Multicellular network analysis of melanoma heterogeneity by scRNA-seq.

Objective: Melanoma neoplasia is a complicated process. Not only melanocytes are involved, stromal cells and immune cells would also regulate cancer development. However, the cell type composition and tumor immune microenvironment of melanoma are poorly understood.

Method: Here we report a map of the cellular landscape of human melanoma via analyzing published single-cell RNA sequencing (scRNA-seq) dataset. Transcriptional profiles of 4645 cells obtained from 19 melanoma tissues were dissected.

Result: Using gene expression patterns and flow cytometry, 8 discrete cell populations were identified including endothelial cells (ECs), cancer related fibroblasts (CAFs), macrophages, B cells, T cells (NK cells), memory T cells (MTCs), melanocytes and podocytes. By constructing the cell-specific network (CSN) for each cell population, scRNA-seq data can be used for clustering and pseudo-trajectory analyzing from network perspective. In addition, the differentially expressed genes (DEGs) between malignant and non-malignant melanocytes were identified and analyzed together with clinical data from The Cancer Genome Atlas (TCGA).

Conclusion: This study shows a comprehensive view of melanoma at the single cell resolution which outlines the characteristics of resident cells in tumor. Particular, it provides an immune microenvironment map of melanoma.