Clinically, breast cancers are divided into three distinct groups: those that express the estrogen hormone receptor (ER+) (typically also express the progesterone receptor (PR+)), those that overexpress the ErbB2 (HER2) oncogene (HER2+), and those that express none of these three markers (termed “triple negative” breast cancer TNBC).
Unlike ER+ and HER2+ breast cancers; there are currently no targeted therapies against TNBC. Treatment of TNBC entails surgery coupled with radio- or chemotherapy, or both. The most commonly used chemotherapies are Taxanes (e.g. Docetaxel, Paclitaxel) and more recently, platinum-based agents (e.g. Cisplatin, Carboplatin). However, other than BRCA1/2 mutation status correlating with increased efficacy of platinum-based agents, there are currently no clinically useful predictors of differential treatment response among these commonly used chemotherapeutics.
We hypothesized that individual PDX may respond differentially to each chemotherapeutic, and as a consequence, a molecular predictor of differential chemotherapy response could be developed that might be useful clinically to predict benefit from one chemotherapy over another.
Using Reverse Phase Protein Array (RPPA) as a discovery platform, we analyzed a series of TNBC PDX models to identify potential protein pathways associated with drug resistance. We have identified MEK1, EZH2, and HDAC6 which are functionally validated in a 16 arms preclinical trial with single or double anti-cancer agents to overcome chemoresistance.
In this study, differential expressed proteins were identified among triple negative breast cancer PDX models upon Docetaxel and Carboplatin treatments. Inhibitors to two proteins (MEK1, EZH2) from the common up-regulated list as well as other targets of interest were used to design a 16 arms preclinical trial with single or double anti-cancer agents to overcome chemoresistance for triple negative breast cancers. Preliminary data for drugs to MEK1, EZH2, or HDAC in combination of Chemo-drugs showed that combined anti-cancer agents are more effective than the single agent.