Research Papers:

In-depth proteomic profiling of the uveal melanoma secretome

Martina Angi, Helen Kalirai, Samuel Prendergast, Deborah Simpson, Dean E. Hammond, Michele C. Madigan, Robert J. Beynon and Sarah E. Coupland _

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Oncotarget. 2016; 7:49623-49635. https://doi.org/10.18632/oncotarget.10418

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Martina Angi1,*, Helen Kalirai1,*, Samuel Prendergast1, Deborah Simpson2, Dean E. Hammond3, Michele C. Madigan4,5, Robert J. Beynon2, Sarah E. Coupland1

1Liverpool Ocular Oncology Research Group, Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, Liverpool, UK

2Centre for Proteome Research, Institute of Integrative Biology, University of Liverpool, Liverpool, UK

3Department of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK

4School of Optometry, University of New South Wales, New South Wales, Australia

5Save Sight Institute, Ophthalmology, University of Sydney, New South Wales, Australia

*These authors contributed equally to this work

Correspondence to:

Sarah E. Coupland, email: [email protected]

Keywords: uveal melanoma, melanocytes, proteomics, secretome, exosome

Received: April 22, 2016     Accepted: June 09, 2016     Published: July 06, 2016


Uveal melanoma (UM), the most common primary intraocular tumour in adults, is characterised by a high frequency of metastases to the liver, typically with a fatal outcome. Proteins secreted from cancer cells (‘secretome’) are biologically important molecules thought to contribute to tumour progression. We examined the UM secretome by applying a label-free nanoLCMS/MS proteomic approach to profile proteins secreted into culture media by primary UM tumours with a high− (HR; n = 11) or low− (LR; n = 4) metastatic risk, compared to normal choroidal melanocytes (NCM) from unaffected post-mortem eyes. Across the three groups, 1843 proteins were identified at a 1% false discovery rate; 758 of these by at least 3 unique peptides, and quantified. The majority (539/758, 71%) of proteins were classified as secreted either by classical (144, 19%), non-classical (43, 6%) or exosomal (352, 46%) mechanisms. Bioinformatic analyzes showed that the secretome composition reflects biological differences and similarities of the samples. Ingenuity® pathway analysis of the secreted protein dataset identified abundant proteins involved in cell proliferation-, growth- and movement. Hepatic fibrosis/hepatic stellate cell activation and the mTORC1-S6K signalling axis were among the most differentially regulated biological processes in UM as compared with NCM. Further analysis of proteins upregulated ≥ 2 in HR-UM only, identified exosomal proteins involved in extracellular matrix remodelling and cancer cell migration/invasion; as well as classically secreted proteins, possibly representing novel biomarkers of metastatic disease. In conclusion, UM secretome analysis identifies novel proteins and pathways that may contribute to metastatic development at distant sites, particularly in the liver.

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