-7/ADR cells did not relate to MCF-7 or MCF-7/ADR'. MCF-7/ADR and the breast cancer cell line MCF-7 are not of the same origin. Long-time culture in the presence of ADR does not cause significant changes in DNA fingerprint patterns.

Defining central themes in breast cancer biology by differential proteomics: conserved regulation of cell spreading and focal adhesion kinase

Breast cancer is a highly heterogeneous disease, an observation that underscores the importance of elucidating conserved molecular characteristics, such as gene and protein expression, across breast cancer cell types toward providing a greater understanding of context-specific features central to this disease. Motivated by the goal of defining central biological themes across breast cancer cell subtypes, we conducted a global proteomic analysis of three breast cancer cell lines, MCF7, SK-BR-3, and MDA-MB-231, and compared these to a model of nontransformed mammary cells (MCF10A). Our results demonstrate modulation of proteins localized to the extracellular matrix, plasma membrane, and nucleus, along with coordinate decreases in proteins that regulate "cell spreading," a cellular event previously shown to be dysregulated in transformed cells. Protein interaction network analysis revealed the clustering of focal adhesion kinase (FAK), a fundamental regulator of cell spreading, with several proteins identified as mutually, differentially abundant across breast cancer cell lines that impact expression and activity of FAK, such as neprilysin and keratin 19. These analyses provide insights into conservation of protein expression across breast cancer cell subtypes, a subset of which warrants further investigation for their roles in the regulation of cell spreading and FAK in breast cancer.

Phenotyping breast cancer cell lines EM-G3, HCC1937, MCF7 and MDA-MB-231 using 2-D electrophoresis and affinity chromatography for glutathione-binding proteins

BACKGROUND

Transformed phenotypes are common to cell lines derived from various cancers. Proteome profiling is a valuable tool that may reveal uncharacteristic cell phenotypes in transformed cells. Changes in expression of glutathione S-transferases (GSTs) and other proteins interacting with glutathione (GSH) in model cell lines could be of particular interest.

METHODS

We compared the phenotypes of breast cell lines EM-G3, HCC1937, MCF7 and MDA-MB-231 using 2-D electrophoresis (2-DE). We further separated GSH-binding proteins from the cell lines using affinity chromatography with GSH-Sepharose 4B, performed 2-DE analysis and identified the main protein spots.

RESULTS

Correlation coefficients among 2-DE gels from the cell lines were lower than 0.65, pointing to dissimilarity among the cell lines. Differences in primary constituents of the cytoskeleton were shown by the 2-D protein maps and western blots. The spot patterns in gels of GSH-binding fractions from primary carcinoma-derived cell lines HCC1937 and EM-G3 were similar to each other, and they differed from the spot patterns of cell lines MCF7 and MDA-MB-231 that were derived from pleural effusions of metastatic mammary carcinoma patients. Major differences in the expression of GST P1-1 and carbonyl reductase [NADPH] 1 were observed among the cell lines, indicating differential abilities of the cell lines to metabolize xenobiotics.

CONCLUSIONS

Our results confirmed the applicability of targeted affinity chromatography to proteome profiling and allowed us to characterize the phenotypes of four breast cancer cell lines.

Integrated gene networks in breast cancer development

Breast cancer is a complex and heterogenous disease. Classical molecular medical approaches cannot fully understand and comprehend its pathogenesis. In this review, the development of new biological markers for the early detection and creation of guided and specific therapy of breast cancer are discussed in light of the rapid advances in the "omics". Results of cancer research in combination with large-scale methods that examine the expression status of genes and proteins have identified a large number of new biomarkers as well as confirmed the human growth hormone as an important player in the pathogenesis of this disease through its autocrine regulation where it influences the activation of Pax5 and HOXA1 gene networks.

A systems biology approach to defining metastatic biomarkers and signaling pathways

Metastasis is the final stage of cancer and the primary cause of mortality for most solid malignancies. This terminal phase of cancer progression has been investigated using a variety of high-throughput technologies (i.e., gene expression arrays, array comparative genomic hybridization (aCGH), and proteomics) to identify prognostic expression profiles and better characterize the metastatic process. For decades, the predominant model for the metastatic process has been the 'progression model', yet recent microarray results tend to support an inherent metastatic capability within primary tumors. Moreover, studies using a highly metastatic transgenic mammary tumor model suggest that germline polymorphisms are significant determinants of metastatic efficiency. Likewise, a strong concordance of survival has been observed between family members with cancer, further supporting the link between genetic inheritance and survival. In addition, chromosomal aberrations and signaling pathways related to metastatic capacity have been identified by array comparative genomic hybridization (aCGH) and proteomic studies, respectively. Lastly, carcinoma enzyme activity profiles using activity-based proteomics (ABPP), may be more clinically useful than expression-based proteomics for certain cancers. Most importantly, the application of these high-throughput techniques should expedite the search for additional biomarkers, germline polymorphisms, and expression signatures with greater prognostic value.

