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Showing results for "rishi kotecha"
Research
Updates in infant acute lymphoblastic leukemia and the potential for targeted therapyOutcomes for infants diagnosed under 1 year of age with KMT2A-rearranged acute lymphoblastic leukemia (ALL) have remained stagnant over the past 20 years. Successive treatment protocols have previously focused on intensification of conventional chemotherapy, but increased treatment-related toxicity and chemoresistance have led to a plateau in survival.
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Successful treatment of a child with acute monoblastic leukaemia who relapsed with T-cell acute lymphoblastic leukaemia: A rare lineage switchRishi S. Kotecha MB ChB (Hons) MRCPCH FRACP PhD Co-Head, Leukaemia Translational Research rishi.kotecha@health.wa.gov.au Co-Head, Leukaemia
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Targeting the bone marrow microenvironment: a novel therapeutic strategy for pre-B acute lymphoblastic leukemiaOur findings shed light on the mechanisms of leukemia-induced bone loss
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Challenges and considerations for antifungal prophylaxis in children with acute myeloid leukemiaChildren 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.
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Pharmacogenomics in pediatric oncology: Australian adolescent or young adult and caregiver perspectivesPreemptive pharmacogenomic (PGx) testing in pediatric oncology patients could reduce toxicity and improve efficacy of medications yet remains underutilized. Consumer identified implementation barriers have not been extensively explored nor included adolescent or young adult (AYA) patient perspectives. This study describes Australian pediatric oncology consumer perspectives on PGx testing, elucidating barriers to implementation.
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Biologic and Clinical Analysis of Childhood Gamma Delta T-ALL Identifies LMO2/STAG2 Rearrangements as Extremely High RiskAcute lymphoblastic leukemia expressing the gamma delta T-cell receptor (γδ T-ALL) is a poorly understood disease. We studied 200 children with γδ T-ALL from 13 clinical study groups to understand the clinical and genetic features of this disease. We found age and genetic drivers were significantly associated with outcome.
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Minimising Adverse Drug Reactions and Verifying Economic Legitimacy-Pharmacogenomics Implementation in Children (MARVEL- PIC): protocol for a national randomised controlled trialDNA-informed prescribing (termed pharmacogenomics, PGx) is the epitome of personalised medicine. Despite international guidelines existing, its implementation in paediatric oncology remains sparse.
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Case Report: Long-Term Survival of a Pediatric Patient With an Intra-Abdominal Undifferentiated Carcinoma of Unknown PrimaryThis report provides detailed characterization of carcinoma of unknown primary (CUP) in a young child and in the absence of defined therapeutic guidelines for pediatric CUP, the successful treatment strategy described should be considered for similar cases.
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Clinical Implications of Minimal Residual Disease Detection in Infants With KMT2A-Rearranged Acute Lymphoblastic Leukemia Treated on the Interfant-06 ProtocolInfant acute lymphoblastic leukemia (ALL) is characterized by a high incidence of KMT2A gene rearrangements and poor outcome. We evaluated the value of minimal residual disease (MRD) in infants with KMT2A-rearranged ALL treated within the Interfant-06 protocol, which compared lymphoid-style consolidation (protocol IB) versus myeloid-style consolidation (araC, daunorubicin, etoposide/mitoxantrone, araC, etoposide).
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Reproducible Bioinformatics Analysis Workflows for Detecting IGH Gene Fusions in B-Cell Acute Lymphoblastic Leukaemia PatientsB-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.