Cell ReportsCancer BiologyPeer-reviewed journal article
Exploiting the polypharmacology of alectinib for synergistic RNA splicing disruption with RBM39 degraders
Yurui MaiD, Evon PooniD, Chenchen Jin, Barbara Martins Da CostaiD, Yuewei Xu, Sadiya Quazi, Nikolaos Zourdoumis, Chiharu WickremesingheiD, Louis ChesleriD, Hector C. KeuniD, Anke M. NijhuisiD
Abstract
Precise control of pre-mRNA splicing is critical for transcriptome integrity, and its disruption is increasingly recognised as a vulnerability in cancer. Here, we identify a functional interplay between two key splicing regulators, RBM39 and serine/arginine protein kinase 1 (SRPK1), and show that dual targeting of these factors severely compromises splicing fidelity in high-risk neuroblastoma. We use the molecular glue indisulam to degrade RBM39 and repurpose the clinical ALK inhibitor alectinib which potently inhibits SRPK1. Co-treatment with indisulam and alectinib inhibited cell proliferation, induced apoptosis, and caused G2/M arrest in multiple cancer cell lines, including MYCN-amplified neuroblastoma. RNA sequencing revealed enhanced splicing defects preferentially in DNA repair and genome maintenance related genes following combination treatment, leading to R-loop accumulation and increased DNA damage. In the Th-MYCN/ALKF1174L neuroblastoma mouse model, combination therapy induced complete tumour regression and significantly improved survival rates compared with monotherapies. These findings demonstrate that combining indisulam and alectinib is a promising approach to treat aggressive malignancies such as high-risk neuroblastoma, exploiting the previously untapped polypharmacology of alectinib as a clinical RNA splicing inhibitor and supporting the therapeutic value of co-targeting interdependent splicing factors for synergistic benefit.
- organism: mouse
- organism: human
- assay: bulk RNA-seq
- research focus: cancer & tumor microenvironment
- research focus: cell type annotation
- research focus: differential expression
- research focus: drug response / drug discovery
- approach: experimental assay
- approach: statistical model
- Citations
- 2
- FWCI
- 4.10
- Field percentile
- top 9%
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