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

Segregation of co-cultured multicellular systems: review and modeling consideration

Cell segregation caused by collective cell migration (CCM) is crucial for morphogenesis, functional development of tissue parts, and is an important aspect in other diseases such as cancer and its metastasis process. Efficiency of the cell segregation depends on the interplay between: (1) biochemical processes such as cell signaling and gene expression and (2) physical interactions between cells. Despite extensive research devoted to study the segregation of various co-cultured systems, we still do not understand the role of physical interactions in cell segregation. Cumulative effects of these physical interactions appear in the form of physical parameters such as: (1) tissue surface tension, (2) viscoelasticity caused by CCM, and (3) solid stress accumulated in multicellular systems. These parameters primarily depend on the interplay between the state of cell-cell adhesion contacts and cell contractility. The role of these physical parameters on the segregation efficiency is discussed on model systems such as co-cultured breast cell spheroids consisting of two subpopulations that are in contact. This review study aims to: (1) summarize biological aspects related to cell segregation, mechanical properties of cell collectives, effects along the biointerface between cell subpopulations and (2) describe from a biophysical/mathematical perspective the same biological aspects summarized before. So that overall it can illustrate the complexity of the biological systems that translate into very complex biophysical/mathematical equations. Moreover, by presenting in parallel these two seemingly different parts (biology vs. equations), this review aims to emphasize the need for experiments to estimate the variety of parameters entering the resulting complex biophysical/mathematical models.

The dynamics along the biointerface between the epithelial and cancer mesenchymal cells: Modeling consideration

Epithelial cancer is the one of most lethal cancer type worldwide. Targeting the early stage of disease would allow dramatic improvements in the survival of cancer patients. The early stage of the disease is related to cancer cell spreading across surrounding healthy epithelium. Consequently, deeper insight into cell dynamics along the biointerface between epithelial and cancer (mesenchymal) cells is necessary in order to control the disease as soon as possible. Cell dynamics along this epithelial-cancer biointerface is the result of the interplay between various biological and physical mechanisms. Despite extensive research devoted to study cancer cell spreading across the epithelium, we still do not understand the physical mechanisms which influences the dynamics along the biointerface. These physical mechanisms are related to the interplay between physical parameters such as: (1) interfacial tension between cancer and epithelial subpopulations, (2) established interfacial tension gradients, (3) the bending rigidity of the biointerface and its impact on the interfacial tension, (4) surface tension of the subpopulations, (5) viscoelasticity caused by collective cell migration, and (6) cell residual stress accumulation. The main goal of this study is to review some of these physical parameters in the context of the epithelial/cancer biointerface elaborated on the model system such as the biointerface between breast epithelial MCF-10A cells and cancer MDA-MB-231 cells and then to incorporate these parameters into a new biophysical model that could describe the dynamics of the biointerface. We conclude by discussing three biophysical scenarios for cell dynamics along the biointerface, which can occur depending on the magnitude of the generated shear stress: a smooth biointerface, a slightly-perturbed biointerface and an intensively-perturbed biointerface in the context of the Kelvin-Helmholtz instability. These scenarios are related to the probability of cancer invasion.

Chemical inhibition of FBXO7 reduces inflammation and confers neuroprotection by stabilizing the mitochondrial kinase PINK1

Mitochondrial quality control is mediated by the PTEN-induced kinase 1 (PINK1), a cytoprotective protein that is dysregulated in inflammatory lung injury and neurodegenerative diseases. Here, we show that a ubiquitin E3 ligase receptor component, FBXO7, targets PINK1 for its cellular disposal. FBXO7, by mediating PINK1 ubiquitylation and degradation, was sufficient to induce mitochondrial injury and inflammation in experimental pneumonia. A computational simulation-based screen led to the identification of a small molecule, BC1464, which abrogated FBXO7 and PINK1 association, leading to increased cellular PINK1 concentrations and activities, and limiting mitochondrial damage. BC1464 exerted antiinflammatory activity in human tissue explants and murine lung inflammation models. Furthermore, BC1464 conferred neuroprotection in primary cortical neurons, human neuroblastoma cells, and patient-derived cells in several culture models of Parkinson's disease. The data highlight a unique opportunity to use small molecule antagonists that disrupt PINK1 interaction with the ubiquitin apparatus to enhance mitochondrial quality, limit inflammatory injury, and maintain neuronal viability.

