MCL‐1 inhibition triggers a largely reversible cardiac stress signature in a humanised mouse model

Abstract

BACKGROUND AND PURPOSE: Myeloid cell leukaemia-1 (MCL-1) is an essential anti-apoptotic protein and a promising therapeutic target in oncology. Early clinical studies of MCL-1 inhibitors reported unexpected elevations in cardiac troponin, raising concerns about potential cardiotoxicity. Conventional murine models may incompletely capture human-relevant cardiac effects due to species-specific differences in MCL-1 pharmacology. EXPERIMENTAL APPROACH: We investigated the cardiac effects of the selective MCL-1 inhibitor MIK665 in a humanised MCL-1 mouse model. Animals were treated once weekly and assessed for cardiac biomarkers, left ventricular function by echocardiography, and myocardial transcriptomic changes at peak treatment (Day 14) and after treatment cessation (Day 21). Bulk RNA sequencing was used to characterise differential gene expression, pathway enrichment and higher-order transcriptional modules. KEY RESULTS: MIK665 treatment induced a time-dependent increase in circulating cardiac troponin T without detectable impairment of left ventricular systolic function. Transcriptomic analysis revealed coordinated suppression of mitochondrial and contractile gene programmes during treatment, accompanied by activation of stress- and immune-associated pathways. After treatment cessation, cardiac troponin levels declined and the myocardial transcriptome shifted towards a distinct recovery-associated profile. CONCLUSIONS AND IMPLICATIONS: Pharmacological MCL-1 inhibition induced a cardiac biomarker and transcriptional stress response characterised by troponin release and dynamic myocardial transcriptomic remodelling. Additional functional and histological analyses did not reveal overt systolic dysfunction, strain-detectable impairment, or increased fibrotic remodelling. These alterations are consistent with a largely reversible cardiac stress response rather than overt structural or functional cardiotoxicity. These findings support the use of refined, humanised preclinical models to improve translational cardiac safety assessment.