scholarly journals A Genome-wide Survey of Mutations in the Jurkat Cell Line

2017 ◽  
Author(s):  
Louis Gioia ◽  
Azeem Siddique ◽  
Steven R. Head ◽  
Daniel R. Salomon ◽  
Andrew I. Su

The Jurkat cell line has an extensive history as a model of T cell signaling. But at the turn of the 21st century, some irregularities were observed in Jurkat’s expression of central regulators of T cell receptor signaling, which raised doubts about how closely the cell line paralleled normal human T cells. While numerous expression deficiencies have been described in Jurkat, genetic explanations have only been provided for a handful of defects. Here, we report a comprehensive catolog of genomic variation in the Jurkat cell line based on whole-genome sequencing. With this list of all detectable, non-reference sequences, we prioritize potentially damaging mutations by mining public databases for functional effects. We confirm the majority of documented mutations in Jurkat and propose links from detrimental gene variants to observed expression abnormalities in the cell line. This work ties together decades of molecular experiments and serves as a resource that will streamline both the interpretation of past research and the design of future Jurkat studies.

1988 ◽  
Vol 168 (5) ◽  
pp. 1899-1916 ◽  
Author(s):  
J A Bluestone ◽  
R Q Cron ◽  
M Cotterman ◽  
B A Houlden ◽  
L A Matis

Analyses of TCR-bearing murine and human T cells have defined a unique subpopulation of T cells that express the TCR-gamma/delta proteins. The specificity of TCR-gamma/delta T cells and their role in the immune response have not yet been elucidated. Here we examine alloreactive TCR-gamma/delta T cell lines and clones that recognize MHC-encoded antigens. A BALB/c nu/nu (H-2d)-derived H-2k specific T cell line and derived clones were both cytolytic and released lymphokines after recognition of a non-classical H-2 antigen encoded in the TL region of the MHC. These cells expressed the V gamma 2/C gamma 1 protein in association with a TCR-delta gene product encoded by a Va gene segment rearranged to two D delta and one J delta variable elements. A second MHC-specific B10 nu/nu (H-2b) TCR-gamma/delta T cell line appeared to recognize a classical H-2D-encoded MHC molecule and expressed a distinct V gamma/C gamma 4-encoded protein. These data suggest that many TCR-gamma/delta-expressing T cells may recognize MHC-linked antigens encoded within distinct subregions of the MHC. The role of MHC-specific TCR-gamma/delta cells in immune responses and their immunological significance are discussed.


2017 ◽  
Vol 18 (7) ◽  
pp. 1409 ◽  
Author(s):  
Man Liu ◽  
Rumana Yasmeen ◽  
Naomi Fukagawa ◽  
Liangli Yu ◽  
Young Kim ◽  
...  

2020 ◽  
Vol 5 ◽  
pp. 42 ◽  
Author(s):  
Suet Ling Felce ◽  
Gillian Farnie ◽  
Michael L. Dustin ◽  
James H. Felce

Background: The leukaemia-derived Jurkat E6.1 cell line has been used as a model T cell in the study of many aspects of T cell biology, most notably activation in response to T cell receptor (TCR) engagement. Methods: We present whole-transcriptome RNA-Sequencing data for Jurkat E6.1 cells in the resting state and two hours post-activation via TCR and CD28. We compare early transcriptional responses in the presence and absence of the chemokines CXCL12 and CCL19, and perform a basic comparison between observed transcriptional responses in Jurkat E6.1 cells and those in primary human T cells using publicly deposited data. Results: Jurkat E6.1 cells have many of the hallmarks of standard T cell transcriptional responses to activation, but lack most of the depth of responses in primary cells. Conclusions: These data indicate that Jurkat E6.1 cells hence represent only a highly simplified model of early T cell transcriptional responses.


Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 18-19
Author(s):  
Scott Howard ◽  
Ansu Kumar ◽  
Anusha Pampana ◽  
Yashaswini S Ullal ◽  
Anuj Tyagi ◽  
...  

