Method optimisation for peptide profiling of microdissected breast carcinoma tissue by matrix-assisted laser desorption/ionisation-time of flight and matrix-assisted laser desorption/ionisation-time of flight/time of flight-mass spectrometry

Transforming Diagnosis and Therapeutics Using Cancer Genomics

In past quarter of the century, much has been understood about the genetic variation and abnormal genes that activate cancer in humans. All the cancers somehow possess alterations in the DNA sequence of cancer cell's genome. In present, we are heading toward the era where it is possible to obtain complete genome of the cancer cells for their better diagnosis, categorization and to explore treatment options.

‘Breast Cancer Resistance Likelihood and Personalized Treatment Through Integrated Multiomics’

In recent times, enormous progress has been made in improving the diagnosis and therapeutic strategies for breast carcinoma, yet it remains the most prevalent cancer and second highest contributor to cancer-related deaths in women. Breast cancer (BC) affects one in eight females globally. In 2018 alone, 1.4 million cases were identified worldwide in postmenopausal women and 645,000 cases in premenopausal females, and this burden is constantly increasing. This shows that still a lot of efforts are required to discover therapeutic remedies for this disease. One of the major clinical complications associated with the treatment of breast carcinoma is the development of therapeutic resistance. Multidrug resistance (MDR) and consequent relapse on therapy are prevalent issues related to breast carcinoma; it is due to our incomplete understanding of the molecular mechanisms of breast carcinoma disease. Therefore, elucidating the molecular mechanisms involved in drug resistance is critical. For management of breast carcinoma, the treatment decision not only depends on the assessment of prognosis factors but also on the evaluation of pathological and clinical factors. Integrated data assessments of these multiple factors of breast carcinoma through multiomics can provide significant insight and hope for making therapeutic decisions. This omics approach is particularly helpful since it identifies the biomarkers of disease progression and treatment progress by collective characterization and quantification of pools of biological molecules within and among the cancerous cells. The scrupulous understanding of cancer and its treatment at the molecular level led to the concept of a personalized approach, which is one of the most significant advancements in modern oncology. Likewise, there are certain genetic and non-genetic tests available for BC which can help in personalized therapy. Genetically inherited risks can be screened for personal predisposition to BC, and genetic changes or variations (mutations) can also be identified to decide on the best treatment. Ultimately, further understanding of BC at the molecular level (multiomics) will define more precise choices in personalized medicine. In this review, we have summarized therapeutic resistance associated with BC and the techniques used for its management.

Proteomic characterization of microdissected breast tissue environment provides a protein-level overview of malignant transformation

Both healthy and cancerous breast tissue is heterogeneous, which is a bottleneck for proteomics‐based biomarker analysis, as it obscures the cellular origin of a measured protein. We therefore aimed at obtaining a protein‐level interpretation of malignant transformation through global proteome analysis of a variety of laser capture microdissected cells originating from benign and malignant breast tissues. We compared proteomic differences between these tissues, both from cells of epithelial origin and the stromal environment, and performed string analysis. Differences in protein abundances corresponded with several hallmarks of cancer, including loss of cell adhesion, transformation to a migratory phenotype, and enhanced energy metabolism. Furthermore, despite enriching for (tumor) epithelial cells, many changes to the extracellular matrix were detected in microdissected cells of epithelial origin. The stromal compartment was heterogeneous and richer in the number of fibroblast and immune cells in malignant sections, compared to benign tissue sections. Furthermore, stroma could be clearly divided into reactive and nonreactive based on extracellular matrix disassembly proteins. We conclude that proteomics analysis of both microdissected epithelium and stroma gives an additional layer of information and more detailed insight into malignant transformation.

Proteomic Profiling in the Brain of CLN1 Disease Model Reveals Affected Functional Modules

