A proteomic approach to investigate potential biomarkers directed against membrane-associated breast cancer proteins

Autoantibodies as Potential Biomarkers in Breast Cancer

Breast cancer is a major cause of mortality in women; however, technologies for early stage screening and diagnosis (e.g., mammography and other imaging technologies) are not optimal for the accurate detection of cancer. This creates demand for a more effective diagnostic means to replace or be complementary to existing technologies for early discovery of breast cancer. Cancer neoantigens could reflect tumorigenesis, but they are hardly detectable at the early stage. Autoantibodies, however, are biologically amplified and hence may be measurable early on, making them promising biomarkers to discriminate breast cancer from healthy tissue accurately. In this review, we summarized the recent findings of breast cancer specific antigens and autoantibodies, which may be useful in early detection, disease stratification, and monitoring of treatment responses of breast cancer.

Identification of potential breast cancer markers in nipple discharge by protein profile analysis using two-dimensional nano-liquid chromatography/nanoelectrospray ionization-mass spectrometry

PURPOSE

This research aimed to establish a diagnostic technique for breast cancer using nipple discharge (ND), with the objective of preventive diagnosis. ND has been proposed as a source of secreted proteomes that reflect early pathological changes in the ductal-lobular epithelial microenvironment, and could thus provide breast-specific cancer biomarkers that could be accessed noninvasively as a new clinical diagnostic technique.

EXPERIMENTAL DESIGN

Minute amounts of ND from patients with and without breast cancer (n = 19 and 12, respectively) were collected at the hospital and kept frozen until just before use. They were analyzed using high-pH RP peptide fractionations/low-pH RP 2D nano-LC/ESI-MS/MS. Biomarker candidates were also investigated using Western blot analysis and sandwich ELISA on ND and/or sera.

RESULTS

We found distinct tendencies in protein expression and three candidate breast cancer biomarkers (carbonic anhydrase 2, catalase, and peroxiredoxin-2) whose levels differed significantly between ND specimens from patients with and without breast cancer.

CONCLUSIONS AND CLINICAL RELEVANCE

These tendencies in protein expression and markers provide new ways to identify breast cancer patients. Therefore, RP/RP 2D LC/MS/MS analyses of ND and the above three markers are supported as a new breast cancer diagnostic technique.

In-depth proteomic analyses of ovarian cancer cell line exosomes reveals differential enrichment of functional categories compared to the NCI 60 proteome

Molecular communication between cancer cells and its stromal microenvironment is a key factor for cancer progression. Alongside classic secretory pathways, it has recently been proposed that small membranous vesicles are alternative mediators of intercellular communication. Exosomes carry an effector-rich proteome with the ability to modulate various functional properties of the recipient cell. In this study, exosomes isolated from four epithelial ovarian cancer cell lines (OVCAR3, OVCAR433, OVCAR5 and SKOV3) were characterized using mass spectrometry-based proteomics. Using an optimized workflow consisting of efficient exosome solubilization and the latest generation of proteomic instrumentation, we demonstrate improved detection depth. Systematic comparison of our cancer cell line exosome proteome against public data (Exocarta) and the recently published NCI 60 proteome revealed enrichment of functional categories related to signaling biology and biomarker discovery.

Immunohistochemical analysis of medullary breast carcinoma autoantigens in different histological types of breast carcinomas

BACKGROUND

On the past decade a plethora of investigations were directed on identification of molecules involved in breast tumorogenesis, which could represent a powerful tool for monitoring, diagnostics and treatment of this disease. In current study we analyzed six previously identified medullary breast carcinoma autoantigens including LGALS3BP, RAD50, FAM50A, RBPJ, PABPC4, LRRFIP1 with cancer restricted serological profile in different histological types of breast cancer.

METHODS

Semi-quantitative immunohistochemical analysis of 20 tissue samples including medullary breast carcinoma, invasive ductal carcinoma, invasive lobular carcinoma and non-cancerous tissues obtained from patients with fibrocystic disease (each of five) was performed using specifically generated polyclonal antibodies. Differences in expression patterns were evaluated considering percent of positively stained cells, insensitivity of staining and subcellular localization in cells of all tissue samples.

RESULTS

All 6 antigens predominantly expressed in the most cells of all histological types of breast tumors and non-cancerous tissues with slight differences in intensity of staining and subcellular localization. The most significant differences in expression pattern were revealed for RAD50 and LGALS3BP in different histological types of breast cancer and for PABPC4 and FAM50A antigens in immune cells infiltrating breast tumors.

