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Targeting enhancer reprogramming to mitigate MEK inhibitor resistance in preclinical models of advanced ovarian cancer
Shini Liu, … , Ying Xiong, Jing Tan
Shini Liu, … , Ying Xiong, Jing Tan
Published August 31, 2021
Citation Information: J Clin Invest. 2021;131(20):e145035. https://doi.org/10.1172/JCI145035.
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Research Article Oncology

Targeting enhancer reprogramming to mitigate MEK inhibitor resistance in preclinical models of advanced ovarian cancer

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Abstract

Ovarian cancer is characterized by aberrant activation of the mitogen-activated protein kinase (MAPK), highlighting the importance of targeting the MAPK pathway as an attractive therapeutic strategy. However, the clinical efficacy of MEK inhibitors is limited by intrinsic or acquired drug resistance. Here, we established patient-derived ovarian cancer models resistant to MEK inhibitors and demonstrated that resistance to the clinically approved MEK inhibitor trametinib was associated with enhancer reprogramming. We also showed that enhancer decommissioning induced the downregulation of negative regulators of the MAPK pathway, leading to constitutive ERK activation and acquired resistance to trametinib. Epigenetic compound screening uncovered that HDAC inhibitors could alter the enhancer reprogramming and upregulate the expression of MAPK negative regulators, resulting in sustained MAPK inhibition and reversal of trametinib resistance. Consequently, a combination of HDAC inhibitor and trametinib demonstrated a synergistic antitumor effect in vitro and in vivo, including patient-derived xenograft mouse models. These findings demonstrated that enhancer reprogramming of the MAPK regulatory pathway might serve as a potential mechanism underlying MAPK inhibitor resistance and concurrent targeting of epigenetic pathways and MAPK signaling might provide an effective treatment strategy for advanced ovarian cancer.

Authors

Shini Liu, Qiong Zou, Jie-Ping Chen, Xiaosai Yao, Peiyong Guan, Weiting Liang, Peng Deng, Xiaowei Lai, Jiaxin Yin, Jinghong Chen, Rui Chen, Zhaoliang Yu, Rong Xiao, Yichen Sun, Jing Han Hong, Hui Liu, Huaiwu Lu, Jianfeng Chen, Jin-Xin Bei, Joanna Koh, Jason Yongsheng Chan, Baohua Wang, Tiebang Kang, Qiang Yu, Bin-Tean Teh, Jihong Liu, Ying Xiong, Jing Tan

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