PINK1 Interacts with VCP/p97 and Activates PKA to Promote NSFL1C/p47 Phosphorylation and Dendritic Arborization in Neurons

While PTEN-induced kinase 1 (PINK1) is well characterized for its role in mitochondrial homeostasis, much less is known concerning its ability to prevent synaptodendritic degeneration. Using unbiased proteomic methods, we identified valosin-containing protein (VCP) as a major PINK1-interacting protein. RNAi studies demonstrate that both VCP and its cofactor NSFL1C/p47 are necessary for the ability of PINK1 to increase dendritic complexity. Moreover, PINK1 regulates phosphorylation of p47, but not the VCP co-factor UFD1. Although neither VCP nor p47 interact directly with PKA, we found that PINK1 binds and phosphorylates the catalytic subunit of PKA at T197 [PKAcat(pT197)], a site known to activate the PKA holoenzyme. PKA in turn phosphorylates p47 at a novel site (S176) to regulate dendritic complexity. Given that PINK1 physically interacts with both the PKA holoenzyme and the VCP-p47 complex to promote dendritic arborization, we propose that PINK1 scaffolds a novel PINK1-VCP-PKA-p47 signaling pathway to orchestrate dendritogenesis in neurons. These findings highlight an important mechanism by which proteins genetically implicated in Parkinson's disease (PD; PINK1) and frontotemporal dementia (FTD; VCP) interact to support the health and maintenance of neuronal arbors.

Protein biomarkers for subtyping breast cancer and implications for future research

INTRODUCTION

Breast cancer subtypes are currently defined by a combination of morphologic, genomic, and proteomic characteristics. These subtypes provide a molecular portrait of the tumor that aids diagnosis, prognosis, and treatment escalation/de-escalation options. Gene expression signatures describing intrinsic breast cancer subtypes for predicting risk of recurrence have been rapidly adopted in the clinic. Despite the use of subtype classifications, many patients develop drug resistance, breast cancer recurrence, or therapy failure. Areas covered: This review provides a summary of immunohistochemistry, reverse phase protein array, mass spectrometry, and integrative studies that are revealing differences in biological functions within and between breast cancer subtypes. We conclude with a discussion of rigor and reproducibility for proteomic-based biomarker discovery. Expert commentary: Innovations in proteomics, including implementation of assay guidelines and standards, are facilitating refinement of breast cancer subtypes. Proteomic and phosphoproteomic information distinguish biologically functional subtypes, are predictive of recurrence, and indicate likelihood of drug resistance. Actionable, activated signal transduction pathways can now be quantified and characterized. Proteomic biomarker validation in large, well-designed studies should become a public health priority to capitalize on the wealth of information gleaned from the proteome.

Differential Proteome Analysis of Extracellular Vesicles from Breast Cancer Cell Lines by Chaperone Affinity Enrichment

The complexity of human tissue fluid precludes timely identification of cancer biomarkers by immunoassay or mass spectrometry. An increasingly attractive strategy is to primarily enrich extracellular vesicles (EVs) released from cancer cells in an accelerated manner compared to normal cells. The Vn96 peptide was herein employed to recover a subset of EVs released into the media from cellular models of breast cancer. Vn96 has affinity for heat shock proteins (HSPs) decorating the surface of EVs. Reflecting their cells of origin, cancer EVs displayed discrete differences from those of normal phenotype. GELFrEE LC/MS identified an extensive proteome from all three sources of EVs, the vast majority having been previously reported in the ExoCarta database. Pathway analysis of the Vn96-affinity proteome unequivocally distinguished EVs from tumorigenic cell lines (SKBR3 and MCF-7) relative to a non-tumorigenic source (MCF-10a), particularly with regard to altered metabolic enzymes, signaling, and chaperone proteins. The protein data sets provide valuable information from material shed by cultured cells. It is probable that a vast amount of biomarker identities may be collected from established and primary cell cultures using the approaches described here.

