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

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.

Early response evaluation by single cell signaling profiling in acute myeloid leukemia.

Aberrant pro-survival signaling is a hallmark of cancer cells, but the response to chemotherapy is poorly understood. In this study, we investigate the initial signaling response to standard induction chemotherapy in a cohort of 32 acute myeloid leukemia (AML) patients, using 36-dimensional mass cytometry. Through supervised and unsupervised machine learning approaches, we find that reduction of extracellular-signal-regulated kinase (ERK) 1/2 and p38 mitogen-activated protein kinase (MAPK) phosphorylation in the myeloid cell compartment 24 h post-chemotherapy is a significant predictor of patient 5-year overall survival in this cohort. Validation by RNA sequencing shows induction of MAPK target gene expression in patients with high phospho-ERK1/2 24 h post-chemotherapy, while proteomics confirm an increase of the p38 prime target MAPK activated protein kinase 2 (MAPKAPK2). In this study, we demonstrate that mass cytometry can be a valuable tool for early response evaluation in AML and elucidate the potential of functional signaling analyses in precision oncology diagnostics.

Repurposing chlorpromazine for anti-leukaemic therapy by nanoparticle encapsulation.

Treatment of acute myeloid leukaemia (AML) relies on decades-old drugs, and while recent years have seen some breakthroughs, AML is still characterised by poor prognosis and survival rate. Drug repurposing can expedite the preclinical development of new therapies, and by nanocarrier encapsulation, the number of potentially viable drug candidates can be further expanded. The anti-psychotic drug chlorpromazine (CPZ) has been identified as a candidate for repurposing for AML therapy. Nanoencapsulation may improve the suitability of CPZ for the treatment of AML by reducing its effect on the central nervous system. Using the emulsion-evaporation technique, we have developed PEGylated PLGA nanoparticles loaded with CPZ for AML therapy. The nanoparticles were characterised to be between 150 and 300 nm by DLS, of spherical morphology by TEM, with a drug loading of at least 6.0% (w/w). After an initial burst release of adsorbed drug, the remaining 80% of the drug was retained in the PLGA nanoparticles for at least 24 h. The CPZ-loaded nanoparticles had equal cytotoxic potential towards AML cells to free CPZ, but acted more slowly, in line with the protracted drug release. Crucially, nanoparticles injected intravenously into zebrafish larvae did not accumulate in the brain, and nanoencapsulation also prevented CPZ from crossing an artificial membrane model. This demonstrates that the purpose for nanoencapsulation of CPZ is fulfilled, namely avoiding effects on the central nervous system while retaining the anti-AML activity of the drug.