Medical Biology - Research Publications

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Type: Journal Article × Author: Bowtell, David × Author: Christie, Elizabeth ×

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    Clinical MDR1 inhibitors enhance Smac-mimetic bioavailability to kill murine LSCs and improve survival in AML models
    Morrish, E ; Copeland, A ; Moujalled, DM ; Powell, JA ; Silke, N ; Lin, A ; Jarman, KE ; Sandow, JJ ; Ebert, G ; Mackiewicz, L ; Beach, JA ; Christie, EL ; Lewis, AC ; Pomilio, G ; Fischer, KC ; MacPherson, L ; Bowtell, DDL ; Webb, A ; Pellegrini, M ; Dawson, MA ; Pitson, SM ; Wei, AH ; Silke, J ; Brumatti, G (AMER SOC HEMATOLOGY, 2020-10-27)
    The specific targeting of inhibitor of apoptosis (IAP) proteins by Smac-mimetic (SM) drugs, such as birinapant, has been tested in clinical trials of acute myeloid leukemia (AML) and certain solid cancers. Despite their promising safety profile, SMs have had variable and limited success. Using a library of more than 5700 bioactive compounds, we screened for approaches that could sensitize AML cells to birinapant and identified multidrug resistance protein 1 inhibitors (MDR1i) as a class of clinically approved drugs that can enhance the efficacy of SM therapy. Genetic or pharmacological inhibition of MDR1 increased intracellular levels of birinapant and sensitized AML cells from leukemia murine models, human leukemia cell lines, and primary AML samples to killing by birinapant. The combination of clinical MDR1 and IAP inhibitors was well tolerated in vivo and more effective against leukemic cells, compared with normal hematopoietic progenitors. Importantly, birinapant combined with third-generation MDR1i effectively killed murine leukemic stem cells (LSCs) and prolonged survival of AML-burdened mice, suggesting a therapeutic opportunity for AML. This study identified a drug combination strategy that, by efficiently killing LSCs, may have the potential to improve outcomes in patients with AML.
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    Inferring structural variant cancer cell fraction
    Cmero, M ; Yuan, K ; Ong, CS ; Schröder, J ; PCAWG Evolution and Heterogeneity Working Group, ; Corcoran, NM ; Papenfuss, T ; Hovens, CM ; Markowetz, F ; Macintyre, G ; PCAWG Consortium, (Nature Research (part of Springer Nature), 2020-02-05)
    We present SVclone, a computational method for inferring the cancer cell fraction of structural variant (SV) breakpoints from whole-genome sequencing data. SVclone accurately determines the variant allele frequencies of both SV breakends, then simultaneously estimates the cancer cell fraction and SV copy number. We assess performance using in silico mixtures of real samples, at known proportions, created from two clonal metastases from the same patient. We find that SVclone's performance is comparable to single-nucleotide variant-based methods, despite having an order of magnitude fewer data points. As part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium, which aggregated whole-genome sequencing data from 2658 cancers across 38 tumour types, we use SVclone to reveal a subset of liver, ovarian and pancreatic cancers with subclonally enriched copy-number neutral rearrangements that show decreased overall survival. SVclone enables improved characterisation of SV intra-tumour heterogeneity.