Abstract
Chimeric antigen receptor (CAR) T-cell therapy represents a major advancement in personalized cancer treatment. Generating robust and well characterized manufacturing processes for cell therapy has become crucial. Traditional manufacturing processes activate and expand T cells in media containing human serum, which supports cell growth and viability. However, serum batches vary significantly from lot to lot and require frequent screening for contaminants that can be detrimental to patients. T cell manufacturing processes independent of human serum will render adoptive T cell therapy less expensive, more consistent, and safer for patients. In order to create a best-in class serum-free medium that is even more robust than serum-containing media, we need to gain a better understanding of the metabolic requirements of T cells during expansion. For this purpose, we have utilized a multi-omics approach to fully characterize the proteomic and metabolomic signatures of T cells expanded in a serum free, xeno free medium at different phases of growth. We sampled cells at days 3, 5, and 7 for label-free proteomics and untargeted extra- and intracellular metabolomics analysis in order to identify metabolic patterns that could be corrected with media supplementation. We identified over 6,043 proteins and 900 metabolites from 4 donors and detected 1,200 significantly different proteins and 312 metabolites. Using an in-house bioinformatics strategy to analyze the multi-omics data, we focused on several metabolic and signaling pathways that were significantly different at days 5 and 7 compared to day 3. The "corrective" media supplementation that we added based on these results demonstrated a tremendous increase in cell growth and viability yielding a 2.6- and 3.2-fold increase in cell growth on days 5 and 7, respectively, and an increase in viability of 15-20% and 11-15% on days 5 and 7, respectively, compared to the un-supplemented prototype. In addition, cells maintained high viability throughout the whole culture and phenotype was not affected. These data demonstrate that multi-omics is a powerful tool for understanding T cell metabolism and identifying components to develop robust and reproducible serum-free media that produces high quality T cells. Disclosures No relevant conflicts of interest to declare.
Published Version
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