Multiple Myeloma (MM) is a haematological cancer caused by abnormal plasma cell expansion in the bone marrow. MM is preceded by an earlier clinically stable stage termed monoclonal gammopathy of undetermined significance (MGUS). Approximately 1% of people with MGUS will develop MM each year yet there is no clinical intervention to prevent this transformation. Alterations in the bone marrow (BM) microenvironment are thought to play a role in this evolution and that changes in the gut microbiome leads to alterations in inflammatory pathways and BM microenvironment. Thus, dysbiosis may impact tumorigenesis in MM and promote MGUS to MM transformation.
Dried plums (prunes) have been used for centuries to regulate gut activity, however recent studies have demonstrated that the carbohydrates and polyphenols found in prunes act as prebiotics. This results in favourable changes in the microbiota and an increase in short chain fatty acid (SCFA) production, n-butyrate and propionate – promoting bone health and reducing inflammation. Anti-cancer properties of SCFA have been identified in different cancers and a reduction in SCFA-producing bacteria is observed in MM patients, however a possible link between dietary intervention and malignant transformation from MGUS to MM remains to be explored.
This project will investigate how dried plums alter gut-derived metabolites to influence MM progression using a combination of in vivo mouse models of MGUS and MM, and in vitro cellular mechanistic studies. Analysis of cellular responses to dietary supplementation with dried plums will be assessed at the cellular level (FACS, mass cytometry) and at the molecular level (qPCR, RNASeq). This work will generate pre-clinical data for future clinical translation for those living with MGUS.
The project would be suitable for candidates interested in prevention and therapy of haematological malignancies, gut dysbiosis and bioinformatics. The student will receive training in in vivo disease models, in vitro disease mechanisms, and computational modelling. Training in scientific writing, presentation, data management, statistical analysis and presentation at national and international conferences will be encouraged.