CombiFlow:combinatorial AML-specific plasma membrane expression profiles allow longitudinal tracking of clones

Acute myeloid leukemia (AML) often presents as an oligoclonal disease whereby multiple genetically distinct subclones can coexist within patients. Differences in signaling and drug sensitivity of such subclones complicate treatment and warrant tools to identify them and track disease progression. We previously identified >50 AML-specific plasma membrane (PM) proteins, and 7 of these (CD82, CD97, FLT3, IL1RAP, TIM3, CD25, and CD123) were implemented in routine diagnostics in patients with AML (n = 256) and myelodysplastic syndrome (n = 33). We developed a pipeline termed CombiFlow in which expression data of multiple PM markers is merged, allowing a principal component–based analysis to identify distinctive marker expression profiles and to generate single-cell t-distributed stochastic neighbor embedding landscapes to longitudinally track clonal evolution. Positivity for one or more of the markers after 2 courses of intensive chemotherapy predicted a shorter relapse-free survival, supporting a role for these markers in measurable residual disease (MRD) detection. CombiFlow also allowed the tracking of clonal evolution in paired diagnosis and relapse samples. Extending the panel to 36 AML-specific markers further refined the CombiFlow pipeline. In conclusion, CombiFlow provides a valuable tool in the diagnosis, MRD detection, clonal tracking, and understanding of clonal heterogeneity in AML

The USP7-TRIM27 axis mediates non-canonical PRC1.1 function and is a druggable target in leukemia

In an attempt to unravel functionality of the non-canonical PRC1.1 Polycomb complex in human leukemogenesis, we show that USP7 and TRIM27 are integral components of PRC1.1. USP7 interactome analyses show that PRC1.1 is the predominant Polycomb complex co-precipitating with USP7. USP7 inhibition results in PRC1.1 disassembly and loss of chromatin binding, coinciding with reduced H2AK119ub and H3K27ac levels and diminished gene transcription of active PRC1.1-controlled loci, whereas H2AK119ub marks are also lost at PRC1 loci. TRIM27 and USP7 are reciprocally required for incorporation into PRC1.1, and TRIM27 knockdown partially rescues USP7 inhibitor sensitivity. USP7 inhibitors effectively impair proliferation in AML cells in vitro, also independent of the USP7-MDM2-TP53 axis, and MLL-AF9-induced leukemia is delayed in vivo in human leukemia xenografts. We propose a model where USP7 counteracts TRIM27 E3 ligase activity, thereby maintaining PRC1.1 integrity and function. Moreover, USP7 inhibition may be a promising new strategy to treat AML patients

Automated cell type annotation and exploration of single-cell signaling dynamics using mass cytometry

Summary: Mass cytometry by time-of-flight (CyTOF) is an emerging technology allowing for in-depth characterization of cellular heterogeneity in cancer and other diseases. Unfortunately, high-dimensional analyses of CyTOF data remain quite demanding. Here, we deploy a bioinformatics framework that tackles two fundamental problems in CyTOF analyses namely (1) automated annotation of cell populations guided by a reference dataset and (2) systematic utilization of single-cell data for effective patient stratification. By applying this framework on several publicly available datasets, we demonstrate that the Scaffold approach achieves good trade-off between sensitivity and specificity for automated cell type annotation. Additionally, a case study focusing on a cohort of 43 leukemia patients reported salient interactions between signaling proteins that are sufficient to predict short-term survival at time of diagnosis using the XGBoost algorithm. Our work introduces an automated and versatile analysis framework for CyTOF data with many applications in future precision medicine projects

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Controversy exists as to whether neoadjuvant chemotherapy improves survival in patients with invasive bladder cancer, despite randomised controlled trials of more than 3000 patients. We undertook a systematic review and meta-analysis to assess the effect of such treatment on survival in patients with this disease

Azithromycin in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Background Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatory actions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19. Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospital with COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients were randomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once per day by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatment groups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment and were twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants and local study staff were not masked to the allocated treatment, but all others involved in the trial were masked to the outcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treat population. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936. Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) were eligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was 65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomly allocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall, 561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days (rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median 10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days (rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, no significant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilation or death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24). Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or other prespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restricted to patients in whom there is a clear antimicrobial indication. Funding UK Research and Innovation (Medical Research Council) and National Institute of Health Research