Prediction of individual response to platinum/paclitaxel combination using novel marker genes in ovarian cancers.

We attempted to identify potent marker genes using a new statistical analysis and developed a prediction system for individual response to platinum/paclitaxel combination chemotherapy in ovarian cancer patients based on the hypothesis that expression analysis of a set of the key drug sensitivity genes for platinum and paclitaxel could allow us to predict therapeutic response to the combination. From 10 human ovarian cancer cell lines, genes correlative in the expression levels with cytotoxicities of cisplatin (CDDP) and paclitaxel were chosen. We first selected five reliable prediction markers for the two drugs from 22 genes already known as sensitivity determinants and then identified another 8 novel genes through a two-dimensional mixed normal model using oligomicroarray expression data. Using expression data of genes quantified by real-time reverse transcription-PCR, we fixed the best linear model, which converted the quantified expression data into an IC(50) of each drug. Multiple regression analysis of the selected genes yielded three prediction formulae for in vitro activity of CDDP and paclitaxel. In the same way, using the same genes selected in vitro, we then attempted to develop prediction formulae for progression-free survival to the platinum/paclitaxel combination. We therefore constructed possible formulae using different sets of 13 selected marker genes (5 known and 8 novel genes): Utility confirmation analyses using another nine test samples seemed to show that the formulae using a set of 8 novel marker genes alone could accurately predict progression-free survival (r = 0.683; P = 0.042).