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Disease spectrum of gastric cancer susceptibility genes

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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.

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Data availability

All data used within this research are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors acknowledge Ann S. Adams (Department of Surgery, Massachusetts General Hospital) for editorial and writing assistance.

Funding

This study received no specific funding.

Author information

Authors and Affiliations

  1. Department of Surgery, Massachusetts General Hospital, Boston, MA, USA

    Sophia K. McKinley

  2. Division of Surgical Oncology, Massachusetts General Hospital and Harvard Medical School, 55 Fruit Street, Yawkey 7, Boston, MA, 02114, USA

    Preeti Singh, Kanhua Yin, Jin Wang, Jingan Zhou, John T. Mullen & Kevin S. Hughes

  3. Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA

    Kanhua Yin & Danielle Braun

  4. Department of Breast Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China

    Jin Wang

  5. Department of General Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China

    Jingan Zhou

  6. Computer Science & Artificial Intelligence, Massachusetts Institute of Technology, Boston, MA, USA

    Yujia Bao & Menghua Wu

  7. Department of Surgical Oncology, P. D Hinduja Hospital, Mumbai, India

    Kush Pathak

  8. Department of Biostatistics, Harvard University T.H. Chan School of Public Health, Boston, MA, USA

    Danielle Braun

Authors
  1. Sophia K. McKinley
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Corresponding author

Correspondence to Kevin S. Hughes.

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Conflict of interest

Kevin S. Hughes receives Honoraria from Hologic (Surgical implant for radiation planning with breast conservation and wire-free breast biopsy) and Myriad Genetics and has a financial interest in CRA Health (Formerly Hughes RiskApps). CRA Health develops risk assessment models/software with a particular focus on breast cancer and colorectal cancer. Dr. Hughes is a founder and owns equity in the company. Dr. Hughes is the Co-Creator of Ask2Me.Org which is freely available for clinical use and is licensed for commercial use by the Dana Farber Cancer Institute and the MGH. Dr. Hughes's interests in CRA Health and Ask2Me.Org were reviewed and are managed by Massachusetts General Hospital and Partners Health Care in accordance with their conflict-of-interest policies. Dr. Braun co-leads the BayesMendel laboratory, which licenses software for the computation of risk prediction models. She does not derive any personal income from these licenses. All revenues are assigned to the lab for software maintenance and upgrades. The other authors declare that they have no conflict of interest.

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We used public databases with no patient data, and ethical committee was waived.

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McKinley, S.K., Singh, P., Yin, K. et al. Disease spectrum of gastric cancer susceptibility genes. Med Oncol 38, 46 (2021). https://doi.org/10.1007/s12032-021-01495-w

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