title: Common peak approach using mass spectrometry data sets for predicting the effects of anticancer drugs on breast cancer.
abstract: We propose a method for biomarker discovery from mass spectrometry data, improving the common peak approach developed by Fushiki et al. (BMC Bioinformatics, 7:358, 2006). The common peak method is a simple way to select the sensible peaks that are shared with many subjects among all detected peaks by combining a standard spectrum alignment and kernel density estimates. The key idea of our proposed method is to apply the common peak approach to each class label separately. Hence, the proposed method gains more informative peaks for predicting class labels, while minor peaks associated with specific subjects are deleted correctly. We used a SELDI-TOF MS data set from laser microdissected cancer tissues for predicting the treatment effects of neoadjuvant therapy using an anticancer drug on breast cancer patients. The AdaBoost algorithm is adopted for pattern recognition, based on the set of candidate peaks selected by the proposed method. The analysis gives good performance in the sense of test errors for classifying the class labels for a given feature vector of selected peak values.
authors.affiliation: Genome Center, Japanese Foundation for Cancer Research, Tokyo, Japan. masaru.ushijima@jfcr.or.jp
authors.forename: Masaru
authors.initials: M
authors.lastname: Ushijima
authors.forename: Satoshi
authors.initials: S
authors.lastname: Miyata
authors.forename: Shinto
authors.initials: S
authors.lastname: Eguchi
authors.forename: Masanori
authors.initials: M
authors.lastname: Kawakita
authors.forename: Masataka
authors.initials: M
authors.lastname: Yoshimoto
authors.forename: Takuji
authors.initials: T
authors.lastname: Iwase
authors.forename: Futoshi
authors.initials: F
authors.lastname: Akiyama
authors.forename: Goi
authors.initials: G
authors.lastname: Sakamoto
authors.forename: Koichi
authors.initials: K
authors.lastname: Nagasaki
authors.forename: Yoshio
authors.initials: Y
authors.lastname: Miki
authors.forename: Tetsuo
authors.initials: T
authors.lastname: Noda
authors.forename: Yutaka
authors.initials: Y
authors.lastname: Hoshikawa
authors.forename: Masaaki
authors.initials: M
authors.lastname: Matsuura