Publications

We present a consensus machine learning approach to identify gene targets of likely importance for pediatric AML risk.

Identification of FOLR1 as a CART cell target and demonstration of preclinical efficacy in vivo.

We used single-cell RNA sequencing and single-cell ATAC sequencing to profile 28 patients representing different pAML subtypes at diagnosis, remission and relapse.

These results indicate that mutations in FLT3, RAS, or TP53 are common in older patients with AML and are associated with specific AML phenotypes as defined by laboratory values, cytogenetics, and clinical outcomes.

We sought to improve outcome in patients with childhood acute myeloid leukaemia (AML) by applying risk-directed therapy that was based on genetic abnormalities of the leukaemic cells and measurements of minimal residual disease (MRD) done by flow cytometry during treatment.

This paper aims to discuss differences between childhood and adult AML, and to highlight recommendations that are specific to children.

We present the molecular landscape of pediatric acute myeloid leukemia (AML) and characterize nearly 1,000 participants in Children’s Oncology Group (COG) AML trials.

Multivariate analysis demonstrated that presence of the Flt3/ITD was the single most significant, independent prognostic factor for poor outcome (P = .009) in pediatric AML.

Here we present a pan-cancer study of somatic alterations, including single nucleotide variants, small insertions or deletions, structural variations, copy number alterations, gene fusions and internal tandem duplications in 1,699 paediatric leukaemias and solid tumours across six histotypes, with whole-genome, whole-exome and transcriptome sequencing data processed under a uniform analytical framework.

We review recent advances in the biologic understanding and treatment of childhood acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), identify therapeutically challenging subgroups, and suggest future directions of research.

We used single-cell RNA sequencing and single-cell ATAC sequencing to profile 28 patients representing different pAML subtypes at diagnosis, remission and relapse.

Identification of FOLR1 as a CART cell target and demonstration of preclinical efficacy in vivo.

We present a consensus machine learning approach to identify gene targets of likely importance for pediatric AML risk.