scholarly journals Optical control of the antigen translocation by synthetic photo-conditional viral inhibitors

2019 ◽  
Vol 10 (7) ◽  
pp. 2001-2005 ◽  
Author(s):  
M. Braner ◽  
N. Koller ◽  
J. Knauer ◽  
V. Herbring ◽  
S. Hank ◽  
...  
Keyword(s):  
Cell Lines ◽  
Antigen Processing ◽  
Immune Cell ◽  
Optical Control ◽  
Primary Cells ◽  
On Demand ◽  
Human Immune ◽  
Spatiotemporal Control ◽  
Viral Inhibitors

By designing and engineering photo-conditional viral inhibitors, spatiotemporal control of the transporter associated with antigen processing TAP was sustained, allowing the on-demand antigen translocation in human immune cell lines and primary cells by light.

scholarly journals Comparative In Vitro Sensitivities of Human Immune Cell Lines, Vaginal and Cervical Epithelial Cell Lines, and Primary Cells to Candidate Microbicides Nonoxynol 9, C31G, and Sodium Dodecyl Sulfate

2002 ◽  
Vol 46 (7) ◽  
pp. 2292-2298 ◽  
Author(s):  
Fred C. Krebs ◽  
Shendra R. Miller ◽  
Bradley J. Catalone ◽  
Raina Fichorova ◽  
Deborah Anderson ◽  
...  
Keyword(s):  
Epithelial Cell ◽  
Sodium Dodecyl Sulfate ◽  
Cell Viability ◽  
Cell Lines ◽  
Sodium Dodecyl ◽  
Primary Cells ◽  
Cytokine Activation ◽  
Dodecyl Sulfate ◽  
Human Immune

ABSTRACT In experiments to assess the in vitro impact of the candidate microbicides nonoxynol 9 (N-9), C31G, and sodium dodecyl sulfate (SDS) on human immune and epithelial cell viability, cell lines and primary cell populations of lymphocytic and monocytic origin were generally shown to be equally sensitive to exposures ranging from 10 min to 48 h. However, U-937 cells were more sensitive to N-9 and C31G after 48 h than were primary monocyte-derived macrophages. Cytokine activation of monocytes and lymphocytes had no effect on cell viability following exposure to these microbicidal compounds. Primary and passaged vaginal epithelial cultures and cell lines differed in sensitivity to N-9 and C31G but not SDS. These studies provide a foundation for in vitro experiments in which cell lines of human immune and epithelial origin can be used as suitable surrogates for primary cells to further investigate the effects of microbicides on cell metabolism, membrane composition, and integrity and the effects of cell type, proliferation, and differentiation on microbicide sensitivity.

scholarly journals Direct cytocidal effect of galectin-9 localized on collagen matrices on human immune cell lines

2014 ◽  
Vol 1840 (6) ◽  
pp. 1892-1901 ◽  
Author(s):  
Youko Fukata ◽  
Aiko Itoh ◽  
Yasuhiro Nonaka ◽  
Takashi Ogawa ◽  
Takanori Nakamura ◽  
...  
Keyword(s):  
Cell Lines ◽  
Immune Cell ◽  
Collagen Matrices ◽  
Cytocidal Effect ◽  
Human Immune

Impact of non-thermal plasma treatment on MAPK signaling pathways of human immune cell lines

Immunobiology ◽  
2013 ◽  
Vol 218 (10) ◽  
pp. 1248-1255 ◽  
Author(s):  
Lena Bundscherer ◽  
Kristian Wende ◽  
Katja Ottmüller ◽  
Annemarie Barton ◽  
Anke Schmidt ◽  
...  
Keyword(s):  
Plasma Treatment ◽  
Signaling Pathways ◽  
Cell Lines ◽  
Thermal Plasma ◽  
Immune Cell ◽  
Mapk Signaling ◽  
Non Thermal Plasma ◽  
Human Immune ◽  
Mapk Signaling Pathways

scholarly journals Monocytic THP-1 Cells Diverge Significantly From Their Native Counterparts: A Comparative Examination of The Chromosomal Conformations And Transcriptomes

2021 ◽  
Author(s):  
Yulong Liu ◽  
Hua Li ◽  
Daniel M Czajkowsky ◽  
Zhifeng Shao
Keyword(s):  
Cell Lines ◽  
Chromatin Structure ◽  
Immune Cell ◽  
Leukemia Cell ◽  
Model Systems ◽  
Leukemia Cell Line ◽  
Primary Cells ◽  
Monocytic Leukemia ◽  
Altered Expression ◽  
Wide Range

