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

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 = 8...

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Veröffentlicht in:Journal of proteome research 2017-03, Vol.16 (3), p.1239-1248
Hauptverfasser: Yu, Su Jong, Kim, Hyunsoo, Min, Hophil, Sohn, Areum, Cho, Young Youn, Yoo, Jeong-Ju, Lee, Dong Hyeon, Cho, Eun Ju, Lee, Jeong-Hoon, Gim, Jungsoo, Park, Taesung, Kim, Yoon Jun, Kim, Chung Yong, Yoon, Jung-Hwan, Kim, Youngsoo
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container_end_page 1248
container_issue 3
container_start_page 1239
container_title Journal of proteome research
container_volume 16
creator Yu, Su Jong
Kim, Hyunsoo
Min, Hophil
Sohn, Areum
Cho, Young Youn
Yoo, Jeong-Ju
Lee, Dong Hyeon
Cho, Eun Ju
Lee, Jeong-Hoon
Gim, Jungsoo
Park, Taesung
Kim, Yoon Jun
Kim, Chung Yong
Yoon, Jung-Hwan
Kim, Youngsoo
description 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.
doi_str_mv 10.1021/acs.jproteome.6b00833
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Proteome Res</addtitle><description>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). 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Proteome Res</addtitle><date>2017-03-03</date><risdate>2017</risdate><volume>16</volume><issue>3</issue><spage>1239</spage><epage>1248</epage><pages>1239-1248</pages><issn>1535-3893</issn><eissn>1535-3907</eissn><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 &lt; 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.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>28112944</pmid><doi>10.1021/acs.jproteome.6b00833</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-8881-0662</orcidid></addata></record>
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subjects Biomarkers, Tumor - blood
Carcinoma, Hepatocellular - blood
Carcinoma, Hepatocellular - mortality
Carcinoma, Hepatocellular - therapy
Chemoembolization, Therapeutic - methods
Cohort Studies
Humans
Prognosis
Prospective Studies
Proteomics - methods
Supervised Machine Learning
Treatment Outcome
title Targeted Proteomics Predicts a Sustained Complete-Response after Transarterial Chemoembolization and Clinical Outcomes in Patients with Hepatocellular Carcinoma: A Prospective Cohort Study
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