Neuronal ceroid lipofuscinoses (NCL) are the most commonly inherited progressive encephalopathies of childhood. Pathologically, they are characterized by endolysosomal storage with different ultrastructural features and biochemical compositions. The molecular mechanisms causing progressive neurodegeneration and common molecular pathways linking expression of different NCL genes are largely unknown. We analyzed proteome alterations in the brains of a mouse model of human infantile CLN1 disease-palmitoyl-protein thioesterase 1 (Ppt1) gene knockout and its wild-type age-matched counterpart at different stages: pre-symptomatic, symptomatic and advanced. For this purpose, we utilized a combination of laser capture microdissection-based quantitative liquid chromatography tandem mass spectrometry (MS) and matrix-assisted laser desorption/ionization time-of-flight MS imaging to quantify/visualize the changes in protein expression in disease-affected brain thalamus and cerebral cortex tissue slices, respectively. Proteomic profiling of the pre-symptomatic stage thalamus revealed alterations mostly in metabolic processes and inhibition of various neuronal functions, i.e., neuritogenesis. Down-regulation in dynamics associated with growth of plasma projections and cellular protrusions was further corroborated by findings from RNA sequencing of CLN1 patients' fibroblasts. Changes detected at the symptomatic stage included: mitochondrial functions, synaptic vesicle transport, myelin proteome and signaling cascades, such as RhoA signaling. Considerable dysregulation of processes related to mitochondrial cell death, RhoA/Huntington's disease signaling and myelin sheath breakdown were observed at the advanced stage of the disease. The identified changes in protein levels were further substantiated by bioinformatics and network approaches, immunohistochemistry on brain tissues and literature knowledge, thus identifying various functional modules affected in the CLN1 childhood encephalopathy.

Laser capture microdissection of fluorescently labeled amyloid plaques from Alzheimer's disease brain tissue for mass spectrometric analysis

Laser capture microdissection (LCM) is used to isolate minute amounts of tissue for subsequent proteomics analysis. An advantage of this technique is that a specific subset of cells or tissue structures can be isolated and enriched from surrounding material. Here, we describe a LCM-based method for the isolation of amyloid plaques from the Alzheimer's disease (AD) brain using fluorescence and nano liquid chromatography (nLC) mass spectrometry (MS) analysis. Using this approach, we detect ~600 proteins in ~250 AD amyloid plaques.

Evaluation of Rapigest Efficacy for the Digestion of Proteins from Cell Cultures and Heart Tissue

INTRODUCTION

Rapigest is an acid-labile detergent used in proteomics for the improvement of protein digestion.

MATERIALS AND METHOD

To test the efficacy of Rapigest for proteomics analysis of different sample types we used protein extracts from S9 cell line and mouse heart tissue and performed protein isolation, digestion and mass spectrometry analysis.

RESULTS

For the S9 cell line, there was no significant difference concerning the number of identifications (peptides, proteins) between Rapigest and No Rapigest samples, though slightly more peptides and proteins were identified in the Rapigest samples. For the mouse heart tissue samples, Rapigest use resulted in the identification of a higher number of proteins. Rapigest did not modify the protein profile with respect to the biological compartments covered by the identified proteins in S9 cell line samples, but produced a small increase in the representation of cytoplasm proteins and a small decrease in the representation of membrane proteins in the mouse heart tissue samples.

DISCUSSIONS

Results are comparable to other studies that evaluated the efficacy of Rapigest for the analysis of tissue samples, recommending Rapigest for the improvement of protein digestion and implicitly identification, without the modification of the protein profile in the samples.

CONCLUSION

Rapigest may be successfully used for the improvement of protein identification from heart tissue samples using mass spectrometry.

A search for novel markers of alcohol abuse using magnetic beads and MALDI-TOF/TOF mass spectrometry

Objective markers are required to assess excessive alcohol consumption, which can lead to a various medical and social problems. In this study, we carried out serum peptidome analyses using the ClinProt(™) system, which consists of magnetic beads and MALDI-TOF/TOF MS, to find novel biomarkers of alcohol abuse in 16 chronic alcoholic patients that were hospitalized for a rehabilitation program. A total of 22 peaks were found to be significantly altered during abstinence. Out of these 22 peaks, 3 peaks that had an m/z of 3000 or less and substantial peak intensities were subjected to MS/MS analysis followed by a MASCOT search. The 1466 Da and the 1616 Da peptides were upregulated on admission and were identified as fragments of fibrinopeptide A and phosphorylated fibrinopeptide A, respectively. On the other hand, the 2660 Da peptide, which was downregulated on admission and increased during abstinence, was identified as a fragment of the fibrinogen α C chain. These peaks were not detectable by the SELDI-TOF MS ProteinChip(®) system analysis. The alterations in these peaks induced by alcohol abuse were also seen in γ glutamyltransferase nonresponders. These protein fragments may be additional biomarkers for excessive alcohol drinking.

