Introduction High grade serous ovarian carcinoma (HGSOC) is a highly lethal gynaecological malignancy. Bulk gene expression profiling has identified novel subgroups of HGSOC but only interrogates the average signal of cells within a tumour. Single cell RNA-sequencing (sc-RNAseq) enables the quantification of gene expression from individual cells, allowing assessment of potential chemoresistant tumour cells. To investigate the heterogenous landscape of HGSOC, we used sc-RNAseq to profile ∼80, 000 cells from six tumour specimens. Here we present a high-resolution spatial analysis of the HGSOC tumour microenvironment (TME) with further demonstration of the cellular subclonal phenotypes.

Methods Two patients with advanced stage HGSOC who were undergoing primary debulking surgery were recruited. Fresh tumour samples obtained from primary and metastatic sites were dissociated into single cells by automated enzymatic technique and sc-RNAseq performed using 10X Genomics. Sequenced libraries were analysed using bioinformatics tools including clustering, principle component analysis and geneset enrichment analysis.

Results The TME is comprised of cancer epithelial cells (CECs), fibroblasts, endothelial, myeloid, T-cells and B-cells with heterogeneous proportions across individual tumour samples. CECs subclustering revealed subpopulations of tumour cells related to epithelial-mesenchymal transition, oxidative phosphorylation and immunosuppression. We found functional programmes of cancer-associated fibroblasts (CAFs) including matrisome, proliferative and immunomodulatory. The immune cells were largely comprised of T-cells with a predilection for CD8+ T-cells and natural killer cells.

Conclusion Our work enriched the single cell repertoire of HGSOC transciptomic landscape and unravelled the heterogenous subpopulations of CECs, CAFs and immune cells which will provide a platform for identification of novel therapeutic targets.