Large-Scale Analysis of Breast Cancer-Related Conformational Changes in Proteins Using SILAC-SPROX

Proteomic methods for disease state characterization and biomarker discovery have traditionally utilized quantitative mass spectrometry methods to identify proteins with altered expression levels in disease states. Here we report on the large-scale use of protein folding stability measurements to characterize different subtypes of breast cancer using the stable isotope labeling with amino acids in cell culture and stability of proteins from rates of oxidation (SILAC-SPROX) technique. Protein folding stability differences were studied in a comparison of two luminal breast cancer subtypes, luminal-A and -B (i.e., MCF-7 and BT-474 cells, respectively), and in a comparison of a luminal-A and basal subtype of the disease (i.e., MCF-7 and MDA-MB-468 cells, respectively). The 242 and 445 protein hits identified with altered stabilities in these comparative analyses included a large fraction with no significant expression level changes. This suggests thermodynamic stability measurements create a new avenue for protein biomarker discovery. A number of the identified protein hits are known from other biochemical studies to play a role in tumorigenesis and cancer progression. This not only substantiates the biological significance of the protein hits identified using the SILAC-SPROX approach, but it also helps elucidate the molecular basis for their disregulation and/or disfunction in cancer.

Effects of rapamycin on cell apoptosis in MCF-7 human breast cancer cells

BACKGROUND

Rapamycin is an effective anti-angiogenic drug. However, the mode of its action remains unclear. Therefore, in this study, we aimed to elucidate the antitumor mechanism of rapamycin, hypothetically via apoptotic promotion, using MCF-7 breast cancer cells.

MATERIALS AND METHODS

MCF-7 cells were plated at a density of 15105 cells/well in 6-well plates. After 24h, cells were treated with a series of concentrations of rapamycin while only adding DMEM medium with PEG for the control regiment and grown at 37oC, 5% CO2 and 95% air for 72h. Trypan blue was used to determine the cell viability and proliferation. Untreated and rapamycin-treated MCF-7 cells were also examined for morphological changes with an inverted-phase contrast microscope. Alteration in cell morphology was ascertained, along with a stage in the cell cycle and proliferation. In addition, cytotoxicity testing was performed using normal mouse breast mammary pads.

RESULTS

Our results clearly showed that rapamycin exhibited inhibitory activity on MCF-7 cell lines. The IC50 value of rapamycin on the MCF-7 cells was determined as 0.4μg/ml (p<0.05). Direct observation by inverted microscopy demonstrated that the MCF-7 cells treated with rapamycin showed characteristic features of apoptosis including cell shrinkage, vascularization and autophagy. Cells underwent early apoptosis up to 24% after 72h. Analysis of the cell cycle showed an increase in the G0G1 phase cell population and a corresponding decrease in the S and G2M phase populations, from 81.5% to 91.3% and 17.3% to 7.9%, respectively.

CONCLUSIONS

This study demonstrated that rapamycin may potentially act as an anti-cancer agent via the inhibition of growth with some morphological changes of the MCF-7 cancer cells, arrest cell cycle progression at G0/G1 phase and induction of apoptosis in late stage of apoptosis. Further studies are needed to further characterize the mode of action of rapamycin as an anti-cancer agent.

Quantification of HER family receptors in breast cancer

The clinical success of trastuzumab in breast cancer taught us that appropriate tumor evaluation is mandatory for the correct identification of patients eligible for targeted therapies. Although HER2 protein expression by immunohistochemistry (IHC) and gene amplification by fluorescence in situ hybridization (FISH) assays are routinely used to select patients to receive trastuzumab, both assays only partially predict response to the drug. In the case of epidermal growth factor receptor (EGFR), the link between the presence of the receptor or its amplification and response to anti-EGFR therapies could not be demonstrated. Even less is known for HER3 and HER4, mainly due to lack of robust and validated assays detecting these proteins. It is becoming evident that, besides FISH and IHC, we need better assays to quantify HER receptors and categorize the patients for individualized treatments. Here, we present the current available methodologies to measure HER family receptors and discuss the clinical implications of target quantification.

BioXpress: an integrated RNA-seq-derived gene expression database for pan-cancer analysis

BioXpress is a gene expression and cancer association database in which the expression levels are mapped to genes using RNA-seq data obtained from The Cancer Genome Atlas, International Cancer Genome Consortium, Expression Atlas and publications. The BioXpress database includes expression data from 64 cancer types, 6361 patients and 17 469 genes with 9513 of the genes displaying differential expression between tumor and normal samples. In addition to data directly retrieved from RNA-seq data repositories, manual biocuration of publications supplements the available cancer association annotations in the database. All cancer types are mapped to Disease Ontology terms to facilitate a uniform pan-cancer analysis. The BioXpress database is easily searched using HUGO Gene Nomenclature Committee gene symbol, UniProtKB/RefSeq accession or, alternatively, can be queried by cancer type with specified significance filters. This interface along with availability of pre-computed downloadable files containing differentially expressed genes in multiple cancers enables straightforward retrieval and display of a broad set of cancer-related genes.

