Single cell characterisation of the mucosal microenvironment in Stomach Inflammation and Related Epithelial Neoplasia (SIREN)

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Stomach cancer is the second most common cause of cancer related death worldwide. In most patients, the diagnosis is established at the stage of advanced disease, when only limited, palliative treatment can be offered resulting in five-year survival rates of around 25%. The majority of these tumours are driven by chronic inflammation of the stomach lining. We know about a sequence of precursor lesions that are often present prior to the actual cancer. National guidelines have recently introduced endoscopic surveillance for patients with these conditions to allow early detection of stomach cancer, but we are still far from reliable individual risk prediction. The main factor causing inflammation of the stomach lining is infection with the bacteria Helicobacter pylori (H. pylori). This infection is usually contracted in infanthood and persists throughout the patient's lifetime. In many patients it does not cause any problems, but in others the immune response caused by the infection is the key factor for further cancer development. It has been suggested that factors that modulate the local immune-response dictate the individual risk for cancer development. This involves genetic factors of both the patient and the bacteria (if present), the composition and type of immune cells present in the stomach lining, and cell-cell interaction of the immune cells with other cellular components of the stomach wall, also including fat cells and surface cells of the lining which maintain the actual barrier function against harmful agents, so-called carcinogens. The fine balance between these elements can be further disturbed by certain medication such as acid blockers, aspirin or statins. The key objective of this study is the generation of a cell atlas of different states of stomach inflammation, including pre-cancerous conditions. This will be achieved by so-called single cell sequencing methods that allow the analysis of messenger molecules produced by individual cell types and cell populations. This will help to gain knowledge on the functional cell-cell-interaction in stomach inflammation on its path to cancer and also on the structural hierarchy of different cell types within the lining of the stomach. We will select specific patients with distinct stages of inflammation in the stomach who have been exposed to different risk factors for gastric cancer, with the main focus on inflammation caused by H. pylori. We will use modern machine learning approaches to generate a bioinformatics model that will allow the prediction of factors that orchestrate the individual immune response. This will further facilitate the establishment of biomarkers for a more precise individual risk prediction with the aim of both early detection and prevention of gastric cancer. This includes the generation of blood-based markers to identify patients with preneoplastic conditions requiring endoscopy, as well as histopathology markers to identify those patients with a high risk of progression towards cancer. Candidate biomarkers identified from the data generated for the stomach cell atlas will be validated in a wider cohort of patients to confirm the feasibility of application in a routine clinical setting. Similarly, we look for targets that can be utilised for the development of drugs that aim at the prevention of further progression of stomach inflammation towards cancer. The combined expertise of the applicant and his partners will allow a precise definition of the contribution of chronic H. pylori infection to a local defective immune response in the stomach, identifying key factors that discriminate the different stages of disease, leading from surface inflammation via pre-cancerous conditions to stomach cancer. Such a multi-modal single cell analysis of the local immune system of the stomach in health, inflammation, pre-cancer and cancer has not yet been undertaken.