QIMR Berghofer scientists, in collaboration with the Valladolid University (Spain), have published two groundbreaking studies that advance the understanding of RNA splicing in the TP53 gene, the gene most closely linked to inherited cancer risk and a major protector against cancer. These discoveries provide new insights into how these genetic ‘errors’ can cause cancer, how the gene is controlled, and how clinicians will, in future, use this information to improve cancer risk assessments in patients.
Journal/conference: Human Genomics and npj Genomic Medicine
Research: Link to Paper 1 | Paper 2
Organisation/s: QIMR Berghofer, The University of Queensland
Media release
From: QIMR Berghofer
QIMR Berghofer scientists, in collaboration with the Valladolid University (Spain), have published two groundbreaking studies that advance the understanding of RNA splicing in the TP53 gene, the gene most closely linked to inherited cancer risk and a major protector against cancer. These discoveries provide new insights into how these genetic ‘errors’ can cause cancer, how the gene is controlled, and how clinicians will in future use this information to improve cancer risk assessments in patients.
The first study, published in Human Genomics (Jan 2025), explored the role of splicing in the pathogenicity of TP53 missense and synonymous variants. Using a TP53 exons 2–9 minigene assay in SKBR3 cells, the team functionally assessed 59 exonic variants predicted by SpliceAI or MaxEntScan to disrupt splicing. Strikingly, aberrant transcript profiles indicative of loss of function were observed for 71% of tested variants, with a significant proportion showing high levels (>50–80%) of aberrant expression. These functional data informed reclassification of 46% of the variants as likely pathogenic or benign, reinforcing the utility of RNA assays in the refinement of variant interpretation per ClinGen guidelines.
The study also provided empirical support for a SpliceAI threshold of ≥0.2 as a reasonable predictor of splicing impact in TP53, while highlighting limitations in correlating prediction scores with transcript abundance. Importantly, integration with the SpliceAI-10k calculator improved the prediction of aberration types, though not their quantitative extent.
Building on this work, the team’s second study, published in NPJ Genomic Medicine (May 2025), delves into the spatial and regulatory determinants of TP53 exon recognition. Through targeted microdeletion assays of exons 3 and 6, researchers identified four splice regulatory element (SRE)-rich regions and established critical donor-to-branchpoint distances influencing splicing fidelity. Notably, deletion of intronic G-runs or SRE clusters triggered profound aberrant splicing, including novel transcript isoforms such as Δ(E6q21). Comparative analyses of 134 single nucleotide variants (SNVs) and 27 deletions revealed that SRE-disrupting SNVs generally caused modest splicing defects (≤26% exon skipping), while multi-SRE deletions had far more pronounced effects.
Together, these studies underscore the importance of incorporating both sequence-based prediction and empirical RNA splicing data into TP53 variant assessment. They also highlight the nuanced influence of local RNA context—including SRE distribution and spatial constraints—on splicing outcomes.
Drs Cristina Fortuno and Daffodil Canson were lead authors of the studies, and say the research is a large step forward in genetic analysis; “By combining functional assays with in silico predictions, we’re able to clarify the mechanisms by which specific TP53 variants exert their effects. This is particularly critical in the context of germline TP53 testing, where variant classification has direct implications for cancer risk management, however most of research so far has focused on missense variants.”
These contributions not only enhance TP53 variant interpretation under ACMG/AMP and ClinGen frameworks but also serve as a model for broader splicing analyses across clinically relevant genes.