Basic Study
Copyright ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jan 14, 2020; 26(2): 134-153
Published online Jan 14, 2020. doi: 10.3748/wjg.v26.i2.134
Construction of a risk score prognosis model based on hepatocellular carcinoma microenvironment
Fa-Peng Zhang, Yi-Pei Huang, Wei-Xin Luo, Wan-Yu Deng, Chao-Qun Liu, Lei-Bo Xu, Chao Liu
Fa-Peng Zhang, Yi-Pei Huang, Wei-Xin Luo, Wan-Yu Deng, Chao-Qun Liu, Lei-Bo Xu, Chao Liu, Department of Biliary Pancreatic Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
Fa-Peng Zhang, Yi-Pei Huang, Wei-Xin Luo, Wan-Yu Deng, Chao-Qun Liu, Lei-Bo Xu, Chao Liu, Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China
Wan-Yu Deng, College of Life Science, Shangrao Normal University, Shangrao 334001, Jiangxi Province, China
Author contributions: Zhang FP, Xu LB and Liu C designed the research; Zhang FP, Huang YP and Luo WX collected and analyzed data; Deng WY and Liu CQ prepared the figures; Zhang FP, Xu LB and Liu C wrote and revised the manuscript.
Supported by National Natural Science Foundation of China, No. 81972255, No. 81772597 and No. 81672412; Guangdong Natural Science Foundation, No. 2017A030311002; Guangdong Science and Technology Foundation, No. 2017A020215196; Fundamental Research Funds for the Central Universities of Sun Yat-Sen University, No. 17ykpy44; Science Foundation of Jiangxi, No. 20181BAB214002; Education Department Science and Technology Foundation of Jiangxi, No. GJJ170936; and Grant from Guangdong Science and Technology Department, No. 2017B030314026.
Institutional review board statement: This study was reviewed and approved by the Ethics Committee of the Sun Yat-Sen Memorial Hospital, Guangzhou, China.
Conflict-of-interest statement: All authors declare no conflict-of-interest related to this article.
Data sharing statement: The data used in this manuscript are accessible at https://cancergenome.nih.gov/, https://icgc.org/, and https://www.ncbi.nlm.nih.gov/geo/.
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 which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Chao Liu, MD, PhD, Chairman, Director, Professor, Department of Hepato-Pancreato-Biliary Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou 510120, Guangdong Province, China. liuchao3@mail.sysu.edu.cn
Received: September 30, 2019
Peer-review started: September 30, 2019
First decision: November 10, 2019
Revised: November 23, 2019
Accepted: December 7, 2019
Article in press: January 7, 2020
Published online: January 14, 2020
Abstract
BACKGROUND

Hepatocellular carcinoma (HCC) is a common cancer with a poor prognosis. Previous studies revealed that the tumor microenvironment (TME) plays an important role in HCC progression, recurrence, and metastasis, leading to poor prognosis. However, the effects of genes involved in TME on the prognosis of HCC patients remain unclear. Here, we investigated the HCC microenvironment to identify prognostic genes for HCC.

AIM

To identify a robust gene signature associated with the HCC microenvironment to improve prognosis prediction of HCC.

METHODS

We computed the immune/stromal scores of HCC patients obtained from The Cancer Genome Atlas based on the ESTIMATE algorithm. Additionally, a risk score model was established based on Differentially Expressed Genes (DEGs) between high‐ and low‐immune/stromal score patients.

RESULTS

The risk score model consisting of eight genes was constructed and validated in the HCC patients. The patients were divided into high- or low-risk groups. The genes (Disabled homolog 2, Musculin, C-X-C motif chemokine ligand 8, Galectin 3, B-cell-activating transcription factor, Killer cell lectin like receptor B1, Endoglin and adenomatosis polyposis coli tumor suppressor) involved in our risk score model were considered to be potential immunotherapy targets, and they may provide better performance in combination. Functional enrichment analysis showed that the immune response and T cell receptor signaling pathway represented the major function and pathway, respectively, related to the immune-related genes in the DEGs between high- and low-risk groups. The receiver operating characteristic (ROC) curve analysis confirmed the good potency of the risk score prognostic model. Moreover, we validated the risk score model using the International Cancer Genome Consortium and the Gene Expression Omnibus database. A nomogram was established to predict the overall survival of HCC patients.

CONCLUSION

The risk score model and the nomogram will benefit HCC patients through personalized immunotherapy.

Keywords: Hepatocellular carcinoma, Prognostic model, Immune related gene, Microenvironment, Risk score, Overall survival

Core tip: We constructed a risk score model based on hepatocellular carcinoma (HCC) microenvironment that could predict the overall survival (OS) of HCC. It has a high sensitivity and specificity in predicting the OS, and was validated using the Gene Expression Omnibus and the International Cancer Genome Consortium dataset. In addition, the risk score model is associated with immunosuppressive environment and immune checkpoint expression, which will assist clinicians in selecting personalized immunotherapy for HCC patients.