Cancer Centre
Unlocking the key to leukaemia progression in kids
Team
Leukaemia Translational Research projects
Reports and Findings
Pharmacokinetics of PEGasparaginase in Infants with Acute Lymphoblastic Leukemia
PEGasparaginase is known to be a critical drug for treating pediatric acute lymphoblastic leukemia (ALL), however, there is insufficient evidence to determine the optimal dose for infants who are less than one year of age at diagnosis. This international study was conducted to identify the pharmacokinetics of PEGasparaginase in infants with newly diagnosed ALL and gather insight into the clearance and dosing of this population.
Children's Cancers Published research Early Childhood Development Leukaemia Translational ResearchFDA-approved disulfiram as a novel treatment for aggressive leukemia
Acute leukemia continues to be a major cause of death from disease worldwide and current chemotherapeutic agents are associated with significant morbidity in survivors. While better and safer treatments for acute leukemia are urgently needed, standard drug development pipelines are lengthy and drug repurposing therefore provides a promising approach.
Children's Cancers Published research Leukaemia Translational ResearchInflammation induces α1-adrenoceptor expression in peripheral blood mononuclear cells of patients with complex regional pain syndrome
Persistent regional and systemic inflammation may promote pain and hyperalgesia in complex regional pain syndrome. In this study, we investigated whether stimulation of α1-adrenoceptors on peripheral blood mononuclear cells might contribute to this inflammatory state.
Published research Pregnancy and Early Life Immunology Leukaemia Translational Research Subsite: CancerReproducible Bioinformatics Analysis Workflows for Detecting IGH Gene Fusions in B-Cell Acute Lymphoblastic Leukaemia Patients
B-cell acute lymphoblastic leukaemia (B-ALL) is characterised by diverse genomic alterations, the most frequent being gene fusions detected via transcriptomic analysis (mRNA-seq). Due to its hypervariable nature, gene fusions involving the Immunoglobulin Heavy Chain (IGH) locus can be difficult to detect with standard gene fusion calling algorithms and significant computational resources and analysis times are required. We aimed to optimize a gene fusion calling workflow to achieve best-case sensitivity for IGH gene fusion detection.
Children's Cancers Published research Leukaemia Translational Research Subsite: Cancer