Basic Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Hepatol. Dec 27, 2022; 14(12): 1997-2011
Published online Dec 27, 2022. doi: 10.4254/wjh.v14.i12.1997
Immunological classification of hepatitis B virus-positive hepatocellular carcinoma by transcriptome analysis
Sheng-Wei Li, Li-Fan Han, Yin He, Xiao-Sheng Wang
Sheng-Wei Li, Li-Fan Han, Yin He, Xiao-Sheng Wang, Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing 211198, Jiangsu Province, China
Author contributions: Li SW contributed to software, validation, formal analysis, investigation, data curation, visualization, writing - review & editing; Han LF contributed to software, formal analysis, data curation; He Y contributed to data curation; Wang XS contributed to conceptualization, methodology, resources, investigation, writing - original draft, supervision, project administration, funding acquisition.
Institutional review board statement: Because we did not perform any human/animal experiments in this research, we could not provide the following file: Institutional review board approval form or document.
Institutional animal care and use committee statement: Because we did not perform any animal experiments in this research, we could not provide the file.
Conflict-of-interest statement: All the authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Data sharing statement: No additional data are available.
ARRIVE guidelines statement: The authors have read the ARRIVE guidelines, and the manuscript was prepared and revised according to the ARRIVE guidelines.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See:
Corresponding author: Xiao-Sheng Wang, PhD, Associate Professor, Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, No. 639 Longmian Avenue, Jiangning District, Nanjing 211198, Jiangsu Province, China.
Received: September 5, 2022
Peer-review started: September 5, 2022
First decision: September 30, 2022
Revised: October 12, 2022
Accepted: November 22, 2022
Article in press: November 22, 2022
Published online: December 27, 2022
Research background

Hepatocellular carcinoma (HCC) is a major cancer of the liver that constitutes around 90% of liver cancer cases. Although traditional therapeutic approaches, including surgery, chemotherapy, radiotherapy, and targeted therapy, are effective in improving the survival of HCC patients, the overall survival prognosis of HCC patients is generally unfavorable. More recently, immunotherapy, such as immune checkpoint blockade, has achieved success in the treatment of various cancers, including HCC. However, only a small proportion of cancer patients respond well to immunotherapies to date.

Research motivation

Certain predictive markers for cancer immunotherapy responses have been uncovered, e.g., PD-L1 expression, tumor mutation burden (TMB), and mismatch repair deficiency. In addition, the tumor immune microenvironment (TIME) plays an important role in immunotherapy responses. Overall, the “hot” tumors infiltrated by a substantial number of tumor-infiltrating lymphocytes (TILs) are more responsive to immunotherapies, compared to the “cold” tumors lacking TILs. Hence, an investigation of the TIME in HCC would aid in the prediction of immunotherapy responses.

Research objectives

Despite these previous studies, the discovery of immune-specific subtypes of hepatitis B virus-positive (HBV+) HCC is worth investigating, considering that HBV infection is a major cause of HCC.

Research methods

In this study, to characterize the immunological landscape of HBV+ HCC, we identified its immune-specific subtypes by the unsupervised machine learning in transcriptomic data. Furthermore, we comprehensively compared the clinical and molecular features of these subtypes.

Research results

Compared to Imm-L, Imm-H displayed stronger immunity, more stromal components, lower tumor purity, lower stemness and intratumor heterogeneity, lower-level copy number alterations, higher global methylation level, and better overall and disease-free survival prognosis.

Research conclusions

Our immune-specific subtyping of HBV+ HCC may provide new biological insights as well as clinical implications for the management of this disease.

Research perspectives

This study is interesting for several reasons. First, for the first time, we identified immune-specific subtypes of HBV+ HCC based on immune signature scores and demonstrated that this new subtyping method was reproducible in three different datasets. Second, our subtyping method captures the comprehensive heterogeneity of HBV+ HCC in the tumor microenvironment, genomic integrity, protein expression profiles, DNA methylation profiles, tumor stemness, intratumor heterogeneity, and clinical outcomes. Third, our data suggest that it is copy number alterations but not tumor mutations responsible for the different immunity between the “hot” and “cold” tumor subtypes in HBV+ HCC. Finally, our identification of the immune-specific subtypes of HBV+ HCC may provide new insights into the tumor biology and identify the HBV+ HCC patients beneficial from immunotherapy.