English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

RNA-seq analysis identifies different transcriptomic types and developmental trajectories of primary melanomas

MPS-Authors
/persons/resource/persons72638

Dannemann,  Michael       
The Minerva Research Group for Bioinformatics, Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Max Planck Society;
Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Max Planck Society;

Kelso,  Janet
The Minerva Research Group for Bioinformatics, Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Max Planck Society;
Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Max Planck Society;

/persons/resource/persons72877

Nickel,  Birgit
Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Max Planck Society;

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Kunz, M., Löffler-Wirth, H., Dannemann, M., Willscher, E., Doose, G., Kelso, J., et al. (2018). RNA-seq analysis identifies different transcriptomic types and developmental trajectories of primary melanomas. Oncogene, 37, 6136-6151. doi:0.1038/s41388-018-0385-y.


Cite as: https://hdl.handle.net/21.11116/0000-0002-9E0C-0
Abstract
Recent studies revealed trajectories of mutational events in early melanomagenesis, but the accompanying changes in gene expression are far less understood. Therefore, we performed a comprehensive RNA-seq analysis of laser-microdissected melanocytic nevi (n = 23) and primary melanoma samples (n = 57) and characterized the molecular mechanisms of early melanoma development. Using self-organizing maps, unsupervised clustering, and analysis of pseudotime (PT) dynamics to identify evolutionary trajectories, we describe here two transcriptomic types of melanocytic nevi (N1 and N2) and primary melanomas (M1 and M2). N1/M1 lesions are characterized by pigmentation-type and MITF gene signatures, and a high prevalence of NRAS mutations in M1 melanomas. N2/M2 lesions are characterized by inflammatory-type and AXL gene signatures with an equal distribution of wild-type and mutated BRAF and low prevalence of NRAS mutations in M2 melanomas. Interestingly, N1 nevi and M1 melanomas and N2 nevi and M2 melanomas, respectively, cluster together, but there is no clustering in a stage-dependent manner. Transcriptional signatures of M1 melanomas harbor signatures of BRAF/MEK inhibitor resistance and M2 melanomas harbor signatures of anti-PD-1 antibody treatment resistance. Pseudotime dynamics of nevus and melanoma samples are suggestive for a switch-like immune-escape mechanism in melanoma development with downregulation of immune genes paralleled by an increasing expression of a cell cycle signature in late-stage melanomas. Taken together, the transcriptome analysis identifies gene signatures and mechanisms underlying development of melanoma in early and late stages with relevance for diagnostics and therapy.