High TWIST1 mRNA expression is associated with poor prognosis in lymph node-negative and estrogen receptor-positive human breast cancer and is co-expressed with stromal as well as ECM related genes

INTRODUCTION

The TWIST homolog 1 (TWIST1) is a transcription factor that induces epithelial to mesenchymal transition (EMT), a key process in metastasis. The purpose of this study was to investigate whether TWIST1 expression predicts disease progression in a large breast cancer cohort with long-term clinical follow-up, and to reveal the biology related to TWIST1 mediated disease progression.

METHODS

TWIST1 mRNA expression level was analyzed by quantitative real-time reverse polymerase chain reaction (RT-PCR) in 1,427 primary breast cancers. In uni- and multivariate analysis using Cox regression, TWIST1 mRNA expression level was associated with metastasis-free survival (MFS), disease-free survival (DFS) and overall survival (OS). Separate analyses in lymph node-negative patients (LNN, n = 778) who did not receive adjuvant systemic therapy, before and after stratification into estrogen receptor (ER)-positive (n = 552) and ER-negative (n = 226) disease, were also performed. The association of TWIST1 mRNA with survival endpoints was assessed using Kaplan-Meier analysis. Using gene expression arrays, genes showing a significant Spearman rank correlation with TWIST1 were used to identify overrepresented Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG)-annotated biological pathways.

RESULTS

Increased mRNA expression level of TWIST1 analyzed as a continuous variable in both uni- and multivariate analysis was associated with shorter MFS in all patients (hazard ratio (HR): 1.17, 95% confidence interval, (95% CI):1.09 to 1.26; and HR: 1.17, 95% CI: 1.08 to 1.26; respectively), in LNN patients (HR: 1.22, 95% CI: 1.09 to 1.36; and HR: 1.21, 95% CI: 1.07 to 1.36; respectively) and in the ER-positive subgroup of LNN patients (HR: 1.34, 95% CI: 1.17 to 1.53; and HR: 1.32, 95% CI: 1.14 to 1.53; respectively). Similarly, high TWIST1 expression was associated with shorter DFS and OS in all patients and in the LNN/ER-positive subgroup. In contrast, no association of TWIST1 mRNA expression with MFS, DFS or OS was observed in ER-negative patients. Genes highly correlated with TWIST1 were significantly enriched for cell adhesion and ECM-related signaling pathways. Furthermore, TWIST1 mRNA was highly expressed in tumor stroma and positively related to tumor stromal content (P <0.001).

CONCLUSIONS

TWIST1 mRNA expression is an independent prognostic factor for poor prognosis in LNN/ER-positive breast cancer. The biological associations suggest an involvement of the tumor microenvironment in TWIST1's adverse role in breast cancer.

Proteomics pipeline for biomarker discovery of laser capture microdissected breast cancer tissue

Mass spectrometry (MS)-based label-free proteomics offers an unbiased approach to screen biomarkers related to disease progression and therapy-resistance of breast cancer on the global scale. However, multi-step sample preparation can introduce large variation in generated data, while inappropriate statistical methods will lead to false positive hits. All these issues have hampered the identification of reliable protein markers. A workflow, which integrates reproducible and robust sample preparation and data handling methods, is highly desirable in clinical proteomics investigations. Here we describe a label-free tissue proteomics pipeline, which encompasses laser capture microdissection (LCM) followed by nanoscale liquid chromatography and high resolution MS. This pipeline routinely identifies on average ∼10,000 peptides corresponding to ∼1,800 proteins from sub-microgram amounts of protein extracted from ∼4,000 LCM breast cancer epithelial cells. Highly reproducible abundance data were generated from different technical and biological replicates. As a proof-of-principle, comparative proteome analysis was performed on estrogen receptor α positive or negative (ER+/-) samples, and commonly known differentially expressed proteins related to ER expression in breast cancer were identified. Therefore, we show that our tissue proteomics pipeline is robust and applicable for the identification of breast cancer specific protein markers.

Proteomic studies in breast cancer (Review)

Breast cancer is one of the most common types of invasive cancer in females worldwide. Despite major advances in early cancer detection and emerging therapeutic strategies, further improvement has to be achieved for precise diagnosis to reduce the chance of metastasis and relapses. Recent proteomic technologies have offered a promising opportunity for the identification of new breast cancer biomarkers. Matrix-assisted laser desorption/ionization, time-of-flight mass spectrometry (MALDI-TOF MS) and the derived surface-enhanced laser desorption/ionization mass spectrometry (SELDI-TOF MS) enable the development of high-throughput proteome analysis based on comprehensive reliable biomarkers. In this review, we examined proteomic technologies and their applications, and provided focus on the proteomics-based profiling analyses of tumor tissues/cells in order to identify and confirm novel biomarkers of breast cancer.

