Multi-omics Combined with Machine Learning Facilitating the Diagnosis of Gastric Cancer


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Abstract

:Gastric cancer (GC) is a highly intricate gastrointestinal malignancy. Early detection of gastric cancer forms the cornerstone of precision medicine. Several studies have been conducted to investigate early biomarkers of gastric cancer using genomics, transcriptomics, proteomics, and metabolomics, respectively. However, endogenous substances associated with various omics are concurrently altered during gastric cancer development. Furthermore, environmental exposures and family history can also induce modifications in endogenous substances. Therefore, in this study, we primarily investigated alterations in DNA mutation, DNA methylation, mRNA, lncRNA, miRNA, circRNA, and protein, as well as glucose, amino acid, nucleotide, and lipid metabolism levels in the context of GC development, employing genomics, transcriptomics, proteomics, and metabolomics. Additionally, we elucidate the impact of exposure factors, including HP, EBV, nitrosamines, smoking, alcohol consumption, and family history, on diagnostic biomarkers of gastric cancer. Lastly, we provide a summary of the application of machine learning in integrating multi-omics data. Thus, this review aims to elucidate: i) the biomarkers of gastric cancer related to genomics, transcriptomics, proteomics, and metabolomics; ii) the influence of environmental exposure and family history on multiomics data; iii) the integrated analysis of multi-omics data using machine learning techniques.

About the authors

Jie Li

Key Laboratory of Environmental Medicine Engineerin, Ministry of Education, School of Public Health, Southeast University

Email: info@benthamscience.net

Siyi Xu

Jiangsu Provincial Key Laboratory of Critical Care Medicine, School of Public Health, Southeast University

Email: info@benthamscience.net

Feng Zhu

Physical and Chemical Laboratory,, Jiangsu Provincial Center for Disease Control & Prevention

Email: info@benthamscience.net

Fei Shen

Physical and Chemical Laboratory, Jiangsu Provincial Center for Disease Control & Prevention

Email: info@benthamscience.net

Tianyi Zhang

Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University

Email: info@benthamscience.net

Xin Wan

Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University

Email: info@benthamscience.net

Saisai Gong

Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University

Email: info@benthamscience.net

Geyu Liang

Key Laboratory of Environmental Medicine Engineerin, Ministry of Education, School of Public Health, Southeast University

Author for correspondence.
Email: info@benthamscience.net

Yonglin Zhou

Physical and Chemical Laboratory,, Jiangsu Provincial Center for Disease Control and Prevention

Author for correspondence.
Email: info@benthamscience.net

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