Proteomic analysis of tumor necrosis factor-alpha resistant human breast cancer cells reveals a MEK5/Erk5-mediated epithelial-mesenchymal transition phenotype

Introduction

Despite intensive study of the mechanisms of chemotherapeutic drug resistance in human breast cancer, few reports have systematically investigated the mechanisms that underlie resistance to the chemotherapy-sensitizing agent tumor necrosis factor (TNF)-α. Additionally, the relationship between TNF-α resistance mediated by MEK5/Erk5 signaling and epithelial-mesenchymal transition (EMT), a process associated with promotion of invasion, metastasis, and recurrence in breast cancer, has not previously been investigated.

Methods

To compare differences in the proteome of the TNF-α resistant MCF-7 breast cancer cell line MCF-7-MEK5 (in which TNF-α resistance is mediated by MEK5/Erk5 signaling) and its parental TNF-a sensitive MCF-7 cell line MCF-7-VEC, two-dimensional gel electrophoresis and high performance capillary liquid chromatography coupled with tandem mass spectrometry approaches were used. Differential protein expression was verified at the transcriptional level using RT-PCR assays. An EMT phenotype was confirmed using immunofluorescence staining and gene expression analyses. A short hairpin RNA strategy targeting Erk5 was utilized to investigate the requirement for the MEK/Erk5 pathway in EMT.

Results

Proteomic analyses and PCR assays were used to identify and confirm differential expression of proteins. In MCF-7-MEK5 versus MCF-7-VEC cells, vimentin (VIM), glutathione-S-transferase P (GSTP1), and creatine kinase B-type (CKB) were upregulated, and keratin 8 (KRT8), keratin 19 (KRT19) and glutathione-S-transferase Mu 3 (GSTM3) were downregulated. Morphology and immunofluorescence staining for E-cadherin and vimentin revealed an EMT phenotype in the MCF-7-MEK5 cells. Furthermore, EMT regulatory genes SNAI2 (slug), ZEB1 (δ-EF1), and N-cadherin (CDH2) were upregulated, whereas E-cadherin (CDH1) was downregulated in MCF-7-MEK5 cells versus MCF-7-VEC cells. RNA interference targeting of Erk5 reversed MEK5-mediated EMT gene expression.

Conclusions

This study demonstrates that MEK5 over-expression promotes a TNF-α resistance phenotype associated with distinct proteomic changes (upregulation of VIM/vim, GSTP1/gstp1, and CKB/ckb; and downregulation of KRT8/krt8, KRT19/krt19, and GSTM3/gstm3). We further demonstrate that MEK5-mediated progression to an EMT phenotype is dependent upon intact Erk5 and associated with upregulation of SNAI2 and ZEB1 expression.

Glycomic profiling of invasive and non-invasive breast cancer cells

Quantitative profiling of glycans with different structures appears essential for a better understanding of the cellular adhesion phenomena associated with malignant transformation and the underlying aberrant glycosylation of cancer cells. Using the recently developed glycomic techniques and mass-spectrometric measurements, we compare the N-linked and O-linked oligosaccharide profiles for different breast cancer cell lines with those of normal epithelial cells. Statistically significant differences in certain neutral, sialylated and fucosylated structures are readily discerned through quantitative measurements, indicating a potential of distinguishing invasive and non-invasive cancer attributes. The glycomic profile data cluster accordingly using Principal Component Analysis, verifying further glycobiological differences due to the differences between normal and cancer cell lines.

American Society of Clinical Oncology 2007 update of recommendations for the use of tumor markers in breast cancer

PURPOSE

To update the recommendations for the use of tumor marker tests in the prevention, screening, treatment, and surveillance of breast cancer.