CONCLUSIONS

This pilot study made possible to select 4 antigens LGALS3BP, RAD50, PABPC4, and FAM50A as promising candidates for more comprehensive research as potential molecular markers for breast cancer diagnostics and therapy.

VIRTUAL SLIDES

The virtual slides' for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1860649350796892.

Phosphoproteomics: A possible route to novel biomarkers of breast cancer

Proteomics is rapidly transforming the way that cancer and other pathologies are investigated. The ability to identify hundreds of proteins and to compare their abundance in different clinical samples presents a unique opportunity for direct identification of novel disease markers. Furthermore, recent advances allow us to analyse and compare PTMs. This gives an additional dimension for defining a new class of protein biomarker based not only on abundance and expression but also on the occurrence of covalent modifications specific to a disease state or therapy response. Such modifications are often a consequence of the activation/inactivation of a particular disease related pathway. In this review we evaluate the available information on breast cancer related protein-phosphorylation events, illustrating the rationale for investigating this PTM as a target for breast cancer research with eventual clinical relevance. We present a critical survey of the published experimental strategies to study protein phosphorylation on a system wide scale and highlight recent specific advances in breast cancer phosphoproteomics. Finally we discuss the feasibility of establishing novel biomarkers for breast cancer based on the detection of patterns of specific protein phosphorylation events.

Pressure cycling technology in systems biology

Systems biologists frequently seek to integrate complex data sets of diverse analytes into a comprehensive picture of an organism's biological state under defined environmental conditions. Although one would prefer to collect these data from the same sample, technical limitations with traditional sample preparation methods often commit the investigator to extracting one type of analyte at the expense of losing all others. Often, volume further constrains the range of experiments that can be collected from a single sample. The practical solution employed to date has been to rely on information collected from multiple replicate experiments and similar historical or reported data. While this approach has been popular, the integration of information collected from disparate single-analyte sample preparation streams increases uncertainty due to nonalignment during comparative analysis, and such gaps accumulate quickly when combining multiple data sets. Regrettably, discontinuities between separate data streams can confound a whole understanding of the biological system being investigated. This difficulty is further compounded for researchers handling highly pathogenic samples, in which it is often necessary to use harsh chemicals or high-energy sterilization procedures that damage the target analytes. Ultra-high pressure cycling technology (PCT), also known as barocycling, is an emerging sample preparation strategy that has distinct advantages for systems biology studies because it neither commits the researcher to pursuing a specific analyte nor leads to the degradation of target material. In fact, samples prepared under pressure cycling conditions have been shown to yield a more complete set of analytes due to uniform disruption of the sample matrix coupled with an advantageous high pressure solvent environment. Fortunately, PCT safely sterilizes and extracts complex or pathogenic viral, bacterial, and spore samples without adversely affecting the constituent biomolecules valued as informative and meaningful analytes. This chapter provides procedures and findings associated with incorporating PCT into systems biology as a new and enabling approach to preanalytical sample treatment.

A proteomic approach based on multiple parallel separation for the unambiguous identification of an antibody cognate antigen

Autoantibodies obtained from cancer patients have been identified as useful tools for cancer diagnostics, prognostics, and as potential targets for immunotherapy. Serological proteome analysis in combination with 2-DE is a classic strategy for identification of tumor-associated antigens in the serum of cancer patients. However, serological proteome analysis cannot always indicate the true antigen out of a complex proteome identified from a single protein spot because the most abundant protein is not always the most antigenic. To address this problem, we utilized multiple parallel separation (MPS) for proteome separation. The common identities present in the fractions obtained using different separation methods were regarded as the true antigens. The merit of our MPS technique was validated using anti-ARPC2 and anti-PTEN antibodies. Next, we applied the MPS technique for the identification of glycyl-tRNA synthetase as the cognate antigen for an autoantibody that was overexpressed in the plasma of breast cancer patients. These results reveal that MPS can unambiguously identify an antibody cognate antigen by reducing false-positives. Therefore, MPS could be used for the characterization of diagnostic antibodies raised in laboratory animals as well as autoantibodies isolated from diseased patients.

Hydrophobic protein in colorectal cancer in relation to tumor stages and grades

AIM: To identify differentially expressed hydrophobic proteins in colorectal cancer.

