Rapid minigene workflow for functional reclassification of splicing variants in hereditary cancer diagnostics

Next-generation sequencing of cancer predisposition genes is routinely used in hereditary cancer diagnostics. However, a substantial fraction of detected variants remains clinically unresolved. Using a customised 77-gene panel, we analysed 2142 individuals and identified 384 pathogenic or likely pathogenic variants across 54 genes, corresponding to a diagnostic yield of approximately 18%. Despite this, 17% of cases carried variants of uncertain significance, many of which were suspected to affect pre-mRNA splicing and are particularly challenging to interpret due to the limited reliability of in silico predictions and lack of experimental evidence.

To address this diagnostic gap, we developed a streamlined minigene-based workflow for rapid functional evaluation of splicing variants and applied it retrospectively. The approach relies on synthetic DNA and recombination-based cloning, eliminating the need for patient-derived RNA and enabling efficient construct generation within a clinically compatible timeframe. Computational prioritisation using AlphaGenome was integrated to support variant selection, while experimental assays provided direct evidence of splicing outcomes.

Application of this strategy allowed the reclassification of previously unresolved variants and clarified cases with discordant computational evidence. Importantly, the workflow is designed for implementation in routine diagnostic settings, with a turnaround time aligned with clinical reporting requirements.

This approach provides a robust and scalable framework for functional interpretation of splicing variants, improving diagnostic resolution and supporting more informed clinical decision-making in hereditary cancer genetics.