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TP53 mutations in high grade serous ovarian cancer and impact on clinical outcomes: a comparison of next generation sequencing and bioinformatics analyses
  1. Victoria Mandilaras1,
  2. Swati Garg2,
  3. Michael Cabanero3,
  4. Qian Tan1,
  5. Chiara Pastrello4,
  6. Julia Burnier1,
  7. Katherine Karakasis1,
  8. Lisa Wang1,
  9. Neesha C Dhani1,
  10. Marcus O Butler1,
  11. Philippe L Bedard1,
  12. Lillian L Siu1,
  13. Blaise Clarke3,
  14. Patricia Ann Shaw3,
  15. Tracy Stockley2,
  16. Igor Jurisica4,5,6,
  17. Amit M Oza1 and
  18. Stephanie Lheureux1
  1. 1Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
  2. 2Advanced Molecular Diagnostics Laboratory, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
  3. 3Department of Laboratory Medicine and Pathology, University Health Network, Toronto, Ontario, Canada
  4. 4Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
  5. 5Departments of Medical Biophysics and Computer Science, University of Toronto, Toronto, Ontario, Canada
  6. 6Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovakia
  1. Correspondence to Stephanie Lheureux, Division on Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, ON M5G 2M9, Canada; stephanie.lheureux{at}


Objective Mutations in TP53 are found in the majority of high grade serous ovarian cancers, leading to gain of function or loss of function of its protein product, p53, involved in oncogenesis. There have been conflicting reports as to the impact of the type of these on prognosis. We aim to further elucidate this relationship in our cohort of patients.

Methods 229 patients with high grade serous ovarian cancer underwent tumor profiling through an institutional molecular screening program with targeted next generation sequencing. TP53 mutations were classified using methods previously described in the literature. Immunohistochemistry on formalin-fixed paraffin embedded tissue was used to assess for TP53 mutation. Using divisive hierarchal clustering, we generated patient clusters with similar clinicopathologic characteristics to investigate differences in outcomes.

Results Six different classification schemes of TP53 mutations were studied. These did not show an association with first platinum-free interval or overall survival. Next generation sequencing reliably predicted mutation in 80% of cases, similar to the proportion detected by immunohistochemistry. Divisive hierarchical clustering generated four main clusters, with cluster 3 having a significantly worse prognosis (p<0.0001; log-rank test). This cluster had a higher concentration of gain of function mutations and these patients were less likely to have undergone optimal debulking surgery.

Conclusions Different classifications of TP53 mutations did not show an impact on outcomes in this study. Immunohistochemistry was a good predictor for TP53 mutation. Cluster analysis showed that a subgroup of patients with gain of function mutations (cluster 3) had a worse prognosis.

  • ovarian cancer
  • TP53
  • oncomorphic TP53 mutation
  • gain of function mutation
  • loss of function mutation

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  • Funding This study was funded by the Pamela Mary Hosang Ovarian Cancer Research Fund at The Princess Margaret Cancer Foundation, the Cedars Cancer Foundation Henry R Shibata Fellowship, and the Ontario Research Fund (#34876).

  • Competing interests None declared.

  • Provenance and peer review Not commissioned, externally peer reviewed.