MCL1 inhibition is effective against a subset of small-cell lung cancer with high MCL1 and low BCL-XL expression

Autor: Yuichi Sakamori, Naoki Nakajima, Toyohiro Hirai, Takahiro Tsuji, Akihiko Yoshizawa, Toshi Menju, Hiroaki Ozasa, Hitomi Ajimizu, Hiroshi Date, Hironori Yoshida, Yuto Yasuda, Tomoko Funazo, Masatoshi Yamazoe, Takashi Nomizo, Young Hak Kim
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Cell Death & Disease
Cell Death and Disease, Vol 11, Iss 3, Pp 1-15 (2020)
ISSN: 2041-4889
Popis: There have been few advances in the treatment of small-cell lung cancer (SCLC) because of the lack of targets. MCL1, a member of the anti-apoptotic BCL-2 family, may be a treatment target in several cancers, including SCLC. However, whether the expression profile of the anti-apoptotic BCL-2 family affects MCL1 inhibition strategy is unknown. A tissue microarray (TMA) was created from consecutive patients who were diagnosed with SCLC and had previously undergone surgery at Kyoto University Hospital (Kyoto, Japan) between 2001 and 2017. We used S63845, a MCL1 inhibitor, to assess the cytotoxic capacity in SCLC cell lines including a patient-derived cell line in vitro and in vivo. The combination of S63845 with navitoclax, a double BCL-XL/BCL-2 inhibitor, was also employed to examine the comprehensive inhibition of the anti-apoptotic BCL-2 family. Immunohistochemistry of a TMA from patients with surgically resected SCLC demonstrated high MCL1 expression with low BCL-XL and BCL-2 to be the most common expression profile. S63845 was effective in high MCL1- and low BCL-XL-expressing SCLC cell lines. S63845 induced BAK-dependent apoptosis in vitro, and the anti-tumor efficacy was confirmed in an in vivo model. Although knockdown of BCL-XL and BCL-2 improved the cytotoxic activity of S63845 and its combination with navitoclax increased the anti-tumor cytotoxicity, the therapeutic range of S63845 with navitoclax was narrow in in vivo studies. Our study suggests MCL1 inhibition therapy be applied for high MCL1- and low BCL-XL-expressing SCLC patients.
Databáze: OpenAIRE