READ ME File For 'Engineering Chimeric Antigen Receptor (CAR) T Cells with Novel Costimulatory Domains dataset'

Dataset DOI: 10.5258/SOTON/PG/D147

ReadMe Author: Hatice Nurdan Aksoy Kilinc, University of Southampton ORCID ID https://orcid.org/0000-0002-4081-977X

This dataset supports the thesis:
Aksoy Kilinc, H. N. (2026). Engineering chimeric antigen receptor (CAR) T cells with novel costimulatory domains. [Doctoral Thesis, University of Southampton]. https://doi.org/10.5258/SOTON/PG/T147


Date of data collection: [2021-2025]

Information about geographic location of data collection: University of Southampton, United Kingdom (laboratory-based experimental work)

Licence: Creative Commons Attribution 4.0 International (CC BY 4.0)

Related projects/Funders: This research was primarily funded by the Republic of Türkiye, Ministry of National Education, with additional support from the Gerald Kerkut Charitable Trust.


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DATA & FILE OVERVIEW
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This dataset contains experimental data supporting multiple chapters of the thesis:

Chapter 3 – Chronic antigen stimulation and in vitro functional assays
Excel datasets from chronic antigen stimulation experiments
GraphPad Prism files for data analysis
Cytotoxicity assay Prism files
Jurkat assay data including CD69 and IL-2 readouts from patient samples
Seahorse metabolic assay data
Chapter 4 – In vivo tumour models
Early-stage tumour growth analysis (GraphPad Prism files and Excel data)
Late-stage tumour experiments:
Flow cytometry raw data files
Processed flow cytometry data
GraphPad Prism analysis files
Survival curve datasets
Chapter 5 – Humanised mouse model experiments
Humanised mouse in vivo experimental data
GraphPad Prism analysis files
Additional supporting Prism datasets for immune response and tumour progression analysis
Notes
Data were generated using CAR T-cell engineering experiments with novel costimulatory domains
Both in vitro (Jurkat, primary T cells, patient samples) and in vivo (NSG and humanised mouse models) systems were used
Flow cytometry data were analysed using FlowJo v10
Statistical analysis and data visualisation were performed using GraphPad Prism v9 and Microsoft Excel
Flow cytometry datasets include raw and processed outputs