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Targeting PRMT5 in cancer: Mechanistic insights and clinical progress

Joohyun Lee, Jiye Kim, Inah Hwang

2025Biomedicine & Pharmacotherapy7 citationsDOIOpen Access PDF

Abstract

Arginine methylation is increasingly recognized as a key regulatory mechanism in cancer, exerting broad influence over chromatin organization, RNA metabolism, and oncogenic signaling. Protein arginine methyltransferase 5 (PRMT5) catalyzes symmetric dimethylation of arginine residues on both histone and non-histone substrates. Through these modifications, PRMT5 modulates transcription, alternative splicing, DNA repair, and apoptosis, which collectively support malignant transformation and disease progression. Elevated expression or hyperactivation of PRMT5 has been documented across multiple cancer types, where it contributes to tumor cell survival, proliferation, metastasis, and therapeutic resistance. Early-generation inhibitors directed against the substrate-binding groove or the S-adenosylmethionine (SAM)-binding pocket demonstrated proof of mechanism but were limited by modest clinical efficacy and dose-limiting toxicities. More recently, methylthioadenosine (MTA)-cooperative inhibitors have shown enhanced selectivity in MTAP-deleted tumors by exploiting a synthetic lethal vulnerability, offering new opportunities for precision oncology. Ongoing investigations will be critical to define the therapeutic window of PRMT5 inhibition and to optimize rational combination strategies. This review provides a comprehensive overview of current insights into the oncogenic functions of PRMT5 and highlights emerging therapeutic strategies aimed at improving cancer treatment.

Topics & Concepts

Protein arginine methyltransferase 5ChromatinEpigeneticsCancer researchMethyltransferaseArginineMechanism (biology)BiologyHistoneComputational biologyCancerMethylationRNAEpigenesisDNA damageCell biologyDiseaseDNA methylationBioinformaticsMalignant transformationChemistryMedicineRegulation of gene expressionNeoplastic transformationMechanism of actionCancer cellCancer-related gene regulationEpigenetics and DNA MethylationMachine Learning in Bioinformatics
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