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Showing results for "rishi kotecha"
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.
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.
Rishi S. Kotecha MB ChB (Hons) MRCPCH FRACP PhD Co-Head, Leukaemia Translational Research rishi.kotecha@health.wa.gov.au Co-Head, 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.
Infant 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).
Development of standardised guidance by national and regional authorities for reducing the risk of SARS-CoV-2 transmission to children with cancer
We have revealed a novel SH2D1A gene mutation in a patient with XLP resulting in fulminant refractory EBV-driven HLH, which is a recognized severe complication
Our findings shed light on the mechanisms of leukemia-induced bone loss
We report a term male with congenital acute erythroleukemia who achieved sustained remission with low-dose cytosine arabinoside alone
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.