Science Philanthropy / University Medical Center Groningen (UMCG)
Predicting response to immunotherapy based on diet and microbiome
The gut microbiome is increasingly being recognized as a modulator of health and disease, including immune homeostasis. The treatment of cancer through drugs that stimulate the immune response has improved the prognosis for many patients, especially for advanced melanoma. The most widely used form are checkpoint inhibitors (ICI). Recent evidence from mouse models and small human cohorts have revealed a link between the gut microbiome (GM) and responsiveness to ICI. Still, there is limited consensus on the specific microbiome characteristics linked to ICI clinical benefit. To disentangle some of these associations, the PRIMM cohort was setup between KCL in the UK and UMCG in the Netherlands. In an interim analysis, baseline and longitudinal blood and stool samples of more than 150 advanced cutaneous melanoma patients have been collected to perform multiple omics assays including metabolomics.
Given that nutrition may represent the safest and easiest modulator of the gut microbiome, understanding the relationship between nutrition, the microbiome, and anti-cancer immunity could a) generate hypotheses for mechanistic work in pre-clinical models, and b) open highly interesting therapeutic avenues for cancer patients.
Seerave Foundation is supporting two independent centers performing complementary prospective clinical studies:
- University Medical Center Groningen (UMCG), Netherlands, under the supervision of Prof. Geke Hospers and Prof. Rinse Weersma. The Seerave Fellows at UMCG will coordinate the efforts undertaken.
- King’s College London (KCL), United Kingdom, under the supervision of Prof. Tim Spector and Dr. Veronique Bataille. KCL will lead a consortium of UK Melanoma Centres
Both studies aim at performing longitudinal analysis of the nutritional status and the composition and function of the gut microbiome in melanoma patients undergoing immunotherapy.
The ultimate goal is to integrate the collected data into predictive “–omics signatures” including other biomarkers from blood and tumors, host genetics and immunomics as well as other clinical parameters.