Vector Copy Distribution at a Single-Cell Level Enhances Analytical Characterization of Gene-Modified Cell Therapies

Santeramo, Ilaria; Bagnati, Marta; Harvey, Emily Jane; Hassan, Enas A.; Surmacz-Cordle, B.; Marshall, Damian; Cerbo, Vincenzo Di

doi:10.1016/j.omtm.2020.04.016

Cited by 18 publications

(16 citation statements)

References 48 publications

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“…The frequency distribution (as visualized by changing widths of violin plots in Fig. 2f) of transgenic TCR expression after Tx MOI lo indicates that a fraction of cells might have received more than one transgene copy, which would be in line with previously reported single-cell VCN distributions (35). Another potential source of transgene expression variability is the genomic integration site itself.…”

Section: Resultssupporting

confidence: 88%

“…In case of conventional editing, both variable VCN and random transgene integration independently increase the variability of TCR transcription, surface expression, and functionality – especially after transduction with a low virus MOI. On the one hand, this can be explained by VCN heterogeneity between single cells (35). On the other hand, differential accessibility of a transgene at a specific genomic locus should have a large impact on transgene transcription (49).…”

Section: Discussionmentioning

confidence: 99%

“…In addition to the absence of the endogenous TCR, the quantity and site of transgenic TCR integration events represent crucial aspects for T cell product functionality and safety. Upon conventional transduction, advanced analysis of single-cell vector copy numbers (VCN) revealed up to 44 transgene integrations in a primary T cell (35). Both the US Food & Drug Administration (FDA) as well as the European Medicines Agency (EMA) highlight that the risk of gene-modified cell therapies via insertional oncogenesis (36) should be reduced through the limitation of VCN (37).…”

Section: Introductionmentioning

confidence: 99%

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Targeted T cell receptor gene editing provides predictable T cell product function for immunotherapy

Müller

Jarosch

Hammel

et al. 2020

Preprint

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Adoptive transfer of T cells expressing a transgenic T cell receptor (TCR) has the potential to revolutionize immunotherapy of infectious diseases and cancer. However, the generation of defined TCR-transgenic T cell medicinal products with predictable in vivo function still poses a major challenge and limits broader and more successful application of this ‘living drug’. Here, by studying 51 different TCRs, we show that conventional genetic engineering by viral transduction leads to variable TCR expression and T cell product functionality as a result of interference with the endogenous TCR, variable transgene copy numbers, and un-targeted transgene integration. In contrast, CRISPR/Cas9-mediated TCR gene editing enables defined, targeted TCR insertion with concomitant knock-out of the endogenous receptor. Thereby, T cell products display more homogenous and physiological TCR expression which results in increased functionality and – importantly – less variable in vivo T cell responses in comparison to conventionally generated T cells. Hence, targeted TCR gene editing increases the predictability of TCR-transgenic T cell product function, which represents a crucial aspect for clinical application in adoptive T cell immunotherapy.BRIEF SUMMARYSafer, more functional and predictable transgenic T cell products for immunotherapy can be generated via CRISPR/Cas9-mediated targeted TCR engineering

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Section: Resultssupporting

confidence: 88%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Targeted T cell receptor gene editing provides predictable T cell product function for immunotherapy

Müller

Jarosch

Hammel

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…In their assay, target amplicons were first pre-amplified to generate sufficient template material, prior to dPCR for vector and reference amplicons. Their single-cell assay generated results that were consistent with bulk measurements (14). However, their method has yet to be applied for CAR VCN measurements.…”

Section: Digital Polymerase Chain Reactionmentioning

confidence: 57%

The Chimeric Antigen Receptor Detection Toolkit

Huang

2020

Front. Immunol.

