Original Article

Diverse modes of clonal evolution in HBV-related hepatocellular carcinoma revealed by single-cell genome sequencing

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Abstract

Hepatocellular carcinoma (HCC) is a cancer of substantial morphologic, genetic and phenotypic diversity. Yet we do not understand the relationship between intratumor heterogeneity and the associated morphologic/histological characteristics of the tumor. Using single-cell whole-genome sequencing to profile 96 tumor cells (30-36 each) and 15 normal liver cells (5 each), collected from three male patients with HBV-associated HCC, we confirmed that copy number variations occur early in hepatocarcinogenesis but thereafter remain relatively stable throughout tumor progression. Importantly, we showed that specific HCCs can be of monoclonal or polyclonal origins. Tumors with confluent multinodular morphology are the typical polyclonal tumors and display the highest intratumor heterogeneity. In addition to mutational and copy number profiles, we dissected the clonal origins of HCC using HBV-derived foreign genomic markers. In monoclonal HCC, all the tumor single cells exhibit the same HBV integrations, indicating that HBV integration is an early driver event and remains extremely stable during tumor progression. In addition, our results indicated that both models of metastasis, late dissemination and early seeding, have a role in HCC progression. Notably, early intrahepatic spreading of the initiating clone leads to the formation of synchronous multifocal tumors. Meanwhile, we identified a potential driver gene ZNF717 in HCC, which exhibits a high frequency of mutation at both single-cell and population levels, as a tumor suppressor acting through regulating the IL-6/STAT3 pathway. These findings highlight multiple distinct tumor evolutionary mechanisms in HCC, which suggests the need for specific treatment strategies.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (81522036, 81572292 and 81372648 to QG; 81672956 and 81472413 to CL); Basic Research Project from Technology Commission of Shanghai Municipality (17JC1402200) and National Program for Special Support of Eminent Professionals and Science to QG; the Key Program (QYZDB-SSW-SMC036), External Cooperation Program (GJHZ201312) and the National Key Basic Research Program of China (2015CB856000) to XZ.

Author information

Author notes

    • Meng Duan
    • , Junfeng Hao
    •  & Sijia Cui

    These three authors contributed equally to this work.

Affiliations

  1. Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai 200032, China

    • Meng Duan
    • , Shu Zhang
    • , Zhichao Wang
    • , Jieyi Shi
    • , Longzi Liu
    • , Xiaoying Wang
    • , Aiwu Ke
    • , Jian Zhou
    • , Jia Fan
    •  & Qiang Gao
  2. Core Facility for Protein Research, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China

    • Junfeng Hao
    •  & Chong Li
  3. Hangzhou Cancer Institute, Hangzhou Cancer Hospital, Hangzhou, Zhejiang 310002, China

    • Sijia Cui
  4. Cancer Theme, South Australian Health and Medical Research Institute and Department of Medicine, University of Adelaide, Adelaide, SA, Australia

    • Daniel L Worthley
  5. Cancer Research Institute, Xiangya School of Medicine, Central South University, Changsha, Hunan 410013, China

    • Ya Cao
  6. School of Mathematical Sciences and Center for Statistical Science, Peking University, Beijing 100871, China

    • Ruibin Xi
  7. Key Laboratory of Molecular Virology & Immunology, Institute Pasteur of Shanghai, Chinese Academy of Sciences, Shanghai 200032, China

    • Xiaoming Zhang
  8. Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, China

    • Jian Zhou
    •  & Jia Fan
  9. State Key Laboratory of Genetic Engineering, Fudan University, Shanghai 200433, China

    • Qiang Gao

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Corresponding authors

Correspondence to Jia Fan or Chong Li or Qiang Gao.

Supplementary information

PDF files

  1. 1.

    Supplementary information, Figure S1

    Morphologic and histological features of three HCC used for SCG.

  2. 2.

    Supplementary information, Figure S2

    Depth and distribution of coverage for each sequencing library based on SCG (A) and population sequencing (B).

  3. 3.

    Supplementary information, Figure S3

    Somatic Mutation Pattern Spectrums of each HCC based on SCG.

  4. 4.

    Supplementary information, Figure S4

    Sanger sequencing validation of 11 HBV integration sites.

  5. 5.

    Supplementary information, Figure S5

    The technical amplification and sequencing error rate of MALBAC data of the single cell samples.

  6. 6.

    Supplementary information, Figure S6

    The Q20 and Q30 bases fraction of the single cell samples.

  7. 7.

    Supplementary information, Figure S7

    Statistical significance of gain and loss regions in the SCGs of the three HCC patients.

  8. 8.

    Supplementary information, Figure S8

    The mutation landscape and driver-gene prediction.

  9. 9.

    Supplementary information, Figure S9

    ZNF717 knockdown promoted growth, migration, adhesion and invasion and inhibited apoptosis in HCC cells.

  10. 10.

    Supplementary information, Figure S10

    ZNF717 knockdown in HCC enhanced MMP2, CD44 and ITGA3 expression.

  11. 11.

    Supplementary information, Figure S11

    Immunohistochemistry staining of phosphorylated STAT3 and its prognostic significance in HCC patients.

  12. 12.

    Supplementary information, Figure S12

    ZNF717 suppresses the transcription of STAT3.

  13. 13.

    Supplementary information, Table S1

    Clinicopathologic information of the 3 HCC patients.

  14. 14.

    Supplementary information, Table S2

    HBV integration sites detected by SCG.

  15. 15.

    Supplementary information, Data S1

    Materials and Methods

Excel files

  1. 1.

    Supplementary information, Table S3

    Common CNV identified by SCG in monoclonal tumors H-PT and H-CM.

  2. 2.

    Supplementary information, Table S4

    Somatic point mutations detected in the three HCC by SCG.

  3. 3.

    Supplementary information, Table S5

    Common SNVs identified by Larva in the non-coding region of monoclonal tumors H-PT and H-CM.

(Supplementary information is linked to the online version of the paper on the Cell Research website.)