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":"用于评估肝癌患者治疗反应的细胞外囊泡数字评分法。","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). 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引用次数: 0
摘要
背景:目前还没有有效的生物标志物来评估肝细胞癌(HCC)治疗反应(TR)。细胞外囊泡(EVs)是一种很有前途的循环生物标志物,可以检测治疗后HCC患者的微小残留病变。方法:我们使用HCC EV数字评分法建立HCC EV TR评分,包括点击化学介导的HCC EV富集,然后通过rt -数字PCR对HCC EV特异性基因进行绝对定量。我们选择了6个HCC ev特异性基因,并通过以下途径进行了验证:1)一个全面的数据分析管道,包括前所未有的大量肝脏转录组数据集(n = 9160); 2)在HCC组织上进行RNAscope验证(n = 6); 3)一项针对早期或中期HCC和肝硬化患者的试点研究(n = 70)。在一项2期回顾性病例对照研究(n = 100)中评估HCC EV TR评分的表现。结果:根据2期病例对照研究中治疗前后血浆样本计算的HCC EV TR评分,在训练组(ROC曲线下面积[AUROC]为0.90,n = 49)和验证组(AUROC为0.88,n = 51)中准确区分了治疗后存活和非存活的HCC。在训练集中确定的最佳截止值为0.76时,HCC EV TR评分在检测活肿瘤方面具有很高的准确性(敏感性:76.5%,特异性:88.2%),并且在6例患者中发现了最初未在MRI上观察到的残留疾病,中位提前时间为63天。结论:这种基于ev的数字评分方法在增强肝细胞癌治疗反应评估的横断成像方面显示出巨大的前景。
Extracellular vesicle digital scoring assay for assessment of treatment responses in hepatocellular carcinoma patients.
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.
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