帕博西利布
CDKN2A
细胞周期蛋白依赖激酶4
蛋白激酶抑制剂
激酶
生物标志物
背景(考古学)
药理学
癌症研究
生物
计算生物学
细胞生物学
癌症
蛋白激酶A
细胞周期蛋白依赖激酶2
生物化学
遗传学
转移性乳腺癌
乳腺癌
古生物学
作者
Jennifer L. Green,Eric Okerberg,Josilyn Sejd,Marta Palafox,Laia Monserrat,Senait Alemayehu,Jiangyue Wu,Maria Sykes,Arwin Aban,Violeta Serra,Tyzoon Nomanbhoy
标识
DOI:10.1158/1535-7163.mct-18-0755
摘要
Abstract The interaction of a drug with its target is critical to achieve drug efficacy. In cases where cellular environment influences target engagement, differences between individuals and cell types present a challenge for a priori prediction of drug efficacy. As such, characterization of environments conducive to achieving the desired pharmacologic outcome is warranted. We recently reported that the clinical CDK4/6 inhibitor palbociclib displays cell type–specific target engagement: Palbociclib engaged CDK4 in cells biologically sensitive to the drug, but not in biologically insensitive cells. Here, we report a molecular explanation for this phenomenon. Palbociclib target engagement is determined by the interaction of CDK4 with CDKN2A, a physiologically relevant protein inhibitor of CDK4. Because both the drug and CDKN2A prevent CDK4 kinase activity, discrimination between these modes of inhibition is not possible by traditional kinase assays. Here, we describe a chemo-proteomics approach that demonstrates high CDK4 target engagement by palbociclib in cells without functional CDKN2A and attenuated target engagement when CDKN2A (or related CDKN2/INK4 family proteins) is abundant. Analysis of biological sensitivity in engineered isogenic cells with low or absent CDKN2A and of a panel of previously characterized cell lines indicates that high levels of CDKN2A predict insensitivity to palbociclib, whereas low levels do not correlate with sensitivity. Therefore, high CDKN2A may provide a useful biomarker to exclude patients from CDK4/6 inhibitor therapy. This work exemplifies modulation of kinase target engagement by endogenous proteinaceous regulators and highlights the importance of cellular context in predicting inhibitor efficacy.
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