Database URL:http://hive.biochemistry.gwu.edu/tools/bioxpress

Elevated AKAP12 in paclitaxel-resistant serous ovarian cancer cells is prognostic and predictive of poor survival in patients

A majority of high-grade (HG) serous ovarian cancer (SOC) patients develop resistant disease despite high initial response rates to platinum/paclitaxel-based chemotherapy. We identified shed/secreted proteins in preclinical models of paclitaxel-resistant human HGSOC models and correlated these candidate proteins with patient outcomes using public data from HGSOC patients. Proteomic analyses of a HGSOC cell line secretome was compared to those from a syngeneic paclitaxel-resistant variant and from a line established from an intrinsically chemorefractory HGSOC patient. Associations between the identified candidate proteins and patient outcome were assessed in a discovery cohort of 545 patients and two validation cohorts totaling 795 independent SOC patients. Among the 81 differentially abundant proteins identified (q < 0.05) from paclitaxel-sensitive vs -resistant HGSOC cell secretomes, AKAP12 was verified to be elevated in all models of paclitaxel-resistant HGSOC. Furthermore, elevated AKAP12 transcript expression was associated with worse progression-free and overall survival. Associations with outcome were observed in three independent cohorts and remained significant after adjusted multivariate modeling. We further provide evidence to support that differential gene methylation status is associated with elevated expression of AKAP12 in taxol-resistant ovarian cancer cells and ovarian cancer patient subsets. Elevated expression and shedding/secretion of AKAP12 is characteristic of paclitaxel-resistant HGSOC cells, and elevated AKAP12 transcript expression is a poor prognostic and predictive marker for progression-free and overall survival in SOC patients.

Systematic nucleo-cytoplasmic trafficking of proteins following exposure of MCF7 breast cancer cells to estradiol

We have used a proteomics subcellular spatial razor approach to look at changes in total protein abundance and in protein distribution between the nucleus and cytoplasm following exposure of MCF7 breast cancer cells to estradiol. The dominant response of MCF7 cells to estrogen stimulation involves dynamic changes in protein subcellular spatial distribution rather than changes in total protein abundance. Of the 3604 quantitatively monitored proteins, only about 2% show substantial changes in total abundance (>2-fold), whereas about 20% of the proteins show substantial changes in local abundance and/or redistribution of their subcellular location, with up to 16-fold changes in their local concentration in the nucleus or the cytoplasm. We propose that dynamic redistribution of the subcellular location of multiple proteins in response to stimuli is a fundamental characteristic of cells and suggest that perturbation of cellular spatial control may be an important feature of cancer.

Systemic alteration of cell-surface and secreted glycoprotein expression in malignant breast cancer cell lines

Breast cancer cell lines express fewer transmembrane and secreted glycoproteins than nonmalignant ones. The objective of these experiments was to characterize the changes in the expression of several hundred glycoproteins quantitatively. Secreted and cell-surface glycoproteins were isolated using a glycoprotein capture protocol and then identified by tandem mass spectrometry. Glycoproteins expressed by a group of cell lines originating from malignant tumors of the breast were compared with those expressed by a nonmalignant set. The average number of spectral counts (proportional to relative protein abundance) and the total number of glycopeptides in the malignant samples were reduced to about two-thirds of the level in the nonmalignant samples. Most glycoproteins were expressed at a different level in the malignant samples, with nearly as many increasing as decreasing. The glycoproteins with reduced expression accounted for a larger change in spectral counts, and hence for the net loss of spectral counts in the malignant lines. Similar results were found when the glycoproteins were studied via identified glycosylation sites only, or through identified sites together with non-glycopeptides. The overall reduction is largely due to the loss of integrins, laminins and other proteins that form or interact with the basement membrane.

