Presented by Prof Toon Van Gorp (University of Leuven)
Professor Toon Van Gorp, an oncological gynaecologist from the University of Leuven, Belgium, proudly presents the oral presentation by Dr Liselore Loverix, one of his former PhD students, at ESGO 2024 in Barcelona. Dr Loverix’s research focused on enhancing the predictive accuracy of the Leuven PARPi Benefit Test in high-grade serous ovarian cancer.
In collaboration with the ENGOT HRD consortium, the LEUVEN HRD test was developed as an alternative to the Myriad myChoice PLUS test, aiming to increase accessibility and reduce costs for European cancer patients. Utilizing samples from the PAOLA-1 study, it was demonstrated that the performance of this test matched that of the Myriad test.
However, the LEUVEN HRD test could be refined in predicting the benefit of the PARPi + bevacizumab treatment. In addition to conventional genomic instability parameters (LOH + TAI + LST), the location of the BRCA mutation was examined, hypothesizing that not all mutations respond equally to PARPi, and the loss of heterozygosity across the genome. Rather than relying on a cutoff value, the goal was to provide a binary response (YES or NO) regarding the benefit of adding PARPi to the treatment regimen.
Half of the samples from the PAOLA-1 study served as a test set, while the other half acted as a validation set. In conclusion, the new algorithm resulted in a test that outperformed the Myriad test in predicting the PARPi benefit. In HRD-positive patients treated with a PARPi, the HR for the Myriad test was 0.41, whereas the new test yielded an HR of 0.31. The difference was even more pronounced in wild-type BRCA patients, with an HR of 0.41 for the Myriad test versus an exceptionally low 0.18 for the optimised Leuven HRD test.
This test represents a groundbreaking development, allowing to differentiate patients who will respond to PARPi from those who will not. Its introduction into clinical practice is anticipated.
References:
Loverix L., 2024, The Leuven PARPi Benefit Test As Improved Approach For Prediction Of PARPi Benefit In The PAOLA-1/ENGOTov25 Trial. ESGO eAcademy; 411085; ESGO2024_0309_039