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Comprehensive Liquid Profiling of Circulating Tumor DNA and Protein Biomarkers in Long-Term Follow-Up Patients with Hepatocellular Carcinoma

肝细胞癌 医学 肿瘤科 内科学 体细胞 循环肿瘤DNA 微小残留病 拷贝数变化 生物信息学 癌症 基因组 生物 基因 遗传学 白血病
作者
Zhixiong Cai,Geng Chen,Yongyi Zeng,Xiuqing Dong,Zhenli Li,Yanbing Huang,Fuli Xin,Liman Qiu,Haipo Xu,Wei Zhang,Xiaoping Su,Xiaolong Liu,Jingfeng Liu
出处
期刊:Clinical Cancer Research [American Association for Cancer Research]
卷期号:25 (17): 5284-5294 被引量:123
标识
DOI:10.1158/1078-0432.ccr-18-3477
摘要

Circulating tumor DNA (ctDNA) provides a novel approach for detecting tumor burden and predicting clinical outcomes of hepatocellular carcinoma (HCC). Here, we performed a thorough evaluation of HCC circulating genetic features and further fully integrated them to build a robust strategy for HCC monitoring and prognostic outcome assessment.We performed target sequencing and low-coverage whole-genome sequencing on plasma samples collected from 34 long-term follow-up patients with HCC to capture tumor somatic SNVs and CNVs, respectively. Clinical information was also obtained to evaluate the prognostic performance of ctDNA comparing with clinically applied protein biomarkers.All plasma samples before surgery showed somatic genetic variations resembling corresponding tumor tissues. During follow-up, SNVs and CNVs dynamically changed correlating to patients' tumor burden. We integrated the comprehensive ctDNA mutation profiles to provide a robust strategy to accurately assess patients' tumor burden with high consistence comparing with imaging results. This strategy could discover tumor occurrence in advance of imaging for an average of 4.6 months, and showed superior performance than serum biomarkers AFP, AFP-L3%, and Des-Gamma-Carboxy Prothrombin (DCP). Furthermore, our strategy could precisely detect minimal residual disease (MRD) in advance and predict patients' prognostic outcomes for both relapse-free survival (P = 0.001) and overall survival (P = 0.001); further combining ctDNA with DCP could increase the sensitivity for MRD detection.We demonstrated that plasma CNV and SNV levels dynamically correlated with patients' tumor burden in HCC. Our strategy of comprehensive mutation profile integration could accurately and better evaluate patients' prognostic risk and detect tumor occurrence in advance than traditional strategies.
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