AUTHOR=Gong Xumeng , Hou Dong , Zhou Shengning , Tan Jianan , Zhong Guangyu , Yang Bing , Xie Lang , Han Fanghai , Zhong Lin TITLE=FMO family may serve as novel marker and potential therapeutic target for the peritoneal metastasis in gastric cancer JOURNAL=Frontiers in Oncology VOLUME=Volume 13 - 2023 YEAR=2023 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2023.1144775 DOI=10.3389/fonc.2023.1144775 ISSN=2234-943X ABSTRACT=Objective: To explore the relationship between Flavin-containing monooxygenases (FMOs) and peritoneal metastasis (PM) in gastric cancer (GC). Materials and Methods: To analyze the correlation between the expression of FMOs and cancers, pan-cancer analysis was performed by TIMER 2.0. One dataset form TCGA was used to analyze the correlation between FMOs and clinicopathological features of GC. PM is the most common mode of metastasis in GC. To further analyze the correlation between FMOs and PM of GC, a dataset for PM was produced from the NCBI GEO database. The relationship between FMOs and PM of GC was explored, and a novel PM risk signature was constructed by LASSO regression analysis. The regression model`s validity was tested by multi-sampling. For predicting PM of GC, a nomogram was established based on the model. The mechanism of FMOs in PM of GC, GO and KEGG analysis were further performed by the TCGA datasets and GEO dataset. Finally, the potential relationship between FMOs and immunotherapy was analyzed. Results: FMO1 was overexpression, FMO2 and FMO4 were under-expression in GC. The results were confirmed by TCGA dataset. What`s more, FMO1 and FMO2 were correlated positively with T, N stage of GC in the TCGA dataset. The expression of FMO1 and FMO2 were risk factor for GC Overexpression of FMO1 was significantly correlated with worse DFS and OS. FMO1 is highly expressed in GC with PM. FMO1and FMO2 were positively correlated with PM of GC. We identified a 12-gene panel for prediction of PM risk signature by LASSO (AUC= 0.948, 95%CI:0.896-1.000). A 10-gene panel for prediction of PM was identified (AUC= 0.932, 95%CI:0.874-0.990), which contain FMO1 and FMO2. In order to establish a model convenient for clinical application, a 7-gene panel was identified (AUC = 0.927, 95% CI: 0.877-0.977), which was successfully validated by multi-sampling. The results of GO and KEGG analysis suggest FMO1 and FMO2 regulate extracellular matrix and cell adhesion. FMO1 and FMO2 were positively correlated with the immune score and the infiltration of immune cells in GC. Conclusion: PM of GC correlated strongly with FMOs, FMO1 and FMO2 are novel diagnoses and therapeutic targets.