The overall goal of the current proposal is to develop a clinically useful predictor of PARP inhibitor (PARPi) sensitivity/resistance to spare toxicities and cost for patients unlikely to derive benefit. Our hypothesis is that a combined mutation and methylation analysis performed immediately before initiation of therapy will provide a useful predictor of PARPi response. To test this hypothesis, our approach is to complete development of a high throughput and quantitative methylation assay for key HR genes and refine our assays using banked tumor tissues formalin fixed paraffin embedded (FFPE) neoplastic samples from phase II PARPi trials, then test these assays using samples from 4 large phase III randomized controlled trials (RCT) in OC and BC that employ three different PARPi. We propose three specific aims:
Aim 1 : Develop a clinical grade, quantitative methylation assay and a combined methylation and mutation assay (MMA) to define those BRCA wildtype cancers with best response to PARP inhibitors.
Aim 2 : Validate the combined HRR mutation and methylation assay (MMA) as a predictor of PARPi response in 2 randomized controlled trials of recurrent breast and ovarian cancer.
Aim 3 : Validate MMA as a predictor of PARPi response in 2 randomized controlled trials for primary treatment of advanced ovarian cancer. Together, these studies will provide insight into mechanisms of PARPi sensitivity while developing a clinical predictor for both breast and ovarian cancer, which could apply to other cancer types. These studies will lead to more precise therapeutic application of PARP inhibitors, reducing toxicity and cost while maximizing patient benefit.
The overall goal of the current proposal is to develop and validate a combined mutation and methylation assay as a clinical predictor of PARP inhibitor response. We will develop and refine a quantitative methylation assay, then test whether combining methylation and mutation analyses can predict PARP inhibitor sensitivity in patients with BRCA wildtype cancers using clinical samples from 4 large randomized controlled trials in ovarian and breast cancer.
