RESUMO
Using multi-color flow cytometry analysis, we studied the immunophenotypical differences between leukemic cells from patients with AML/MDS and hematopoietic stem and progenitor cells (HSPCs) from patients in complete remission (CR) following their successful treatment. The panel of markers included CD34, CD38, CD45RA, CD123 as representatives for a hierarchical hematopoietic stem and progenitor cell (HSPC) classification as well as programmed death ligand 1 (PD-L1). Rather than restricting the evaluation on a 2- or 3-dimensional analysis, we applied a t-distributed stochastic neighbor embedding (t-SNE) approach to obtain deeper insight and segregation between leukemic cells and normal HPSCs. For that purpose, we created a t-SNE map, which resulted in the visualization of 27 cell clusters based on their similarity concerning the composition and intensity of antigen expression. Two of these clusters were "leukemia-related" containing a great proportion of CD34+/CD38- hematopoietic stem cells (HSCs) or CD34+ cells with a strong co-expression of CD45RA/CD123, respectively. CD34+ cells within the latter cluster were also highly positive for PD-L1 reflecting their immunosuppressive capacity. Beyond this proof of principle study, the inclusion of additional markers will be helpful to refine the differentiation between normal HSPCs and leukemic cells, particularly in the context of minimal disease detection and antigen-targeted therapeutic interventions. Furthermore, we suggest a protocol for the assignment of new cell ensembles in quantitative terms, via a numerical value, the Pearson coefficient, based on a similarity comparison of the t-SNE pattern with a reference.
RESUMO
Many biomedical applications of nanoparticles on the cellular level require a characterisation of their subcellular distribution. Depending on the nanoparticle and its preferred intracellular compartment, this may be a nontrivial task, and consequently, the available methodologies are constantly increasing. Here, we show that super-resolution microscopy in combination with spatial statistics (SMSS), comprising the pair correlation and the nearest neighbour function, is a powerful tool to identify spatial correlations between nanoparticles and moving vesicles. Furthermore, various types of motion like for example diffusive, active or Lévy flight transport can be distinguished within this concept via suitable statistical functions, which also contain information about the factors limiting the motion, as well as regarding characteristic length scales. The SMSS concept fills a methodological gap related to mobile intracellular nanoparticle hosts and its extension to further scenarios is straightforward. It is exemplified on MCF-7 cells after exposure to carbon nanodots, demonstrating that these particles are stored predominantly in the lysosomes.
RESUMO
Carbon nanodots (CNDs) comprise a class of next generation nanomaterials with a wide variety of potential applications. Here, we report on their uptake into primary hematopoietic cells from three normal donors and malignant cells from five patients with de novo acute myeloid leukemia (AML). A significant CND uptake was observed in all cell types of the normal and leukemic cells. Still, the uptake was significantly smaller for the CD34+ and CD33+ myeloid subsets of the malignant cell population as compared to the normal blood-derived CD34+ and CD33+ cells. For the T and B lymphoid cell populations as defined by CD3 and CD19 within the leukemic and normal samples a similar uptake was observed. The CNDs accumulate preferentially in small clusters in the periphery of the nucleus as already shown in previous studies for CD34+ progenitor/stem cells and human breast cancer cells. This particular subcellular localization could be useful for targeting the lysosomal compartment, which plays a pivotal role in the context of autophagy associated survival of AML cells. Our results demonstrate the usability of CNDs beyond their application for in vitro and in vivo fluorescence labeling or drug delivery into normal and malignant cells.