Noninvasive chimeric DNA profiling identifies tumor-originated HBV integrants contributing to viral antigen expression in liver cancer.


Journal

Hepatology international
ISSN: 1936-0541
Titre abrégé: Hepatol Int
Pays: United States
ID NLM: 101304009

Informations de publication

Date de publication:
May 2020
Historique:
received: 09 09 2019
accepted: 18 01 2020
pubmed: 27 2 2020
medline: 17 4 2021
entrez: 27 2 2020
Statut: ppublish

Résumé

Host genome integration of HBV sequence is considered to be significant in HBV antigen expression and the development of hepatocellular carcinoma (HCC). We developed a probe-based capture strategy to enrich integrated HBV DNA for deep-sequencing analysis of integration sites in paired patient samples derived from tumor, liver tissue adjacent to tumor, saliva and plasma, as a platform for exploring the correlation, significance and utility of detecting integrations in these sample types. Most significantly, alpha fetoprotein levels significantly correlated to the amounts of integrations detected in tumor. Viral-host chimeric DNA fragments were successfully detected at high sequencing coverage in plasma rather than saliva samples from HCC patients, and each fragment of this type was only seen once in plasma from chronic hepatitis B patients. Almost all plasma chimeric fragments were derived from integrations in tumor rather than in adjacent liver tissues. Over 50% of them may produce viral-host chimeric transcripts according to deep RNA sequencing in paired tissue samples. Particularly, in patients with low HBV DNA level (< 250 UI/ml), the seemingly normal HBsAg titers may be explained by larger amounts of integrations detected. Meanwhile, we developed a strategy to predict integrants by pairing breakpoints for each integration event. Among four resolved viral patterns, the majority of Pattern I events (81.2%) retained the complete opening reading frame for HBV surface proteins. We achieve the efficient enrichment of plasma cell-free chimeric DNA from integration site, and demonstrate that chimeric DNA profiling in plasma is a promising noninvasive approach to monitor HBV integration in liver cancer development and to determine the ability of integrated sequences to express viral proteins that can be targeted, e.g. by immunotherapies.

Sections du résumé

BACKGROUND BACKGROUND
Host genome integration of HBV sequence is considered to be significant in HBV antigen expression and the development of hepatocellular carcinoma (HCC).
METHOD METHODS
We developed a probe-based capture strategy to enrich integrated HBV DNA for deep-sequencing analysis of integration sites in paired patient samples derived from tumor, liver tissue adjacent to tumor, saliva and plasma, as a platform for exploring the correlation, significance and utility of detecting integrations in these sample types.
RESULTS RESULTS
Most significantly, alpha fetoprotein levels significantly correlated to the amounts of integrations detected in tumor. Viral-host chimeric DNA fragments were successfully detected at high sequencing coverage in plasma rather than saliva samples from HCC patients, and each fragment of this type was only seen once in plasma from chronic hepatitis B patients. Almost all plasma chimeric fragments were derived from integrations in tumor rather than in adjacent liver tissues. Over 50% of them may produce viral-host chimeric transcripts according to deep RNA sequencing in paired tissue samples. Particularly, in patients with low HBV DNA level (< 250 UI/ml), the seemingly normal HBsAg titers may be explained by larger amounts of integrations detected. Meanwhile, we developed a strategy to predict integrants by pairing breakpoints for each integration event. Among four resolved viral patterns, the majority of Pattern I events (81.2%) retained the complete opening reading frame for HBV surface proteins.
CONCLUSION CONCLUSIONS
We achieve the efficient enrichment of plasma cell-free chimeric DNA from integration site, and demonstrate that chimeric DNA profiling in plasma is a promising noninvasive approach to monitor HBV integration in liver cancer development and to determine the ability of integrated sequences to express viral proteins that can be targeted, e.g. by immunotherapies.

Identifiants

pubmed: 32100258
doi: 10.1007/s12072-020-10016-2
pii: 10.1007/s12072-020-10016-2
doi:

Substances chimiques

Antigens, Viral 0
Cell-Free Nucleic Acids 0
DNA, Viral 0
Integration Host Factors 0
alpha-Fetoproteins 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

326-337

Subventions

Organisme : Youth Innovation Promotion Association of the Chinese Academy of Sciences
ID : 2016098
Organisme : National Natural Science Foundation of China
ID : 81201700
Organisme : Major State Basic Research Development Program of China
ID : 2014CB542006
Organisme : Key Research Program of the Chinese Academy of Sciences
ID : KJZD-EW-L14
Organisme : Beijing Natural Science Foundation
ID : 7192158
Organisme : Fundamental Research Funds for the Central Universities
ID : 3332018032
Organisme : Capital's Funds for Health Improvement and Research
ID : 2018-1-1151

Auteurs

Wei Chen (W)

Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, NO.1 Beichen West Road, Chaoyang, Beijing, 100101, China.
Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100083, China.

Ke Zhang (K)

Institute of Virology, Technical University of Munich/Helmholtz Zentrum München, Trogerstrasse 30, 81675, Munich, Germany.
Janssen China Research and Development Center, Shanghai, 201210, China.

Peiling Dong (P)

Department of Hepatology, Beijing You'an Hospital Affiliated with Capital Medical University, Beijing, 100069, China.

Gregory Fanning (G)

Janssen China Research and Development Center, Shanghai, 201210, China.

Chengcheng Tao (C)

Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, NO.1 Beichen West Road, Chaoyang, Beijing, 100101, China.

Haikun Zhang (H)

Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, NO.1 Beichen West Road, Chaoyang, Beijing, 100101, China.

Shicheng Guo (S)

Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, USA.

Zheng Wang (Z)

Department of Hepatology, Beijing You'an Hospital Affiliated with Capital Medical University, Beijing, 100069, China.

Yaqiang Hong (Y)

Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, NO.1 Beichen West Road, Chaoyang, Beijing, 100101, China.
Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing, 100084, China.

Xiaobo Yang (X)

Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.

Shujuan Lai (S)

Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, NO.1 Beichen West Road, Chaoyang, Beijing, 100101, China.

Huiguo Ding (H)

Department of Hepatology, Beijing You'an Hospital Affiliated with Capital Medical University, Beijing, 100069, China.

Haitao Zhao (H)

Department of Liver Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.

Changqing Zeng (C)

Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, NO.1 Beichen West Road, Chaoyang, Beijing, 100101, China. czeng@big.ac.cn.

Ulrike Protzer (U)

Institute of Virology, Technical University of Munich/Helmholtz Zentrum München, Trogerstrasse 30, 81675, Munich, Germany. protzer@tum.de.
German Center for Infection Research (DZIF), Munich Partner Site, Munich, Germany. protzer@tum.de.

Dake Zhang (D)

Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences, NO.1 Beichen West Road, Chaoyang, Beijing, 100101, China. zhangdk@big.ac.cn.
Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100083, China. zhangdk@big.ac.cn.

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Classifications MeSH