用于评估肝细胞癌患者治疗反应的细胞外囊泡数字评分测定法。

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

作者信息

Zhao Chen, Lee Yi-Te, Melehy Andrew, Kim Minhyung, Yang Jacqueline Ziqian, Zhang Ceng, Kim Jina, Zhang Ryan Y, Lee Junseok, Kim Hyoyong, Ju Yong, Tsai Yuan-Jen, Zhou Xianghong Jasmine, Han Steven-Huy B, Sadeghi Saeed, Finn Richard S, Saab Sammy, Lu David S, Chiang Jason, Park Jae-Ho, Brennan Todd V, Wisel Steven A, Alsudaney Manaf, Kuo Alexander, Ayoub Walid S, Kim Hyunseok, Trivedi Hirsh D, Wang Yun, Vipani Aarshi, Kim Irene K, Todo Tsuyoshi, Steggerda Justin A, Voidonikolas Georgios, Kosari Kambiz, Nissen Nicholas N, Saouaf Rola, Singal Amit G, Sim Myung Shin, Elashoff David A, You Sungyong, Agopian Vatche G, Yang Ju Dong, Tseng Hsian-Rong, Zhu Yazhen

机构信息

Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.

Department of Molecular and Medical Pharmacology, California Nanosystems Institute, Crump Institute for Molecular Imaging, University of California, Los Angeles (UCLA), Los Angeles, CA, 90095, USA.

出版信息

J Exp Clin Cancer Res. 2025 May 1;44(1):136. doi: 10.1186/s13046-025-03379-7.

DOI:10.1186/s13046-025-03379-7

PMID:40307890

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12044846/

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.

摘要

背景

目前尚无经过验证的生物标志物可用于评估肝细胞癌（HCC）的治疗反应（TR）。细胞外囊泡（EVs）是很有前景的循环生物标志物，可能检测出接受治疗的HCC患者的微小残留病灶。

方法

我们使用HCC EV数字评分测定法开发了HCC EV TR评分，该方法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。通过以下方式选择并验证了六个HCC EV特异性基因：i）通过全面的数据分析流程，使用前所未有的大量肝脏转录组数据集（n = 9160）；ii）对HCC组织（n = 6）进行RNAscope验证；iii）对早期或中期HCC和肝硬化患者进行一项试点研究（n = 70）。在一项2期回顾性病例对照研究（n = 100）中评估了HCC EV TR评分的性能。

结果

在2期病例对照研究中，根据治疗前和治疗后的血浆样本计算出的HCC EV TR评分，在训练集（ROC曲线下面积[AUROC]为0.90，n = 49）和验证集（AUROC为0.88，n = 51）中准确区分了治疗后存活与非存活的HCC。在训练集中确定的最佳临界值为0.76时，HCC EV TR评分在检测存活肿瘤方面具有较高的准确性（敏感性：76.5%，特异性：88.2%），并在6例患者中发现了MRI最初未观察到的残留病灶，中位提前期为63天。