Abstract C119: Identification of gene expression biomarkers that predict sensitivity to the PARP inhibitor olaparib
Authors: Lau Alan , Dry Jonathan , Harbron Chris , Knights Charlotte , Riches Lucy , Mangena Ramu , Avis Tim , Brown Helen , Runswick Sarah , Dearden Simon , O'Shaughnessy Aisling , Unwin Louise , Prime John E. , Hodgson Darren , Carmichael James , O'Connor Mark J. 
Published: June 2012

Abstract
Background: The oral PARP inhibitor olaparib (AZD2281, KU-0059436) is in Phase II clinical trials in patients with BRCA-mutated breast and ovarian cancer. Early results in these trials have provided positive clinical evidence for the targeted therapy concept of synthetic lethality using PARP inhibitors in molecularly-defined tumors with little effect on normal tissues. However, olaparib offers the potential to treat a broader range of patient tumors and pre-clinical studies have indicated that homologous recombination deficiency (HRD) due to loss of other DNA repair genes or through impaired cell-cycle checkpoints can also lead to sensitivity to PARP inhibitors. The ability to stratify patients whose tumors will respond to treatment will be critical to realise the potential of this targeted therapy approach. In order to identify predictive biomarkers of olaparib response and to provide further insights into mechanisms of olaparib sensitivity a study was undertaken using a panel of cell lines correlating response with molecular profiles.
Methods: A cross tumor-type panel of 95 cell lines (KU-95 panel) representing breast, ovarian, colorectal, lung, head & neck and pancreatic cancers was tested for sensitivity to olaparib using 2D-clonogenic survival assays. Baseline (untreated) gene expression profiles using Affymetrix genome-wide U133A 2.0 arrays together with protein expression and mutational status of genes, such as BRCA1, known to modify of olaparib response were determined for each cell line. Novel statistical, bioinformatics and pathway analysis approaches were used to identify genes that are predictive for olaparib response.
Results: Across the KU-95 cell-line panel, 30 cell lines were highly sensitive to olaparib (IC50 &lt;1 M) treatment and 36 were resistant (IC50 &gt;4 M). Deleterious mutations in BRCA1 or BRCA2 genes were associated with only a small subset of highly sensitive cell lines indicating the presence of other factors able to modulate olaparib responsiveness. Directed analysis of several other DNA repair genes showed correlations with response consistent with previous data. Genome-wide transcriptome and pathway mapping analysis revealed DNA repair and proliferation associated genes to be most consistently correlated with olaparib sensitivity. Based on results from all these approaches a candidate baseline gene expression profile predictive of olaparib response was established.
Conclusions: By profiling a large panel of cell lines we have determined that factors in addition to BRCA mutation can be linked with olaparib sensitivity. A list of candidate gene transcripts was identified that predicts sensitivity to olaparib across a broad range of tumor types in vitro and may have utility as predictive biomarkers in the clinic. Studies are already underway to determine whether this baseline transcript tumor profile can be correlated with patient responses to olaparib.
Citation Information: Mol Cancer Ther 2009;8(12 Suppl):C119.