Clinical characteristics and bioinformatics analysis of familial adenomatous polyposis
Objective To thoroughly analyze the two main subtypes of familial adenomatous polyposis(FAP),to understand the similarities and differences in their clinical characteristics,and to explore the relationship between APC gene mutations and disease progression.Methods This retrospective study encompassed 65 FAP patients who were treated and treated at the People's Hospital of Wuhan University from January 2013 to December 2023,including 36 classical FAP(CFAP)and 29 attenuated FAP(AFAP)cases.By analyzing the clinical data of these patients and datasets from gene expression databases,we identified differentially expressed genes(DEGs)and conducted Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis,as well as Gene Set Enrichment Analysis(GSEA).Results Clinical data analysis revealed significant differences between CFAP and AFAP patients in terms of age of onset,symptom manifestation,and risks of colorectal cancer development.Gene expression analysis highlighted significant differences between these two FAP subtypes,especially in terms of cell proliferation,apoptosis,and signal pathway regulation.The DEGs were primarily involved in biological processes such as response to symbiont,viral processes,and positive regulation of cytokine production,with KEGG pathway enrichment analysis indicating their involvement in NOD-like receptor signaling pathways.GSEA suggested that fundamental biological processes like the cell cycle,mitosis,and DNA synthesis played crucial roles in the development of CFAP.Conclusion By integrating bioinformatics methods and clinical data analysis,this study has revealed significant clinical and molecular differences between the CFAP and AFAP subtypes of FAP.These differences are vital for understanding the disease progression mechanisms of different FAP subtypes,providing new insights and potential targets for clinical diagnosis and treatment of FAP,and providing an important foundation for future treatment and management.
万方数据
维普
