Melanoblast transcriptome analysis reveals pathways promoting melanoma metastasis

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作者
Kerrie L. Marie
Antonella Sassano
Howard H. Yang
Aleksandra M. Michalowski
Helen T. Michael
Theresa Guo
Yien Che Tsai
Allan M. Weissman
Maxwell P. Lee
Lisa M. Jenkins
M. Raza Zaidi
Eva Pérez-Guijarro
Chi-Ping Day
Kris Ylaya
Stephen M. Hewitt
Nimit L. Patel
Heinz Arnheiter
Sean Davis
Paul S. Meltzer
Glenn Merlino
Pravin J. Mishra
机构
[1] National Institutes of Health,Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute
[2] Johns Hopkins Medical Institutions,Department of Otolaryngology—Head and Neck Surgery, Sidney Kimmel Comprehensive Cancer Center
[3] National Cancer Institute,Laboratory of Protein Dynamics and Signaling, Center for Cancer Research
[4] National Institutes of Health,Laboratory of Cell Biology, Center for Cancer Research, National Cancer Institute
[5] Lewis Katz School of Medicine at Temple University,Fels Institute for Cancer Research and Molecular Biology
[6] National Institutes of Health,Experimental Pathology Laboratory, Center for Cancer Research, National Cancer Institute
[7] Leidos Biomedical Research Inc.,Small Animal Imaging Program, Frederick National Laboratory for Cancer Research
[8] National Institute of Health,Mammalian Development Section, National Institute of Neurological Disorders and Stroke
[9] National Institutes of Health,Genetics Branch, Center for Cancer Research, National Cancer Institute
[10] Ohio State University Comprehensive Cancer Center,James Cancer Hospital and Solove Research Institute
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摘要
Cutaneous malignant melanoma is an aggressive cancer of melanocytes with a strong propensity to metastasize. We posit that melanoma cells acquire metastatic capability by adopting an embryonic-like phenotype, and that a lineage approach would uncover metastatic melanoma biology. Using a genetically engineered mouse model to generate a rich melanoblast transcriptome dataset, we identify melanoblast-specific genes whose expression contribute to metastatic competence and derive a 43-gene signature that predicts patient survival. We identify a melanoblast gene, KDELR3, whose loss impairs experimental metastasis. In contrast, KDELR1 deficiency enhances metastasis, providing the first example of different disease etiologies within the KDELR-family of retrograde transporters. We show that KDELR3 regulates the metastasis suppressor, KAI1, and report an interaction with the E3 ubiquitin-protein ligase gp78, a regulator of KAI1 degradation. Our work demonstrates that the melanoblast transcriptome can be mined to uncover targetable pathways for melanoma therapy.
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