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J. Exp. Clin. Cancer Res., Published: 01 May 2025 | https://doi.org/10.1186/s13046-025-03379-7
Extracellular vesicle digital scoring assay for assessment of treatment responses in hepatocellular carcinoma patients
Chen Zhao1,2,3, Yi‑Te Lee4, Andrew Melehy5, Minhyung Kim6, Jacqueline Ziqian Yang1,2, Ceng Zhang2, Jina Kim6, Ryan Y. Zhang2, Junseok Lee2, Hyoyong Kim2, Yong Ju2, Yuan‑Jen Tsai2,7, Xianghong Jasmine Zhou1, Steven‑Huy B. Han8, Saeed Sadeghi8, Richard S. Finn8, Sammy Saab8, David S. Lu9, Jason Chiang9, Jae‑Ho Park4, Todd V. Brennan10,11, Steven A. Wisel10,11, Manaf Alsudaney11, Alexander Kuo4,11, Walid S. Ayoub4,11, Hyunseok Kim4,11, Hirsh D. Trivedi4,11, Yun Wang4,11, Aarshi Vipani4,11, Irene K. Kim11, Tsuyoshi Todo11, Justin A. Steggerda11, Georgios Voidonikolas11, Kambiz Kosari11, Nicholas N. Nissen11, Rola Saouaf12, Amit G. Singal13, Myung Shin Sim14, David A. Elashof8, Sungyong You6,15*, Vatche G. Agopian5,16*, Ju Dong Yang4,11,15*, Hsian‑Rong Tseng2,16* and Yazhen Zhu1,2,16*
1Department of Pathology and Laboratory Medicine, David Gefen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.
2Department of Molecular and Medical Pharmacology, California Nanosystems Institute, Crump Institute for Molecular Imaging, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.
3Cancer Center, Renmin Hospital of Wuhan University, Wuhan 430060, People’s Republic of China.
4Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
5Department of Surgery, David Gefen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.
6Department of Urology and Computational Bio‑medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
7Department of Family Medicine, Taipei Medical University Hospital, Taipei 110301, Taiwan.
8Department of Medicine, David Gefen School of Medicine, University of California, Los Angles (UCLA), Los Angeles, CA 90095, USA.
9Department of Interventional Radiology, David Gefen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.
10Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
11Comprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
12Department of Radiology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
13Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
14Department of Medicine Statistics Core, David Gefen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.
15Cedars‑Sinai Medical Center, Samuel Oschin Comprehensive Cancer Institute, Los Angeles, CA 90048, USA.
16Jonsson Comprehensive Cancer Center, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.
*Correspondence: Sungyong You, Vatche G. Agopian, Ju Dong Yang, Hsian‑Rong Tseng, Yazhen Zhu
1Department of Pathology and Laboratory Medicine, David Gefen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.
2Department of Molecular and Medical Pharmacology, California Nanosystems Institute, Crump Institute for Molecular Imaging, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.
3Cancer Center, Renmin Hospital of Wuhan University, Wuhan 430060, People’s Republic of China.
4Karsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
5Department of Surgery, David Gefen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.
6Department of Urology and Computational Bio‑medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
7Department of Family Medicine, Taipei Medical University Hospital, Taipei 110301, Taiwan.
8Department of Medicine, David Gefen School of Medicine, University of California, Los Angles (UCLA), Los Angeles, CA 90095, USA.
9Department of Interventional Radiology, David Gefen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.
10Department of Surgery, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
11Comprehensive Transplant Center, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
12Department of Radiology, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
13Division of Digestive and Liver Diseases, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.
14Department of Medicine Statistics Core, David Gefen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.
15Cedars‑Sinai Medical Center, Samuel Oschin Comprehensive Cancer Institute, Los Angeles, CA 90048, USA.
16Jonsson Comprehensive Cancer Center, University of California, Los Angeles (UCLA), Los Angeles, CA 90095, USA.
*Correspondence: Sungyong You, Vatche G. Agopian, Ju Dong Yang, Hsian‑Rong Tseng, Yazhen Zhu
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.
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.
논문정보
- Research article
- 2025년 05월 (BRIC 등록일 2025-05-08)
- 국외 연구진
- 바이오·의료융합 > 다학제 융합/복합
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