Chen Zhao, Yi-Te Lee, Andrew Melehy, Minhyung Kim, Jacqueline Ziqian Yang, Ceng Zhang, Jina Kim, Ryan Y Zhang, Junseok Lee, Hyoyong Kim, Yong Ju, Yuan-Jen Tsai, Xianghong Jasmine Zhou, Steven-Huy B Han, Saeed Sadeghi, Richard S Finn, Sammy Saab, David S Lu, Jason Chiang, Jae-Ho Park, Todd V Brennan, Steven A Wisel, Manaf Alsudaney, Alexander Kuo, Walid S Ayoub, Hyunseok Kim, Hirsh D Trivedi, Yun Wang, Aarshi Vipani, Irene K Kim, Tsuyoshi Todo, Justin A Steggerda, Georgios Voidonikolas, Kambiz Kosari, Nicholas N Nissen, Rola Saouaf, Amit G Singal, Myung Shin Sim, David A Elashoff, Sungyong You, Vatche G Agopian, Ju Dong Yang, Hsian-Rong Tseng, Yazhen Zhu
{"title":"Extracellular vesicle digital scoring assay for assessment of treatment responses in hepatocellular carcinoma patients.","authors":"Chen Zhao, Yi-Te Lee, Andrew Melehy, Minhyung Kim, Jacqueline Ziqian Yang, Ceng Zhang, Jina Kim, Ryan Y Zhang, Junseok Lee, Hyoyong Kim, Yong Ju, Yuan-Jen Tsai, Xianghong Jasmine Zhou, Steven-Huy B Han, Saeed Sadeghi, Richard S Finn, Sammy Saab, David S Lu, Jason Chiang, Jae-Ho Park, Todd V Brennan, Steven A Wisel, Manaf Alsudaney, Alexander Kuo, Walid S Ayoub, Hyunseok Kim, Hirsh D Trivedi, Yun Wang, Aarshi Vipani, Irene K Kim, Tsuyoshi Todo, Justin A Steggerda, Georgios Voidonikolas, Kambiz Kosari, Nicholas N Nissen, Rola Saouaf, Amit G Singal, Myung Shin Sim, David A Elashoff, Sungyong You, Vatche G Agopian, Ju Dong Yang, Hsian-Rong Tseng, Yazhen Zhu","doi":"10.1186/s13046-025-03379-7","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>There are no validated biomarkers for assessing hepatocellular carcinoma (HCC) treatment response (TR). Extracellular vesicles (EVs) are promising circulating biomarkers that may detect minimal residual disease in patients with treated HCC.</p><p><strong>Methods: </strong>We developed the HCC EV TR Score using HCC EV Digital Scoring Assay involving click chemistry-mediated enrichment of HCC EVs, followed by absolute quantification of HCC EV-specific genes by RT-digital PCR. Six HCC EV-specific genes were selected and validated through i) a comprehensive data analysis pipeline with an unprecedentedly large collection of liver transcriptome datasets (n = 9,160), ii) RNAscope validation on HCC tissues (n = 6), and iii) a pilot study on early- or intermediate-stage HCC and liver cirrhosis patients (n = 70). The performance of HCC EV TR Score was assessed in a phase-2 retrospective case-control study (n = 100).</p><p><strong>Results: </strong>HCC EV TR Scores, calculated from pre- and post-treatment plasma samples in the phase-2 case-control study, accurately differentiated post-treatment viable from nonviable HCC in the training (area under the ROC curve [AUROC] of 0.90, n = 49) and validation set (AUROC of 0.88, n = 51). At an optimal cutoff of 0.76 identified in the training set, HCC EV TR Score had high accuracy in detecting viable tumors (sensitivity: 76.5%, specificity: 88.2%) and found residual disease not initially observed on MRI in six patients with a median lead time of 63 days.</p><p><strong>Conclusions: </strong>This EV-based digital scoring approach shows great promise to augment cross-sectional imaging for the assessment of HCC treatment response.</p>","PeriodicalId":50199,"journal":{"name":"Journal of Experimental & Clinical Cancer Research","volume":"44 1","pages":"136"},"PeriodicalIF":11.4000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12044846/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Experimental & Clinical Cancer Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13046-025-03379-7","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: There are no validated biomarkers for assessing hepatocellular carcinoma (HCC) treatment response (TR). Extracellular vesicles (EVs) are promising circulating biomarkers that may detect minimal residual disease in patients with treated HCC.
Methods: We developed the HCC EV TR Score using HCC EV Digital Scoring Assay involving click chemistry-mediated enrichment of HCC EVs, followed by absolute quantification of HCC EV-specific genes by RT-digital PCR. Six HCC EV-specific genes were selected and validated through i) a comprehensive data analysis pipeline with an unprecedentedly large collection of liver transcriptome datasets (n = 9,160), ii) RNAscope validation on HCC tissues (n = 6), and iii) a pilot study on early- or intermediate-stage HCC and liver cirrhosis patients (n = 70). The performance of HCC EV TR Score was assessed in a phase-2 retrospective case-control study (n = 100).
Results: HCC EV TR Scores, calculated from pre- and post-treatment plasma samples in the phase-2 case-control study, accurately differentiated post-treatment viable from nonviable HCC in the training (area under the ROC curve [AUROC] of 0.90, n = 49) and validation set (AUROC of 0.88, n = 51). At an optimal cutoff of 0.76 identified in the training set, HCC EV TR Score had high accuracy in detecting viable tumors (sensitivity: 76.5%, specificity: 88.2%) and found residual disease not initially observed on MRI in six patients with a median lead time of 63 days.
Conclusions: This EV-based digital scoring approach shows great promise to augment cross-sectional imaging for the assessment of HCC treatment response.
期刊介绍:
The Journal of Experimental & Clinical Cancer Research is an esteemed peer-reviewed publication that focuses on cancer research, encompassing everything from fundamental discoveries to practical applications.
We welcome submissions that showcase groundbreaking advancements in the field of cancer research, especially those that bridge the gap between laboratory findings and clinical implementation. Our goal is to foster a deeper understanding of cancer, improve prevention and detection strategies, facilitate accurate diagnosis, and enhance treatment options.
We are particularly interested in manuscripts that shed light on the mechanisms behind the development and progression of cancer, including metastasis. Additionally, we encourage submissions that explore molecular alterations or biomarkers that can help predict the efficacy of different treatments or identify drug resistance. Translational research related to targeted therapies, personalized medicine, tumor immunotherapy, and innovative approaches applicable to clinical investigations are also of great interest to us.
We provide a platform for the dissemination of large-scale molecular characterizations of human tumors and encourage researchers to share their insights, discoveries, and methodologies with the wider scientific community.
By publishing high-quality research articles, reviews, and commentaries, the Journal of Experimental & Clinical Cancer Research strives to contribute to the continuous improvement of cancer care and make a meaningful impact on patients' lives.