Prediction of prognosis, immunogenicity and efficacy of immunotherapy based on cholesterol metabolism in gastric cancer

Chengjun Zhu; Mengpei Yan; Zhijun Zhang; Yikai Shen; Wangwen Wang; Zetian Chen; Changsheng Cai; Hongda Liu; Zekuan Xu; Zheng Li

doi:10.3389/fonc.2024.1518010

Prediction of prognosis, immunogenicity and efficacy of immunotherapy based on cholesterol metabolism in gastric cancer

Front Oncol. 2024 Dec 24:14:1518010. doi: 10.3389/fonc.2024.1518010. eCollection 2024.

Authors

Chengjun Zhu^#^{1

2}, Mengpei Yan^#^{1

2}, Zhijun Zhang^#^{1

2}, Yikai Shen^#^{1

2}, Wangwen Wang³, Zetian Chen^{1

2}, Changsheng Cai^{1

2}, Hongda Liu^{1

2}, Zekuan Xu^{1

2

4

5}, Zheng Li^{1

2}

Affiliations

¹ Department of General Surgery, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
² Gastric Cancer Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
³ Department of Geriatric Gastroenterology, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
⁴ Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.
⁵ The Institute of Gastric Cancer, Nanjing Medical University, Nanjing, China.

^# Contributed equally.

Abstract

Background: Cholesterol metabolism plays a crucial role in tumor progression and immune response modulation. However, the precise connection between cholesterol metabolism-related genes (CMRGs) and their implications for clinical prognosis, the tumor microenvironment (TME), and the outcomes of immunotherapy in gastric cancer remains to be fully elucidated.

Methods: Transcriptome data and related clinical information from 675 gastric cancer patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A total of 50 cholesterol metabolism-related genes (CMRGs) were identified from the Kyoto Encyclopedia of Genes and Genomes (KEGG, hsa04979). Consensus clustering analysis was used to classify patients into distinct molecular subgroups, while principal component analysis (PCA) was applied to develop a prognostic scoring system for predicting survival and immunotherapy response. The scoring system was validated using three independent cohorts of gastric cancer patients.

Results: Based on 49 CMRGs, 675 gastric cancer patients were categorized into three distinct subgroups with varying prognoses, tumor microenvironment features, and clinical characteristics. Further differential gene analysis and consensus clustering identified two additional subgroups. The prognostic scoring system developed through PCA demonstrated that the high-score subgroup had significantly improved survival, higher tumor mutational burden (TMB), and microsatellite instability (MSI), as well as a greater number of mutated genes, indicating greater sensitivity to immunotherapy. This system was validated in a real-world cohort undergoing immunotherapy. Additionally, the correlation between GPC3 expression and cholesterol levels was confirmed, highlighting GPC3's potential biological role.

Conclusion: This study highlights the importance of CMRGs in gastric cancer, deepens our understanding of the tumor immune microenvironment, and guides individualized immunotherapy.

Keywords: cholesterol; gastric cancer; immunotherapy; prognosis; tumor microenvironment.

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was partially supported by National Natural Science Foundation of China (82472943), Youth Program of National Natural Science Foundation of China (82002562), Jiangsu Province Hospital (the First Affiliated Hospital with Nanjing Medical University) Clinical Capacity Enhancement Project (JSPH-MC-2022-12), Support Program for Young and Middle-aged Teachers of Nanjing Medical University, and National Natural Science Foundation of China (82072708).