Background <p>Von Hippel–Lindau (VHL) syndrome is a rare autosomal dominant multisystem tumour syndrome caused by germline <i>VHL</i> mutations. The traditional classification of VHL syndrome, which is largely based on pheochromocytoma penetrance, is insufficient for individualised surveillance and management. This study aimed to improve mutation-specific risk stratification and define genotype–phenotype correlations of recurrent hotspot mutations in a large Chinese cohort.</p> Methods <p>This retrospective single-centre study included 674 patients with VHL disease from 283 unrelated families. Four recurrent hotspot mutation subtypes were analysed: codon 65 missense mutations, exon 2 deletion, c.481C &gt; T, and c.224_226del. Kaplan–Meier analysis and univariate and multivariate Cox regression models were used to assess age-related tumour risks and survival outcomes.</p> Results <p>Codon 65 missense mutations were associated with a lower risk of retinal angioma and pheochromocytoma, indicating a relatively mild phenotype. Exon 2 deletion was characterised by a higher prevalence, earlier onset, and increased age-related risk of retinal angioma and worse renal cell carcinoma (RCC)-specific survival. Increased prevalences and age-related risks of central nervous system hemangioblastoma (CHB), RCC, and pancreatic cysts or tumours were associated with c.481C &gt; T mutations. The c.224_226del subtype showed a distinct CHB-predominant phenotype, with higher CHB incidence, earlier onset, lower pancreatic lesion risk, and higher overall mortality.</p> Conclusion <p>Recurrent hotspot VHL mutation subtypes were associated with distinct clinical phenotypes and prognostic patterns. Mutation subtype-based classification (covering 19.6% of patients with VHL syndrome) may provide more precise guidance for surveillance, clinical decision-making, and genetic counselling than traditional broad classification models.</p> Graphical abstract <p></p>

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Hotspot mutations and tumour spectrum in von Hippel–Lindau syndrome: genotype–phenotype analysis of a large Chinese cohort

  • Chuandong Wang,
  • Jianhui Qiu,
  • Tao Liu,
  • Yuhang Bao,
  • Jingcheng Zhou,
  • Yizhou Wang,
  • Kan Gong

摘要

Background

Von Hippel–Lindau (VHL) syndrome is a rare autosomal dominant multisystem tumour syndrome caused by germline VHL mutations. The traditional classification of VHL syndrome, which is largely based on pheochromocytoma penetrance, is insufficient for individualised surveillance and management. This study aimed to improve mutation-specific risk stratification and define genotype–phenotype correlations of recurrent hotspot mutations in a large Chinese cohort.

Methods

This retrospective single-centre study included 674 patients with VHL disease from 283 unrelated families. Four recurrent hotspot mutation subtypes were analysed: codon 65 missense mutations, exon 2 deletion, c.481C > T, and c.224_226del. Kaplan–Meier analysis and univariate and multivariate Cox regression models were used to assess age-related tumour risks and survival outcomes.

Results

Codon 65 missense mutations were associated with a lower risk of retinal angioma and pheochromocytoma, indicating a relatively mild phenotype. Exon 2 deletion was characterised by a higher prevalence, earlier onset, and increased age-related risk of retinal angioma and worse renal cell carcinoma (RCC)-specific survival. Increased prevalences and age-related risks of central nervous system hemangioblastoma (CHB), RCC, and pancreatic cysts or tumours were associated with c.481C > T mutations. The c.224_226del subtype showed a distinct CHB-predominant phenotype, with higher CHB incidence, earlier onset, lower pancreatic lesion risk, and higher overall mortality.

Conclusion

Recurrent hotspot VHL mutation subtypes were associated with distinct clinical phenotypes and prognostic patterns. Mutation subtype-based classification (covering 19.6% of patients with VHL syndrome) may provide more precise guidance for surveillance, clinical decision-making, and genetic counselling than traditional broad classification models.

Graphical abstract