Publications by authors named "Rachel Astles"

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Classes of ITD Predict Outcomes in AML Patients Treated with FLT3 Inhibitors.

Clin Cancer Res 2019 01 4;25(2):573-583. Epub 2018 Sep 4.

Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania.

Purpose: Recurrent internal tandem duplication (ITD) mutations are observed in various cancers including acute myeloid leukemia (AML), where ITD mutations in tyrosine kinase receptor FLT3 are associated with poor prognostic outcomes. Several FLT3 inhibitors (FLT3i) are in clinical trials for high-risk -ITD-positive AML. However, the variability of survival following FLT3i treatment suggests that the mere presence of -ITD mutations might not guarantee effective clinical response. Motivated by the heterogeneity of -ITD mutations, we investigated the effects of -ITD structural features on the response of AML patients to treatment. We developed the HeatITup (HEAT diffusion for Internal Tandem dUPlication) algorithm to identify and quantitate ITD structural features including nucleotide composition. Using HeatITup, we studied the impact of ITD structural features on the clinical response to FLT3i and induction chemotherapy in -ITD-positive AML patients.

Results: HeatITup accurately identifies and classifies ITDs into newly defined categories of "typical" or "atypical" based on their nucleotide composition. A typical ITD's insert sequence completely matches the wild-type whereas an atypical ITD's insert contains nucleotides exogenous to the wild-type . Our analysis shows marked divergence between typical and atypical ITD mutation features. Furthermore, our data suggest that AML patients carrying typical -ITDs benefited significantly more from both FLT3i and induction chemotherapy treatments than patients with atypical -ITDs.

Conclusions: These results underscore the importance of structural discernment of complex somatic mutations such as ITDs in progressing toward personalized treatment of AML patients, and enable researchers and clinicians to unravel ITD complexity using the provided software..
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http://dx.doi.org/10.1158/1078-0432.CCR-18-0655DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6335170PMC
January 2019