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Chimeric antigen receptor-T (CAR-T) cell therapy is a promising frontier of immunoengineering and cancer immunotherapy. Methods that detect, quantify, track, and visualize the CAR, have catalyzed the rapid advancement of CART cell therapy from preclinical models to clinical adoption. For instance, CAR-staining/labeling agents have enabled flow cytometry analysis, imaging applications, cell sorting, and high-dimensional clinical profiling. Molecular assays, such as quantitative polymerase chain reaction, integration site analysis, and RNA-sequencing, have characterized CAR transduction, expression, and in vivo CART cell expansion kinetics. In vitro visualization methods, including confocal and total internal reflection fluorescence microscopy, have captured the molecular details underlying CAR immunological synapse formation, signaling, and cytotoxicity. In vivo tracking methods, including two-photon microscopy, bioluminescence imaging, and positron emission tomography scanning, have monitored CART cell biodistribution across blood, tissue, and tumor. Here, we review the plethora of CAR detection methods, which can operate at the genomic, transcriptomic, proteomic, and organismal levels. For each method, we discuss: (1) what it measures; (2) how it works; (3) its scientific and clinical importance; (4) relevant examples of its use; (5) specific protocols for CAR detection; and (6) its strengths and weaknesses. Finally, we consider current scientific and clinical needs in order to provide future perspectives for improved CAR detection.

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“…Thereafter, the concentration of nucleotide acid is calculated using Poisson statistics according to the percentage of positive droplets [ 18 – 20 ]. Because ddPCR does not need a standard curve, it has advantages in terms of accuracy, reproducibility, and sensitivity in quantification of a wide variety of genetic materials, such as mitochondrial DNA [ 21 ], tumor-cell-free DNA [ 22 ], circulating microRNA [ 23 ], and virus copies, especially for severe acute respiratory syndrome coronavirus 2 [ 24 ], plant DNA [ 25 ], low-level somatic mosaicism [ 26 ], and even absolute gene copies in a single cell [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

Development and Evaluation of a Droplet Digital PCR Assay for 8p23 β-Defensin Cluster Copy Number Determination

et al. 2021

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Introduction It has been proposed that the copy number (CN) variation (CNV) in β-defensin genes (DEFB) on human chromosome 8p23 determines phenotypic differences in inflammatory diseases. However, no method for accurate and easy DEFB CN quantification is yet available. Objective Droplet digital polymerase chain reaction (ddPCR) is a novel method for CNV quantification and has been used for genes such as CCL4L , CCL3L1 , AMY1 , and HER2 . However, to date, no ddPCR assay has been available for DEFB CN determination. In the present study, we aimed to develop and evaluate such a ddPCR assay. Methods The assay was designed using DEFB4 and RPP30 as the target and the reference gene, respectively. To evaluate the assay, 283 DNA samples with known CNs previously determined using the multiple ligation-dependent probe amplification (MLPA) method, the current gold standard, were used as standards. To discover the optimal DNA template amount, we tested 80 to 2.5 ng DNA by a serial of one to two dilutions of eight samples. To evaluate the reproducibility of the assay, 31 samples were repeated to calculate the intra- and inter-assay variations. To further validate the reliability of the assay, the CNs of all 283 samples were determined using ddPCR. To compare results with those using quantitative PCR (qPCR), DEFB CNs for 48 samples were determined using qPCR with the same primers and probes. Results In a one-dimensional plot, the positive and negative droplets were clearly separated in both DEFB4 and RPP30 detection channels. In a two-dimensional plot, four populations of droplets were observed. The 20 ng template DNA proved optimal, with either high (80 ng) or low (10, 5, 2.5 ng) template input leading to ambiguous or inaccurate results. For the 31 standard samples, DEFB CNs were accurately determined with small intra- and inter-assay variations (coefficient of variation < 0.04 for both). In the validation cohort, ddPCR provided the correct CN for all 283 samples with high confidence. qPCR measurements for the 48 samples produced noisy data with high uncertainty and low accuracy. Conclusions ddPCR is an accurate, reproducible, easy-to-use, cheap, high-throughput method for DEFB CN determination. ddPCR could be applied to DEFB CN quantification in large-scale case–control studies. Supplementary Information The online version contains supplementary material available at 10.1007/s40291-021-00546-2.

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Vector Copy Distribution at a Single-Cell Level Enhances Analytical Characterization of Gene-Modified Cell Therapies

Cited by 18 publications

References 48 publications

Targeted T cell receptor gene editing provides predictable T cell product function for immunotherapy

Targeted T cell receptor gene editing provides predictable T cell product function for immunotherapy

The Chimeric Antigen Receptor Detection Toolkit

Development and Evaluation of a Droplet Digital PCR Assay for 8p23 β-Defensin Cluster Copy Number Determination

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