METHODS: Eighteen pairs of colorectal cancerous tissues in addition to tissues from normal mucosa were analysed. Hydrophobic proteins were extracted from the tissues, separated using 2-D gel electrophoresis and analysed using Liquid Chromatography Tandem Mass Spectrometry (LC/MS/MS). Statistical analysis of the proteins was carried out in order to determine the significance of each protein to colorectal cancer (CRC) and also their relation to CRC stages, grades and patients’ gender.

RESULTS: Thirteen differentially expressed proteins which were expressed abundantly in either cancerous or normal tissues were identified. A number of these proteins were found to relate strongly with a particular stage or grade of CRC. In addition, the association of these proteins with patient gender also appeared to be significant.

CONCLUSION: Stomatin-like protein 2 was found to be a promising biomarker for CRC, especially in female patients. The differentially expressed proteins identified were associated with CRC and may act as drug target candidates.

Differential protein expression analysis using stable isotope labeling and PQD linear ion trap MS technology

An isotope tags for relative and absolute quantitation (iTRAQ)-based reversed-phase liquid chromatography (RPLC)-tandem mass spectrometry (MS/MS) method was developed for differential protein expression profiling in complex cellular extracts. The estrogen positive MCF-7 cell line, cultured in the presence of 17beta-estradiol (E2) and tamoxifen (Tam), was used as a model system. MS analysis was performed with a linear trap quadrupole (LTQ) instrument operated by using pulsed Q dissociation (PQD) detection. Optimization experiments were conducted to maximize the iTRAQ labeling efficiency and the number of quantified proteins. MS data filtering criteria were chosen to result in a false positive identification rate of <4%. The reproducibility of protein identifications was approximately 60%-67% between duplicate, and approximately 50% among triplicate LC-MS/MS runs, respectively. The run-to-run reproducibility, in terms of relative standard deviations (RSD) of global mean iTRAQ ratios, was better than 10%. The quantitation accuracy improved with the number of peptides used for protein identification. From a total of 530 identified proteins (P < 0.001) in the E2/Tam treated MCF-7 cells, a list of 255 proteins (quantified by at least two peptides) was generated for differential expression analysis. A method was developed for the selection, normalization, and statistical evaluation of such datasets. An approximate approximately 2-fold change in protein expression levels was necessary for a protein to be selected as a biomarker candidate. According to this data processing strategy, approximately 16 proteins involved in biological processes such as apoptosis, RNA processing/metabolism, DNA replication/transcription/repair, cell proliferation and metastasis, were found to be up- or down-regulated.

MRM screening/biomarker discovery with linear ion trap MS: a library of human cancer-specific peptides

BACKGROUND

The discovery of novel protein biomarkers is essential in the clinical setting to enable early disease diagnosis and increase survivability rates. To facilitate differential expression analysis and biomarker discovery, a variety of tandem mass spectrometry (MS/MS)-based protein profiling techniques have been developed. For achieving sensitive detection and accurate quantitation, targeted MS screening approaches, such as multiple reaction monitoring (MRM), have been implemented.

METHODS

MCF-7 breast cancer protein cellular extracts were analyzed by 2D-strong cation exchange (SCX)/reversed phase liquid chromatography (RPLC) separations interfaced to linear ion trap MS detection. MS data were interpreted with the Sequest-based Bioworks software (Thermo Electron). In-house developed Perl-scripts were used to calculate the spectral counts and the representative fragment ions for each peptide.

RESULTS

In this work, we report on the generation of a library of 9,677 peptides (p < 0.001), representing approximately 1,572 proteins from human breast cancer cells, that can be used for MRM/MS-based biomarker screening studies. For each protein, the library provides the number and sequence of detectable peptides, the charge state, the spectral count, the molecular weight, the parameters that characterize the quality of the tandem mass spectrum (p-value, DeltaM, Xcorr, DeltaCn, Sp, no. of matching a, b, y ions in the spectrum), the retention time, and the top 10 most intense product ions that correspond to a given peptide. Only proteins identified by at least two spectral counts are listed. The experimental distribution of protein frequencies, as a function of molecular weight, closely matched the theoretical distribution of proteins in the human proteome, as provided in the SwissProt database. The amino acid sequence coverage of the identified proteins ranged from 0.04% to 98.3%. The highest-abundance proteins in the cellular extract had a molecular weight (MW)<50,000.

CONCLUSION

Preliminary experiments have demonstrated that putative biomarkers, that are not detectable by conventional data dependent MS acquisition methods in complex un-fractionated samples, can be reliable identified with the information provided in this library. Based on the spectral count, the quality of a tandem mass spectrum and the m/z values for a parent peptide and its most abundant daughter ions, MRM conditions can be selected to enable the detection of target peptides and proteins.

