The potential, analysis and prospect of ctDNA sequencing in hepatocellular carcinoma

Yubo Ding; Jingwei Yao; Meiling Wen; Xiong Liu; Jialu Huang; Minghui Zhang; Yu Zhang; Yufan Lv; Zhuoyi Xie; JianHong Zuo

doi:10.7717/peerj.13473

The potential, analysis and prospect of ctDNA sequencing in hepatocellular carcinoma

PeerJ. 2022 May 17:10:e13473. doi: 10.7717/peerj.13473. eCollection 2022.

Authors

Yubo Ding^#^{1

2}, Jingwei Yao^#^{1

2}, Meiling Wen³, Xiong Liu⁴, Jialu Huang², Minghui Zhang², Yu Zhang², Yufan Lv¹, Zhuoyi Xie², JianHong Zuo^{1

2

5}

Affiliations

¹ The Affiliated Nanhua Hospital of University of South China, Hengyang, Hunan, China.
² University of South China, Transformation Research Lab, Hunan Province Key Laboratory of Tumor Cellular and Molecular Pathology, Hengyang Medical School, Hengyang, Hunan, China.
³ The First Affiliated Hospital, University of South China, Hengyang, China.
⁴ Department of Otolaryngology-Head and Neck Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, China.
⁵ Clinical Laboratory, The Third Affiliated Hospital of University of South China, Hengyang, Hunan, China.

^# Contributed equally.

Abstract

Background: The genome map of hepatocellular carcinoma (HCC) is complex. In order to explore whether circulating tumor cell DNA (ctDNA) can be used as the basis for sequencing and use ctDNA to find tumor related biomarkers, we analyzed the mutant genes of ctDNA in patients with liver cancer by sequencing.

Methods: We used next-generation targeted sequencing technology to identify mutations in patients with liver cancer. The ctDNA from 10 patients with hepatocellular carcinoma (including eight cases of primary hepatocellular carcinoma and two cases of secondary hepatocellular carcinoma) was sequenced. We used SAMtools to detect and screen single nucleotide polymorphisms (SNPs) and insertion deletion mutations (INDELs) and ANNOVAR to annotate the structure and function of the detected mutations. Screening of pathogenic and possible pathogenic genes was performed using American College of Medical Genetics and Genomics (ACMG) guidelines. GO analysis and KEGG analysis of pathogenic and possible pathogenic genes were performed using the DAVID database, and protein-protein interaction network analysis of pathogenic and possible pathogenic genes was performed using the STRING database. Then, the Kaplan-Meier plotter database, GEPIA database and HPA database were used to analyse the relationship between pathogenic and possible pathogenic genes and patients with liver cancer.

Results: Targeted capture and deep sequencing of 560 cancer-related genes in 10 liver cancer ctDNA samples revealed 8,950 single nucleotide variation (SNV) mutations and 70 INDELS. The most commonly mutated gene was PDE4DIP, followed by SYNE1, KMT2C, PKHD1 and FN1. We compared these results to the COSMIC database and determined that ctDNA could be used for sequencing. According to the ACMG guidelines, we identified 54 pathogenic and possible pathogenic mutations in 39 genes in exons and splice regions of 10 HCC patients and performed GO analysis, KEGG analysis, and PPI network analysis. Through further analysis, four genes significantly related to the prognosis of liver cancer were identified.

Conclusion: In this study, our findings indicate that ctDNA can be used for sequencing. Our results provide some molecular data for the mapping of genetic variation in Chinese patients with liver cancer, which enriches the understanding of HCC pathogenesis and provides new ideas for the diagnosis and prognosis of HCC patients.

Keywords: Circulating tumor DNA; Gene mutation; Liver cancer; Next-generation sequencing; Pathway analysis.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Carcinoma, Hepatocellular* / genetics
Circulating Tumor DNA* / genetics
Gene Regulatory Networks
Humans
Liver Neoplasms* / diagnosis
Protein Interaction Maps

Substances

Circulating Tumor DNA

Grants and funding

This work is supported by the Key Research Program from the Science and Technology Department of Ningxia Hui Autonomous Region, China (2019BFH02012); the Key Research Program of Hunan Health Committee (20201909); the National Natural Science Foundation of China (82173008); and the Program of Hengyang science and Technology Bureau (2017-1, 2020-67). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.