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2022-RA-1136-ESGO A single-cell map of rare ovarian cancer
  1. Tina Laga1,2,
  2. Pieter Busschaert2,3,
  3. Siel Olbrecht1,
  4. Liselore Loverix1,2,
  5. Francesca Lodi2,
  6. Thaïs Baert1,
  7. Toon Van Gorp1,
  8. Anne-Sophie Van Rompuy4,
  9. Ignace Vergote1,
  10. Diether Lambrechts2 and
  11. Els Van Nieuwenhuysen1
  1. 1Department of Gynecology and Obstetrics and Leuven Cancer Institute, Division of Gynecological Oncology, University Hospital Leuven, Belgium
  2. 2VIB Center for Cancer Biology, KU Leuven, Belgium
  3. 3Gynaecological Oncology, Division of Gynecological Oncology, University Hospital Leuven, Belgium
  4. 4Department of Pathology, University hospital of Leuven, Leuven, Belgium


Introduction/Background Non-epithelial ovarian tumours encompass a heterogeneous group of neoplasms that mainly include germ cell tumours (GCT) and sex-cord stromal tumours (SCST). These tumours are characterised by an extensive inter- and intratumoral heterogeneity. By applying single-cell RNA sequencing (scRNA-seq), we attempt to elucidate the complexity of the tumour microenvironment.

Methodology We performed scRNA-seq of 66 919 cells collected from 12 patients. Most fresh tissue samples were derived from SCST (n=9), including 7 adult granulosa cell tumours, 1 primary juvenile granulosa cell tumour and 1 primary Sertoli-Leydig cell tumour. Three samples were obtained from treatment-naïve GCT (2 immature teratomas and one dysgerminoma). For each phenotype of tumour cells, immune cells, endothelial cells and cancer-associated fibroblasts, we identified specific transcriptomic markers.

Results Based on differential expression analysis and expression of transcriptomic markers, we identified 27 clusters consisting of 9 tumour cell and 18 stromal cell clusters. The first results of subcluster analysis revealed nearly absence of B cells in all granulosa cell tumours. In addition, the immune cell subcluster mainly consists of T cells derived from the dysgerminoma (58%) and Sertoli-Leydig cell (20%) samples. Further characterisation and differentiation of distinct subclusters is currently ongoing and will be presented.

Conclusion With this analysis we aim to generate a publicly accessible comprehensive blueprint of the tumour micro-environment, aiding other researchers to gain high-resolution insights in the heterogeneity and complexity of these rare ovarian cancers.

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