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

Benjamin Balluff, Mareike Elsner, Andreas Kowarsch, Sandra Rauser, Stephan Meding, Christoph Schuhmacher, Marcus Feith, Ken Herrmann, Christoph Röcken, Roland M. Schmid, Heinz Höfler, Axel Walch, Matthias P. Ebert

Research output: Contribution to journalArticlepeer-review

65 Scopus citations


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.

Original languageEnglish
Pages (from-to)6317-6322
Number of pages6
JournalJournal of Proteome Research
Issue number12
StatePublished - 3 Dec 2010


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