Publications by authors named "Julia Wlosik"
Mass cytometry enables deep profiling of biological samples at single-cell resolution. This technology is more than relevant in cancer research due to high cellular heterogeneity and complexity. Downstream analysis of high-dimensional datasets increasingly relies on machine learning (ML) to extract clinically relevant information, including supervised algorithms for classification and regression purposes.
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- The protocol outlines a detailed process for analyzing natural killer (NK) cells from blood samples using mass cytometry.
- It involves three main steps: incubating PBMCs with metal-conjugated antibodies for extracellular profiling, followed by fixation and staining for intracellular proteins, and finally acquiring data using a mass cytometer.
- High-dimensional analysis provides insights into different NK cell subsets and their unique characteristics, with further information available in the referenced study by Chretien et al. (2021).
Article Synopsis
- Natural killer (NK) cells are crucial in fighting leukemia, but their function is hindered by leukemic blasts, leading to the presence of dysfunctional NK cells in acute myeloid leukemia (AML).
- In a study involving patients with newly diagnosed AML, researchers found a significant accumulation of a specific subset of NK cells (CD56CD16) that resemble those seen in HIV-infected individuals, indicating a potential disruption in their activation and function.
- A higher percentage of these CD56CD16 NK cells at diagnosis correlated with poorer clinical outcomes, suggesting they might be a marker for immune evasion as AML progresses.