METHODS

For the 2007 update, an Update Committee composed of members from the full Panel was formed to complete the review and analysis of data published since 1999. Computerized literature searches of MEDLINE and the Cochrane Collaboration Library were performed. The Update Committee's literature review focused attention on available systematic reviews and meta-analyses of published tumor marker studies. In general, significant health outcomes (overall survival, disease-free survival, quality of life, lesser toxicity, and cost-effectiveness) were used for making recommendations. Recommendations and

CONCLUSIONS

Thirteen categories of breast tumor markers were considered, six of which were new for the guideline. The following categories showed evidence of clinical utility and were recommended for use in practice: CA 15-3, CA 27.29, carcinoembryonic antigen, estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, urokinase plasminogen activator, plasminogen activator inhibitor 1, and certain multiparameter gene expression assays. Not all applications for these markers were supported, however. The following categories demonstrated insufficient evidence to support routine use in clinical practice: DNA/ploidy by flow cytometry, p53, cathepsin D, cyclin E, proteomics, certain multiparameter assays, detection of bone marrow micrometastases, and circulating tumor cells.

Breast cancer proteomics: clinical perspectives

Breast cancer is the one of leading causes of cancer-related deaths in women within economically developed regions of the world. A major focus of present research into this malignancy is the identification of new biomarkers and drug targets to improve detection and treatment. Proteomics represents one of the latest technological developments in this context. It aims to analyse the complex circuitry of the breast cancer proteome. Here, the authors review how breast cancer proteomics has progressed so far, with emphasis on its potential application to clinically relevant scenarios.

Alterations in the mitochondrial proteome of adriamycin resistant MCF-7 breast cancer cells

A 2D-gel based comparative proteomic analysis has been conducted of changes in mitochondrial protein abundances in MCF-7 human breast cancer cells selected for resistance to Adriamycin accompanied by verapamil. We identified and compared 156 unique proteins from 184 spots. Eleven mitochondrial proteins were found with abundances altered more than 2-fold. Transcription was evaluated for two of these, using quantitative RT-PCR. Implications of the changes are considered with respect to drug resistance.

Proteomic analysis in cancer research: potential application in clinical use

The ultimate goal of cancer proteomics is to adapt proteomic technologies for routine use in clinical laboratories for the purpose of diagnostic and prognostic classification of disease states, as well as in evaluating drug toxicity and efficacy. The novel technologies allows researchers to facilitate the comprehensive analyses of genomes, transcriptomes, and proteomes in health and disease. The information that is expected from such technologies may soon exert a dramatic change in cancer research and impact dramatically on the care of cancer patients. Analysis of tumor-specific proteomic profiles may also allow better understanding of tumor development and the identification of novel targets for cancer therapy. The localization of gene products, which is often difficult to deduce from the sequence, can be determined experimentally. Mechanisms, such as regulation of protein function by proteolysis, recycling, and isolation in cell compartments, affect gene products, not genes. Finally, protein-protein interactions and the molecular composition of cellular structures can be determined only at the protein level. The biological variability among patient samples as well as the great dynamic range of biomarker concentrations are currently the main challenges facing efforts to deduce diagnostic patterns that are unique to specific disease states. While several strategies exist to address this problem, we have tried to offer a wide perspective about the current possibilities.

Expanding the protein catalogue in the proteome reference map of human breast cancer cells

In this report we present a catalogue of 162 proteins (including isoforms and variants) identified in a prototype of proteomic map of breast cancer cells. This work represents the prosecution of previous studies describing the protein complement of breast cancer cells of the line 8701-BC, which has been well characterized for several parameters, providing to be a useful model for the study of breast cancer-associated candidate biomarkers. In particular, 110 spots were identified ex novo by PMF, or validated following previous gel matching identification method; 30 were identified by N-terminal microsequencing and the remaining by gel matching with maps available from our former work. As a consequence of the expanded number of proteins, we have updated our previous classification extending the number of protein groups from 4 to 13. In order to facilitate comparative proteome studies of different kinds of breast cancers, in this report we provide the whole complement of proteins so far identified and grouped into the new classification. A consistent number of them were not described before in other proteomic maps of breast cancer cells or tissues, and therefore they represent a valuable contribution for breast cancer protein databases and for future application in basic and clinical researches.

