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Methodology
Validation of a method evaluating T cell metabolic potential in compliance with ICH Q2 (R1)
Patricia Letondal
Univ. Bourgogne Franche-Comté, INSERM, EFS BFC, UMR1098, RIGHT Interactions Greffon-Hôte-Tumeur/Ingénierie Cellulaire et Génique, F-25000 Besançon, France
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Journal of Translational Medicine.
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.
Keywords
T cell based immunotherapies, T cell metabolic potential, Internal quality control
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Peer Review Timeline
CURRENT STATUS: Published
Version 1
Posted 18 Sep, 2020
Published
On 06 Jan, 2021
No community comments so far
Editorial decision: Major revision
On 04 Nov, 2020
Reviewer #5 agreed
On 01 Nov, 2020
Review #3 received
Received 25 Oct, 2020
Review #2 received
Received 18 Oct, 2020
Review #1 received
Received 17 Oct, 2020
Reviewer #3 agreed
On 05 Oct, 2020
Reviewer #4 agreed
On 05 Oct, 2020
Reviewer #2 agreed
On 04 Oct, 2020
Reviewers invited
Invitations sent on 03 Oct, 2020
Reviewer #1 agreed
On 03 Oct, 2020
Editor assigned
On 25 Sep, 2020
Editor invited
On 24 Sep, 2020
Submission checks complete
On 16 Sep, 2020
First submitted
On 11 Sep, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cellular Metabolism
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This preprint is under consideration at Journal of Translational Medicine. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Methodology
Validation of a method evaluating T cell metabolic potential in compliance with ICH Q2 (R1)
Patricia Letondal
Univ. Bourgogne Franche-Comté, INSERM, EFS BFC, UMR1098, RIGHT Interactions Greffon-Hôte-Tumeur/Ingénierie Cellulaire et Génique, F-25000 Besançon, France
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 1
Posted 18 Sep, 2020
Published
On 06 Jan, 2021
No community comments so far
Editorial decision: Major revision
On 04 Nov, 2020
Reviewer #5 agreed
On 01 Nov, 2020
Review #3 received
Received 25 Oct, 2020
Review #2 received
Received 18 Oct, 2020
Review #1 received
Received 17 Oct, 2020
Reviewer #3 agreed
On 05 Oct, 2020
Reviewer #4 agreed
On 05 Oct, 2020
Reviewer #2 agreed
On 04 Oct, 2020
Reviewers invited
Invitations sent on 03 Oct, 2020
Reviewer #1 agreed
On 03 Oct, 2020
Editor assigned
On 25 Sep, 2020
Editor invited
On 24 Sep, 2020
Submission checks complete
On 16 Sep, 2020
First submitted
On 11 Sep, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Cellular Metabolism
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Journal of Translational Medicine.
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.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6