Spatial transcriptomics reveals ovarian cancer subclones with distinct tumour microenvironments

High-grade serous ovarian carcinoma (HGSOC) is characterised by recurrence, chemotherapy resistance and overall poor prognosis. Genetic heterogeneity of tumour cells and the microenvironment of the tumour have been hypothesised as key determinants of treatment resistance and relapse. Here, using a combination of spatial and single cell transcriptomics (10x Visium and Chromium platforms), we examine tumour genetic heterogeneity and infiltrating populations of HGSOC samples from eight patients with variable response to neoadjuvant chemotherapy. The figure shows: a) HnE stains, b) gene expression-based clusters, c) Giotto tumour cell enrichment scores, and d) InferCNV clusters.

Tissue Dissociation and Storage Biases

Elena Denisenko, et al.

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. In this paper, we compared several methods to determine the benefits and drawbacks. The above figure (Figure 3 from the manuscript) highlights some of the differences.