4.6 Article

iTRAQ Quantitative Proteomic Comparison of Metastatic and Non-Metastatic Uveal Melanoma Tumors

Journal

PLOS ONE
Volume 10, Issue 8, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0135543

Keywords

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Funding

  1. National Institutes of Health [EY018147, EY14239, EY15638, EY21840, EY022134]
  2. Ohio Biomedical Research and Technology Transfer (BRTT) [05-29]
  3. Challenge Grant from Research to Prevent Blindness (RPB)
  4. RPB Senior Investigator Award
  5. Cleveland Clinic Foundation

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Background Uveal melanoma is the most common malignancy of the adult eye. The overall mortality rate is high because this aggressive cancer often metastasizes before ophthalmic diagnosis. Quantitative proteomic analysis of primary metastasizing and non-metastasizing tumors was pursued for insights into mechanisms and biomarkers of uveal melanoma metastasis. Methods Eight metastatic and 7 non-metastatic human primary uveal melanoma tumors were analyzed by LC MS/MS iTRAQ technology with Bruch's membrane/choroid complex from normal postmortem eyes as control tissue. Tryptic peptides from tumor and control proteins were labeled with iTRAQ tags, fractionated by cation exchange chromatography, and analyzed by LC MS/MS. Protein identification utilized the Mascot search engine and the human Uni-Prot/Swiss-Protein database with false discovery <= 1%; protein quantitation utilized the Mascot weighted average method. Proteins designated differentially expressed exhibited quantitative differences (p <= 0.05, t-test) in a training set of five metastatic and five non-metastatic tumors. Logistic regression models developed from the training set were used to classify the metastatic status of five independent tumors. Results Of 1644 proteins identified and quantified in 5 metastatic and 5 non-metastatic tumors, 12 proteins were found uniquely in >= 3 metastatic tumors, 28 were found significantly elevated and 30 significantly decreased only in metastatic tumors, and 31 were designated differentially expressed between metastatic and non-metastatic tumors. Logistic regression modeling of differentially expressed collagen alpha-3(VI) and heat shock protein beta-1 allowed correct prediction of metastasis status for each of five independent tumor specimens. Conclusions The present data provide new clues to molecular differences in metastatic and non-metastatic uveal melanoma tumors. While sample size is limited and validation required, the results support collagen alpha-3(VI) and heat shock protein beta-1 as candidate biomarkers of uveal melanoma metastasis and establish a quantitative proteomic database for uveal melanoma primary tumors.

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