Cytomechanical and topological investigation of MCF-7 cells by scanning force microscopy

Despite enormous advances in breast cancer biology, there is an increased demand for new technologies/methods that are able to provide supplementary information to genomics and proteomics. Here, we exploit scanning force microscopy (SFM) in combination with confocal microscopy, to investigate the morphological and mechanical properties of two neoplastic cell lines: (i) MCF-7 (human breast cancer) and (ii) HeLa (human cervical carcinoma). Living and fixed cells either in phosphate buffer solution (PBS) or in air have been studied, and the viscoelastic properties (including the Young's modulus) of cells grown onto standard and modified (e.g. by fibronectin, one of the cellular matrix components) substrates have been measured. We observed different Young's modulus values, influenced by the adhesion and growth behaviour onto specific substrate surfaces.

Tissue culture-based breast cancer biomarker discovery platform

Current cancer biomarkers suffer from low diagnostic sensitivity and specificity and have not yet made a major impact on reducing cancer burden. Proteomic methods based on mass spectrometry have matured significantly over the past few years and hold promise to deliver candidate markers for diagnosis, prognosis or monitoring therapeutic response. Because of the complex nature of biological fluids such as plasma, biomarker discovery efforts using proteomics have not as yet delivered any novel tumor markers. Recently, there has been a rise in the number of publications utilizing a cell culture-based model of cancer to identify novel candidate tumor markers. The secretome of cancer cell lines constitutes an important class of proteins that can act locally and systemically in the body. Secreted proteins, in addition to serving as serological markers, play a central role in physiology and pathophysiology. In this review, we focus on the proteomics of breast cancer and the different strategies to mine for biomarkers, with particular emphasis on a cell culture-based model developed in our laboratory.

Comparative analysis of the protein profiles from primary gastric tumors and their adjacent regions: MAWBP could be a new protein candidate involved in gastric cancer

The study of tumor biomarkers is generally facilitated by the adoption of proteomic strategies. With limitations of techniques and individual varieties of biological samples, the biomarkers for gastric cancer (GC) have not reached a common agreement derived from the proteomic investigations. Herein, we reported a new set of data for screening the biomarkers from the gastric tissues, on the basis of the proteomic strategy developed in our laboratory. Ten pairs of the clinic samples were collected and treated with protein extraction. The gastric proteins were well-resolved by 2-DE, and the GC-associated proteins were identified by MALDI-TOF/TOF MS following image analysis, including 12 up-regulated and 13 down-regulated unique ones. MAWBP was found to be one of the new GC proteins which appeared with lower expression in the GC tissues. We expanded a systematical examination to deeply pursue the relevance between MAWBP and GC. Quantitatively, we measured the expression of MAWBP with Western blot and Real-Time PCR. Extendedly, we estimated the existence of MAWBP with immunohistochemical staining in a large number of the GC cases. Specifically, we inquired whether MAWD, a protein with high affinity to MAWBP, could coexpress and interact with MAWBP in vivo. On the basis of all the results, we concluded that MAWBP could be a new GC-related protein even though its physiological roles remain unexplored.

Cancer immunomics: from serological proteome analysis to multiple affinity protein profiling

Cancer remains one of the leading causes of death worldwide. Thus, to identify any useful biomarkers is still a need. We performed "cancer immunomics" to identify autoantibody signatures produced in response to the presence of either breast or colorectal cancer. SERological proteome analysis (SERPA) was performed by two-dimensional (2-D) electrophoresis separation, immunoblotting, image analysis, and mass spectrometry. Alternatively, to identify the antigens recognized by the autoantibodies of cancer patients, we developed an approach combining 2-D immunoaffinity chromatography, enzymatic digestion of the isolated antigens, nano flow separation of the resulting peptides, and identification: MAPPing (multiple affinity protein profiling). By these approaches we identified both proteins recognized by autoantibodies independently of a cancer status, and a limited number of proteins reacting preferentially with cancer sera.

