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Updated: May 21, 2026

Exploring the Arginine Methylome by Nuclear Magnetic Resonance Spectroscopy
Published on: December 16, 2021
Protein arginine methyltransferase 6-dependent gene expression and splicing: association with breast cancer outcomes
Dennis H Dowhan1, Matthew J Harrison, Natalie A Eriksson
1Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia. d.dowhan@uq.edu.au
Abstract:
Protein arginine methyltransferase-6 (PRMT6) regulates steroid-dependent transcription and alternative splicing and is implicated in endocrine system development and function, cell death, cell cycle, gene expression and cancer. Despite its role in these processes, little is known about its function and cellular targets in breast cancer. To identify novel gene targets regulated by PRMT6 in breast cancer cells, we used a combination of small interfering RNA and exon-specific microarray profiling in vitro coupled to in vivo validation in normal breast and primary human breast tumours. This approach, which allows the examination of genome-wide changes in individual exon usage and total transcript levels, demonstrated that PRMT6 knockdown significantly affected i) the transcription of 159 genes and ii) alternate splicing of 449 genes. The PRMT6-dependent transcriptional and alternative splicing targets identified in vitro were validated in human breast tumours. Using the list of genes differentially expressed between normal and PRMT6 knockdown cells, we generated a PRMT6-dependent gene expression signature that provides an indication of PRMT6 dysfunction in breast cancer cells. Interrogation of several well-studied breast cancer microarray expression datasets with the PRMT6 gene expression signature demonstrated that PRMT6 dysfunction is associated with better overall relapse-free and distant metastasis-free survival in the oestrogen receptor (ER (ESR1)) breast cancer subgroup. These results suggest that dysregulation of PRMT6-dependent transcription and alternative splicing may be involved in breast cancer pathophysiology and the molecular consequences identifying a unique and informative biomarker profile.
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