Abstract Immortalized cell lines have long been used as model systems to systematically investigate biological processes under controlled and reproducible conditions, providing insights that have greatly advanced cellular biology and medical sciences. Recently, the widely used monocytic leukemia cell line, THP-1, was comprehensively examined to understand mechanistic relationships between the 3D chromatin structure and transcription during the trans-differentiation of monocytes to macrophages. To corroborate these observations in primary cells, we analyze in situ Hi-C and RNA-seq data of human primary monocytes and their differentiated macrophages in comparison to that obtained from the monocytic/macrophagic THP-1 cells. Surprisingly, we find significant differences between the primary cells and the THP-1 cells at all levels of chromatin structure, from loops to topologically associated domains to compartments. Importantly, the compartment-level differences correlate significantly with transcription: those genes that are in A-compartments in the primary cells but are in B-compartments in the THP-1 cells exhibit a higher level of expression in the primary cells than in the THP-1 cells, and vice versa. Overall, the genes in these different compartments are enriched for a wide range of pathways, and, at least in the case of the monocytic cells, their altered expression in certain pathways in the THP-1 cells argues for a less immune cell-like phenotype, suggesting that immortalization or prolonged culturing of THP-1 caused a divergence of these cells from their native counterparts. It is thus essential to reexamine phenotypic details observed in cell lines with their native counterparts so as to ensure a proper understanding of functional cell states in vivo.

scholarly journals Small-sized, stable lipid nanoparticle for the efficient delivery of siRNA to human immune cell lines

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Takashi Nakamura ◽  
Moeka Kuroi ◽  
Yuki Fujiwara ◽  
Shota Warashina ◽  
Yusuke Sato ◽  
...  
Keyword(s):  
Cell Lines ◽  
Immune Cell ◽  
Lipid Nanoparticle ◽  
Efficient Delivery ◽  
Human Immune

scholarly journals 302 Characterization of TIGIT and PVR expression in colorectal liver metastases

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A325-A325
Author(s):  
Antoine Bernard ◽  
David Henault ◽  
Sandy Pelletier ◽  
Pamela Thebault ◽  
Benoit Barrette ◽  
...  
Keyword(s):  
T Cells ◽  
Liver Metastases ◽  
Cell Lines ◽  
Cancer Cell ◽  
Antigen Processing ◽  
Immune Cell ◽  
Cancer Cell Lines ◽  
Immune Checkpoints ◽  
Mismatch Repair Gene ◽  
Ifn Γ

BackgroundMetastatic colorectal cancer (CRC) is common and lethal and generally not responsive to current immunotherapies. We hypothesize that efficacious T cell-based immunotherapy can be developed for this malignancy, provided that immune checkpoints relevant to liver metastasis, the first site of disease progression, are targeted. Here, we characterized CRC liver metastases by RNAseq, FACS and in vitro functional assays to identify candidate immune checkpoints.MethodsWe performed deep RNAseq clustering and differential gene expression analysis on bulk RNA extracted from 52 mismatch repair gene proficient CRC liver metastases. By multiparameter FACS, we analyzed the expression of candidate immune checkpoints in cell suspensions derived from 18 liver metastases, matched non-tumoral livers, and pre-operative PBMCs. We evaluated IFN-γ (ELISA) secretion and tumor lysis (Incucyte) of tumor-infiltrating T lymphocytes (TILs) expanded from liver metastases stimulated by autologous cancer cells with or without monoclonal antibodies blocking candidate immune checkpoints.ResultsOut of 52 metastases, 21 (40.3%) clustered as immune reactive (IR) defined by concurrent high expression of transcripts related to antigen processing, immune cell lineage, immune checkpoints, interferon-gamma response, cytokines, and chemokines, whereas 25 (48.1%) were classified as non-IR. Of all inhibitory ligands assessed, PVR and PVRL2 had the highest expression, both in IR and non-IR metastases, and higher than PD-L1 and PD-L2 expression. The expression of corresponding receptors TIGIT and CD226 was significantly higher in IR compared to non-IR metastases, at absolute levels higher than PD-1. By FACS analysis, PVR and PVRL2 expression by tumor-infiltrating myeloid and tumor cells was higher than PD-L1 and PD-L2 expression. High PVR expression was also found in hepatocytes, liver macrophages and circulating monocytes in the same patients. In TILs, TIGIT was significantly overexpressed in activated CD4+CD25+ (74.8 ±3.0%) and CD8+CD25+ (68.7 ± 8.4%) compared to resting CD25neg T cells, an expression pattern that was not seen for PD-1 or in T cells infiltrating the liver or circulating in the blood. The majority of cancer cell lines derived from liver metastases expressed PVR, but low levels of PD-L1. TIL clones expanded from liver metastases expressed TIGIT at various levels inducible by TCR stimulation. Upon co-culture with autologous cancer cell lines, TIL clones were more lytic and secreted more IFN-γ in presence of anti-TIGIT blocking antibody.ConclusionsBy expression and functional data, the TIGIT/PVR immune suppressive axis appears as a biologically promising target for the development of immunotherapy in patients with CRC metastatic to the liver.AcknowledgementsThis work is supported by Bristol Myers Squibb and by the Quebec Cancer Consortium. A.B. holds a postdoctoral scholarship award from the Institut du cancer de Montréal. S.T. holds a Junior 2 clinical-scientist salary award from the Fond de recherche Santé-Québec. The University of Montreal Roger des Groseillers Research Chair in hepatopancreatobiliary surgical oncology supports the biobanking and clinicopathological database associated with this project.Ethics ApprovalInstitutional review board approvals were obtain to conduct this project (16.262) and all patients provided informed consent to contribute to this project with biospecimens and clinicopathological data (09.237).

