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Showing results for "rishi kotecha"
A new study led by Australian researchers has outlined for the first time the best treatment options for children suffering from meningioma
Symptomatic methotrexate-related central neurotoxicity (MTX neurotoxicity) is a severe toxicity experienced during acute lymphoblastic leukemia (ALL) therapy with potential long-term neurologic complications. Risk factors and long-term outcomes require further study.
Infant MLL-AF4-driven acute lymphoblastic leukemia (ALL) is a devastating disease with dismal prognosis. A lack of understanding of the unique biology of this disease, particularly its prenatal origin, has hindered improvement of survival. We perform multiple RNA sequencing experiments on fetal, neonatal, and adult hematopoietic stem and progenitor cells from human and mouse.
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
Rishi S. Kotecha MB ChB (Hons) MRCPCH FRACP PhD Co-Head, Leukaemia Translational Research rishi.kotecha@health.wa.gov.au Co-Head, Leukaemia
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.