A proteome comparison between physiological angiogenesis and angiogenesis in glioblastoma

The molecular pathways involved in neovascularization of regenerating tissues and tumor angiogenesis resemble each other. However, the regulatory mechanisms of neovascularization under neoplastic circumstances are unbalanced leading to abnormal protein expression patterns resulting in the formation of defective and often abortive tumor vessels. Because gliomas are among the most vascularized tumors, we compared the protein expression profiles of proliferating vessels in glioblastoma with those in tissues in which physiological angiogenesis takes place. By using a combination of laser microdissection and LTQ Orbitrap mass spectrometry comparisons of protein profiles were made. The approach yielded 29 and 12 differentially expressed proteins for glioblastoma and endometrium blood vessels, respectively. The aberrant expression of five proteins, i.e. periostin, tenascin-C, TGF-beta induced protein, integrin alpha-V, and laminin subunit beta-2 were validated by immunohistochemistry. In addition, pathway analysis of the differentially expressed proteins was performed and significant differences in the usage of angiogenic pathways were found. We conclude that there are essential differences in protein expression profiles between tumor and normal physiological angiogenesis.

Optimized nLC-MS workflow for laser capture microdissected breast cancer tissue

Reliable sample preparation is of utmost importance for comparative proteome analysis, particularly when investigating minute amounts of clinical specimens, such as laser capture microdissected tumor tissue. In this study, we present an optimized nanoLC-MS workflow specifically for the analysis of laser capture microdissected breast cancer tissue. Analytical performance of different laser capture microdissection (LCM) functions available on the PALM system, time dependent trypsin digestion efficiency, effect of sample preparation and digestion time on peptide modification, semi-tryptic peptides and missed cleavages were evaluated. Our results show that microdissection from uncoated glass slides results in protein degradation; that protease and phosphatase inhibitors do not result in detectable improvement in number of peptides or semi-tryptic peptides; and that digestion time longer than four hours drastically reduces the number of missed cleavages, but also increases the number of unexpectedly modified peptides. Overalkylation was the most dominant side-reaction, which significantly increased overnight (P=0.05). The latter effect could almost completely be reverted by the use of a quenching agent (P=0.001). Taken together, our results show that it is of importance to carefully control sample handling steps so that reliable protein identification and quantitation can be performed within comparative proteomics studies using LCM. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Biospecimen reporting for improved study quality (BRISQ)

Human biospecimens are subject to a number of different collection, processing, and storage factors that can significantly alter their molecular composition and consistency. These biospecimen preanalytical factors, in turn, influence experimental outcomes and the ability to reproduce scientific results. Currently, the extent and type of information specific to the biospecimen preanalytical conditions reported in scientific publications and regulatory submissions varies widely. To improve the quality of research utilizing human tissues, it is critical that information regarding the handling of biospecimens be reported in a thorough, accurate, and standardized manner. The Biospecimen Reporting for Improved Study Quality (BRISQ) recommendations outlined herein are intended to apply to any study in which human biospecimens are used. The purpose of reporting these details is to supply others, from researchers to regulators, with more consistent and standardized information to better evaluate, interpret, compare, and reproduce the experimental results. The BRISQ guidelines are proposed as an important and timely resource tool to strengthen communication and publications around biospecimen-related research and help reassure patient contributors and the advocacy community that the contributions are valued and respected.

Biospecimen Reporting for Improved Study Quality

Human biospecimens are subject to a number of different collection, processing, and storage factors that can significantly alter their molecular composition and consistency. These biospecimen preanalytical factors, in turn, influence experimental outcomes and the ability to reproduce scientific results. Currently, the extent and type of information specific to the biospecimen preanalytical conditions reported in scientific publications and regulatory submissions varies widely. To improve the quality of research utilizing human tissues, it is critical that information regarding the handling of biospecimens be reported in a thorough, accurate, and standardized manner. The Biospecimen Reporting for Improved Study Quality recommendations outlined herein are intended to apply to any study in which human biospecimens are used. The purpose of reporting these details is to supply others, from researchers to regulators, with more consistent and standardized information to better evaluate, interpret, compare, and reproduce the experimental results. The Biospecimen Reporting for Improved Study Quality guidelines are proposed as an important and timely resource tool to strengthen communication and publications around biospecimen-related research and help reassure patient contributors and the advocacy community that the contributions are valued and respected.

