Pseudotime Dynamics in Melanoma Single-Cell Transcriptomes Reveals Different Mechanisms of Tumor Progression.

Abstract:

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.

Health Atlas ID: 7QFXD9A47T-4

PubMed ID: 29614062

Projects: Leipzig Melanoma Studies

Publication type: Not specified

Journal: Biology (Basel)

Human Diseases: Melanoma

Citation: Biology (Basel). 2018 Apr 3;7(2). pii: biology7020023. doi: 10.3390/biology7020023.

Date Published: 3rd Apr 2018

Registered Mode: by PubMed ID

Authors: H. Loeffler-Wirth, H. Binder, E. Willscher, T. Gerber, M. Kunz

Help
help Creator
Creators
Not specified
Submitter
Activity

Views: 1316

Created: 6th May 2019 at 13:41

help Attributions

None

Related items

Powered by
(v.1.11.master)
Copyright © 2008 - 2020 The University of Manchester and HITS gGmbH
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig