BET on Combination Therapy to Fight HER2 positive Breast Cancer Escaping Treatment
Breast cancer accounts for one quarter of all cancer cases, resulting in over half a million deaths worldwide per year. Fifteen to twenty percent of all breast cancer diagnoses belong to the HER2 positive subtype. Only about one-third of these patients respond well to standard therapy. But even patients that initially respond eventually develop resistance. Using HER2 positive human breast cancer cell lines, researchers at the University of North Carolina discovered one of the mechanisms underpinning drug resistance in breast cancer and found a way to prevent it from occurring.
Breast cancer is the leading type of cancer diagnosed in women worldwide. About one in five cases shows amplification of the human epidermal growth factor receptor 2 (HER2) gene, which is more prevalent in young women. HER2 positive breast cancers are more aggressive and spread more quickly than other types because HER2 is capable of driving tumor cell replication. Anti-HER2 therapies focus on the inhibition of the receptor’s kinase activity to switch off its growth promoting function and they often produce long periods of remission in early stage breast cancer. However, repetitive exposure to the drug over the course of several chemotherapy cycles or the presence of metastases may result in the rapid emergence of resistance.
Lapatinib is one of the HER-2 inhibitors currently used in the clinic that functions by silencing its kinase activity. Protein kinases are vital components of any cell for performing a multitude of different tasks and their ubiquitous inhibition is very toxic. Switching off one kinase at the time, trying to avoid this toxicity is not a valid long term alternative because cancer cells develop the ability to shift to other kinase signaling nodes. This cancer cell behavior drives patients into relapse and is known as “adaptive kinome reprogramming”.
BET Bromodomain Proteins Drive Cancer Cells to Resistance
Combination therapies, targeting more than one signaling at the time, are required to prevent the occurrence of drug resistance. Researchers at UNC School of Medicine and UNC Lineberger Comprehensive Cancer Center identified, using mass spectrometry, what pathways are activated to compensate for HER2 inhibition in cancer cells undergoing treatment. Surprisingly they discovered that, following lapatinib exposure, a defined set of other protein kinases become activated in vitro. More importantly these alternative signaling have a common upstream activator called BRD-4, a protein belonging to the BET family of bromodomain transcription factors that bind to DNA to allow the expression of their target genes. This discovery has a simple but important implication: in order to prevent HER2 positive cancer cells from developing drug resistance, it is necessary to prevent them from activating BET. BET inhibitors have been effective in AML treatment in mice and in in vitro studies and further validation is undergoing Phase I clinical trials. According to the results from the UNC study, one specific BET inhibitor, called JQ1, preferentially modulates the kinome reprogramming induced by lapatinib. By combining therapies that switch off HER2 kinase activity with BET inhibitors, UNC researcher were able to stop the growth of HER2 positive cancer cells and to restore long-term sensitivity of lapatinib-resistant cell lines in vitro. The team is now working on translating in vivo their findings using animal models that develop HER2 positive breast cancer.
Preclinical models are essential to explore the mechanisms of drug resistance and to provide a fast route from preclinical testing to clinical validation of new compounds. Crown Bioscience has developed several highly predictive breast cancer models for preclinical drug evaluation included in our HuPrime® and PDXact™ collections of patients derived xenografts (PDX). Our fully validated and extensively characterized PDX models can be employed in HuTrials™, our surrogate Phase II mouse clinical trials to identify responder and non-responder populations, gene signatures and predictive biomarkers for patient stratification in the clinic using our HuSignature™ and our HuMark™ translational platforms. Our breast cancer services also include syngenic models, GEMM, and MuPrime™ models - allografts of spontaneous murine tumors, studied in fully immunocompetent mice.
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