Maximizing peptide identification events in proteomic workflows using data-dependent acquisition (DDA)

Current analytical strategies for collecting proteomic data using data-dependent acquisition (DDA) are limited by the low analytical reproducibility of the method. Proteomic discovery efforts that exploit the benefits of DDA, such as providing peptide sequence information, but that enable improved analytical reproducibility, represent an ideal scenario for maximizing measureable peptide identifications in "shotgun"-type proteomic studies. Therefore, we propose an analytical workflow combining DDA with retention time aligned extracted ion chromatogram (XIC) areas obtained from high mass accuracy MS1 data acquired in parallel. We applied this workflow to the analyses of sample matrixes prepared from mouse blood plasma and brain tissues and observed increases in peptide detection of up to 30.5% due to the comparison of peptide MS1 XIC areas following retention time alignment of co-identified peptides. Furthermore, we show that the approach is quantitative using peptide standards diluted into a complex matrix. These data revealed that peptide MS1 XIC areas provide linear response of over three orders of magnitude down to low femtomole (fmol) levels. These findings argue that augmenting "shotgun" proteomic workflows with retention time alignment of peptide identifications and comparative analyses of corresponding peptide MS1 XIC areas improve the analytical performance of global proteomic discovery methods using DDA.

Progesterone enhances calcitriol antitumor activity by upregulating vitamin D receptor expression and promoting apoptosis in endometrial cancer cells

Human studies suggest that progesterone and calcitriol may prove beneficial in preventing or inhibiting oncogenesis, but the underlying mechanism is not fully understood. The current study investigates the effects of progesterone, calcitriol, and their combination on immortalized human endometrial epithelial cells and endometrial cancer cells and identifies their targets of action. Combination treatment with both agents enhanced vitamin D receptor expression and inhibited cell proliferation through caspase-3 activation and induction of G0-G1 cell-cycle arrest with associated downregulation of cyclins D1 and D3 and p27 induction. We used mass spectrometry-based proteomics to measure protein abundance differences between calcitriol-, progesterone-, or combination-exposed endometrial cells. A total of 117 proteins showed differential expression among these three treatments. Four proteins were then selected for validation studies: histone H1.4 (HIST1H1E), histidine triad nucleotide-binding protein 2 (HINT2), IFN-induced, double-stranded RNA-activated protein kinase (EIF2AK2), and Bcl-2-associated X protein (BAX). Abundance levels of selected candidates were low in endometrial cancer cell lines versus the immortalized endometrial epithelial cell line. All four proteins displayed elevated expression in cancer cells upon exposure to calcitriol, progesterone, or the combination. Further BAX analysis through gain- or loss-of-function experiments revealed that upregulation of BAX decreased cell proliferation by changing the BAX:BCL-2 ratio. Knockdown of BAX attenuated progesterone- and calcitriol-induced cell growth inhibition. Our results showed that progesterone and calcitriol upregulate the expression of BAX along with other apoptosis-related proteins, which induce inhibition of endometrial cancer cell growth by apoptosis and cell-cycle arrest.

Profiling and metaanalysis of epidermal keratinocytes responses to epidermal growth factor

BACKGROUND

One challenge of systems biology is the integration of new data into the preexisting, and then re-interpretation of the integrated data. Here we use readily available metaanalysis computational methods to integrate new data on the transcriptomic effects of EGF in primary human epidermal keratinocytes with preexisting transcriptomics data in keratinocytes and in EGF-treated non-epidermal cell types.

RESULTS

We find that EGF promotes keratinocyte proliferation, attachment and motility and, surprisingly, induces DUSPs that attenuate the EGF signal. Our metaanalysis identified overlapping effects of EGF with those of IL-1 and IFNγ, activators of keratinocyte in inflammation and wound healing. We also identified the genes and pathways suppressed by EGF but induced by agents promoting epidermal differentiation. Metaanalysis comparison with the EGF effects in other cell types identified extensive similarities between responses in keratinocytes and in other epithelial cell types, but specific differences with the EGF effects in endothelial cells, and in transformed, oncogenic epithelial cell lines.

CONCLUSIONS

This work defines the specific transcriptional effects of EGF on human epidermal keratinocytes. Our approach can serve as a suitable paradigm for integration of new omics data into preexisting databases and re-analysis of the integrated data sets.