Laser capture microdissection applications in breast cancer proteomics

Breast cancer tissues are characterized by cellular heterogeneity, representing a mixture of, e.g., healthy epithelial ducts, invasive or in situ tumor cells, surrounding stroma, infiltrating immune cells, blood vessels, and capillaries. As a consequence, protein extracts from whole tissue lysates also represent a variety of cell types present in the tissues under examination. This, however, seriously hampers the analysis of tumor cell-specific signals, which is of interest when performing biomarker discovery-type of studies. Therefore, laser capture microdissection is a perfect tool to isolate a relatively pure population of cells of interest, such as tumor cells. In this chapter, we describe the use of the PALM MicroBeam system for laser microdissection and pressure catapulting. Protocols are provided for sectioning, staining, microdissection, sample preparation, and mass spectrometric analysis of snap frozen breast cancer tissue.

Clinical proteomics of breast cancer

Despite the lifetimes that increased in breast cancers due to the the early screening programs and new therapeutic strategies, many cases still are being lost due to the metastatic relapses. For this reason, new approaches such as the proteomic techniques have currently become the prime objectives of breast cancer researches. Various omic-based techniques have been applied with increasing success to the molecular characterisation of breast tumours, which have resulted in a more detailed classification scheme and have produced clinical diagnostic tests that have been applied to both the prognosis and the prediction of outcome to the treatment. Implementation of the proteomics-based techniques is also seen as crucial if we are to develop a systems biology approach in the discovery of biomarkers of the early diagnosis, prognosis and prediction of the outcome of the breast cancer therapies. In this review, we discuss the studies that have been conducted thus far, for the discovery of diagnostic, prognostic and predictive biomarkers, and evaluate the potential of the discriminating proteins identified in this research for clinical use as breast cancer biomarkers.

Accelerated tryptic digestion for the analysis of biopharmaceutical monoclonal antibodies in plasma by liquid chromatography with tandem mass spectrometric detection

Accelerated tryptic digestion of a therapeutic protein including microwave irradiation and thermal transfer by convection at 60 degrees C and 37 degrees C was investigated. An analytical setup was devised to follow the protein digestion rate using 1D gel electrophoresis and liquid chromatography coupled a triple quadrupole linear ion trap mass spectrometer. The formation kinetic of its tryptic peptides was monitored in the selected monitoring mode (LC-SRM/MS). Different digestion end points (e.g. 2, 5, 10, 15, 30 and 60min) as well as an overnight digestion were tested using a therapeutic human monoclonal antibody (mAb) with the goal of its LC-SRM/MS quantification in human plasma. The peptides from the human mAb were generated at different rates and were classified into three categories: (1) the fast forming peptides, (2) the slow forming peptides and (3) the peptides degrading over time. For many monitored peptides, a heating temperature of 37 degrees C with a 750rpm mixing applied for at least 30min provided equivalent results to microwave-assisted digestion and generally allowed the achievement of an equivalent peptide concentration as an overnight digestion carried out at 37 degrees C. The disappearance of the protein of the heavy and light chains can be monitored by 1D gel electrophoresis but was found not to be representative of the final tryptic peptide concentrations. For quantitative purposes a stable isotope labeled version ((13)C(4), (15)N(1)) of the therapeutic protein was used. The labeled protein as internal standard was found to be very efficient to compensate for incomplete digestion or losses during sample preparation.

Optimization of protein solubilization for the analysis of the CD14 human monocyte membrane proteome using LC-MS/MS

