Leanne de Kock

BACKGROUND: Single-cell RNA sequencing has been widely adopted to estimate the cellular composition of heterogeneous tissues and obtain transcriptional profiles of individual cells. Multiple approaches for optimal sample dissociation and storage of single cells have been proposed as have single-nuclei profiling methods. What has been lacking is a systematic comparison of their relative biases and benefits. RESULTS: Here, we compare gene expression and cellular composition of single-cell suspensions prepared from adult mouse kidney using two tissue dissociation protocols. For each sample, we also compare fresh cells to cryopreserved and methanol-fixed cells. Lastly, we compare this single-cell data to that generated using three single-nucleus RNA sequencing workflows. Our data confirms prior reports that digestion on ice avoids the stress response observed with 37 °C dissociation. It also reveals cell types more abundant either in the cold or warm dissociations that may represent populations that require gentler or harsher conditions to be released intact. For cell storage, cryopreservation of dissociated cells results in a major loss of epithelial cell types; in contrast, methanol fixation maintains the cellular composition but suffers from ambient RNA leakage. Finally, cell type composition differences are observed between single-cell and single-nucleus RNA sequencing libraries. In particular, we note an underrepresentation of T, B, and NK lymphocytes in the single-nucleus libraries. CONCLUSIONS: Systematic comparison of recovered cell types and their transcriptional profiles across the workflows has highlighted protocol-specific biases and thus enables researchers starting single-cell experiments to make an informed choice.

Ovarian Sertoli-Leydig cell tumors (SLCTs) are uncommon sex cord-stromal tumors associated with both germ-line and somatic DICER1 mutations, the frequency of which has varied widely in different studies (0% to 62.5%). The current World Health Organization Classification includes 3 histologic types of SLCTs (well-differentiated, moderately differentiated, and poorly differentiated); heterologous elements and/or retiform patterns may be present in moderately and poorly differentiated neoplasms. We investigated the frequency of DICER1 mutations in a series of 38 ovarian tumors initially diagnosed as SLCTs, and explored whether identified mutations were associated with specific morphologic features. Specialist pathology review performed blinded to molecular results confirmed 34 tumors to be SLCTs (22 moderately differentiated, 8 poorly differentiated; 4 well-differentiated), while the remaining 4 neoplasms were considered not to represent SLCTs. Of the 34 cases diagnosed as SLCTs, 30 (88%) harbored ≥1 DICER1 mutation. All 30 moderately differentiated/poorly differentiated SLCTs contained mutations, but we did not find deleterious DICER1 mutations in the 4 well-differentiated SLCTs. Our study reports the highest DICER1 mutation frequency to date in SLCTs, with 100% of moderately differentiated and poorly differentiated tumors being DICER1-mutated. This suggests that DICER1 mutation may be a defining feature of these neoplasms. Although the number of cases is limited, well-differentiated SLCTs appear to be DICER1-independent. Moderately differentiated and poorly differentiated SLCT components often coexist with each other and form part of a spectrum, while well-differentiated SLCTs usually occur in pure form, suggesting that fundamentally, these represent 2 separate and independent tumor types with a different pathogenesis. We suggest that all patients with ovarian SLCTs undergo germ-line DICER1 mutation testing.

High-grade serous ovarian carcinoma (HGSOC) is genetically unstable and characterised by the presence of subclones with distinct genotypes. Intratumoural heterogeneity is linked to recurrence, chemotherapy resistance, and poor prognosis. Here, we use spatial transcriptomics to identify HGSOC subclones and study their association with infiltrating cell populations. Visium spatial transcriptomics reveals multiple tumour subclones with different copy number alterations present within individual tumour sections. These subclones differentially express various ligands and receptors and are predicted to differentially associate with different stromal and immune cell populations. In one sample, CosMx single molecule imaging reveals subclones differentially associating with immune cell populations, fibroblasts, and endothelial cells. Cell-to-cell communication analysis identifies subclone-specific signalling to stromal and immune cells and multiple subclone-specific autocrine loops. Our study highlights the high degree of subclonal heterogeneity in HGSOC and suggests that subclone-specific ligand and receptor expression patterns likely modulate how HGSOC cells interact with their local microenvironment.