Investigator
Research Associate · University of Cambridge, Early Cancer Institute/MRC Cancer Unit/Department of Medical Genetics
Basal expression of RAD51 foci predicts olaparib response in patient-derived ovarian cancer xenografts
The search for biomarkers to evaluate ovarian cancer (OC) homologous recombination (HR) function and predict the response to therapy is an urgent clinical need to improve the selection of patients who could benefit from platinum- and olaparib (poly-ADP ribose polymerase inhibitors, PARPi)-based therapies. We used a large collection of OC patient-derived xenografts (PDXs) (n = 47) and evaluated their HR status based on BRCA1/2 mutations, BRCA1 promoter methylation and the HRDetect score. RAD51 foci were quantified in formalin-fixed, paraffin-embedded untreated tumour specimens by immunofluorescence and the messenger RNA expression of 21 DNA repair genes by real-time PCR. Tumour HR deficiency predicted both platinum and olaparib responses. The basal level of RAD51 foci evaluated in geminin-positive/replicating cells strongly inversely correlated with olaparib response (p = 0.011); in particular, the lower the foci score, the greater the sensitivity to olaparib, while low RAD51 foci score seems to associate with platinum activity. The basal RAD51 foci score is a candidate predictive biomarker of olaparib response in OC patients as it can be easily translatable in a clinical setting. Moreover, the findings corroborate the importance of OC-PDXs as a reliable tool to identify and validate biomarkers of response to therapy.
Research Associate
University of Cambridge · Early Cancer Institute/MRC Cancer Unit/Department of Medical Genetics
Post Doctoral Fellow
Wellcome Trust Sanger Institute · Cancer, Ageing and Somatic Mutation
Post Doctoral Scientist
University College Dublin · Systems Biology Ireland
Ph.D. in Computing Science
University of Glasgow · School of Computing Science
M.Sc. in Informatics
University of Edinburgh · School of Informatics
Laurea Specialistica in Informatica - M.Sc. in Informatics
Università degli Studi di Trento · Dipartimento di Scienze Matematiche Fisiche e Naturali
GB