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Zhao W, Qiu L, Liu H, Xu Y, Zhan M, Zhang W, Xin Y, He X, Yang X, Bai J, Xiao J, Guan Y, Li Q, Chang L, Yi X, Li Y, Chen X, Lu L. Circulating tumor DNA as a potential prognostic and predictive biomarker during interventional therapy of unresectable primary liver cancer. J Gastrointest Oncol 2020; 11:1065-1077. [PMID: 33209498 PMCID: PMC7657842 DOI: 10.21037/jgo-20-409] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2020] [Accepted: 10/09/2020] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Imaging and alpha fetoprotein (AFP) measurement are used as surveillance methods during interventional therapy in patients with unresectable liver cancer, but their accuracy has been challenged in patients receiving drug perfusion therapy. Circulating tumor DNA (ctDNA) can reflect tumor load and treatment efficacy. Studies of the prognostic value of ctDNA in unresectable liver cancer are needed. METHODS Forty-two patients with unresectable liver cancer were prospective enrolled in this study. Pre-treatment, in-treatment plasma samples and available matched tissue samples were collected. Targeted-capture sequencing of 1,021 genes that are frequently mutated in solid tumors. RESULTS Targeted-capture sequencing of 1,021 genes that are frequently mutated in solid tumors revealed that the most frequently mutated genes in ctDNA were TP53 (52.4%) and TERT (35.7%). The ctDNA abundance was more closely correlated with tumor size than the AFP level and was also related to BCLC stage (P<0.001). Gene mutations profile in ctDNA with progressed disease. PD patients were enriched in TP53 mutation group compared with TP53 wildtype group (P=0.0221). Moreover, interventional therapy was more effective in patients without TP53 mutation (OS: P=0.0589; PFS: 0.0411). The dynamic change of ctDNA showed consistent or more sensitivity than imaging for evaluating treatment response. The tumor mutation burden was highly consistent between tissue and blood samples (P<0.0001). CONCLUSIONS ctDNA was a reliable biomarker to assist in diagnosis and evaluation of prognosis and treatment efficacy in advanced liver cancer. Considering that biopsy is unnecessary when advanced liver cancer is diagnosed, ctDNA may be an ideal biomarker for evaluating tumor mutation burden prior to immunotherapy.
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Affiliation(s)
- Wei Zhao
- Zhuhai Interventional Medical Center, Zhuhai Precision Medical Center, Zhuhai People’s Hospital, Zhuhai Hospital Affiliated with Jinan University, Zhuhai, China
| | - Lige Qiu
- Zhuhai Interventional Medical Center, Zhuhai Precision Medical Center, Zhuhai People’s Hospital, Zhuhai Hospital Affiliated with Jinan University, Zhuhai, China
- 2 Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Shenzhen, China
| | - Huajiang Liu
- Department of Intervention Therapy, The First Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Ying Xu
- Department of Computer Science and Technology, School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China
| | - Meixiao Zhan
- Zhuhai Interventional Medical Center, Zhuhai Precision Medical Center, Zhuhai People’s Hospital, Zhuhai Hospital Affiliated with Jinan University, Zhuhai, China
| | - Wei Zhang
- 2 Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Shenzhen, China
| | - Yongjie Xin
- Zhuhai Interventional Medical Center, Zhuhai Precision Medical Center, Zhuhai People’s Hospital, Zhuhai Hospital Affiliated with Jinan University, Zhuhai, China
| | - Xu He
- Zhuhai Interventional Medical Center, Zhuhai Precision Medical Center, Zhuhai People’s Hospital, Zhuhai Hospital Affiliated with Jinan University, Zhuhai, China
| | - Xiangyu Yang
- Zhuhai Interventional Medical Center, Zhuhai Precision Medical Center, Zhuhai People’s Hospital, Zhuhai Hospital Affiliated with Jinan University, Zhuhai, China
| | - Jing Bai
- Geneplus-Beijing Institute, Beijing, China
| | - Jing Xiao
- Zhuhai Interventional Medical Center, Zhuhai Precision Medical Center, Zhuhai People’s Hospital, Zhuhai Hospital Affiliated with Jinan University, Zhuhai, China
| | - Yanfang Guan
- Department of Computer Science and Technology, School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, China
- Geneplus-Beijing Institute, Beijing, China
| | - Qiyang Li
- 2 Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Shenzhen, China
| | | | - Xin Yi
- Geneplus-Beijing Institute, Beijing, China
| | - Yong Li
- Zhuhai Interventional Medical Center, Zhuhai Precision Medical Center, Zhuhai People’s Hospital, Zhuhai Hospital Affiliated with Jinan University, Zhuhai, China
| | - Xudong Chen
- 2 Clinical Medical College of Jinan University, Shenzhen People’s Hospital, Shenzhen, China
| | - Ligong Lu
- Zhuhai Interventional Medical Center, Zhuhai Precision Medical Center, Zhuhai People’s Hospital, Zhuhai Hospital Affiliated with Jinan University, Zhuhai, China
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