Description

Massively parallel RNA sequencing of single cells reveals potential drug targets in high-grade serous ovarian cancer

Erdogan Pekcan Erkan¹, Jun Dai¹, Kaiyang Zhang², Katja Kaipio³, Tarja Lamminen³, Kaisa Huhtinen³, Johanna Hynninen⁴, Seija Grénman⁴, Olli Carpén⁵, Sampsa Hautaniemi², Anna Vähärautio¹

¹Department of Medical Genetics, Medicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland; ²Genome-Scale Biology Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland; ³Department of Pathology, Medicity Research Unit, University of Turku and Turku University Hospital, Turku, Finland; ⁴Obstetrics and Gynecology, University of Turku and Turku University Hospital, Turku, Finland; ⁵Helsinki Biobank, University of Helsinki and Helsinki University Hospital, Helsinki, Finland

High-grade serous ovarian cancer (HGSOC) is characterized by high recurrence rate and intratumoral heterogeneity. Not all patients with HGSOC respond to platinum-based first-line therapy, and novel therapeutic agents are being tested in clinical trials. We carried out droplet-based RNA sequencing on single cells that were freshly dissociated from a tumor specimen to answer two major questions: 1) Which cell populations can be found in HGSOC, and 2) what are the differences between transcriptomic profiles of different cell populations. The preliminary RNA sequencing data revealed a putative cancer stem-like cell population, which expressed several members of the aldehyde dehydrogenase family, POUF51, PROM2, and NOTCH4. We also analyzed expression levels of targets for i) FDA-approved drugs for ovarian cancer and ii) drugs that are currently in clinical trials. The putative cancer stem-like cell population expressed high levels of 30 drug targets. We are currently collecting additional tumor specimens, and also starting functional characterization of these genes in HGSOC primary cells and cell lines. Overall, massively parallel RNA sequencing of single cells from HGSOC patients provides invaluable information on intratumoral heterogeneity, and can be used to identify vulnerabilities of cancer cells. This opens new avenues to develop treatment strategies tailored for individual HGSOC patients.