Clinical proteomics and OMICS clues useful in translational medicine research

Since the advent of the new proteomics era more than a decade ago, large-scale studies of protein profiling have been used to identify distinctive molecular signatures in a wide array of biological systems, spanning areas of basic biological research, clinical diagnostics, and biomarker discovery directed toward therapeutic applications. Recent advances in protein separation and identification techniques have significantly improved proteomic approaches, leading to enhancement of the depth and breadth of proteome coverage.

Proteomic signatures, specific for multiple diseases, including cancer and pre-invasive lesions, are emerging. This article combines, in a simple manner, relevant proteomic and OMICS clues used in the discovery and development of diagnostic and prognostic biomarkers that are applicable to all clinical fields, thus helping to improve applications of clinical proteomic strategies for translational medicine research.

Quantitative analysis of energy metabolic pathways in MCF-7 breast cancer cells by selected reaction monitoring assay

To investigate the quantitative response of energy metabolic pathways in human MCF-7 breast cancer cells to hypoxia, glucose deprivation, and estradiol stimulation, we developed a targeted proteomics assay for accurate quantification of protein expression in glycolysis/gluconeogenesis, TCA cycle, and pentose phosphate pathways. Cell growth conditions were selected to roughly mimic the exposure of cells in the cancer tissue to the intermittent hypoxia, glucose deprivation, and hormonal stimulation. Targeted proteomics assay allowed for reproducible quantification of 76 proteins in four different growth conditions after 24 and 48 h of perturbation. Differential expression of a number of control and metabolic pathway proteins in response to the change of growth conditions was found. Elevated expression of the majority of glycolytic enzymes was observed in hypoxia. Cancer cells, as opposed to near-normal MCF-10A cells, exhibited significantly increased expression of key energy metabolic pathway enzymes (FBP1, IDH2, and G6PD) that are known to redirect cellular metabolism and increase carbon flux through the pentose phosphate pathway. Our quantitative proteomic protocol is based on a mass spectrometry-compatible acid-labile detergent and is described in detail. Optimized parameters of a multiplex selected reaction monitoring (SRM) assay for 76 proteins, 134 proteotypic peptides, and 401 transitions are included and can be downloaded and used with any SRM-compatible mass spectrometer. The presented workflow is an integrated tool for hypothesis-driven studies of mammalian cells as well as functional studies of proteins, and can greatly complement experimental methods in systems biology, metabolic engineering, and metabolic transformation of cancer cells.

Relevant phosphoproteomic and mass spectrometry: approaches useful in clinical research

Background

"It's not what we do, it's the way that we do it". Never has this maxim been truer in proteomics than now. Mass Spectrometry-based proteomics/phosphoproteomics tools are critical to understand the structure and dynamics (spatial and temporal) of signalling that engages and migrates through the entire proteome. Approaches such as affinity purification followed by Mass Spectrometry (MS) have been used to elucidate relevant biological questions disease vs. health. Thousands of proteins interact via physical and chemical association. Moreover, certain proteins can covalently modify other proteins post-translationally. These post-translational modifications (PTMs) ultimately give rise to the emergent functions of cells in sequence, space and time.

Findings

Understanding the functions of phosphorylated proteins thus requires one to study proteomes as linked-systems rather than collections of individual protein molecules. Indeed, the interacting proteome or protein-network knowledge has recently received much attention, as network-systems (signalling pathways) are effective snapshots in time, of the proteome as a whole. MS approaches are clearly essential, in spite of the difficulties of some low abundance proteins for future clinical advances.

Conclusion

Clinical proteomics-MS has come a long way in the past decade in terms of technology/platform development, protein chemistry, and together with bioinformatics and other OMICS tools to identify molecular signatures of diseases based on protein pathways and signalling cascades. Hence, there is great promise for disease diagnosis, prognosis, and prediction of therapeutic outcome on an individualized basis. However, and as a general rule, without correct study design, strategy and implementation of robust analytical methodologies, the efforts, efficiency and expectations to make biomarkers (especially phosphorylated kinases) a useful reality in the near future, can easily be hampered.

Protein-based identification of quantitative trait loci associated with malignant transformation in two HER2+ cellular models of breast cancer

BACKGROUND

A contemporary view of the cancer genome reveals extensive rearrangement compared to normal cells. Yet how these genetic alterations translate into specific proteomic changes that underpin acquiring the hallmarks of cancer remains unresolved. The objectives of this study were to quantify alterations in protein expression in two HER2+ cellular models of breast cancer and to infer differentially regulated signaling pathways in these models associated with the hallmarks of cancer.

