Bioanalytical Methods for Characterization of CAR‐T Cellular Kinetics: Comparison of PCR Assays and Matrices

CD19 流式细胞术 分子生物学 实时聚合酶链反应 聚合酶链反应 化学 计算生物学 生物 基因 遗传学
作者
Madhan Masilamani,Vibha Jawa,Yan‐Shan Dai,Romita Das,Alice Park,Manisha Lamba,Fan Wu,Xirong Zheng,Edwin Lu,Carol Gleason,Tim Mack,Johanna Mora,Sekhar Surapaneni
出处
期刊:Clinical Pharmacology & Therapeutics [Wiley]
卷期号:114 (3): 664-672 被引量:5
标识
DOI:10.1002/cpt.2991
摘要

Recently, multiple chimeric antigen receptor T-cell (CAR-T)-based therapies have been approved for treating hematological malignancies, targeting CD19 and B-cell maturation antigen. Unlike protein or antibody therapies, CAR-T therapies are "living cell" therapies whose pharmacokinetics are characterized by expansion, distribution, contraction, and persistence. Therefore, this unique modality requires a different approach for quantitation compared with conventional ligand binding assays implemented for most biologics. Cellular (flow cytometry) or molecular assays (polymerase chain reaction (PCR)) can be deployed with each having unique advantages and disadvantages. In this article, we describe the molecular assays utilized: quantitative PCR (qPCR), which was the initial platform used to estimate transgene copy numbers and more recently droplet digital PCR (ddPCR) which quantitates the absolute copy numbers of CAR transgene. The comparability of the two methods in patient samples and of each method across different matrices (isolated CD3+ T-cells or whole blood) was also performed. The results show a good correlation between qPCR and ddPCR for the amplification of same gene in clinical samples from a CAR-T therapy trial. In addition, our studies show that the qPCR-based amplification of transgene levels was well-correlated, independent of DNA sources (either CD3+ T-cells or whole blood). Our results also highlight that ddPCR can be a better platform for monitoring samples at the early phase of CAR-T dosing prior to expansion and during long-term monitoring as they can detect samples with very low copy numbers with high sensitivity, in addition to easier implementation and sample logistics.
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