Best practices for the development, analytical validation and clinical implementation of flow cytometric methods for chimeric antigen receptor T cell analyses

Sarikonda, Ghanashyam; Mathieu, Mélissa; Natalia, Mahwish; Pahuja, Anil; Xue, Qiong; Pierog, Piotr; Trampont, Paul C.; Decman, Vilma; Reynolds, Susan D.; Hanafi, Laïla-Aïcha; Sun, Yongliang; Eck, Steven; Hedrick, Michael N.; Stewart, Jennifer J.; Tangri, Shabnam; Litwin, Virginia; Dakappagari, Naveen

doi:10.1002/cyto.b.21985

Cited by 23 publications

(32 citation statements)

References 27 publications

(50 reference statements)

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“…Within-run imprecision was performed using 12 samples, displaying different leukocyte counts. The limit of detection (LOD) was calculated as the limit of blank (LOB) + 1.654 * standard deviation (SD) (shown in the ESM ) [ 19 ].…”

Section: Methodsmentioning

confidence: 99%

Microparticle-tagged image-based cell counting (ImmunoSpin) for CD4 + T cells

Hwang

Yang

et al. 2021

Microchim Acta

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Affordable point-of-care (POC) CD4 + T lymphocyte counting techniques have been developed as alternatives to flow cytometry-based instruments caring for patients with human immunodeficiency virus (HIV)-1. However, POC CD4 enumeration technologies can be inaccurate. Here, we developed a microparticle-based visual detector of CD4 + T lymphocytes (ImmunoSpin) using microparticles conjugated with anti-CD4 antibodies, independent of microfluidic or fluorescence detection systems. Visual enumeration of CD4 + T cells under conventional light microscope was accurate compared to flow cytometry. Microparticle-tagged CD4 + T cells were well-recognized under a light microscope. ImmunoSpin showed very good precision (coefficients of variation of ImmunoSpin were ≤ 10%) and high correlation with clinical-grade flow cytometry for the enumeration of CD4 + T cells (y = 0.4232 + 0.9485 × for the %CD4 + T cell count, R2 = 0.99). At thresholds of 200 and 350 cells/µL, there was no misclassification of the ImmunoSpin system compared to the reference flow cytometry. ImmunoSpin showed clear differential classification of CD4 + T lymphocytes from granulocytes and monocytes. Because non-fluorescence microparticle-tags and cytospin slides are used in ImmunoSpin, they can be applied to an automatic digital image analyzer. Slide preparation allows long-term storage, no analysis time limitations, and image transfer in remote areas. Graphical abstract

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Section: Methodsmentioning

confidence: 99%

Microparticle-tagged image-based cell counting (ImmunoSpin) for CD4 + T cells

Hwang

Yang

et al. 2021

Microchim Acta

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“…Importantly, limitations related to sample age or sample type are currently not understood, and gating strategies that support the definition of sCD19-binding versus non-binding cells would be desirable. Additionally, data on the level of detection (LOD), the limit of blank (LOB), and the precision of the assay would provide valuable information about how robust the assay is (Sarikonda et al, 2020). We, therefore, optimized our in-house designed sCD19-based CAR-T19 detecting assay and examined the above parameters.…”

Section: Introductionmentioning

confidence: 99%

Detection of CAR‐T19 cells in peripheral blood and cerebrospinal fluid: An assay applicable to routine diagnostic laboratories

Johansson

Gallagher

Burgoyne

et al. 2021

Cytometry Part B Clinical

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Background: Chimeric antigen receptor-modified T-cells targeting CD19 (CAR-T19) are licensed for treating relapsed/refractory diffuse large B-cell lymphoma and B-acute lymphoblastic leukemia. Predicting treatment responses and toxicity (e.g., cytokine release syndrome and neurotoxicity) remains a big challenge. CAR-T19 monitoring could increase our understanding of treatment responses and be of relevance to patient management. A robust method for accurate CAR-T19 detection is therefore extremely desirable.Methods: An assay that uses fluorochrome-conjugated human recombinant soluble CD19 was tested against two commercially available CAR-T19 therapies and a CAR-T19 cell line developed in-house. Precision, concordance, and analyte stability were tested using peripheral blood obtained from CAR-T19-treated patients and controls. Results:The assay showed good accuracy, and had a limit of blank for whole blood samples of 0.13%. Reproducibility and inter-operator concordance were satisfactory (CVs <15%). The assay distinguished CAR-T19 from reactive T-cells in cerebrospinal fluid (CSF) from patients with suspected immune effector cell-associated neurotoxicity syndrome (ICANS), and was adapted to study memory T-cell compartments in treated patients. Conclusion:The assay enabled routine monitoring of CAR-T19 in blood and CSF samples. Despite profound cytopenia in many lymphoma patients, results were obtained regularly from only 4 ml of blood. The assay can be adapted easily to characterize the memory and exhaustion status of CAR-T19 and native T-cells. Importantly, it does not rely on CAR construct specificity; thus, it can be used to detect any CD19-targeted CAR cell. Finally, our validation process can serve as a blueprint for other fluorochrome proteins used to detect CAR cells.