A case study in misidentification of cancer cell lines: MCF-7/AdrR cells (re-designated NCI/ADR-RES) are derived from OVCAR-8 human ovarian carcinoma cells

Multidrug-resistant MCF-7 breast adenocarcinoma cells (originally named MCF-7/AdrR cells and later re-designated NCI/ADR-RES) have served as an important and widely used research tool during the last two decades. However, the real identity of these cells has been in doubt since 1998 and has since been debated. The origin of NCI/ADR-RES cells has now been revealed by SNP and karyotypic analyses, carried out at the Sanger Institute and the NCI, respectively. The results of these analyses, recently posted on the Web, show that NCI/ADR-RES cells are derived from OVCAR-8 ovarian adenocarcinoma cells. The case of NCI/ADR-RES cells highlights a wide-spread problem of cell line cross-contamination and misidentification. Fortunately, this is a tractable problem that can be avoided by scrupulous genotyping of cell stocks and adoption of a few simple rules in cell culture practice.

Proteomic evidence for roles for nucleolin and poly[ADP-ribosyl] transferase in drug resistance

One-hundred twenty-four proteins have been identified in the soluble nuclear protein mixture from MCF-7 human breast cancer cells, of which more than 90% are classically categorized as nuclear proteins. Proteins were also studied from three drug resistant MDF-7 lines, selected previously from the same parent line by exposure to etoposide, to mitoxantrone, or to adriamycin in the presence of verapamil. Both quantitative gel comparisons and stable isotope labeling were used to identify a total of fourteen proteins whose abundances are altered by more than 2-fold in the three resistant lines. Several cytoskeleton proteins, cytokeratin 8, cytokeratin 19, septin 2, and alpha tropomyosin, are decreased in common across the three resistant cell lines. PARP-l (poly[ADP-ribosyl]transefrase or connexion) is found to be less abundant in all three resistant lines. Nucleolin is more abundant in lines resistant to etoposide and mitoxantrone, while the mitotic checkpoint protein BUB 3 is more abundant in the line resistant to adriamycin/verapamil.

Application of proteomics in the study of tumor metastasis

Tumor metastasis is the dominant cause of death in cancer patients. However, the molecular and cellular mechanisms underlying tumor metastasis are still elusive. The identification of protein molecules with their expressions correlated to the metastatic process would help to understand the metastatic mechanisms and thus facilitate the development of strategies for the therapeutic interventions and clinical management of cancer. Proteomics is a systematic research approach aiming to provide the global characterization of protein expression and function under given conditions. Proteomic technology has been widely used in biomarker discovery and pathogenetic studies including tumor metastasis. This article provides a brief review of the application of proteomics in identifying molecular factors in tumor metastasis process. The combination of proteomics with other experimental approaches in biochemistry, cell biology, molecular genetics and chemistry, together with the development of new technologies and improvements in existing methodologies will continue to extend its application in studying cancer metastasis.

Metabolic Labeling of Human Primary Retinal Pigment Epithelial Cells for Accurate Comparative Proteomics

Metabolic labeling was evaluated, using both 13C6-Arg and 13C6, 15N2-Lys amino acids, for a primary human retinal pigment epithelial cell (hRPE) culture prepared from an autopsy eye of an 81 year old donor. Satisfactory incorporation (>90%) was achieved with both stable isotope labeled amino acids after four passages (roughly 7 population doublings). The degree of incorporation was found to be efficient with both amino acids as well as in different proteins. The presence of 10% whole serum in the culture medium did not interfere with the incorporation of the exogenous stable isotope labeled amino acids. Metabolic labeling of these human primary retinal pigment epithelial cells was further tested to quantify protein ratios between proliferating and resting cells using a combination of 2-DG and MALDI-TOF-TOF/MS analysis. Using computational data processing and analysis, we obtained accurate protein ratio measurement for every single identified protein (156 proteins) in the 2-Dg array. Of these 156 proteins, 12 proteins were found significantly increased in dividing versus resting cells by at least a factor of 1.5 while 13 other proteins were found increased in resting versus dividing cells by at least the same fold. Most of these differentially expressed proteins are directly involved in cell proliferation, protein synthesis, and actin-remodeling and differentiation.

Evaluation of Metabolic Labeling for Comparative Proteomics in Breast Cancer Cells

Protein expression patterns in the cytosol of MCF-7 cells resistant to adriamycin and to adriamycin/verapamil were compared to that of the parental MCF-7 cell line and to each other using metabolic labeling and two-dimensional gel electrophoresis. Growing the parental MCF-7 cell line in 13C6-arginine- and 13C6-lysine-enriched medium resulted in C-terminal labeling of all tryptic peptides. The culture media was optimized for the incorporation of these labeled amino acids under conditions that also supported cell growth. Protein abundances were found to be distinctive in MCF-7 cells resistant to adriamycin and those selected for resistance to both adriamycin and verapamil.