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Proteomics of Primary Uveal Melanoma: Insights into Metastasis and Protein Biomarkers.
Jang, Geeng-Fu; Crabb, Jack S; Hu, Bo; Willard, Belinda; Kalirai, Helen; Singh, Arun D; Coupland, Sarah E; Crabb, John W.
Afiliación
  • Jang GF; Cole Eye Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Crabb JS; Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Hu B; Cole Eye Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Willard B; Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Kalirai H; Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Singh AD; Proteomics and Metabolomics Facility, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
  • Coupland SE; Liverpool Ocular Oncology Research Centre, Department of Molecular and Clinical Cancer Medicine, University of Liverpool, William Henry Duncan Building, West Derby Street, Liverpool L7 8TX, UK.
  • Crabb JW; Cole Eye Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
Cancers (Basel) ; 13(14)2021 Jul 14.
Article en En | MEDLINE | ID: mdl-34298739
ABSTRACT
Uveal melanoma metastases are lethal and remain incurable. A quantitative proteomic analysis of 53 metastasizing and 47 non-metastasizing primary uveal melanoma (pUM) was pursued for insights into UM metastasis and protein biomarkers. The metastatic status of the pUM specimens was defined based on clinical data, survival histories, prognostic analyses, and liver histopathology. LC MS/MS iTRAQ technology, the Mascot search engine, and the UniProt human database were used to identify and quantify pUM proteins relative to the normal choroid excised from UM donor eyes. The determined proteomes of all 100 tumors were very similar, encompassing a total of 3935 pUM proteins. Proteins differentially expressed (DE) between metastasizing and non-metastasizing pUM (n = 402) were employed in bioinformatic analyses that predicted significant differences in the immune system between metastasizing and non-metastasizing pUM. The immune proteins (n = 778) identified in this study support the immune-suppressive nature and low abundance of immune checkpoint regulators in pUM, and suggest CDH1, HLA-DPA1, and several DE immune kinases and phosphatases as possible candidates for immune therapy checkpoint blockade. Prediction modeling identified 32 proteins capable of predicting metastasizing versus non-metastasizing pUM with 93% discriminatory accuracy, supporting the potential for protein-based prognostic methods for detecting UM metastasis.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Cancers (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Cancers (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos
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