ena-STUDY-EUROPEAN RESEARCH INSTITUTE FOR THE BIOLOGY OF AGEING, UNIVERSITY OF GRONINGEN, UNIVERSITY MEDICAL CENTER GRONINGEN-17-09-2018-15:52:06:770-1076
A living biobank of ovarian cancer ex vivo models reveals profound mitotic heterogeneity
High grade serous ovarian cancer (HGSOC) is characterised by TP53 mutation and chromosome instability (CIN). To provide models for delineating CIN mechanisms and exploring novel therapeutics, we describe a workflow for generating ex vivo cultures with extensive proliferative potential. 15 models from the “living biobank” were validated by p53 profiling, exome sequencing and global transcriptomics, and karyotyped using single-cell whole genome sequencing. Time-lapse microscopy revealed catastrophic and highly heterogeneous mitoses, indicating that analysis of established cell lines grossly underestimates mitotic dysfunction in advanced human tumours. Drug profiling revealed cisplatin sensitivities consistent with patient responses, and cell fate following taxol exposure also shows extensive heterogeneity. By complementing cancer genomics and clinical data, this workflow has the potential to facilitate personalized approaches to treat HGSOC.
High grade serous ovarian cancer (HGSOC) is characterised by TP53 mutation and chromosome instability (CIN). To provide models for delineating CIN mechanisms and exploring novel therapeutics, we describe a workflow for generating ex vivo cultures with extensive proliferative potential. 15 models from the “living biobank” were validated by p53 profiling, exome sequencing and global transcriptomics, and karyotyped using single-cell whole genome sequencing. Time-lapse microscopy revealed catastrophic and highly heterogeneous mitoses, indicating that analysis of established cell lines grossly underestimates mitotic dysfunction in advanced human tumours. Drug profiling revealed cisplatin sensitivities consistent with patient responses, and cell fate following taxol exposure also shows extensive heterogeneity. By complementing cancer genomics and clinical data, this workflow has the potential to facilitate personalized approaches to treat HGSOC.