Improving the efficacy of chemotherapy drugs for the treatment of triple-negative breast cancers.

107 Background: Approximately 15-20% of all breast cancers account for triple-negative breast cancers that exhibit aggressive, distinct metastatic pattern and poor prognosis. More than 50% of patients with triple negative breast cancers develop chemoresistance and do not respond to chemotherapeutic drugs, leading to early relapse and shorter survival. Understanding the mechanisms underlying such resistance is therefore crucial for the development of new, efficacious cancer drugs. Methods: Through high-throughput miRNA inhibitor library screens, we have identified miRNA inhibitors that sensitize resistant triple negative breast cancer cells to paclitaxel, a drug commonly used to treat triple negative breast cancers. Results: Through high-throughput miRNA inhibitor library screens, we have identified miRNA inhibitors that sensitize resistant triple negative breast cancer cells to paclitaxel, a drug commonly used to treat triple negative breast cancers. Since miRNAs are endogenously expressed and can be easily manipulated using synthetic oligoribonucleotides, we believe that they represent more attractive targets than the single gene or gene product that is the target of conventional cancer treatments that are typically prone to drug resistance. Supporting this, we have recently demonstrated that miRNAs can be systemically delivered to treat breast cancer lung metastasis without any hepatotoxicity. In addition to being a potent therapeutic regimen, our preliminary analyses reveal that miRNAs can be bonafide early prognostic markers to monitor treatment response to specific drugs in triple-negative breast cancers. Conclusions: Taken together, these findings suggest that miRNA can serve as potent therapeutic adjuvants and although the data content of miRNA profiles is far less than that of gene expression profiles, by virtue of their ability to modulate entire spectrum of genes and pathways miRNAs have potential to be better classifiers for the prognosis and response to treatment of cancers. We believe that the identification of miRNAs that mediate chemoresistance could lead to more efficient treatment selection at the patient level and an improved response rates at the population level.