Leah Kelly

• Detection of GD2 negative cells in bone marrow from patients with high-risk neuroblastoma using machine learning
• MSci Biomedical Sciences

Neuroblastoma (NB) is the most common childhood extracranial solid tumour and one of the most difficult childhood cancers to cure. A treatment given to many patients with high-risk neuroblastoma (metastatic disease in a patient > 1 year) is anti-GD2 immunotherapy.

Neuroblastoma often metastasises to bone marrow which is sampled in all patients at diagnosis and relapse. In a previous study, matched blood and bone marrow samples were collected from NB patients to detect GD2+ve/CD45-ve neuroblastoma circulating tumour cells from blood and disseminated tumour cells (DTCs) from bone marrow (BM) using an instrument called an ImageStream Imaging Flow Cytometer.

Using the data acquired by the ImageStream, using a machine learning algorithm, this study demonstrated additional GD2 negative DTCs could be detected in high-risk NB patients. This method may be useful for detecting GD2 loss following anti-GD2 immunotherapy, however a larger cohort of patients should be studied to confirm clinical significance.