Cancer Research and Treatment

Original Articles

Discrepancy between Genetically Predicted and Observed Alcohol Intake and Its Impact on Gastric Cancer Susceptibility: Ga-Eun Yie, Cheol Min Shin, Kyungtaek Park, Jinyeon Jo, Ah Ra Do, Sungkyoung Choi, Jung Hun Ohn, Sejoon Lee, Jeongseon Kim, Sun Ha Jee, Seung Joo Kang, Nayoung Kim, Sungho Won; Received January 24, 2025 Accepted May 15, 2025 Published online May 30, 2025; DOI: https://doi.org/10.4143/crt.2025.109 [Accepted]

Abstract PDF: Purpose
We aimed to investigate how genetic predisposition to drinking and gastric cancer (GC) modifies the association between alcohol consumption and GC risk in the Korean population.
Materials and Methods
PRS for GC (PRS-GC) and alcohol consumption (PRS-Alcohol) were formulated using genome-wide association results from BioBank Japan. Validation was performed using Korean cohorts (SNUBH-GENIE cohort), incorporating 8,846 controls and 531 patients with GC. Subsequently, these PRSs were applied to an independent Korean cohort of 67,771 participants, including 313 patients with GC during the follow-up for 14 years (KoGES cohort).
Results
In KoGES cohort, the influence of alcohol consumption on GC risk was significantly altered by the PRS-GC and exhibited a synergistic interaction effect. PRS-Alcohol itself shows a negative correlation with GC risk. However, when actual alcohol consumption significantly exceeded genetically predicted levels, the risk of alcohol-related GC was notably increased (adjusted hazard ratio: 1.32, 95% confidence interval: 1.01-1.72). Heavy drinkers in the high-PRS-GC/low-PRS-Alcohol group had a 2.16 times higher risk of GC than non-to-light drinkers, which was prominent in males.
Conclusion
Korean drinkers with higher PRS-GC who consume alcohol more than genetically predicted levels are susceptible to GC. PRS-GC and PRS-Alcohol may be beneficial for assessing the impact of alcohol consumption on GC risk in Koreans.

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Gastrointestinal cancer

An Innovative Prognostic Model Based on Four Genes in Asian Patient with Gastric Cancer: Jiahui Chen, Anqiang Wang, Jun Ji, Kai Zhou, Zhaode Bu, Guoqing Lyu, Jiafu Ji; Cancer Res Treat. 2021;53(1):148-161. Published online August 31, 2020; DOI: https://doi.org/10.4143/crt.2020.424

Abstract PDF Supplementary Material PubReader ePub

Purpose
Gastric cancer (GC) has substantial biological differences between Asian and non-Asian populations, which makes it difficult to have a unified predictive measure for all people. We aimed to identify novel prognostic biomarkers to help predict the prognosis of Asian GC patients.
Materials and Methods
We investigated the differential gene expression between GC and normal tissues of GSE66229. Univariate, multivariate and Lasso Cox regression analyses were conducted to establish a four-gene-related prognostic model based on the risk score. The risk score was based on a linear combination of the expression levels of individual genes multiplied by their multivariate Cox regression coefficients. Validation of the prognostic model was conducted using The Cancer Genome Atlas (TCGA) database. A nomogram containing clinical characteristics and the prognostic model was established to predict the prognosis of Asian GC patients.
Results
Four genes (RBPMS2, RGN, PLEKHS1, and CT83) were selected to establish the prognostic model, and it was validated in the TCGA Asian cohort. Receiver operating characteristic analysis confirmed the sensitivity and specificity of the prognostic model. Based on the prognostic model, a nomogram containing clinical characteristics and the prognostic model was established, and Harrell’s concordance index of the nomogram for evaluating the overall survival significantly higher than the model only focuses on the pathologic stage (0.74 vs. 0.64, p < 0.001).
Conclusion
The four-gene-related prognostic model and the nomogram based on it are reliable tools for predicting the overall survival of Asian GC patients.

