Article

Classification of HER2/neu status in gastric cancer using a breast-cancer derived proteome classifier.

Department of Medicine II, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
Journal of Proteome Research (Impact Factor: 5.06). 11/2010; 9(12):6317-22. DOI: 10.1021/pr100573s
Source: PubMed

ABSTRACT HER2-testing in breast and gastric cancers is mandatory for the treatment with trastuzumab. We hypothesized that imaging mass spectrometry (IMS) of breast cancers may be useful for generating a classifier that may determine HER2-status in other cancer entities irrespective of primary tumor site. A total of 107 breast (n = 48) and gastric (n = 59) cryo tissue samples was analyzed by IMS (HER2 was present in 29 cases). The obtained proteomic profiles were used to create HER2 prediction models using different classification algorithms. A breast cancer proteome derived classifier, with HER2 present in 15 cases, correctly predicted HER2-status in gastric cancers with a sensitivity of 65% and a specificity of 92%. To create a universal classifier for HER2-status, breast and nonbreast cancer samples were combined, which increased sensitivity to 78%, and specificity was 88%. Our proof of principle study provides evidence that HER2-status can be identified on a proteomic level across different cancer types suggesting that HER2 overexpression may constitute a unique molecular event independent of the tumor site. Furthermore, these results indicate that IMS may be useful for the determination of potential drugable targets, as it offers a quicker, cheaper, and more objective analysis than the standard HER2-testing procedures immunohistochemistry and fluorescence in situ hybridization.

0 Bookmarks
 · 
85 Views
  • [Show abstract] [Hide abstract]
    ABSTRACT: Matrix assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a method that allows the investigation of the molecular content of tissues within its morphological context. Since it is able to measure the distribution of hundreds of analytes at once, while being label free, this method has great potential which has been increasingly recognized in the field of tissue-based research. In the last few years, MALDI-IMS has been successfully used for the molecular assessment of tissue samples mainly in biomedical research and also in other scientific fields. The present article will give an update on the application of MALDI-IMS in clinical and preclinical research. It will also give an overview of the multitude of technical advancements of this method in recent years. This includes developments in instrumentation, sample preparation, computational data analysis and protein identification. It will also highlight a number of emerging fields for application of MALDI-IMS like drug imaging where MALDI-IMS is used for studying the spatial distribution of drugs in tissues.
    Histochemie 09/2011; 136(3):227-44. · 2.61 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Mass spectrometry (MS) imaging links molecular information and the spatial distribution of analytes within a sample. In contrast to most histochemical techniques, mass spectrometry imaging can differentiate molecular modifications and does not require labeling of targeted compounds. We have recently introduced the first mass spectrometry imaging method that provides highly specific molecular information (high resolution and accuracy in mass) at cellular dimensions (high resolution in space). This method is based on a matrix-assisted laser desorption/ionization (MALDI) imaging source working at atmospheric pressure which is coupled to an orbital trapping mass spectrometer. Here, we present a number of application examples and demonstrate the benefit of 'mass spectrometry imaging with high resolution in mass and space.' Phospholipids, peptides and drug compounds were imaged in a number of tissue samples at a spatial resolution of 5-10 μm. Proteins were analyzed after on-tissue tryptic digestion at 50-μm resolution. Additional applications include the analysis of single cells and of human lung carcinoma tissue as well as the first MALDI imaging measurement of tissue at 3 μm pixel size. MS image analysis for all these experiments showed excellent correlation with histological staining evaluation. The high mass resolution (R = 30,000) and mass accuracy (typically 1 ppm) proved to be essential for specific image generation and reliable identification of analytes in tissue samples. The ability to combine the required high-quality mass analysis with spatial resolution in the range of single cells is a unique feature of our method. With that, it has the potential to supplement classical histochemical protocols and to provide new insights about molecular processes on the cellular level.
    Histochemie 05/2013; · 2.61 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Diagnosis of the origin of metastasis is mandatory for adequate therapy. In the past, classification of tumors was based on histology (morphological expression of a complex protein pattern), while supportive immunohistochemical investigation relied only on few "tumor-specific" proteins. At present, histopathological diagnosis is based on clinical information, morphology, immunohistochemistry, and may include molecular methods. This process is complex, expensive, requires an experienced pathologist and may be time consuming. Currently, proteomic methods have been introduced in various clinical disciplines. MALDI IMS combines detection of numerous proteins with morphological features, and seems to be the ideal tool for objective and fast histopathological tumor classification. To study a special tumor type and to identify predictive patterns that could discriminate metastatic breast from pancreatic carcinoma MALDI IMS was applied to multi-tissue paraffin blocks. A statistical classification model was created using a training set of primary carcinoma biopsies. This model was validated on two testing sets of different breast and pancreatic carcinoma specimens. We could discern breast from pancreatic primary tumors with an overall accuracy of 83.38 %, a sensitivity of 85.95 % and a specificity of 76.96 %. Furthermore, breast and pancreatic liver metastases were tested and classified correctly. This article is protected by copyright. All rights reserved.
    Proteomics 01/2014; · 4.43 Impact Factor