2022-RA-1136-ESGO A single-cell map of rare ovarian cancer. (20th October 2022)

• Record Type: Journal Article
• Authors: Laga, Tina; Busschaert, Pieter; Olbrecht, Siel; Loverix, Liselore; Lodi, Francesca; Baert, Thaïs; Gorp, Toon Van; Rompuy, Anne-Sophie Van; Vergote, Ignace; Lambrechts, Diether; Nieuwenhuysen, Els Van
• Is Part Of: International journal of gynecological cancer. Volume 32(2022)Supplement 2
• Page Start: A412
• Page End: A413
• Publication Date: 2022-10-20
• Subjects: Generative organs, Female -- Cancer -- Periodicals; 616.99465
• DOI: 10.1136/ijgc-2022-ESGO.884
• Languages: English
• ISSNs: 1048-891X

Abstract

Abstract : 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.