Isolation of Autophagy Competent from Cancer Cells by Differential Large-Scale Multilayered Density Gradient Centrifugations

Author(s):  
Merve Kacal ◽  
Helin Vakifahmetoglu-Norberg
2020 ◽  
Author(s):  
Xiaoqing Wang ◽  
Collin Tokheim ◽  
Binbin Wang ◽  
Shengqing Stan Gu ◽  
Qin Tang ◽  
...  

SUMMARYDespite remarkable clinical efficacies of immune checkpoint blockade (ICB) in cancer treatment, ICB benefits in triple-negative breast cancer (TNBC) remain limited. Through pooled in vivo CRISPR knockout (KO) screens in syngeneic TNBC mouse models, we found that inhibition of the E3 ubiquitin ligase Cop1 in cancer cells decreases the secretion of macrophage-associated chemokines, reduces tumor macrophage infiltration, and shows synergy in anti-tumor immunity with ICB. Transcriptomics, epigenomics, and proteomics analyses revealed Cop1 functions through proteasomal degradation of the C/ebpδ protein. Cop1 substrate Trib2 functions as a scaffold linking Cop1 and C/ebpδ, which leads to polyubiquitination of C/ebpδ. Cop1 inhibition stabilizes C/ebpδ to suppress the expression of macrophage chemoattractant genes. Our integrated approach implicates Cop1 as a target for improving cancer immunotherapy efficacy by regulating chemokine secretion and macrophage levels in the TNBC tumor microenvironment.HighlightsLarge-scale in vivo CRISPR screens identify new immune targets regulating the tumor microenvironmentCop1 knockout in cancer cells enhances anti-tumor immunityCop1 modulates chemokine secretion and macrophage infiltration into tumorsCop1 targets C/ebpδ degradation via Trib2 and influences ICB response


2020 ◽  
Vol 21 (11) ◽  
pp. 4127
Author(s):  
Xu Han ◽  
James Kapaldo ◽  
Yueying Liu ◽  
M. Sharon Stack ◽  
Elahe Alizadeh ◽  
...  

The effective clinical application of atmospheric pressure plasma jet (APPJ) treatments requires a well-founded methodology that can describe the interactions between the plasma jet and a treated sample and the temporal and spatial changes that result from the treatment. In this study, we developed a large-scale image analysis method to identify the cell-cycle stage and quantify damage to nuclear DNA in single cells. The method was then tested and used to examine spatio-temporal distributions of nuclear DNA damage in two cell lines from the same anatomic location, namely the oral cavity, after treatment with a nitrogen APPJ. One cell line was malignant, and the other, nonmalignant. The results showed that DNA damage in cancer cells was maximized at the plasma jet treatment region, where the APPJ directly contacted the sample, and declined radially outward. As incubation continued, DNA damage in cancer cells decreased slightly over the first 4 h before rapidly decreasing by approximately 60% at 8 h post-treatment. In nonmalignant cells, no damage was observed within 1 h after treatment, but damage was detected 2 h after treatment. Notably, the damage was 5-fold less than that detected in irradiated cancer cells. Moreover, examining damage with respect to the cell cycle showed that S phase cells were more susceptible to DNA damage than either G1 or G2 phase cells. The proposed methodology for large-scale image analysis is not limited to APPJ post-treatment applications and can be utilized to evaluate biological samples affected by any type of radiation, and, more so, the cell-cycle classification can be used on any cell type with any nuclear DNA staining.


2012 ◽  
Vol 30 (30_suppl) ◽  
pp. 9-9
Author(s):  
Taku Nakahara ◽  
Diane McCarthy ◽  
Yoshiaki Miura ◽  
Hidehisa Asada

9 Background: While the importance of glycosylation in many cancers is well established, the use of glycomics in biomarker research has lagged behind genomics and proteomics. This is due, in part, to the lack of practical platforms capable of analyzing clinically relevant sample numbers. To address these challenges, we have developed a novel glycomics technology (the GlycanMap platform) that combines a high-throughput assay with custom bioinformatics and rapidly provides both biomarker candidates and information on the underlying biology. Methods: N-glycans were enzymatically released from their parent glycoproteins and captured on chemoselective beads. After washing to remove non-glycan components, purified glycans were derivatized to stabilize labile sialic acids and released from the beads. The steps described above were automated on a 96-well format robotics system to maximize throughput and reduce variability and can be performed in less than 24 hours. Released glycans were analyzed by MALDI-TOF MS using internal standards to facilitate quantitation. In addition to comparing individual glycans between groups, glycan changes were also analyzed with respect to known glycan biosynthetic pathways. Results: The automated assay was compatible with multiple biological sample types, including serum/plasma, tissue, and cell lysates. Human serum was used to assess assay performance and yielded 50-60 glycans with CVs of 10-15% and good linearity. The lower limit of detection was approximately 100 nM. The assay was applied to drug-treated colon cancer cells (HCT116) and revealed significant (> 2-fold) changes in 17 glycans. Projection of these glycan changes on the known N-glycan pathway showed that the most significant changes occurred in the medial-Golgi. Conclusions: We have developed and optimized a high-throughput glycomics platform to facilitate large-scale biomarker studies and assured its practical performance in terms of sensitivity, repeatability, and linearity. Application of this assay to drug-treated colon cancer cells demonstrated that projection of individual glycan changes against known glycan pathways provided additional information about biological mechanism and relevance.


2016 ◽  
Vol 7 (12) ◽  
pp. e2492-e2492 ◽  
Author(s):  
Lesley A Mathews Griner ◽  
Xiaohu Zhang ◽  
Rajarshi Guha ◽  
Crystal McKnight ◽  
Ian S Goldlust ◽  
...  

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