RESULTS

A proteomic workflow was used to identify proteins in two HER2 positive tumorigenic cell lines (BT474 and SKBR3) that were differentially expressed relative to a normal human mammary epithelial cell line (184A1). A total of 64 (BT474-184A1) and 69 (SKBR3-184A1) proteins were uniquely identified that were differentially expressed by at least 1.5-fold. Pathway inference tools were used to interpret these proteins in terms of functionally enriched pathways in the tumor cell lines. We observed "protein ubiquitination" and "apoptosis signaling" pathways were both enriched in the two breast cancer models while "IGF signaling" and "cell motility" pathways were enriched in BT474 and "amino acid metabolism" were enriched in the SKBR3 cell line.

CONCLUSION

While "protein ubiquitination" and "apoptosis signaling" pathways were common to both the cell lines, the observed patterns of protein expression suggest that the evasion of apoptosis in each tumorigenic cell line occurs via different mechanisms. Evidently, apoptosis is regulated in BT474 via down regulation of Bid and in SKBR3 via up regulation of Calpain-11 as compared to 184A1.

Integrated proteomic, transcriptomic, and biological network analysis of breast carcinoma reveals molecular features of tumorigenesis and clinical relapse

Gene and protein expression changes observed with tumorigenesis are often interpreted independently of each other and out of context of biological networks. To address these limitations, this study examined several approaches to integrate transcriptomic and proteomic data with known protein-protein and signaling interactions in estrogen receptor positive (ER+) breast cancer tumors. An approach that built networks from differentially expressed proteins and identified among them networks enriched in differentially expressed genes yielded the greatest success. This method identified a set of genes and proteins linking pathways of cellular stress response, cancer metabolism, and tumor microenvironment. The proposed network underscores several biologically intriguing events not previously studied in the context of ER+ breast cancer, including the overexpression of p38 mitogen-activated protein kinase and the overexpression of poly(ADP-ribose) polymerase 1. A gene-based expression signature biomarker built from this network was significantly predictive of clinical relapse in multiple independent cohorts of ER+ breast cancer patients, even after correcting for standard clinicopathological variables. The results of this study demonstrate the utility and power of an integrated quantitative proteomic, transcriptomic, and network analysis approach to discover robust and clinically meaningful molecular changes in tumors.

Glycoprotein profiles of human breast cells demonstrate a clear clustering of normal/benign versus malignant cell lines and basal versus luminal cell lines

Gene expression profiling has defined molecular subtypes of breast cancer including those identified as luminal and basal. To determine if glycoproteins distinguish various subtypes of breast cancer, we obtained glycoprotein profiles from 14 breast cell lines. Unsupervised hierarchical cluster analysis demonstrated that the glycoprotein profiles obtained can serve as molecular signatures to classify subtypes of breast cancer, as well as to distinguish normal and benign breast cells from breast cancer cells. Statistical analyses were used to identify glycoproteins that are overexpressed in normal versus cancer breast cells, and those that are overexpressed in luminal versus basal breast cancer. Among the glycoproteins distinguishing normal breast cells from cancer cells are several proteins known to be involved in cell adhesion, including proteins previously identified as being altered in breast cancer. Basal breast cancer cell lines overexpressed a number of CD antigens, including several integrin subunits, relative to luminal breast cancer cell lines, whereas luminal breast cancer cells overexpressed carbonic anhydrase 12, clusterin, and cell adhesion molecule 1. The differential expression of glycoproteins in these breast cancer cell lines readily allows the classification of the lines into normal, benign, malignant, basal, and luminal groups.