Citations

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Discovery and Exploration of Small Molecule Binders for CT83: Computational Insights from Homology Modeling, Virtual Screening, MD Simulations, Interaction Fingerprint, and Network Communications
Varun Dewaker, Sung Taek Park, Jae Jun Lee, Hyeong Su Kim
ACS Omega.2025;[Epub] CrossRef
Nivolumab plus anlotinib hydrochloride in advanced gastric adenocarcinoma and esophageal squamous cell carcinoma: the phase II OASIS trial
Jing Wu, Shilong Zhang, Shan Yu, Guo An, Yi Wang, Yiyi Yu, Li Liang, Yan Wang, Xiaojing Xu, YanShi Xiong, Di Shao, Zhun Shi, Nannan Li, Jingyuan Wang, Dawei Jin, Tianshu Liu, Yuehong Cui
Nature Communications.2024;[Epub] CrossRef
An integrated analysis of prognostic mRNA signature in early- and progressive-stage gastric adenocarcinoma
Xiaoling Hong, Kai Zhuang, Na Xu, Jiang Wang, Yong Liu, Siqi Tang, Junzhang Zhao, Zunnan Huang
Frontiers in Molecular Biosciences.2023;[Epub] CrossRef
Analysis and application of RNA binding protein gene pairs to predict the prognosis of gastric cancer
Zhi-kun Ning, Hua-kai Tian, Jiang Liu, Ce-gui Hu, Zi-tao Liu, Hui Li, Zhen Zong
Heliyon.2023; 9(7): e18242. CrossRef
PLEKHS1 drives PI3Ks and remodels pathway homeostasis in PTEN-null prostate
Tamara A.M. Chessa, Piotr Jung, Arqum Anwar, Sabine Suire, Karen E. Anderson, David Barneda, Anna Kielkowska, Barzan A. Sadiq, Ieng Wai Lai, Sergio Felisbino, Daniel J. Turnham, Helen B. Pearson, Wayne A. Phillips, Junko Sasaki, Takehiko Sasaki, David Oxl
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Dun Pan, Hui Chen, Jiaxiang Xu, Xin Lin, Liangqing Li
BMC Gastroenterology.2023;[Epub] CrossRef
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Jiadong Chu, Na Sun, Wei Hu, Xuanli Chen, Nengjun Yi, Yueping Shen, Andy T. Y. Lau
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International Journal of Genomics.2022; 2022: 1. CrossRef
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Jun Ji, Jiahui Chen, Anqiang Wang, Wei Zhang, Hongge Ju, Yang Liu, Leping Li
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Multiomics analysis reveals CT83 is the most specific gene for triple negative breast cancer and its hypomethylation is oncogenic in breast cancer
Chen Chen, Dan Gao, Jinlong Huo, Rui Qu, Youming Guo, Xiaochi Hu, Libo Luo
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International Immunopharmacology.2021; 101: 108258. CrossRef

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Genetic Risk Score, Combined Lifestyle Factors and Risk of Colorectal Cancer: Young Ae Cho, Jeonghee Lee, Jae Hwan Oh, Hee Jin Chang, Dae Kyung Sohn, Aesun Shin, Jeongseon Kim; Cancer Res Treat. 2019;51(3):1033-1040. Published online October 18, 2018; DOI: https://doi.org/10.4143/crt.2018.447

Abstract PDF Supplementary Material PubReader ePub

Purpose
Both genetic and lifestyle factors contribute to the risk of colorectal cancer, but each individual factor has a limited effect. Therefore, we investigated the association between colorectal cancer and the combined effects of genetic factors or/and lifestyle risk factors.
Materials and Methods
In a case-control study of 632 colorectal cancer patients and 1,295 healthy controls, we quantified the genetic risk score for colorectal cancer using 13 polymorphisms. Furthermore, we determined a combined lifestyle risk score including obesity, physical activity, smoking, alcohol consumption, and dietary inflammatory index. The associations between colorectal cancer and risk score using these factors were examined using a logistic regression model.
Results
Higher genetic risk scores were associated with an increased risk of colorectal cancer (odds ratio [OR], 2.57; 95% confidence interval [CI], 1.89 to 3.49 for the highest tertile vs. lowest tertile). Among the modifiable factors, previous body mass index, physical inactivity, heavy alcohol consumption, and a high inflammatory diet were associated with an increased risk of colorectal cancer. A higher lifestyle risk score was associated with an increased risk of colorectal cancer (OR, 5.82; 95% CI, 4.02 to 8.44 for the highest tertile vs. lowest tertile). This association was similar in each genetic risk category.
Conclusion
Adherence to a healthy lifestyle is associated with a substantially reduced risk of colorectal cancer regardless of individuals’ genetic risk.

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