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Journal of Translational Medicine BioMed Central Open Access Research Mass spectrometry-based serum proteome pattern analysis in molecular diagnostics of early stage breast cancer Monika Pietrowska†1, Lukasz Marczak†2, Joanna Polanska†3, Katarzyna Behrendt1, Elzbieta Nowicka1, Anna Walaszczyk1, Aleksandra Chmura1, Regina Deja1, Maciej Stobiecki2, Andrzej Polanski3,4, Rafal Tarnawski1 and Piotr Widlak*1 Address: 1Maria Skłodowska-Curie Memorial Cancer Center and Institute of Oncology, Gliwice, Poland, 2Polish Academy of Science, Institute of Bioorganic Chemistry, Poznan, Poland, 3Silesian University of Technology, Gliwice, Poland and 4Polish-Japanese Institute of Information Technology, Bytom, Poland Email: Monika Pietrowska - m_pietrowska@io.gliwice.pl; Lukasz Marczak - lukasmar@ibch.poznan.pl; Joanna Polanska - joanna.polanska@polsl.pl; Katarzyna Behrendt - kbehrendt@io.gliwice.pl; Elzbieta Nowicka - enowicka@io.gliwice.pl; Anna Walaszczyk - awalaszczyk@io.gliwice.pl; Aleksandra Chmura - bialka@io.gliwice.pl; Regina Deja - markery@io.gliwice.pl; Maciej Stobiecki - mackis@ibch.poznan.pl; Andrzej Polanski - andrzej.polanski@polsl.pl; Rafal Tarnawski - rafaltarnawski@gmail.com; Piotr Widlak* - widlak@io.gliwice.pl * Corresponding author †Equal contributors Published: 13 July 2009 Journal of Translational Medicine 2009, 7:60 doi:10.1186/1479-5876-7-60 Received: 21 April 2009 Accepted: 13 July 2009 This article is available from: http://www.translational-medicine.com/content/7/1/60 © 2009 Pietrowska et al; licensee BioMed Central Ltd This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited Abstract Background: Mass spectrometric analysis of the blood proteome is an emerging method of clinical proteomics The approach exploiting multi-protein/peptide sets (fingerprints) detected by mass spectrometry that reflect overall features of a specimen's proteome, termed proteome pattern analysis, have been already shown in several studies to have applicability in cancer diagnostics We aimed to identify serum proteome patterns specific for early stage breast cancer patients using MALDI-ToF mass spectrometry Methods: Blood samples were collected before the start of therapy in a group of 92 patients diagnosed at stages I and II of the disease, and in a group of age-matched healthy controls (104 women) Serum specimens were purified and the low-molecular-weight proteome fraction was examined using MALDI-ToF mass spectrometry after removal of albumin and other highmolecular-weight serum proteins Protein ions registered in a mass range between 2,000 and 10,000 Da were analyzed using a new bioinformatic tool created in our group, which included modeling spectra as a sum of Gaussian bell-shaped curves Results: We have identified features of serum proteome patterns that were significantly different between blood samples of healthy individuals and early stage breast cancer patients The classifier built of three spectral components that differentiated controls and cancer patients had 83% sensitivity and 85% specificity Spectral components (i.e., protein ions) that were the most frequent in such classifiers had approximate m/z values of 2303, 2866 and 3579 Da (a biomarker built from these three components showed 88% sensitivity and 78% specificity) Of note, we did not find a significant correlation between features of serum proteome patterns and established prognostic or predictive factors like tumor size, nodal involvement, histopathological grade, estrogen and progesterone receptor expression In addition, we observed a significantly (p = 0.0003) increased Page of 13 (page number not for citation purposes) Journal of Translational Medicine 2009, 7:60 http://www.translational-medicine.com/content/7/1/60 level of osteopontin in blood of the group of cancer patients studied (however, the plasma level of osteopontin classified cancer samples with 88% sensitivity but only 28% specificity) Conclusion: MALDI-ToF spectrometry of serum has an obvious potential to differentiate samples between early breast cancer patients and healthy controls Importantly, a classifier built on MSbased serum proteome patterns outperforms available protein biomarkers analyzed in blood by immunoassays Background In recent years cancer diagnostics has been taking enormous advantage of genomics and proteomics, novel fields of modern biology Proteomics is the study of the proteome, the complete protein components of the cell, tissue or organism, which in contrast to the genome is dynamic and fluctuates depending on a combination of numerous internal and external factors (e.g., physiological status, dietary behavior, stress, disease and medical treatment) Identifying and understanding changes in the proteome related to disease development and therapy progression is the subject of clinical/disease proteomics [1,2] It is currently well appreciated that because of the complexity of molecular processes involved in cancer no particular molecular feature alone, neither gene nor protein, could be a reliable biomarker in cancer diagnosis Instead, multi-component molecular classifiers, exemplified by multi-gene cancer signatures implemented in the functional genomics field, are built and successfully applied Multi-gene signatures identified for breast cancer have proved their diagnostic power even though detailed knowledge about the function of particular genes that build such signatures may not be available at present [3,4] The low molecular weight (