Proteomic profiling of membrane proteins is of vital importance in the search for disease biomarkers and drug development. However, the slow pace in this field has resulted mainly from the difficulty to analyze membrane proteins by mass spectrometry (MS). The objective of this investigation was to explore and optimize solubilization of membrane proteins for shotgun membrane proteomics of the CD14 human monocytes by examining different systems that rely on: i) an organic solvent (methanol) ii) an acid-labile detergent 3-[3-(1,1-bisalkyloxyethyl)pyridin-1-yl]propane-1-sulfonate (PPS), iii) a combination of both agents (methanol+PPS). Solubilization efficiency of different buffers was first compared using bacteriorhodopsin as a model membrane protein. Selected approaches were then applied on a membrane subproteome isolated from a highly enriched human monocyte population that was approximately 98% positive for CD14 expression as determined by FACS analysis. A methanol-based buffer yielded 194 proteins of which 93 (48%) were mapped as integral membrane proteins. The combination of methanol and acid-cleavable detergent gave similar results; 203 identified proteins of which 93 (46%) were mapped integral membrane proteins. However, employing PPS 216 proteins were identified of which 75 (35%) were mapped as integral membrane proteins. These results indicate that methanol alone or in combination with PPS yielded significantly higher membrane protein identification/enrichment than the PPS alone.

An in-solution ultrasonication-assisted digestion method for improved extracellular matrix proteome coverage

Epithelial cell behavior is coordinated by the composition of the surrounding extracellular matrix (ECM); thus ECM protein identification is critical for understanding normal biology and disease states. Proteomic analyses of ECM proteins have been hindered by the insoluble and digestion-resistant nature of ECM. Here we explore the utility of combining rapid ultrasonication- and surfactant-assisted digestion for the detailed proteomics analysis of ECM samples. When compared with traditional overnight digestion, this optimized method dramatically improved the sequence coverage for collagen I, revealed the presence of hundreds of previously unidentified proteins in Matrigel, and identified a protein profile for ECM isolated from rat mammary glands that was substantially different from that found in Matrigel. In a three-dimensional culture assay to investigate epithelial cell-ECM interactions, mammary epithelial cells were found to undergo extensive branching morphogenesis when plated with mammary gland-derived matrix in comparison with Matrigel. Cumulatively these data highlight the tissue-specific nature of ECM composition and function and underscore the need for optimized techniques, such as those described here, for the proteomics characterization of ECM samples.

Identification of a putative protein profile associated with tamoxifen therapy resistance in breast cancer

Tamoxifen resistance is a major cause of death in patients with recurrent breast cancer. Current clinical factors can correctly predict therapy response in only half of the treated patients. Identification of proteins that are associated with tamoxifen resistance is a first step toward better response prediction and tailored treatment of patients. In the present study we intended to identify putative protein biomarkers indicative of tamoxifen therapy resistance in breast cancer using nano-LC coupled with FTICR MS. Comparative proteome analysis was performed on ∼5,500 pooled tumor cells (corresponding to ∼550 ng of protein lysate/analysis) obtained through laser capture microdissection (LCM) from two independently processed data sets (n = 24 and n = 27) containing both tamoxifen therapy-sensitive and therapy-resistant tumors. Peptides and proteins were identified by matching mass and elution time of newly acquired LC-MS features to information in previously generated accurate mass and time tag reference databases. A total of 17,263 unique peptides were identified that corresponded to 2,556 non-redundant proteins identified with ≥2 peptides. 1,713 overlapping proteins between the two data sets were used for further analysis. Comparative proteome analysis revealed 100 putatively differentially abundant proteins between tamoxifen-sensitive and tamoxifen-resistant tumors. The presence and relative abundance for 47 differentially abundant proteins were verified by targeted nano-LC-MS/MS in a selection of unpooled, non-microdissected discovery set tumor tissue extracts. ENPP1, EIF3E, and GNB4 were significantly associated with progression-free survival upon tamoxifen treatment for recurrent disease. Differential abundance of our top discriminating protein, extracellular matrix metalloproteinase inducer, was validated by tissue microarray in an independent patient cohort (n = 156). Extracellular matrix metalloproteinase inducer levels were higher in therapy-resistant tumors and significantly associated with an earlier tumor progression following first line tamoxifen treatment (hazard ratio, 1.87; 95% confidence interval, 1.25–2.80; p = 0.002). In summary, comparative proteomics performed on laser capture microdissection-derived breast tumor cells using nano-LC-FTICR MS technology revealed a set of putative biomarkers associated with tamoxifen therapy resistance in recurrent breast cancer.

