Issue highlights—May 2024

Abstract

Just 50 years ago, in 1974, the first fluorescence-activated cell sorter (FACS) was ready for sale. Becton-Dickenson (BD) with a license from Stanford University introduced the FACS sorting platform, which was called the FACS-1. The Herzenberg group at Stanford patented this new flow cytometry (FC) platform 2 years earlier. To this day the popular acronym “FACS” is misused in that most BD FC are cell analyzers, yet they are all called FACS machines. Whether or not a flow cytometer can sort cells, they all detect receptors bound with fluorescent tags on leukocyte subsets. Herzenberg's brilliant idea to integrate four essential 20th-century discoveries related to cellular metrics into a single platform set the stage for a new phase of complex analytical platforms to support the fight against diseases. They include multi-laser excitation, hybridoma technology for tagging fluorescently tagged monoclonal antibodies, signal processing with fast microchips and multi-channel cell sorting.

Thanks to rapid access to information, when visiting Paul Robertson's virtual library of Cytometry History at Perdue University, it is possible to appreciate how rapidly flow cytometry has matured in over five decades. In minutes, one learns about the interactions between Mack Fulwyler, Len Herzenberg, Bob Auer, Ceasar Milstein, Howard Shapiro and many other fascinating pioneers of the bio-convergence revolution of the 20th-century. The cell sorting technology uses piezo-based oscillation to charge saline droplet-enveloped cells, which are transported to be analyzed and sorted to isolate leukocyte phenotypes of interest. The droplet formation for cell sorting was Fulwyler's adaptation of technology developed for inkjet printers. With fluorescence activation, cells of interest become visible and available to be sorted for functional verification if required. In the 19th century, philosopher Arthur Schopenhauer said, “Talent hits a target no one can hit; genius hits a target no one else can see.” For a half-century, thanks to Herzenberg's contribution, most of us with talent could see leukocyte subsets with statistical significance. Steady advancements in FC continue, and multi-labeled cells can be analyzed with confidence in clinical FC laboratories with tenacity and some talent. This nostalgic indulgence is now over, and the highlights of this issue are to follow.

Three original articles and two reports on best practices are covered. The first original article is about a novel optimization method to monitor B-cell maturation antigen-targeted chimeric antigen receptors in peripheral blood. The second is an update in the understanding of the role of CD20⁺ T-cells. The third article is about the performance of a novel 8-color panel for measurable residual disease assessment in CLL. The first best practice report validates a T-cell receptor β-chain on the constant region (TRBC) immunophenotyping protocol. This new technology improves the diagnosis of T-cell neoplasm. The other best practice report covers a more comprehensive monocyte subset analysis with flow cytometry, with increased sensitivity.

“Optimization of a flow cytometry test for routine monitoring of B-cell maturation antigen-targeted CAR in peripheral blood” is about monitoring B-cell maturation with targeted chimeric antigen T-cell receptors. The authors report encouraging news about the overall treatment success with multiple myeloma. Even on occasions when initial treatment fails, resorting to relapsed or refractory disease treatment results are encouraging with the two available FDA-licensed drugs. The authors discuss the need for a biomarker to offer a clinical outcome assessment tool. This is possible because of the availability of two reportable variables: CAR T-cell expansion kinetics with toxicity and the ability to accurately quantify B-cell maturation antigen (BCMA) CAR T-cells from peripheral blood. An earlier report from Das et al. (2022) indicated that immunophenotypic profile situation and post-therapy alteration in antigenic expression are available in normal, reactive, and aberrant plasma cells (NPC, RPC, and APC), respectively, for impact on measurable residual disease (MRD) assessment in multiple myeloma (MM). They concluded that antigenic aberrations on polyclonal PC signify the importance of MRD assay validation on a large cohort under normal and reactive conditions. The Das group focused on a cell-surface protein B-cell maturation antigen: CD269 as it emerged as a promising target for CAR-T cell and MAb therapies in MM. However, the knowledge of the BCMA expression pattern in myeloma patients from the Indian subcontinent was not available at that time. A study presented by Sriram et al. (2022) is an in-depth report of BCMA expression on abnormal plasma cells (APC) in Indian MM patients. In the UK, in a 2022 MRD assessment, MM was not incorporated into routine clinical use outside of trials. A report was released (McMillan et al., 2023) about achieving minimal residual disease (MRD) negativity following treatment for multiple myeloma (MM) is associated with improved progression-free and overall survival. They suggest a reference MCF MM MRD method, which was stable for up to 6 days following sample collection, allowing broader access by smaller laboratories to further investigate the predictive value and clinical utility of MRD assessments.

