Cargando…

Quantitative proteome analysis of Merkel cell carcinoma cell lines using SILAC

BACKGROUND: Merkel cell carcinoma (MCC) is an aggressive neuroendocrine tumour of the skin with growing incidence. To better understand the biology of this malignant disease, immortalized cell lines are used in research for in vitro experiments. However, a comprehensive quantitative proteome analysi...

Descripción completa

Detalles Bibliográficos
Autores principales: Kotowski, Ulana, Erović, Boban M., Schnöll, Julia, Stanek, Victoria, Janik, Stefan, Steurer, Martin, Mitulović, Goran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6921584/
https://www.ncbi.nlm.nih.gov/pubmed/31889939
http://dx.doi.org/10.1186/s12014-019-9263-z
Descripción
Sumario:BACKGROUND: Merkel cell carcinoma (MCC) is an aggressive neuroendocrine tumour of the skin with growing incidence. To better understand the biology of this malignant disease, immortalized cell lines are used in research for in vitro experiments. However, a comprehensive quantitative proteome analysis of these cell lines has not been performed so far. METHODS: Stable isotope labelling by amino acids in cell culture (SILAC) was applied to six MCC cell lines (BroLi, MKL-1, MKL-2, PeTa, WaGa, and MCC13). Following tryptic digest of labelled proteins, peptides were analysed by mass spectrometry. Proteome patterns of MCC cell lines were compared to the proteome profile of an immortalized keratinocyte cell line (HaCaT). RESULTS: In total, 142 proteins were upregulated and 43 proteins were downregulated. Altered proteins included mitoferrin-1, histone H2A type 1-H, protein-arginine deiminase type-6, heterogeneous nuclear ribonucleoproteins A2/B1, protein SLX4IP and clathrin light chain B. Furthermore, several proteins of the histone family and their variants were highly abundant in MCC cell lines. CONCLUSIONS: The results of this study present a new protein map of MCC and provide deeper insights in the biology of MCC. Data are available via ProteomeXchange with identifier PXD008181.