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Targeted Proteomics Predicts a Sustained Complete-Response after Transarterial Chemoembolization and Clinical Outcomes in Patients with Hepatocellular Carcinoma: A Prospective Cohort Study

Authors
Yu, Su JongKim, HyunsooMin, HophilSohn, AreumCho, Young YounYoo, Jeong-JuLee, Dong HyeonCho, Eun JuLee, Jeong-HoonGim, JungsooPark, TaesungKim, Yoon JunKim, Chung YongYoon, Jung-HwanKim, Youngsoo
Issue Date
Mar-2017
Publisher
AMER CHEMICAL SOC
Keywords
TACE; HCC; proteomics; prognostic biomarker; multiple reaction monitoring-mass spectrometry (MRM-MS)
Citation
JOURNAL OF PROTEOME RESEARCH, v.16, no.3, pp 1239 - 1248
Pages
10
Journal Title
JOURNAL OF PROTEOME RESEARCH
Volume
16
Number
3
Start Page
1239
End Page
1248
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/70817
DOI
10.1021/acs.jproteome.6b00833
ISSN
1535-3893
1535-3907
Abstract
This study was aimed to identify blood-based biomarkers to predict a sustained complete response (CR) after transarterial chemoembolization (TACE) using targeted proteomics. Consecutive patients with HCC who had undergone TACE were prospectively enrolled (training (n = 100) and validation set (n = 80)). Serum samples were obtained before and 6 months after TACE. Treatment responses were evaluated using the modified Response Evaluation Criteria in Solid Tumors (mRECIST). In the training set, the MRM-MS assay identified five marker candidate proteins (LRG1, APCS, BCHE, C7, and FCN3). When this five-marker panel was combined with the best-performing clinical variables (tumor number, baseline PIVKA, and baseline AFP), the resulting ensemble model had the highest area under the receiver operating curve (AUROC) value in predicting a sustained CR after TACE in the training and validation sets (0.881 and 0.813, respectively). Furthermore, the ensemble model was an independent predictor of rapid progression (hazard ratio (HR), 2.889; 95% confidence interval (CI), 1.612-5.178; P value < 0.001) and overall an unfavorable survival rate (HR, 1.985; 95% CI, 1.024-3.848; P value = 0.042) in the entire population by multivariate analysis. Targeted proteomics-based ensemble model can predict clinical outcomes after TACE. Therefore, this model can aid in determining the best candidates for TACE and the need for adjuvant therapy.
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