Background:Early T-cell Precursor Acute Lymphoblastic Leukemia (ETP-ALL), an orphan disease, is a sub-type of T-Cell Acute Lymphoblastic Leukemia (T-ALL) with very poor prognosis and limited therapy options. ETP-ALL is a heterogeneous disease with many distinct genomic profiles, often with more myeloid than lymphoid characteristics. However, standard of care (SOC) drugs for acute myeloid leukemia (AML) have shown limited efficacy for ETP-ALL (PMID: 32733662, 25435716). The genomic profiles of ETP-ALL patients have more complex cytogenetics and larger numbers of genomic aberrations when compared to non-ETP-ALL (T-ALL) profiles (PMID: 22237106, 30641417). We present an alternative multi-gene analysis approach using the Cellworks Omics Biology Model (CBM) workflow to identify unique, intersecting protein pathways in patient-specific disease profiles. The CBM predictive workflow was used to design novel personalized therapy options for an ETP-ALL representative PEER human lymphoid cell line in comparison to a T-ALL JURKAT cell line. The predicted combination therapies were then validated in a lab model. Methods:A PEER cell line was selected to represent ETP-ALL and a JURKAT cell line was selected as a representative for non-ETP T-ALL. Next Generation Sequencing (NGS) was performed for the PEER cell line. For the JURKAT cell line, publicly available NGS whole exome sequencing from cBioPortal and Sanger, along with array CGH from Agilent, were used. The genomic data for the PEER and JURKAT cell lines were used as inputs to the CBM to generate dynamic patient-specific disease protein network maps. Biomarkers and pathway characteristics unique to the PEER and JURKAT cell lines were identified. A digital drug library of targeted FDA-approved agents was simulated on the disease models using both single drug agents and drug combinations at varying doses. The treatment impact was assessed by quantitatively measuring drug effect on a cell growth score, which is a composite of the quantified values of cell proliferation, survival and apoptosis along with impact on the patient-specific disease biomarker score. Comparative dose response studies were run to assess IC50 differences for both cell lines. Cellworks VenturaTM predicted novel therapy combinations for the ETP-ALL representative PEER cell line, which were then prospectively validated by in vitro experiments. The same therapy options were predicted to be less effective in the T-ALL representative JURKAT cell line, which was also confirmed by in vitro studies. Results:The CBM predicted three novel combination therapies for the ETP-ALL representative PEER cell line: nilotinib + cytarabine, bortezomib + cytarabine and bortezomib + idarubicin. All three therapies were predicted to be less effective in JURKAT cells. In vitro, PEER cells were sensitive to all 3 combinations, as predicted by the CBM; whereas, JURKAT cell lines were not sensitive to the first 2 combinations (as predicted), but were sensitive to bortezomib + idarubicin. The CBM analysis is supported by scientific rationales for these combinations based on the genomics-driven disease characteristics of the cell-line. The reasons for drug sensitivity and resistance were determined. These combinations were then prospectively validated in vitro on both cell lines and the experimental responses matched the predicted outcomes. Conclusion:The Cellworks Omics Biology Model integrates the multiple genomic abnormalities in a patient to identify disease network characteristics unlike other NGS analytic tools that attempt to interpret the impact of each genomic alteration in isolation. CBM identified 3 novel therapy options for ETP-ALL that were validated in vitro, similar to anecdotal experience in vivo. This predictive technology can improve clinical decision-making and identify novel treatment options. Disclosures Howard: Cellworks:Consultancy;Servier:Consultancy, Other: Speaker;EUSA Pharma:Consultancy;Sanofi:Consultancy, Other: Speaker;Boston Scientific:Consultancy.Kumar:Cellworks Research India Private Limited:Current Employment.Pampana:Cellworks Research India Private Limited:Current Employment.Ullal:Cellworks Research India Private Limited:Current Employment.Tyagi:Cellworks Research India Private Limited:Current Employment.Lala:Cellworks Research India Private Limited:Current Employment.Kumari:Cellworks Research India Private Limited:Current Employment.Joseph:Cellworks Research India Private Limited:Current Employment.Raju:Cellworks Research India Private Limited:Current Employment.Balakrishnan:Cellworks Research India Private Limited:Current Employment.Mundkur:Cellworks Group Inc.:Current Employment.Macpherson:Cellworks Group Inc.:Current Employment.Nair:Cellworks Research India Private Limited:Current Employment.Kapoor:Cellworks Research India Private Limited:Current Employment.


2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Patricia Mercier-Letondal ◽  
Chrystel Marton ◽  
Yann Godet ◽  
Jeanne Galaine

Abstract Background Metabolic cell features are able to give reliable information on cell functional state. Thus, metabolic potential assessment of T cells in malignancy setting represents a promising area, especially in adoptive cell therapy procedures. Easy to set up and convenient Seahorse technology have recently been proposed by Agilent Technologies and it could be used to monitor T cells metabolic potential. However, this method demonstrates an inter-assay variability and lacks practices standardization. Results We aimed to overcome these shortcomings thanks to a lymphoblastic derived JURKAT cell line seeding in each experiment to standardize the Seahorse process. We used an adapted XF Cell MitoStress Kit protocol, consisting in the evaluation of basal, stressed and maximal glycolysis and oxidative phosphorylation related parameters, through sequential addition of oligomycin and carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone (FCCP) to a glucose containing medium. Data were acquired and analyzed through Agilent Seahorse XFe96 analyzer. Indeed, we validated this method in the light of ICH Q2 (R1) guidelines. We were able to confirm the specificity and accuracy of the method. We also demonstrated the precision, linearity and range of the method in our experimental conditions. Conclusion The validation of the method consisting in a JURKAT cell line experimental incorporation as a control material contributes to improve the Seahorse technology’s robustness. These results lay the groundwork for the implementation of this technology to optimize T cell based cellular therapy products production process and monitoring.


BMC Genomics ◽  
2018 ◽  
Vol 19 (1) ◽  
Author(s):  
Louis Gioia ◽  
Azeem Siddique ◽  
Steven R. Head ◽  
Daniel R. Salomon ◽  
Andrew I. Su

2020 ◽  
Author(s):  
Patricia Letondal ◽  
Chrystel Marton ◽  
Yann Godet ◽  
Jeanne Galaine

Abstract Background Metabolic cell features are able to give reliable information on cell functional state. Thus, metabolic potential assessment of T cells in malignancy setting represents a promising area, especially in adoptive cell therapy procedures. Easy to set up and convenient Seahorse technology have recently been proposed by Agilent Technologies and it could be used to monitor T cells metabolic potential. However, this method demonstrates an inter-assay variability and lacks practices standardization. Results We aimed to overcome these shortcomings thanks to a lymphoblastic derived JURKAT cell line seeding in each experiment to standardize the Seahorse process. We used an adapted XF Cell MitoStress Kit protocol, consisting in the evaluation of basal, stressed and maximal glycolysis and oxidative phosphorylation related parameters, through sequential addition of oligomycin and FCCP to a glucose containing medium. Data were acquired and analyzed through Agilent Seahorse XFe96 analyzer. Indeed, we validated this method in the light of ICH Q2 (R1) guidelines. We were able to confirm the specificity and accuracy of the method. We also demonstrated the precision, linearity and range of the method in our experimental conditions. Conclusion The validation of the method consisting in a JURKAT cell line experimental incorporation as internal control contributes to improve the Seahorse technology’s robustness. These results lay the groundwork for the implementation of this technology to optimize T cell based cellular therapy products production process and monitoring.


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