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Biology subjects

McLachlan, T.

Publications and source records attributed to McLachlan, T..

2 recordsLinked to original sources

Adaptive resistance to FLT3 inhibitors is potentiated by ROS-driven DNA repair signalling

Alterations in the FMS-like tyrosine kinase 3 (FLT3) gene are the most frequent driver mutations in acute myeloid leukaemia (AML), linked to a high risk of relapse in patients with internal tandem duplications (FLT3-ITD). Tyrosine kinase inhibitors (TKIs) targeting the FLT3 protein are approved for clinical use, yet resistance often emerges. This resistance is mainly seen following the acquisition of additional point mutations in the tyrosine kinase domain (TKD), resulting in a double mutant FLT3-ITD/TKD, which sustains cell signalling and survival despite the presence of FLT3 inhibitors. Here, we developed a FLT3-mutant AML model with adaptive resistance to type II TKIs, sorafenib, and quizartinib by in vitro drug selection. Through global multiomic profiling, we identified upregulation of proteins involved in reactive oxygen species (ROS) production, particularly NADPH-oxidases, driving cellular ROS-addiction, with resistant cells relying on ROS for survival, and genome fidelity preserved by ATM-driven DNA repair. Transcriptomic analysis of adult and paediatric AML (pAML) patients identified high ATM expression as a biomarker for shorter median overall survival in both the de novo and relapsed settings. Inhibition of ATM with clinically relevant therapy WSD-0628 effectively killed TKI- and chemotherapy-resistant AML cells in vitro and significantly extended the survival of mice with sorafenib- and quizartinib-resistant FLT3-ITD AML in vivo. We propose a new treatment strategy to improve survival of patients who develop resistance to sorafenib and quizartinib, as well as relapsed and refractory pAML, exploiting resistance mechanisms to precision therapies and cell-intrinsic features of high-risk cases, highlighting a clinically relevant salvage strategy.

cancer biology↗

High-Throughput Global Phosphoproteomic Profiling Using Phospho Heavy-Labeled-Spiketide FAIMS Stepped-CV DDA (pHASED)

Global high-throughput profiling of oncogenic signaling pathways by phosphoproteomics is increasingly being applied to cancer specimens. Such quantitative unbiased phosphoproteomic profiling of cancer cells identifies oncogenic signaling cascades that drive disease initiation and progression; pathways that are often invisible to genomics sequencing strategies. Therefore, phosphoproteomic profiling has immense potential for informing individualized anti-cancer treatments. However, complicated and extensive sample preparation protocols, coupled with intricate chromatographic separation techniques that are necessary to achieve adequate phosphoproteomic depth, limits the clinical utility of these techniques. Traditionally, phosphoproteomics is performed using isobaric tagged based quantitation coupled with TiO2 enrichment and offline prefractionation prior to nLC-MS/MS. However, the use of isobaric tags and offline HPLC limits the applicability of phosphoproteomics for the analysis of individual patient samples in real-time. To address these limitations, here we have optimized a new protocol, phospho-Heavy-labeled-spiketide FAIMS Stepped-CV DDA (pHASED). pHASED maintained phosphoproteomic coverage yet decreased sample preparation time and complexity by eliminating the variability associated with offline prefractionation. pHASED employed online phosphoproteome deconvolution using high-field asymmetric waveform ion mobility spectrometry (FAIMS) and internal phosphopeptide standards to provide accurate label-free quantitation data. Compared with our traditional tandem mass tag (TMT) phosphoproteomics workflow and optimized using isogenic FLT3-mutant acute myeloid leukemia (AML) cell line models (n=18/workflow), pHASED halved total sample preparation, and running time (TMT=10 days, pHASED=5 days) and doubled the depth of phosphoproteomic coverage in real-time (phosphopeptides = 7,694 pHASED, 3,861 TMT). pHASED coupled with bioinformatic analysis predicted differential activation of the DNA damage and repair ATM signaling pathway in sorafenib-resistant AML cell line models, uncovering a potential therapeutic opportunity that was validated using cytotoxicity assays. Herein, we optimized a rapid, reproducible, and flexible protocol for the characterization of complex cancer phosphoproteomes in real-time, highlighting the potential for phosphoproteomics to aid in the improvement of clinical treatment strategies.

biochemistry↗