Biology subjects

Sarkisian, M. R.

Publications and source records attributed to Sarkisian, M. R..

4 recordsLinked to original sources

bioRxiv2024

Get to know your neighbors with a SNAQ™: A framework for single cell spatial neighborhood analysis in immunohistochemical images

MotivationAnalyzing the local microenvironment of tumor cells can provide significant insights into their complex interactions with their cellular surroundings, including immune cells. By quantifying the prevalence and distances of certain immune cells in the vicinity of tumor cells through a neighborhood analysis, patterns may emerge that indicate specific associations between cell populations. Such analyses can reveal important aspects of tumor-immune dynamics, which may inform therapeutic strategies. This method enables an in-depth exploration of spatial interactions among different cell types, which is crucial for research in oncology, immunology, and developmental biology. ResultsWe introduce an R Markdown script called SNAQTM (Single-cell Spatial Neighborhood Analysis and Quantification), which conducts a neighborhood analysis on immunofluorescent images without the need for extensive coding knowledge. As a demonstration, SNAQTM was used to analyze images of pancreatic ductal adenocarcinoma. Samples stained for DAPI, PanCK, CD68, and PD-L1 were segmented and classified using QuPath. The resulting CSV files were exported into RStudio for further analysis and visualization using SNAQTM. Visualizations include plots revealing the cellular composition of neighborhoods around multiple cell types within a customizable radius. Additionally, the analysis includes measuring the distances between cells of certain types relative to others across multiple regions of interest. Availability and implementationThe R Markdown files that comprise the SNAQTM algorithm and the input data from this paper are freely available on the web at https://github.com/AryehSilver1/SNAQ. Visual Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=70 SRC="FIGDIR/small/606539v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1cda240org.highwire.dtl.DTLVardef@157280forg.highwire.dtl.DTLVardef@1072cf8org.highwire.dtl.DTLVardef@1964e0_HPS_FORMAT_FIGEXP M_FIG C_FIG Created with BioRender.com.

bioinformatics↗

bioRxiv2022

Increasing Ciliary ARL13B Expression Drives Active and Inhibitor-Resistant SMO and GLI into Glioma Primary Cilia

ADP-ribosylation factor-like protein 13B (ARL13B), a regulatory GTPase and guanine exchange factor (GEF) enriches in primary cilia and promotes tumorigenesis in part by regulating Smoothened (SMO), GLI, and Sonic hedgehog (SHH) signaling. Gliomas with increased ARL13B, SMO and GLI2 expression are more aggressive but the relationship to cilia is unclear. Previous studies showed increasing ARL13B in glioblastoma cells promoted ciliary SMO accumulation, independent of exogenous SHH addition. Here we show SMO accumulation is due to increased ciliary, but not extraciliary ARL13B. Increasing ARL13B expression promotes the accumulation of both activated SMO and GLI2 in glioma cilia, but not in NIH3T3 fibroblast cilia. ARL13B-driven increases in ciliary SMO and GLI2 are resistant to SMO inhibitors, GDC-0449 and cyclopamine. Finally, temozolomide chemotherapy which increases ARL13B expression in glioma, stimulates SMO and GLI2 into glioma cilia, but not fibroblast cilia. Collectively, our data suggest factors that elevate ARL13B may drive drug-resistant SMO and GLI into cilia. This suggests the ARL13B-associated mechanism that leads to ciliary SMO/GLI recruitment may promote treatment resistance in glioma.

cancer biology↗

bioRxiv2022

Slow-cycling cells in glioblastoma: a specific population in the cellular mosaic of cancer stem cells

AO_SCPLOWBSTRACTC_SCPLOWGlioblastoma (GBM) exhibits populations of cells that drive tumorigenesis, treatment resistance, and disease progression. Cells with such properties have been described to express specific surface and intracellular markers or exhibit specific functional features including being slow-cycling or quiescent with the ability to generate proliferative progenies. In GBM, each of these cellular fractions was shown to harbor cardinal features of cancer stem cells 1-7. In this study we focus on the comparison of these cells and present evidence of great phenotypic and functional heterogeneity in brain cancer cell populations with stemness properties, especially between slow-cycling cells and cells phenotypically defined based on the expression of markers commonly used to enrich for cancer stem cells (CSCs). Our data support the cancer stem cell mosaicism model with slow-cycling cells representing critical tesserae.

cancer biology↗

bioRxiv2021

Tumor Treating Fields Suppression of Ciliogenesis Enhances Temozolomide Toxicity

Tumor Treating Fields (TTFields) are low intensity, alternating intermediate frequency (200kHz) electrical fields that extend survival of glioblastoma patients receiving maintenance temozolomide (TMZ) chemotherapy. How TTFields exert efficacy on cancer over normal cells, or interact with TMZ is unclear. Primary cilia are microtubule-based organelles triggered by extracellular ligands, mechanical and electrical field stimulation, and are capable of promoting cancer growth and TMZ chemoresistance. We found in both low and high grade patient glioma cell lines that TTFields ablated cilia within 24 hours. Halting TTFields treatment led to recovered frequencies of elongated cilia. Cilia on normal primary astrocytes, neurons, and multiciliated/ependymal cells were less affected by TTFields. The TTFields-mediated loss of glioma cilia was partially rescued by chloroquine pretreatment, suggesting the effect is in part due to autophagy activation. We also observed death of ciliated cells during TTFields by live imaging. Notably, TMZ-induced stimulation of ciliogenesis in both adherent cells and gliomaspheres was blocked by TTFields. Moreover, the inhibitory effects of TTFields and TMZ on tumor cell recurrence correlated with the relative timing of TMZ exposure to TTFields and ARL13B+ cilia. Finally, TTFields disrupted cilia in patient tumors treated ex vivo. Our findings suggest TTFields efficacy may depend on the degree of tumor ciliogenesis and relative timing of TMZ treatment.

cancer biology↗