Restraint stress and stress hormones significantly impact T lymphocyte migration and function through specific alterations of the actin cytoskeleton

Stress triggers complex response mechanisms designed to recognize and adapt to perturbations in homeostasis. The immune system is highly responsive to stress, although the complete mechanisms linking stress and immune mediators including T lymphocytes, are not fully understood. Stress exerts its effects on immune effectors through two primary pathways: the sympathetic-adrenal-medullary pathway, and the hypothalamic-pituitary-adrenal pathway which modulate adaptive immunity and lymphocyte migration. In this report we show that stress via release of stress hormones induces early T cell activation and greatly impacts the cytoskeleton by modulating numerous actin-regulating proteins. In particular, proteomic profiling revealed significant decreases in numerous key actin-binding proteins including moesin. Although confocal microscopy showed that moesin and actin were uniformly distributed on the surface of resting T cells, a remarkable polarization and redistribution of moesin and actin was observed following treatment with stress hormones with moesin localizing at the distal pole complex. In addition, the alteration in moesin localization and eventual decrease in expression were accompanied by a loss of CD43; a receptor involved in negatively regulating T cell activation. In conclusion, we have defined a novel molecular mechanism whereby stress hormones negatively impact T cell activation and migration through regulation of key cytoskeletal and plasma membrane factors.

Using proteomic approach to identify tumor-associated proteins as biomarkers in human esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers in China. The lower survival rate of ESCC is attributed to late diagnosis and poor therapeutic efficacy; therefore, the identification of tumor-associated proteins as biomarkers for early diagnosis, and the discovery of novel targets for therapeutic intervention, seems very important for increasing the survival rate of ESCC. To identify tumor-associated proteins as biomarkers in ESCC, we have analyzed ESCC tissues and adjacent normal tissues by two-dimensional electrophoresis (2DE) and matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) analysis. The results showed that a total of 104 protein spots with different expression levels were found on 2DE, and 47 proteins were eventually identified by MALDI-TOF MS. Among these identified proteins, 33 proteins including keratin 17 (KRT17), biliverdin reductase B (BLVRB), proteasome activator subunit 1 (PSME1), manganese superoxide dismutase (MnSOD), high-mobility group box-1(HMGB1), heat shock protein 70 (HSP70), peroxiredoxin (PRDX1), keratin 13 (KRT13), and so on were overexpressed, and 14 proteins including cystatin B (CSTB), tropomyosin 2 (TPM2), annexin 1 (ANX1), transgelin (TAGLN), keratin 19 (KRT19), stratifin (SFN), and so on were down-expressed in ESCC. Biological functions of these proteins are associated with cell proliferation, cell motility, protein folding, oxidative stress, and signal transduction. In the subsequent study using immunoassay on ESCC serum samples and tissue-array slides, two representative proteins, HSP70 and HMGB1, were selected as examples for the purpose of validation. The results showed that both HSP70 and HMGB1 can induce autoantibody response in ESCC sera and have higher expression in ESCC tissues. Especially, the frequency of antibodies to HSP70 in ESCC sera was significantly higher than that in normal human sera. The preliminary results suggest that some of these identified proteins might contribute to esophageal cell differentiation and carcinogenesis, certain proteins could be used as tumor-associated antigen (TAA) biomarkers in cancer diagnosis, and further studies on these identified proteins should provide more evidence of how these proteins are involved in carcinogenesis of ESCC.

The path to clinical proteomics research: integration of proteomics, genomics, clinical laboratory and regulatory science

Better biomarkers are urgently needed to cancer detection, diagnosis, and prognosis. While the genomics community is making significant advances in understanding the molecular basis of disease, proteomics will delineate the functional units of a cell, proteins and their intricate interaction network and signaling pathways for the underlying disease. Great progress has been made to characterize thousands of proteins qualitatively and quantitatively in complex biological systems by utilizing multi-dimensional sample fractionation strategies, mass spectrometry and protein microarrays. Comparative/quantitative analysis of high-quality clinical biospecimen (e.g., tissue and biofluids) of human cancer proteome landscape has the potential to reveal protein/peptide biomarkers responsible for this disease by means of their altered levels of expression, post-translational modifications as well as different forms of protein variants. Despite technological advances in proteomics, major hurdles still exist in every step of the biomarker development pipeline. The National Cancer Institute's Clinical Proteomic Technologies for Cancer initiative (NCI-CPTC) has taken a critical step to close the gap between biomarker discovery and qualification by introducing a pre-clinical "verification" stage in the pipeline, partnering with clinical laboratory organizations to develop and implement common standards, and developing regulatory science documents with the US Food and Drug Administration to educate the proteomics community on analytical evaluation requirements for multiplex assays in order to ensure the safety and effectiveness of these tests for their intended use.