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Showing results for "rishi kotecha"

Multi-omics analysis defines highly refractory RAS burdened immature subgroup of infant acute lymphoblastic leukemia

KMT2A-rearranged infant acute lymphoblastic leukemia (ALL) represents the most refractory type of childhood leukemia. To uncover the molecular heterogeneity of this disease, we perform RNA sequencing, methylation array analysis, whole exome and targeted deep sequencing on 84 infants with KMT2A-rearranged leukemia.

Successful treatment of a child with acute monoblastic leukaemia who relapsed with T-cell acute lymphoblastic leukaemia: A rare lineage switch

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

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.

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

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.

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. 

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.

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.

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.

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.