Clinical proteomics in breast cancer: a review

Breast cancer imposes a significant healthcare burden on women worldwide. Early detection is of paramount importance in reducing mortality, yet the diagnosis of breast cancer is hampered by the lack of an adequate detection method. In addition, better breast cancer prognostication may improve selection of patients eligible for adjuvant therapy. Hence, new markers for early diagnosis, accurate prognosis and prediction of response to treatment are warranted to improve breast cancer care. Since proteomics can bridge the gap between the genetic alterations underlying cancer and cellular physiology, much is expected from proteome analyses for the detection of better protein biomarkers. Recent technical advances in mass spectrometry, such as matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) and its variant surface-enhanced laser desorption/ionisation (SELDI-) TOF MS, have enabled high-throughput proteome analysis. In the current review, we give a comprehensive overview of the results of expression proteomics (i.e. protein profiling) research performed in breast cancer using these two platforms. Many protein peaks have been reported to bear significant diagnostic, prognostic or predictive value, however, only few candidate markers have been structurally identified yet. In addition, although of pivotal importance in preventing overfitting of data and systematic bias by pre-analytical parameters, validation of biomarker candidates by other, quantitative, methods and/or in new populations is very limited. Moreover, none of the identified candidate biomarkers has been investigated for their utility as breast cancer markers in large, prospective, clinical settings. As such, the candidate biomarkers discussed in this overview have not been validated sufficiently to be used for clinical patient care. Nonetheless, regarding the promising results up to now, MALDI- and SELDI-TOF MS protein profiling studies could eventually fulfil the great promise that protein biomarkers have for improving cancer patient outcome, provided that these studies are performed with adequate statistical power and analytical rigour.

Proteomic approach to breast cancer

BACKGROUND

Breast cancer is the most common cancer affecting women worldwide. Despite tremendous advances in screening, diagnosis, and treatment, the causes of this disease remain elusive and complex. Proteomics is a rapidly developing field that can explore the heterogeneity of breast cancer and supplement the wealth of information gained from genomics.

METHODS

This article serves as an overview of the application of matrix-assisted laser desorption/ionization source with a time-of-flight (MALDI-TOF) proteomic techniques as applied to breast cancer. Examples of the clinical applicability of MALDI-TOF mass spectrometry are provided but represent only a fraction of the potential uses yet to be discovered. In addition, a brief summary of the bioinformatics issues that surround proteomics is included.

RESULTS

Mass spectrometry has provided new proteomic approaches to unravel the complexities of clinical specimens relevant to breast cancer diagnostics. In particular, MALDI-TOF mass spectrometry analysis has been used to differentiate cancer profiles from benign profiles in samples from sera, plasma, tissue, nipple fluid, and ductal lavage. Some discriminating proteins have subsequently been identified.

CONCLUSIONS

Mass spectrometry applications to breast cancer diagnostics continue to be developed but are evolving faster than bioinformatics/statistical analysis can adapt. The future of these techniques in terms of clinical investigation is limitless, but in terms of general applicability, these applications are currently cost-prohibitive.

Breast tumor metastasis: analysis via proteomic profiling

The ability to predict the metastatic behavior of a patient's cancer, as well as to detect and eradicate such recurrences, remain major clinical challenges in oncology. While many potential molecular biomarkers have been identified and tested previously, none have greatly improved the accuracy of specimen evaluation over routine histopathological criteria and, to date, they predict individual outcomes poorly. The ongoing development of high-throughput proteomic profiling technologies is opening new avenues for the investigation of cancer and, through application in tissue-based studies and animal models, will facilitate the identification of molecular signatures that are associated with breast tumor cell phenotype. The appropriate use of these approaches has the potential to provide efficient biomarkers, and to improve our knowledge of tumor biology. This, in turn, will enable the development of targeted therapeutics aimed at ameliorating the lethal dissemination of breast cancer. In this review, we focus on the accumulating proteomic signatures of breast tumor progression, particularly those that correlate with the occurrence of distant metastases, and discuss some of the expected future developments in the field.

Clinical proteomics and breast cancer: strategies for diagnostic and therapeutic biomarker discovery

A major challenge of breast cancer research is the identification of accurate biomarkers that improve screening, early diagnosis, prediction of aggressiveness, and prediction of therapeutic response or toxicity, as well as the identification of new molecular therapeutic targets. The new proteomic techniques promise to be valuable for identifying such tissue and serum markers. The different techniques currently applied to clinical samples of breast cancer and the most important results obtained are summarized in this review.

