Mass Spectrometry (LC-MS/MS) Identified Proteomic Biosignatures of Breast Cancer in Proximal Fluid

Department of Biochemistry, School of Medicine, Boston University , Boston, Massachusetts.
Journal of Proteome Research (Impact Factor: 4.25). 08/2012; 11(10):5034-45. DOI: 10.1021/pr300606e
Source: PubMed


We have begun an early phase of biomarker discovery in three clinically important types of breast cancer using a panel of human cell lines: HER2 positive, hormone receptor positive and HER2 negative, and triple negative (HER2-, ER-, PR-). We identified and characterized the most abundant secreted, sloughed, or leaked proteins released into serum free media from these breast cancer cell lines using a combination of protein fractionation methods before LC-MS/MS mass spectrometry analysis. A total of 249 proteins were detected in the proximal fluid of 7 breast cancer cell lines. The expression of a selected group of high abundance and/or breast cancer-specific potential biomarkers including thromobospondin 1, galectin-3 binding protein, cathepsin D, vimentin, zinc-α2-glycoprotein, CD44, and EGFR from the breast cancer cell lines and in their culture media were further validated by Western blot analysis. Interestingly, mass spectrometry identified a cathepsin D protein single-nucleotide polymorphism (SNP) by alanine to valine replacement from the MCF-7 breast cancer cell line. Comparison of each cell line media proteome displayed unique and consistent biosignatures regardless of the individual group classifications, demonstrating the potential for stratification of breast cancer. On the basis of the cell line media proteome, predictive Tree software was able to categorize each cell line as HER2 positive, HER2 negative, and hormone receptor positive and triple negative based on only two proteins, muscle fructose 1,6-bisphosphate aldolase and keratin 19. In addition, the predictive Tree software clearly identified MCF-7 cell line overexpresing the HER2 receptor with the SNP cathepsin D biomarker.

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Available from: Stephen A Whelan, Mar 05, 2015
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    • "In particular, liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) provides relatively high-quality data with sufficient protein coverage and sensitivity for protein biomarker discovery studies [21] [22] [23] [24] [25] [26] [27] [28] [29] [30]. Toward increased throughput, global protein profiling using label-free LC-MS/MS has received increased interest due to its potential to enable relatively straightforward and comprehensive discovery of quantitative biomarkers in large numbers of clinical samples. "
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    ABSTRACT: The increasing coverage and sensitivity of LC-MS/MS-based proteomics have expanded its applications in systems medicine. In particular, label-free quantitation approaches are enabling biomarker discovery in terms of statistical comparison of proteomic profiles across large numbers of clinical samples. However, it still remains poorly understood how much protein markers can add novel insights compared to markers derived from mRNA transcriptomic profiling. Using paired label-free LC-MS/MS and gene expression microarray measurements from primary samples of patients with acute myeloid leukemia (AML), we demonstrate here that while the quantitative proteomic and transcriptomic profiles were highly correlated, in general, the marker panels showing statistically significant expression changes across the disease and healthy groups were profoundly different between protein and mRNA levels. In particular, the proteomic assay enabled unique links to known leukemic processes, which were missed when using the transcriptomic profiling alone, as well as identified additional links to metabolic regulators and chromatin remodelers, such as GPX1, fumarate hydratase and SET oncogene, which have subsequently been evaluated in independent AML samples. Overall, these results highlighted the complementary and informative view obtained from the quantitative LC-MS/MS approach into the AML de-regulated signaling networks. This article is protected by copyright. All rights reserved.
    Proteomics 11/2014; 14(21-22). DOI:10.1002/pmic.201300460 · 3.81 Impact Factor
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    • "It was used to compare cancerous with non-cancerous tissues and retinoic acid-induced protein 3 was determined over-expressed [77]. In another study, proteomic signatures of cell media from breast cancer cell lines representing different cancer subtypes were assessed [78]. Labelfree approach in combination with a novel algorithm for quantitation was also employed to distinguish classes of leukemias [79]. "
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    ABSTRACT: Biomarkers are indicators of a specific biological state. Their detection in pathological conditions, such as cancer, is important for clinical disease management. One of their greatest values could be in early diagnosis and detection of neoplasms when the cancer is more manageable. Protein biomarkers are expected to be reliable predictors of pathological conditions, as they represent the endpoint of biological processes. The proteomic methodology has rapidly evolved in the past ten years, thus enabling discovery of a vast amount of potential biomarker candidates. However, the majority of novel candidates have not yet reached the integration into clinical environment. To do that, well constructed large population validation studies are necessary as well as development of new algorithms for deciphering complex biological interactions and their involvement in pathological processes. This review focuses on advances in classical proteomic approaches and emerging high-throughput proteomic technologies for identifying cancer biomarkers.
    New Biotechnology 11/2012; 30(3):319-326. DOI:10.1016/j.nbt.2012.11.011 · 2.90 Impact Factor
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    ABSTRACT: Despite major improvements on the knowledge and clinical management, cancer is still a deadly disease. Novel biomarkers for better cancer detection, diagnosis and treatment prediction are urgently needed. Proteins secreted, shed or leaking from the cancer cell, collectively termed the cancer secretome, are promising biomarkers since they might be detectable in blood or other biofluids. Furthermore, the cancer secretome in part represents the tumor microenvironment that plays a key role in tumor promoting processes such as angiogenesis and invasion. The cancer secretome, sampled as conditioned medium from cell lines, tumor/tissue interstitial fluid or tumor proximal body fluids, can be studied comprehensively by nanoLC-MS/MS-based approaches. Here, we outline the importance of current cancer secretome research and describe the mass spectrometry-based analysis of the secretome. Further, we provide an overview of cancer secretome research with a focus on the three most common cancer types: lung, breast and colorectal cancer. We conclude that the cancer secretome research field is a young, but rapidly evolving research field. Up to now, the focus has mainly been on the discovery of novel promising secreted cancer biomarker proteins. An interesting finding that merits attention is that in cancer unconventional secretion, e.g. via vesicles, seems increased. Refinement of current approaches and methods and progress in clinical validation of the current findings are vital in order to move towards applications in cancer management. This article is part of a Special Issue entitled: An Updated Secretome.
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