Bingham, M. A. | Search bioRxiv

bioRxiv2025

Single Cell Spatial Transcriptomics Reveals Immunotherapy-Driven Bone Marrow Niche Remodeling in AML

Given the successful graft-versus-leukemia cell treatment effect observed with allogeneic hematopoietic stem cell transplant for patients with refractory or relapsed acute myeloid leukemia, immunotherapies have also been investigated in the nontransplant setting. Here, we use a multi-omic approach to investigate spatiotemporal interactions in the bone marrow niche between leukemia cells and immune cells in patients with refractory or relapsed acute myeloid leukemia treated with a combination of the immune checkpoint inhibitor pembrolizumab and hypomethylating agent decitabine. We derived precise segmentation data by extensively training nuclear and membrane cell segmentation models, which enabled accurate transcript assignment and deep learning-feature-based image analysis. To overcome read-depth limitations, we integrated the single-cell RNA sequencing data with single-cell-resolution spatial transcriptomic data from the same sample. Quantifying cell-cell distances between cell edges rather than cell centroids allowed us to conduct a more accurate downstream analysis of the tumor microenvironment, revealing that multiple cell types of interest had global enrichment or local enrichment proximal to leukemia cells after pembrolizumab treatment, which could be associated with their clinical responses. Furthermore, ligand-receptor analysis indicated a potential increase in TWEAK signaling between leukemia cells and immune cells after pembrolizumab treatment. HighlightsO_LISpatial transcriptomic analysis of R-AML bone marrow niches provides detailed information about intercellular interactions in the tumor microenvironment. C_LIO_LIImmunotherapy shifts the cell composition of the leukemia neighborhood. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/634753v1_ufig1.gif" ALT="Figure 1"> View larger version (93K): org.highwire.dtl.DTLVardef@955273org.highwire.dtl.DTLVardef@158234corg.highwire.dtl.DTLVardef@175837borg.highwire.dtl.DTLVardef@b0a38_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2022

Circadian Gene Expression in Mouse Renal Proximal Tubule

Circadian variability in kidney function has long been recognized but is often ignored as a potential confounding variable in in vivo physiological experiments. To provide a guide for physiological studies on the kidney proximal tubule, we have now created a data resource consisting of expression levels for all measurable mRNA transcripts in microdissected proximal tubule segments from mice as a function of the time of day. This approach employs small-sample RNA-sequencing (RNA-seq) applied to microdissected renal proximal tubules including both S1 proximal convoluted tubules (PCTs) and S2 proximal straight tubules (PSTs). The data were analyzed using JTK-Cycle to detect periodicity. The data are provided as a user-friendly web page at https://esbl.nhlbi.nih.gov/Databases/Circadian-Prox/. In PCTs, 234 transcripts were found to vary in a circadian manner (3.7 % of total quantified). In PSTs, 334 transcripts were found to vary in a circadian manner (5.3 % of total quantified). Transcripts previously known to be associated with corticosteroid action and transcripts associated with increased flow were found to be overrepresented among circadian transcripts peaking during the "dark" portion of the day (Zeitgeber 14-22), corresponding to the peak levels of corticosterone and glomerular filtration rate in mice. BlurbCircadian variation in gene expression can be an important determinant in the regulation of kidney function. The authors used RNA-seq in microdissected proximal S1 and S2 segments to identify transcripts that vary in a circadian manner. The data were used to construct a user-friendly web resource.

systems biology↗