Disease spectrum of gastric cancer susceptibility genes

• Main Authors: McKinley, Sophia K. (Author), Singh, Preeti (Author), Yin, Kanhua (Author), Wang, Jin (Author), Zhou, Jingan (Author), Bao, Yujia (Author), Wu, Menghua (Author), Pathak, Kush (Author), Mullen, John T. (Author), Braun, Danielle (Author), Hughes, Kevin S. (Author)
• Format: Article
• Language: English
• Published: Springer Science and Business Media LLC, 2022-02-09T16:03:53Z.
• Subjects: Article
• Online Access: Get fulltext

 Abstract Pathogenic variants in germline cancer susceptibility genes can increase the risk of a large number of diseases. Our study aims to assess the disease spectrum of gastric cancer susceptibility genes and to develop a comprehensive resource of gene-disease associations for clinicians. Twenty-seven potential germline gastric cancer susceptibility genes were identified from three review articles and from six commonly used genetic information resources. The diseases associated with each gene were evaluated via a semi-structured review of six genetic resources and an additional literature review using a natural language processing (NLP)-based procedure. Out of 27 candidate genes, 13 were identified as gastric cancer susceptibility genes (APC, ATM, BMPR1A, CDH1, CHEK2, EPCAM, MLH1, MSH2, MSH6, MUTYH-Biallelic, PALB2, SMAD4, and STK11). A total of 145 gene-disease associations (with 45 unique diseases) were found to be associated with these 13 genes. Other gastrointestinal cancers were prominent among identified associations, with 11 of 13 gastric cancer susceptibility genes also associated with colorectal cancer, eight genes associated with pancreatic cancer, and seven genes associated with small intestine cancer. Gastric cancer susceptibility genes are frequently associated with other diseases as well as gastric cancer, with potential implications for how carriers of these genes are screened and managed. Unfortunately, commonly used genetic resources provide heterogeneous information with regard to these genes and their associated diseases, highlighting the importance of developing guides for clinicians that integrate data across available resources and the medical literature.