Abstract
Background: Gastric cancer is characterized by high incidence and mortality rates. Survival improvement relies on the identification of novel prognostic factors and the implementation of stratified precision therapy. FAT4, a crucial tumor suppressor gene, has been shown to be mutated in various tumor types. However, our understanding of the association between FAT4 mutations and the prognosis of patients with gastric cancer is limited.
Methods: In this study, the impact of the FAT4 gene on prognosis was investigated using data from the TCGA database. NGS was performed on real-world gastric adenocarcinoma patients receiving different types of treatment. The conclusions from the public database were further validated. Multivariate Cox regression analysis was conducted to ascertain the prognostic significance of the FAT4 gene in the real-world cohort. Lollipop plots were generated to analyze the mutation sites in the FAT4 gene in the two cohorts, and survival disparities among distinct mutation sites were assessed using Kaplan‒Meier curves. Moreover, GSEA and immune infiltration analysis, based on the XCELL and CIBERSORT databases, were applied to explore the associations between different FAT4 mutation sites and immune infiltration.
Results: The mutational profile of FAT4 has been shown to be associated with increased survival and has been further validated by real-world next-generation sequencing (NGS) in patients with gastric adenocarcinoma. Specifically, mutations in the FAT4 cadherin 21-34 site were linked to even greater survival benefits than were mutations in cadherin 1-20 or wild-type FAT4. Patients with cadherin 21-34 mutations showed increased infiltration of immune cells, including CD4+ and CD8+ T cells, as well as M1 tumor-associated macrophages (TAMs), suggesting a potential connection between FAT4 mutations and enhanced immune infiltration.
Conclusions: This study highlights the importance of the FAT4 gene in predicting gastric cancer prognosis. Further research is needed to explore its comprehensive genetic landscape and impact on patient outcomes. These findings have implications for clinical practice, informing treatment decisions based on FAT4 gene mutations.