PhD in Xenotransplantation

Supervisor(s): Prof Alexander Medvinsky, Dr Andrejs Ivanovs, Dr Carsten Marr (Hemholtz Munich) & Prof Claudio Angione (Alan Turing Institute)/nBackground/nHaematopoietic cell transplant (HCT) is a life-saving therapy for patients with haematological disorders. Umbilical cord blood (UCB) is a clinically accepted source of therapeutic cells and is a vital resource when HLA matched unrelated adult donors are in limited supply. Some UCB, however, show delayed haematopoietic reconstitution and biased lineage differentiation, which needs to be addressed to fully unlock this valuable resource stored in large numbers around the world in stem cells banks. Our preliminary xenograft transplantation analysis revealed UCB molecular traits that can serve as complementary selection criteria to identify UCBs with superior haematopoietic reconstitution capacity. An awarded MRC DPFS grant allowed us to compose a consortium aiming to generate a robust molecular biomarker-based test system for identification of optimal UCB samples for clinical transplantations./nThe proposed PhD project is closely associated with the aforementioned MRC DPFS project and aims to discover additional morphological traits. The methodology is based on the AI image-based analysis of UCB cells transplanted into immunocompromised NSG mice. This project will be conducted in the highly interactive environment of Medvinsky’s laboratory (University of Edinburgh) who are experts in mouse and human haematopoietic stem cell biology, and xenotransplantation into NSG recipients. The study will be co-supervised by experts in machine learning and clinical haematology./nAims/nClassification of umbilical cord blood (UCB) samples by the transplantation outcome./nIdentification of morphological traits in UCB samples correlating with the transplantation outcomes./nDetermine how in vivo UCB transplantation outcomes correlate with in vitro differentiation./nTraining outcomes/nThe student will acquire expertise in:/nMulti-lineage analysis of blood samples using flow cytometry and blood smears./nIn vitro differentiation myeloid and lymphoid assays./nExpertise in machine learning.