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KMID : 1141520200350010132
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Endocrinology and Metabolism
2020 Volume.35 No. 1 p.132 ~ p.141
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Protein Expression of Cyclin B1, Transferrin Receptor, and Fibronectin Is Correlated with the Prognosis of Adrenal Cortical Carcinoma
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Moon Sun-Joon
Kim Jung-Hee
Kong Sung-Hye
Shin Chan-Soo
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Abstract
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Background: Adrenal cortical carcinoma (ACC) is a rare cancer with a variable prognosis. Several prognostic factors of ACC have been previously reported, but a proteomic analysis has not yet been performed. This study aimed to investigate prognostic biomarkers for ACC using a proteomic approach.
Methods: We used reverse-phase protein array data from The Cancer Proteome Atlas, and identified differentially expressed proteins in metastatic ACCs. Multivariate Cox regression analysis adjusted by age and staging was used for survival analysis, and the C-index and category-free net reclassification improvement (cfNRI) were utilized to evaluate additive prognostic value.
Results: In 46 patients with ACC, cyclin B1, transferrin receptor (TfR1), and fibronectin were significantly overexpressed in patients with distant metastasis. In multivariate models, high expression of cyclin B1 and TfR1 was significantly associated with mortality (hazard ratio [HR], 6.13; 95% confidence interval [CI], 1.02 to 36.7; and HR, 6.59; 95% CI, 1.14 to 38.2; respectively), whereas high fibronectin expression was not (HR, 3.92; 95% CI, 0.75 to 20.4). Combinations of high cyclin B1/high TfR1, high cyclin B1/high fibronectin, and high TfR1/high fibronectin were strongly associated with mortality ([HR, 13.72; 95% CI, 1.89 to 99.66], [HR, 9.22; 95% CI, 1.34 to 63.55], and [HR, 18.59; 95% CI, 2.54 to 135.88], respectively). In reclassification analyses, cyclin B1, TfR1, fibronectin, and combinations thereof improved the prognostic performance (C-index, 0.78 to 0.82?0.86; cfNRI, all P values <0.05).
Conclusion: In ACC patients, the overexpression of cyclin B1, TfR1, and fibronectin and combinations thereof were associated with poor prognosis.
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KEYWORD
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Adrenocortical carcinoma, Protein array analysis, Proteomics, Prognosis
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