Posts tagged ALK-rearranged lung cancer
Targeting YAP to overcome acquired resistance to ALK inhibitors in ALK-rearranged lung cancer

Clinical benefit of ALK tyrosine kinase inhibitors (ALK-TKIs) in ALK-rearranged lung cancer has been limited by the inevitable development of acquired resistance, and bypass-molecular resistance mechanisms remain poorly understood. We investigated a novel therapeutic target through screening FDA-approved drugs in ALK-TKI-resistant models. Cerivastatin, the rate-limiting enzyme inhibitor of the mevalonate pathway, showed anti-cancer activity against ALK-TKI resistance in vitro/in vivo, accompanied by cytoplasmic retention and subsequent inactivation of transcriptional co-regulator YAP. The marked induction of YAP-targeted oncogenes (EGFR, AXL, CYR61, and TGFβR2) in resistant cells was abolished by cerivastatin. YAP silencing suppressed tumor growth in resistant cells, patient-derived xenografts, and EML4-ALK transgenic mice, whereas YAP overexpression decreased the responsiveness of parental cells to ALK inhibitor. In matched patient samples before/after ALK inhibitor treatment, nuclear..... READ ARTICLE

EMBO Molecular Medicine DOI:10.15252/emmm.201910581

Authors: Mi Ran Yun, Hun Mi Choi, You Won Lee, Hyeong Seok Joo, Chae Won Park, Jae Woo Choi, Dong Hwi Kim, Han Na Kang, Kyoung-Ho Pyo, Eun Joo Shin, Hyo Sup Shim, Ross A Soo, James Chih-Hsin Yang, Sung Sook Lee, Hyun Chang, Min Hwan Kim, Min Hee Hong, Hye Ryun Kim, Byoung Chul Cho

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Prediction of ALK mutations mediating ALK-TKIs resistance and drug re-purposing to overcome the resistance

We discovered lorlatinib-resistant multiple ALK-compound mutations and an L1256F single mutation as well as the potential therapeutic strategies for these ALK mutations. Our original computational simulation to calculate the binding affinity may be applicable for predicting resistant mutations and for overcoming drug resistance in silico. READ ARTICLE

EBioScience DOI: 10.1016/j.ebiom.2019.01.019

Authors: Koutaroh Okada, Mitsugu Araki, Takuya Sakashita, Biao Ma, Ryo Kanada, Noriko Yanagitani, Atsushi Horiike, Sumi Koike, Tomoo Oh-hara, Kana Watanabe, Keiichi Tamai, Makoto Maemondo, Makoto Nishio, Takeshi Ishikawa, Yasushi, Okuno, Naoya Fjita, Ryohei Katayama

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