Combining laser capture microdissection and proteomics techniques

Laser microdissection is an effective technique to harvest pure cell populations from complex tissue sections. In addition to using the microdissected cells in several DNA and RNA studies, it has been shown that the small number of cells obtained by this technique can also be used for proteomics analysis. Combining laser capture microdissection and different types of mass spectrometers opened ways to find and identify proteins that are specific for various cell types, tissues, and their morbid alterations. Although the combination of microdissection followed by the currently available techniques of proteomics has not yet reached the stage of genome wide representation of all proteins present in a tissue, it is a feasible way to find significant differentially expressed proteins in target tissues. Recent developments in mass spectrometric detection followed by proper statistics and bioinformatics enable to analyze the proteome of not more than 100-200 cells. Obviously, validation of result is essential. The present review describes and discusses the various methods developed to target cell populations of interest by laser microdissection, followed by analysis of their proteome.

Microwave-assisted proteomics

State-of-the-art proteomic analysis has recently undergone a rapid evolution; with more high-throughput analytical instrumentation and informatic tools available, sample preparation is becoming one of the rate-limiting steps in protein characterization workflows. Recently several protocols have appeared in the literature that employ microwave irradiation as a tool for the preparation of biological samples for subsequent mass spectrometric characterization. Techniques for microwave-assisted bio-catalyzed reactions (including sample reduction and alkylation, enzymatic and chemical digestion, removal and analysis of post-translational modifications and characterization of enzymes and protein-interaction sites) are described. This review summarizes the various approaches undertaken, instrumentation employed, and reduction in overall experimental time observed when microwave assistance is applied.

Identification of Glioma Neovascularization-related Proteins by Using MALDI-FTMS and Nano-LC Fractionation to Microdissected Tumor Vessels

The identification of angiogenesis-related proteins is important for the development of new antiangiogenic therapies, and such proteins are potential new biomarkers for gliomas. The aim of this study was to identify proteins that are exclusively present in glioma neovasculature and not in the vasculature of normal brain. We combined advanced proteomics techniques to compare the expression profiles of microdissected blood vessels from glioma with blood vessels of normal control brain samples. We measured the enzymatic generated peptide profiles from these microdissected samples by MALDI-FTMS. Subsequently, the samples were fractionated by nano-LC prior to MALDI-TOF/TOF. This combined approach enabled us to identify four proteins that appeared to be exclusively expressed in the glioma blood vessels. Two of these proteins, fibronectin and colligin 2, were validated on tissue sections using specific antibodies. We found that both proteins are present in active angiogenesis in glioma, other neoplasms, and reactive conditions in which neoangiogenesis takes place. This work proves that gel-free mass spectrometric techniques can be used on relatively small numbers of cells generated by microdissection procedures to successfully identify differentially expressed proteins.

NanoLC-FT-ICR MS improves proteome coverage attainable for ∼3000 laser-microdissected breast carcinoma cells

Proteomics assays hold great promise for unraveling molecular events that underlie human diseases. Effective analysis of clinical samples is essential, but this task is considerably complicated by tissue heterogeneity. Laser capture microdissection (LCM) can be used to selectively isolate target cells from their native tissue environment. However, the small number of cells that is typically procured by LCM severely limits proteome coverage and biomarker discovery potential achievable by conventional proteomics platforms. Herein, we describe the use of nanoLC-FT-ICR MS for analyzing protein digests of 3000 LCM-derived tumor cells from breast carcinoma tissue, corresponding to 300 ng of total protein. A total of 2282 peptides were identified by matching LC-MS data to accurate mass and time (AMT) tag databases that were previously established for human breast (cancer) cell lines. One thousand and three unique proteins were confidently identified with two or more peptides. Based on gene ontology categorization, identified proteins appear to cover a wide variety of biological functions and cellular compartments. This work demonstrates that a substantial number of proteins can be detected and identified from limited number of cells using the AMT tag approach, and opens doors for high-throughput in-depth proteomics analysis of clinical samples.

Piezoelectric ink jet processing of materials for medicaland biological applications

Many advanced medical and biological devices require microscale patterning of cells, proteins, and other biological materials. This article describes the use of piezoelectric ink jet processing in the fabrication of biosensors, cell-based assays, and other microscale medical devices. A microelectromechanical system-based piezoelectric transducer was used to develop uniform fluid flow through nozzles and to prepare well-defined microscale patterns of proteins, monofunctional acrylate ester, sinapinic acid, deoxyribonucleic acid (DNA), and DNA scaffolds on relevant substrates. Our results demonstrate that piezoelectric ink jet deposition is a powerful non-contact, non-destructive additive process for developing biosensors, cell culture systems, and other devices for medical and biological applications.