Minireviews
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Feb 15, 2023; 15(2): 276-285
Published online Feb 15, 2023. doi: 10.4251/wjgo.v15.i2.276
Evaluation of polygenic risk score for risk prediction of gastric cancer
Xiao-Yu Wang, Li-Li Wang, Lin Xu, Shu-Zhen Liang, Meng-Chao Yu, Qiu-Yue Zhang, Quan-Jiang Dong
Xiao-Yu Wang, Li-Li Wang, Lin Xu, Shu-Zhen Liang, Meng-Chao Yu, Quan-Jiang Dong, Central Laboratories and Department of Gastroenterology, Qingdao Municipal Hospital, Qingdao University, Qingdao 266071, Shandong Province, China
Qiu-Yue Zhang, Department of Clinical Laboratory, the Eighth Medical Center of the General Hospital of the People’s Liberation Army, Beijing 100000, China
Author contributions: Wang XY and Liang SZ collected sequencing data; Wang LL and Xu L analyzed the data; Wang XY, Yu MC, and Zhang QY wrote the manuscript; Dong QJ designed the research and supervised the manuscript; all authors reviewed the manuscript and approved the final version of the manuscript.
Supported by the National Natural Science Foundation of China, No. 31870777.
Conflict-of-interest statement: The authors declare that they have no competing interests.
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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Quan-Jiang Dong, MD, PhD, Chief Doctor, Professor, Central Laboratories and Department of Gastroenterology, Qingdao Municipal Hospital, Qingdao University, No. 5 Donghai Middle Road, Qingdao 266071, Shandong Province, China. allyking114@126.com
Received: November 18, 2022
Peer-review started: November 18, 2022
First decision: January 3, 2023
Revised: January 11, 2023
Accepted: February 2, 2023
Article in press: February 2, 2023
Published online: February 15, 2023
Processing time: 88 Days and 22.4 Hours
Abstract

Genetic variations are associated with individual susceptibility to gastric cancer. Recently, polygenic risk score (PRS) models have been established based on genetic variants to predict the risk of gastric cancer. To assess the accuracy of current PRS models in the risk prediction, a systematic review was conducted. A total of eight eligible studies consisted of 544842 participants were included for evaluation of the performance of PRS models. The overall accuracy was moderate with Area under the curve values ranging from 0.5600 to 0.7823. Incorporation of epidemiological factors or Helicobacter pylori (H. pylori) status increased the accuracy for risk prediction, while selection of single nucleotide polymorphism (SNP) and number of SNPs appeared to have little impact on the model performance. To further improve the accuracy of PRS models for risk prediction of gastric cancer, we summarized the association between gastric cancer risk and H. pylori genomic variations, cancer associated bacteria members in the gastric microbiome, discussed the potentials for performance improvement of PRS models with these microbial factors. Future studies on comprehensive PRS models established with human SNPs, epidemiological factors and microbial factors are indicated.

Keywords: Polygenic risk scores; Gastric cancer; Helicobacter pylori; Gastric microbiome

Core Tip: A systematic review was conducted to evaluate current polygenic risk score (PRS) models in gastric cancer risk prediction. Our study showed that PRS models had the potential to predict the risk of gastric cancer with a moderate accuracy. The prediction models’ performance could be improved after incorporating epidemiological factors or Helicobacter pylori (H. pylori) status. The potential of H. pylori genomic variations and members of the gastric microbiome were discussed as candidates for gastric cancer prediction models.