Pseudotime Dynamics in Melanoma Single-Cell Transcriptomes Reveals Different Mechanisms of Tumor Progression.
Henry Loeffler-Wirth, Hans Binder, Edith Willscher, Tobias Gerber, Manfred Kunz
Author Information
Henry Loeffler-Wirth: Interdisciplinary Center for Bioinformatics, University of Leipzig, 04107 Leipzig, Germany. wirth@izbi.uni-leipzig.de.
Hans Binder: Interdisciplinary Center for Bioinformatics, University of Leipzig, 04107 Leipzig, Germany. binder@izbi.uni-leipzig.de.
Edith Willscher: Interdisciplinary Center for Bioinformatics, University of Leipzig, 04107 Leipzig, Germany. willscher@izbi.uni-leipzig.de.
Tobias Gerber: Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology Leipzig, 04103 Leipzig, Germany. tobias_gerber@eva.mpg.de.
Manfred Kunz: Department of Dermatology, Venereology and Allergology, University of Leipzig, 04103 Leipzig, Germany. manfred.kunz@medizin.uni-leipzig.de.
Single-cell transcriptomics has been used for analysis of heterogeneous populations of cells during developmental processes and for analysis of tumor cell heterogeneity. More recently, analysis of pseudotime (PT) dynamics of heterogeneous cell populations has been established as a powerful concept to study developmental processes. Here we perform PT analysis of 3 melanoma short-term cultures with different genetic backgrounds to study specific and concordant properties of PT dynamics of selected cellular programs with impact on melanoma progression. Overall, in our setting of melanoma cells PT dynamics towards higher tumor malignancy appears to be largely driven by cell cycle genes. Single cells of all three short-term cultures show a bipolar expression of microphthalmia-associated transcription factor (MITF) and AXL receptor tyrosine kinase (AXL) signatures. Furthermore, opposing gene expression changes are observed for genes regulated by epigenetic mechanisms suggesting epigenetic reprogramming during melanoma progression. The three melanoma short-term cultures show common themes of PT dynamics such as a stromal signature at initiation, bipolar expression of the MITF/AXL signature and opposing regulation of poised and activated promoters. Differences are observed at the late stage of PT dynamics with high, low or intermediate MITF and anticorrelated AXL signatures. These findings may help to identify targets for interference at different stages of tumor progression.