Fructose metabolism in hepatocytes: primary cells or cell lines?

2007 ◽  
Vol 45 (01) ◽  
Author(s):  
T Speicher ◽  
G Künstle ◽  
A Wendel
Keyword(s):  
Cell Lines ◽  
Primary Cells ◽  
Fructose Metabolism

scholarly journals A Set of Cell Lines Derived from a Genetic Murine Glioblastoma Model Recapitulates Molecular and Morphological Characteristics of Human Tumors

Cancers ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 230
Author(s):  
Barbara Costa ◽  
Michael N.C. Fletcher ◽  
Pavle Boskovic ◽  
Ekaterina L. Ivanova ◽  
Tanja Eisemann ◽  
...  
Keyword(s):  
Cell Lines ◽  
Immune Cell ◽  
Treatment Options ◽  
Morphological Characteristics ◽  
Molecular Heterogeneity ◽  
Double Knockout ◽  
In Vivo Models ◽  
Human Glioblastoma ◽  
Human Gbm

Glioblastomas (GBM) are the most aggressive tumors affecting the central nervous system in adults, causing death within, on average, 15 months after diagnosis. Immunocompetent in-vivo models that closely mirror human GBM are urgently needed for deciphering glioma biology and for the development of effective treatment options. The murine GBM cell lines currently available for engraftment in immunocompetent mice are not only exiguous but also inadequate in representing prominent characteristics of human GBM such as infiltrative behavior, necrotic areas, and pronounced tumor heterogeneity. Therefore, we generated a set of glioblastoma cell lines by repeated in vivo passaging of cells isolated from a neural stem cell-specific Pten/p53 double-knockout genetic mouse brain tumor model. Transcriptome and genome analyses of the cell lines revealed molecular heterogeneity comparable to that observed in human glioblastoma. Upon orthotopic transplantation into syngeneic hosts, they formed high-grade gliomas that faithfully recapitulated the histopathological features, invasiveness and immune cell infiltration characteristic of human glioblastoma. These features make our cell lines unique and useful tools to study multiple aspects of glioblastoma pathomechanism and to test novel treatments in an intact immune microenvironment.

57 Precision neoantigen discovery using novel algorithms and expanded HLA-ligandome datasets

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A62-A62
Author(s):  
Dattatreya Mellacheruvu ◽  
Rachel Pyke ◽  
Charles Abbott ◽  
Nick Phillips ◽  
Sejal Desai ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cell Lines ◽  
Antigen Processing ◽  
Large Scale ◽  
Prediction Models ◽  
K562 Cells ◽  
Machine Learning Algorithms ◽  
Training Data ◽  
High Quality ◽  
Tissue Samples

BackgroundAccurately identified neoantigens can be effective therapeutic agents in both adjuvant and neoadjuvant settings. A key challenge for neoantigen discovery has been the availability of accurate prediction models for MHC peptide presentation. We have shown previously that our proprietary model based on (i) large-scale, in-house mono-allelic data, (ii) custom features that model antigen processing, and (iii) advanced machine learning algorithms has strong performance. We have extended upon our work by systematically integrating large quantities of high-quality, publicly available data, implementing new modelling algorithms, and rigorously testing our models. These extensions lead to substantial improvements in performance and generalizability. Our algorithm, named Systematic HLA Epitope Ranking Pan Algorithm (SHERPA™), is integrated into the ImmunoID NeXT Platform®, our immuno-genomics and transcriptomics platform specifically designed to enable the development of immunotherapies.MethodsIn-house immunopeptidomic data was generated using stably transfected HLA-null K562 cells lines that express a single HLA allele of interest, followed by immunoprecipitation using W6/32 antibody and LC-MS/MS. Public immunopeptidomics data was downloaded from repositories such as MassIVE and processed uniformly using in-house pipelines to generate peptide lists filtered at 1% false discovery rate. Other metrics (features) were either extracted from source data or generated internally by re-processing samples utilizing the ImmunoID NeXT Platform.ResultsWe have generated large-scale and high-quality immunopeptidomics data by using approximately 60 mono-allelic cell lines that unambiguously assign peptides to their presenting alleles to create our primary models. Briefly, our primary ‘binding’ algorithm models MHC-peptide binding using peptide and binding pockets while our primary ‘presentation’ model uses additional features to model antigen processing and presentation. Both primary models have significantly higher precision across all recall values in multiple test data sets, including mono-allelic cell lines and multi-allelic tissue samples. To further improve the performance of our model, we expanded the diversity of our training set using high-quality, publicly available mono-allelic immunopeptidomics data. Furthermore, multi-allelic data was integrated by resolving peptide-to-allele mappings using our primary models. We then trained a new model using the expanded training data and a new composite machine learning architecture. The resulting secondary model further improves performance and generalizability across several tissue samples.ConclusionsImproving technologies for neoantigen discovery is critical for many therapeutic applications, including personalized neoantigen vaccines, and neoantigen-based biomarkers for immunotherapies. Our new and improved algorithm (SHERPA) has significantly higher performance compared to a state-of-the-art public algorithm and furthers this objective.

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