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“…Flow cytometry-based assays are robust, efficient and powerful tools for the analysis, characterization and evaluation of cells during the CAR/TCR T-cell manufacturing process [ 9 ]. Manufacturing CAR/TCR T-cells is a complex process involving blood collection followed by T-cell selection, activation, vector transduction and expansion [ 7 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

“…Manufacturing CAR/TCR T-cells is a complex process involving blood collection followed by T-cell selection, activation, vector transduction and expansion [ 7 , 10 ]. During this process, multiparametric flow cytometry-based evaluation plays an important role in monitoring the manufacturing steps including in-process and lot-release product testing [ 9 ]. The percentage of cells expressing CD3 (T-cell), CD4/CD8 T-cell subset composition and transduction efficiency are almost always measured using flow cytometry.…”

Section: Introductionmentioning

confidence: 99%

“…The percentage of cells expressing CD3 (T-cell), CD4/CD8 T-cell subset composition and transduction efficiency are almost always measured using flow cytometry. Since some flow cytometry reagents used to assess transduction efficiency react with multiple types of CAR or TCR T-cells, laboratories manufacturing multiple genetically engineered T-cell products may need to include an assay in the lot-release testing process that ensures the correct vector was used during the manufacturing process [ 7 , 9 ]. This identity testing may be performed with molecular assays, but it is often preformed using flow cytometry [ 8 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

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Establishment and validation of in-house cryopreserved CAR/TCR-T cell flow cytometry quality control

et al. 2021

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Background Chimeric antigen receptor (CAR) or T-cell receptor (TCR) engineered T-cell therapy has recently emerged as a promising adoptive immunotherapy approach for the treatment of hematologic malignancies and solid tumors. Multiparametric flow cytometry-based assays play a critical role in monitoring cellular manufacturing steps. Since manufacturing CAR/TCR T-cell products must be in compliance with current good manufacturing practices (cGMP), a standard or quality control for flow cytometry assays should be used to ensure the accuracy of flow cytometry results, but none is currently commercially available. Therefore, we established a procedure to generate an in-house cryopreserved CAR/TCR T-cell products for use as a flow cytometry quality control and validated their use. Methods Two CAR T-cell products: CD19/CD22 bispecific CAR T-cells and FGFR4 CAR T-cells and one TCR-engineered T-cell product: KK-LC-1 TCR T-cells were manufactured in Center for Cellular Engineering (CCE), NIH Clinical Center. The products were divided in aliquots, cryopreserved and stored in the liquid nitrogen. The cryopreserved flow cytometry quality controls were tested in flow cytometry assays which measured post-thaw viability, CD3, CD4 and CD8 frequencies as well as the transduction efficiency and vector identity. The long-term stability and shelf-life of cryopreserved quality control cells were evaluated. In addition, the sensitivity as well as the precision assay were also assessed on the cryopreserved quality control cells. Results After thawing, the viability of the cryopreserved CAR/TCR T-cell controls was found to be greater than 50%. The expression of transduction efficiency and vector identity markers by the cryopreserved control cells were stable for at least 1 year; with post-thaw values falling within ± 20% range of the values measured at time of cryopreservation. After thawing and storage at room temperature, the stability of these cryopreserved cells lasted at least 6 h. In addition, our cryopreserved CAR/TCR-T cell quality controls showed a strong correlation between transduction efficiency expression and dilution factors. Furthermore, the results of flow cytometric analysis of the cryopreserved cells among different laboratory technicians and different flow cytometry instruments were comparable, highlighting the reproducibility and reliability of these quality control cells. Conclusion We developed and validated a feasible and reliable procedure to establish a bank of cryopreserved CAR/TCR T-cells for use as flow cytometry quality controls, which can serve as a quality control standard for in-process and lot-release testing of CAR/TCR T-cell products.

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Best practices for the development, analytical validation and clinical implementation of flow cytometric methods for chimeric antigen receptor T cell analyses

Cited by 23 publications

References 27 publications

Microparticle-tagged image-based cell counting (ImmunoSpin) for CD4 + T cells

Microparticle-tagged image-based cell counting (ImmunoSpin) for CD4 + T cells

Detection of CAR‐T19 cells in peripheral blood and cerebrospinal fluid: An assay applicable to routine diagnostic laboratories

Establishment and validation of in-house cryopreserved CAR/TCR-T cell flow cytometry quality control

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