Artificial Intelligence and Bioinformatics in the Malignant Progression of Gastric Cancer

Gastric cancer (GC) is characterized by heterogeneity and complexity and remains one of the leading causes of cancer-related deaths. The molecular mechanisms underlying carcinogenesis and the progression of GC have been central to scientific research and urgently need to be elucidated. With the potent development of next-generation sequencing technologies, a vast amount of bioinformatic data—including genomics, epigenomics, transcriptomics, proteomics, and metabolomics—has been accumulated, providing an extraordinary prospect to explore the heterogeneity and intricacy of GC. Nevertheless, the enormous amount of data created by bioinformatics analyses presents considerable analytical challenges. The application of artificial intelligence (AI), including machine learning and deep learning, has emerged as a powerful resolution to these challenges, obtaining useful information from exponential omics data, particularly in GC. The integration of AI with multi-omics approaches in GC research offers novel insights and powerful tools for gaining a deeper understanding of cancer’s complexities. This article reviews the latest research and progress of AI and bioinformatics analysis in GC oncology over the past several years, focusing on the landscape of GC carcinogenesis, progression, and metastasis. We also discuss the current challenges for improving performance and highlight future directions for more precise and effective treatments for GC patients.