Poster Presentation 25th Lorne Cancer Conference 2013

mTOR Inhibition in Biliary Tract Cancer (#409)

Yvonne Yeung 1 , John Mariadason 1 , Niall Tebbutt 1
  1. Ludwig Institute for Cancer Research, Heidelberg, Vic, Australia

Background

Biliary tract cancers (BTC) are poor prognostic malignancies with few treatment options. PIK kinase signaling pathway hyperactivation is common in malignancy but the rate in BTC is unknown. As a key signalling mediator, mTOR is an attractive target. Responses to mTOR inhibitors have been seen in other tumours with PIK pathway dysregulation. In BTC, promising in vitro data has been reported with the mTOR inhibitor Everolimus and the Phase I/II RADichol trial is being performed currently. Our study aims to evaluate a panel of BTC cell lines for sensitivity to Everolimus with correlation to mutational activation of the PI3K pathway and other biochemical readouts of activity. 

Methods

BTC lines (21) will be treated with Everolimus. Effects on cell growth at 24, 48 and 72 hours will be determined by MTS assay and cell cycle kinetics evaluated using FACS analysis. Whole exome sequencing will be performed and mutation status of PIK3Ca and other proto-oncogenes evaluated. Basal activation status of the pathway will be measured by activation status of mTOR targets p4E-BP1 and pS6K by western blot. Responsive cell lines will be cultured in the presence of growth inhibitory concentrations of Everolimus. Gene expression profiling will be performed to identify differences between resistant clones and the parental line.

Results

MTS assays in colorectal cell lines with varying PIK3Ca and KRas mutation status have shown correlation between PIK3Ca mutation and drug response. Response was not seen with co-existing KRas mutations. 10 BTC cell lines have been treated to date. This study is ongoing with further results to follow. There will be correlation with tumour and clinical results from the RADichol study.

Conclusions

Novel treatments for BTC are urgently needed and Everolimus is a promising new option. The identification of predictive biomarkers will help identify patients most likely to respond and also guide patient selection in further clinical trials.