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Background <p>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> Methods <p>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 (<i>n</i> = 9,160), ii) RNAscope validation on HCC tissues (<i>n</i> = 6), and iii) a pilot study on early- or intermediate-stage HCC and liver cirrhosis patients (<i>n</i> = 70). The performance of HCC EV TR Score was assessed in a phase-2 retrospective case–control study (n = 100).</p> Results <p>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> Conclusions <p>This EV-based digital scoring approach shows great promise to augment cross-sectional imaging for the assessment of HCC treatment response.</p>

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Extracellular vesicle digital scoring assay for assessment of treatment responses in hepatocellular carcinoma patients

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月1日

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  • 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

摘要

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.