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Showing results for "rishi kotecha"

Down syndrome-associated leukaemias: current evidence and challenges

Children with Down syndrome (DS) are at increased risk of developing haematological malignancies, in particular acute megakaryoblastic leukaemia and acute lymphoblastic leukaemia. The microenvironment established by abnormal haematopoiesis driven by trisomy 21 is compounded by additional genetic and epigenetic changes that can drive leukaemogenesis in patients with DS.

Challenges and considerations for antifungal prophylaxis in children with acute myeloid leukemia

Children receiving treatment for acute myeloid leukemia (AML) are at high risk of invasive fungal disease (IFD). Evidence from pediatric studies support the efficacy of antifungal prophylaxis in reducing the burden of IFD in children receiving therapy for AML, yet existing antifungal agents have specific limitations and comparative data to inform the optimal prophylactic approach are lacking.

Imaging Flow Cytometric Identification of Chromosomal Defects in Paediatric Acute Lymphoblastic Leukaemia

Acute lymphoblastic leukaemia is the most common childhood malignancy that remains a leading cause of death in childhood. It may be characterised by multiple known recurrent genetic aberrations that inform prognosis, the most common being hyperdiploidy.

Age-based pegaspargase dosing is safe and achieves therapeutic levels in infants with ALL: report from COG AALL15P1

Rishi S. Kotecha MB ChB (Hons) MRCPCH FRACP PhD Co-Head, Leukaemia Translational Research rishi.kotecha@health.wa.gov.au Co-Head, Leukaemia

A small molecule inhibitor of RNA-binding protein IGF2BP3 shows anti-leukemic activity

The RNA-binding protein IGF2BP3 is an oncofetal protein overexpressed in B-acute lymphoblastic leukemia and is critical for leukemogenesis in experimental models. With cancerspecific expression, functional dispensability for normal development, and an unleveraged prooncogenic function in mRNA homeostasis, IGF2BP3 represents an excellent target.

Imaging of Abdominal Complications in Children With Acute Lymphoblastic Leukaemia

Acute lymphoblastic leukaemia (ALL) is the most common paediatric malignancy and remains one of the most common causes of cancer-related death in children and adolescents. Five-year overall survival rates now exceed 90% with current multidrug chemotherapeutic regimens.

High Expression of NTRK1 in ETV6::RUNX1 Positive Acute Lymphoblastic Leukaemia Drives Factor Independence and Sensitivity to Larotrectinib

ETV6::RUNX1 is one of the most common recurrent genomic abnormalities in acute lymphoblastic leukaemia (ALL) and is associated with a good prognosis. High expression of NTRK1, encoding tropomyosin receptor kinase A (TrkA), confers a poor prognosis in other malignancies and may contribute to therapy resistance in patients with ETV6::RUNX1 B-ALL.

Psychosocial Outcomes in Parents of Children with Acute Lymphoblastic Leukaemia in Australia and New Zealand Through and Beyond Treatment

Parents of children with acute lymphoblastic leukaemia (ALL) experience emotional distress throughout their child's treatment course. This study describes the psychological experience of Australian and New Zealand parents of children diagnosed with ALL. 

Acute Leukaemia of Ambiguous Lineage Presenting as a Focal Bone Lesion: a Case Report

Acute leukaemia is the most common childhood malignancy. Almost all cases are classified as acute lymphoblastic leukaemia or acute myeloid leukaemia. Acute leukaemia of ambiguous lineage (ALAL) is a rare form of acute leukaemia that cannot be classified by a single lineage. Like other acute leukaemias, ALAL typically presents with nonspecific symptoms such as fatigue, fever, or bleeding.

Reproducible 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.