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  • Splicing impact assessment of canonical splice-site LZTR1 variants of uncertain significance highlights the gap between predicted splice disruption and clinical variant interpretation

  • Saharsadat Zargar,1,*
    1. Independent Researcher


  • Introduction: Leucine zipper-like transcription regulator 1 (LZTR1) is a regulator of cellular processes through its involvement in the RAS/MAPK signalling pathway and Golgi complex stability. Pathogenic LZTR1 variants have been associated with multiple hereditary disorders and cancer predisposition syndromes. However, a substantial number of LZTR1 variants remain classified as variants of uncertain significance (VUS), limiting their clinical interpretation . A proportion of these VUS affect canonical splice-sites or are predicted to alter pre-mRNA splicing. Although computational tools frequently predict potential deleterious effects for splice-altering variants, the absence of functional evidence often prevents definitive variant classification.
  • Methods: In this study, canonical splice-site LZTR1 VUS were identified from ClinVar and systematically evaluated to investigate the gap between computational prediction and clinical classification. Germline LZTR1 variants were filtered based on VUS classification and splice-site annotation, resulting in the identification of 11 canonical splice-site variants affecting the ±1 and ±2 splice-sites. The predicted impact of these variants on splicing was assessed using SpliceAI, and sequence-based splice-site alterations were further evaluated using MaxEntScan where applicable. Available clinical submissions, phenotypic information, and functional or literature evidence were also reviewed.
  • Results: SpliceAI predicted high-confidence splice-altering effects for the majority of analysed variants based on the established score thresholds. MaxEntScan identified reduced sequence-based splice-site strength among single nucleotide variants where sequence-based scoring was applicable. Despite these computational predictions, no functional evidence was identified for the selected variants, and all remained classified as VUS.
  • Conclusion: These findings highlight the limitations of computational approaches when used alone for splice variant interpretation and emphasise the need for functional validation. Emerging transcriptomic approaches, including long-read sequencing technologies, may provide further opportunities for resolving unresolved splice variants and improving the clinical interpretation of LZTR1 variation in cancer and hereditary disease contexts.
  • Keywords: LZTR1; variants of uncertain significance; splice-site variants; SpliceAI; functional validation

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