“The role of CD20⁺ T-cells: Insights in human peripheral blood.” This study contributes to the understanding of CD20⁺ T-cell function in the proinflammatory cascade. The distribution of CD20⁻ T-cells among maturation-associated T-cell compartments (naïve, central memory, transitional memory, effector memory, and effector T-cells), their polarization, activation status, and expression of immune-regulatory proteins were evaluated with flow cytometry. Their functions were assessed by measuring IFN-γ, TNF-α and IL-17 production. Compared with CD20⁻ T-cells, CD20⁺ T-cells represent a higher proportion of transitional memory cells. CD20⁺ T-cells display a proinflammatory phenotype, characterized by the expansion of Th1, Th1/17, and Te1 cell subsets. They have been described and immunophenotypically characterized and purified by cell-sorting from neoplastic cells derived from lymph nodes involving T-cell/histiocyte-rich large B-cell lymphoma (Glynn & Fromm, 2020). In 2020, Gatti et al. (2021) published ISCCA's immunophenotypic protocol for monitoring anti-CD20 therapies in autoimmune disorders. Also, in 2020, there was a Letter to the Editor (Gadgeel et al., 2020) about CD20⁺ T-cells in the mediastinal mass tissue with histologically proven PMLBCL and with flow cytometric analysis. CD20⁺ T-cells were identified as CD3, CD7, and CD2 positive cells.

“A novel 8-color FC panel for measurable residual disease (MRD) to monitor chronic lymphocytic leukemia.” The authors report on quantifiable residual disease (MRD) in chronic lymphocytic leukemia (CLL). This prognostic indicator of CLL is of interest as it has been established as predictive of progression-free survival (PFS) and overall survival (OS) in fixed-duration treatment regimens. The authors did a performance evaluation of their novel 8-color panel against the European Research Initiative on CCL (ERIC) 8-color assay. It performed well when compared with ERIC. Stage 0 hematogenous (Hgs) and their association with CD19+ Hgs in anti-CD19 therapy and conventional chemotherapy were reported (Ramalingam et al., 2024). There is the potential to mistake a patient with residual disease if the patient received treatment that included anti-CD19 therapy as it can mimic residual Hgs. Two recent publications are addressing the use of AI to deal with the complexity of 8-color FC assay. AI analysis was used to assess measurable residual disease (Shopsowitz et al., 2024). However, Bazinet et al. (2023) treated MRD after acute myeloid leukemia. They evaluated DeepFlow, an AI-assisted FC analysis software, to determine if it is suitable for performing automated clustering and identifying cell populations. They concluded that the AI-assisted analysis generates CLL MRD results similar to expert manual analysis. Their program also creates a discussion about the strengths and limitations of the AI approach.

“TRBC1 FC assay development validation and reporting considerations.” The authors reassessed the current practice of T-cell clonality by flow cytometry. They explain that because a significant gap existed between surface light chains on B-cells, for a long time it was a dependable marker for workup for hematological samples compared with T-cell oncology workups. T-cell receptor β-chain constant region (TRBC) was introduced as an alternative to TGR-V. Until recently, the assessment of clonal T-cells relied on varying marker expression levels, often providing non-specific interpretation. However, the discovery of TRBC1 puts clonal T-cell assessment by flow cytometry much closer to the clinical evaluation with B-cell clonal analysis. Recently Castillo et al. (2024) published a report about diagnosing T-cell non-Hodgkin lymphomas (NHL) with a MAb specific for T-cell receptor β-constant region1 (TRBC1). A study by Lee et al. (2024) covered an optimized whole-blood assay using human recombinant sBCMA to monitor the presence of BCMA CAR T-cells in peripheral blood. Such monitoring can be incorporated into clinical diagnostics, including the proportions of T-cells expressing the anti-BCMA CAR and absolute counts of CAR T cells/μL blood. Wang et al. (2023) reported a method for optimizing fluorochromes for TRBC1 to improve separation between positive and negative cells.

“Technical gating and interpretation recommendations for partitioning circulating monocyte subsets assessed by flow cytometry.” In the early days of clinical FC, monocytes were a hindrance as they had fewer CD4 MAb receptors than T-helper cells. Hence, they occasionally did compromise CD4 T-cell reporting. A second marker was added to avoid obtaining unreliable T-helper cell counts for HIV disease immunophenotyping (CD3⁺/CD4⁺). Over the past two decades, monocyte assays have been developed to detect CMML. The partitioning of circulatory monocyte subsets by flow cytometry was recommended by Wagner-Ballon et al. (2023). There are three monocyte subsets: cMo(CD14⁺⁺/CD16⁻), iMo(CD14⁺⁺/CD16⁺), and ncMo(CD14^low/−/CD16⁺). In 2021, Devitt et al. (2023) disclosed the validation protocol for monocytic leukemia diagnosis at the European LeukemiaNet International MDS-Flow Cytometry Working Group (ELN iMDS-Flow). A year later, Jurado et al. (2023) published an optimization of monocyte gating protocol and summarized an enhanced validation approach using qualitative and semiquantitative flow cytometry technology.