TP53 variant classification benefits from the availability of large-scale functional data for missense variants generated using cDNA-based assays. However, absence of comprehensive splicing assay data for TP53 confounds the classification of the subset of predicted missense and synonymous variants that are also predicted to alter splicing. Our study aimed to generate and apply splicing assay data for a prioritised group of 59 TP53 predicted missense or synonymous variants that are also predicted to affect splicing by either SpliceAI or MaxEntScan.
| Authors | Fortuno, C; Llinares-Burguet, I; Canson, DM; de la Hoya, M; Bueno-Martínez, E; Sanoguera-Miralles, L; Caldes, S; James, PA; Velasco-Sampedro, EA; Spurdle, AB |
|---|---|
| Journal | Human Genomics |
| Pages | 2 |
| Volume | 19 |
| Date | 8/02/2025 |
| Grant ID | IIRS-21-102 | National Breast Cancer Foundation; APP177524 | National Health and Medical Research Council; APP177524 | National Health and Medical Research Council; ISCIII (PI20/00110) | Spanish Ministry of Science and Innovation, Acción Estratégica en Salud 2019; ISCIII (PI24/00267) | Spanish Ministry of Science and Innovation, Acción Estratégica en Salud 2024; ISCIII (PI23/00047) | Spanish Ministry of Science and Innovation, Acción Estratégica en Salud 2023; ISCIII (PI23/00047) | Spanish Ministry of Science and Innovation, Acción Estratégica en Salud 2023; ISCIII (PI23/00047) | Spanish Ministry of Science and Innovation, Acción Estratégica en Salud 2023 |
| Funding Body | |
| URL | http://www.ncbi.nlm.nih.gov/pubmed/?term=10.1186/s40246-024-00714-5 |