Proteomics analysis of conditioned media from three breast cancer cell lines: a mine for biomarkers and therapeutic targets

A "bottom-up" proteomics approach and a two-dimensional (strong cation exchange followed by reversed-phase) LC-MS/MS strategy on a linear ion trap (LTQ) were utilized to identify and compare expressions of extracellular and membrane-bound proteins in the conditioned media of three breast cell lines (MCF-10A, BT474, and MDA-MB-468). Proteomics analysis of the media identified in excess of 600, 500, and 700 proteins in MCF-10A, BT474, and MDA-MB-468, respectively. We successfully identified the internal control proteins, kallikreins 5, 6, and 10 (ranging in concentration from 2 to 50 microg/liter) in MDA-MB-468 conditioned medium as validated by ELISA and confidently identified Her-2/neu in BT474 cells. Subcellular localization was determined based on Genome Ontology terms for all the 1,139 proteins of which 34% were classified as extracellular and membrane-bound. Proteomics analysis of MDA-MB-468 cell lysate demonstrated that only 5% of all identified proteins were extracellular. This confirmed our hypothesis that examining the CM of cell lines, as opposed to the cell lysates, leads to a significant enrichment in secreted proteins. Tissue specificity, functional classifications, and spectral counting were performed. Elafin, a protease inhibitor, identified in the conditioned media of BT474 and MDA-MB-468 and the three kallikreins (KLK5, KLK6, and KLK10) were validated using an immunoassay on various serum and biological samples. Some of the secreted proteins identified have established roles in breast cancer development (cell growth, differentiation, and metastasis) and/or are linked to early onset breast cancer. Our approach to mining for low abundance molecules could identify proteins in various stages of breast cancer development. Many of the identified proteins are potentially useful to investigate as circulating serum breast cancer biomarkers.

Alterations in the serum glycome due to metastatic prostate cancer

Glycomic profiles derived from human blood sera of 10 healthy males were compared to those from 24 prostate cancer patients. The profiles were acquired using MALDI-MS of permethylated N-glycans released from 10-microL sample aliquots. Quantitative permethylation was attained using solid-phase permethylation. Principal component analysis of the glycomic profiles revealed significant differences among the two sets, allowing their distinct clustering. The first principal component distinguished the 24 prostate cancer patients from the healthy individuals. It was determined that fucosylation of glycan structures is generally higher in cancer samples (ANOVA test p-value of 0.0006). Although more than 50 N-glycan structures were determined, 12 glycan structures, of which six were fucosylated, were significantly different between the two sample sets. Significant differences were confirmed through two independent statistical tests (ANOVA and ROC analyses). Ten of these structures had significantly higher relative intensities in the case of the cancer samples, while the other two were less abundant in the cancer samples. All 12 structures were statistically significant, as suggested by their very low ANOVA scores (<0.001) and ROC analysis, with area under the curve values close to 1 or 0. Accordingly, these structures can be considered as cancer-specific glycans and potential prostate cancer biomarkers. Therefore, serum glycomic profiling appears worthy of further investigation to define its role in cancer early detection and prognostication.

Cancer immunomics using autoantibody signatures for biomarker discovery

The increased incidence of autoantibodies in malignancies has been described since the 1970s. Thus the ability to determine molecular fingerprinting of autoantibodies (antibody signatures) may provide useful clinical diagnostic and prognostic information. This review describes the use of several proteomics approaches for the identification of antigens recognized by these autoantibodies. Serological proteome analysis combines separation of tumor cell proteins on two-dimensional gel electrophoresis gels, Western blotting with sera of patients and healthy subjects, and identification of the detected antigens by MS. Alternatively multiple affinity protein profiling combines isolation of the antigens recognized by patient antibodies by two-dimensional immunoaffinity chromatography and identification by MS/MS. The use and limitations of reverse phase protein microarrays for testing patient serum containing autoantibodies are also considered. Lastly the most important difficulty of any proteomically identified autoantibody signature is validation in patient cohorts or clinical samples.

Proteomic knowledge of human aquaporins

Aquaporins (AQPs) are an ubiquitous family of proteins characterized by sequence similarity and the presence of two NPA (Asp-Pro-Ala) motifs. At present, 13 human AQPs are known and they are divided into two subgroups according to their ability to transport only water molecules (AQP0, AQP1, AQP2, AQP4, AQP5, AQP6, and AQP8), or also glycerol and other small solutes (AQP3, AQP7, AQP9, AQP10, AQP12). The genomic, structural, and functional aspects of this family are briefly described. In particular, proteomic approaches to identify and characterize the most studied AQPs, mainly through SDS-PAGE followed by MS analysis, are discussed. Moreover, the clinical importance of the best studied aquaporin (AQP1) in human diseases is also provided.