Classification of HER2/neu status in gastric cancer using a breast-cancer derived proteome classifier.
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.
Article: New Analysis Workflow for MALDI Imaging Mass Spectrometry: Application to the Discovery and Identification of Potential Markers of Childhood Absence Epilepsy.[show abstract] [hide abstract]
ABSTRACT: Childhood absence epilepsy is a prototypic form of generalized nonconvulsive epilepsy characterized by short impairments of consciousness concomitant with synchronous and bilateral spike-and-wave discharges in the electroencephalogram. For scientists in this field, the BS/Orl and BR/Orl mouse lines, derived from a genetic selection, constitute an original mouse model "in mirror" of absence epilepsy. The potential of MALDI imaging mass spectrometry (IMS) for the discovery of potential biomarkers is increasingly recognized. Interestingly, statistical analysis tools specifically adapted to IMS data sets and methods for the identification of detected proteins play an essential role. In this study, a new cross-classification comparative design using a combined discrete wavelet transformation-support vector machine classification was developed to discriminate spectra of brain sections of BS/Orl and BR/Orl mice. Nineteen m/z ratios were thus highlighted as potential markers with very high recognition rates (87-99%). Seven of these potential markers were identified using a top-down approach, in particular a fragment of Synapsin-I. This protein is yet suspected to be involved in epilepsy. Immunohistochemistry and Western Blot experiments confirmed the differential expression of Synapsin-I observed by IMS, thus tending to validate our approach. Functional assays are being performed to confirm the involvement of Synapsin-I in the mechanisms underlying childhood absence epilepsy.Journal of Proteome Research 09/2012; · 5.11 Impact Factor