Flow Cytometric Analyses of Lymphocyte Markers in Immune Oncology: A Comprehensive Guidance for Validation Practice According to Laws and Standards

Many anticancer therapies such as antibody-based therapies, cellular therapeutics (e.g., genetically modified cells, regulators of cytokine signaling, and signal transduction), and other biologically tailored interventions strongly influence the immune system and require tools for research, diagnosis, and monitoring. In flow cytometry, in vitro diagnostic (IVD) test kits that have been compiled and validated by the manufacturer are not available for all requirements. Laboratories are therefore usually dependent onmodifying commercially available assays or, most often, developing them to meet clinical needs. However, both variants must then undergo full validation to fulfill the IVD regulatory requirements. Flow cytometric immunophenotyping is a multiparametric analysis of parameters, some of which have to be repeatedly adjusted; that must be considered when developing specific antibody panels. Careful adjustments of general rules are required to meet legal and regulatory requirements in the analysis of these assays. Here, we describe the relevant regulatory framework for flow cytometry-based assays and describe methods for the introduction of new antibody combinations into routine work including development of performance specifications, validation, and statistical methodology for design and analysis of the experiments. The aim is to increase reliability, efficiency, and auditability after the introduction of in-house-developed flow cytometry assays

Could Immunophenotype Guide Molecular Analysis in Patients with Myeloid Malignancies?

Objective: Immunophenotype has been correlated with molecular aberrations in several studies. The aim of this study was the discovery of immunophenotypic features related to mutations in AML and MDS patients connected to prognostic factors. Moreover, an effort to evaluate a method for the detection of the most common NPM1 mutations of exon12 and Internal Tandem Duplications (ITD) mutations of FLT3 gene by flow cytometry was performed. Method: Patients with de novo myeloid neoplasms [ AML and MDS (AML-M3 patients were excluded)] were included. FLT3/ITD/TKD and NPM1 mutations were detected by PCR and fragment analysis. The immunophenotypic analysis was performed by multi-dimensional flow cytometry (FC) with a standardized panel of monoclonal antibodies on peripheral blood or bone marrow samples. Nucleophosmin Antibody and CD135 were used for the mutations immunophenotypic detection. Results: NPM1 and/or FLT3 mutations correlated with low or no expression of more immature cells markers such as CD34, CD117, HLADR, as well as higher expression of more mature markers such as CD11b. The higher expression of CD33 should be mentioned as well. The presence of NPM1mut and FLT3/ITD does not seem to be detectable by FC at least using these two monoclonal antibodies. The presence of CD7 aberrant lymphoid marker’s expression was associated with FLT3mut, NPM1wt genotype. CD56 or CD2 positivity was found only in patients’ samples negative for NPM1 and/or FLT3 mutations. Conclusions: Certain immunophenotype findings including the presence of aberrant lymphoid markers may be indicative of the presence of mutations in NPM1 and FLT3 linked to prognosis

Flow Cytometric Analyses of Lymphocyte Markers in Immune Oncology: A Comprehensive Guidance for Validation Practice According to Laws and Standards

Many anticancer therapies such as antibody-based therapies, cellular therapeutics (e.g., genetically modified cells, regulators of cytokine signaling, and signal transduction), and other biologically tailored interventions strongly influence the immune system and require tools for research, diagnosis, and monitoring. In flow cytometry, in vitro diagnostic (IVD) test kits that have been compiled and validated by the manufacturer are not available for all requirements. Laboratories are therefore usually dependent onmodifying commercially available assays or, most often, developing them to meet clinical needs. However, both variants must then undergo full validation to fulfill the IVD regulatory requirements. Flow cytometric immunophenotyping is a multiparametric analysis of parameters, some of which have to be repeatedly adjusted; that must be considered when developing specific antibody panels. Careful adjustments of general rules are required to meet legal and regulatory requirements in the analysis of these assays. Here, we describe the relevant regulatory framework for flow cytometry-based assays and describe methods for the introduction of new antibody combinations into routine work including development of performance specifications, validation, and statistical methodology for design and analysis of the experiments. The aim is to increase reliability, efficiency, and auditability after the introduction of in-house-developed flow cytometry assays

Flow Cytometric Analyses of Lymphocyte Markers in Immune Oncology: A Comprehensive Guidance for Validation Practice According to Laws and Standards

Many anticancer therapies such as antibody-based therapies, cellular therapeutics (e.g., genetically modified cells, regulators of cytokine signaling, and signal transduction), and other biologically tailored interventions strongly influence the immune system and require tools for research, diagnosis, and monitoring. In flow cytometry, in vitro diagnostic (IVD) test kits that have been compiled and validated by the manufacturer are not available for all requirements. Laboratories are therefore usually dependent onmodifying commercially available assays or, most often, developing them to meet clinical needs. However, both variants must then undergo full validation to fulfill the IVD regulatory requirements. Flow cytometric immunophenotyping is a multiparametric analysis of parameters, some of which have to be repeatedly adjusted; that must be considered when developing specific antibody panels. Careful adjustments of general rules are required to meet legal and regulatory requirements in the analysis of these assays. Here, we describe the relevant regulatory framework for flow cytometry-based assays and describe methods for the introduction of new antibody combinations into routine work including development of performance specifications, validation, and statistical methodology for design and analysis of the experiments. The aim is to increase reliability, efficiency, and auditability after the introduction of in-house-developed flow cytometry assays

CSF1/CSF1R Axis Blockade Limits Mesothelioma and Enhances Efficiency of Anti-PDL1 Immunotherapy

Colony-Stimulating Factor 1 (CSF1)/Colony-Stimulating Factor Receptor 1 (CSF1R) signaling orchestrates tumor-associated macrophage (TAM) recruitment and polarization towards a pro-tumor M2 phenotype, the dominant phenotype of TAMs infiltrating mesothelioma tumors. We hypothesized that CSF1/CSF1R inhibition would halt mesothelioma growth by targeting immunosuppressive M2 macrophages and unleashing efficient T cell responses. We also hypothesized that CSF1/CSF1R blockade would enhance the efficacy of a PDL1 inhibitor which directly activates CD8+ cells. We tested a clinically relevant CSF1R inhibitor (BLZ945) in mesothelioma treatment using syngeneic murine models. We evaluated the role of CSF1/CSF1R axis blockade in tumor-infiltrating immune subsets. We examined the effect of combined anti-CSF1R and anti-PDL1 treatment in mesothelioma progression. CSF1R inhibition impedes mesothelioma progression, abrogates infiltration of TAMs, facilitates an M1 anti-tumor phenotype and activates tumor dendritic and CD8+ T cells. CSF1R inhibition triggers a compensatory PD-1/PDL1 upregulation in tumor and immune cells. Combined CSF1R inhibitor with an anti-PDL1 agent was more effective in retarding mesothelioma growth compared to each monotherapy. In experimental mesotheliomas, CSF1R inhibition abrogates tumor progression by limiting suppressive myeloid populations and enhancing CD8+ cell activation and acts synergistically with anti-PDL1

The flow cytometry myeloid progenitor count: A reproducible parameter for diagnosis and prognosis of myelodysplastic syndromes

Background: The bone marrow blast count is central to the diagnosis and monitoring of myelodysplastic syndromes (MDS). It is an independent risk factor for worse prognosis whether based on the morphology blast count or the flow cytometry (FC) myeloid progenitor (MyP) count. It is a principal population in FC MDS analysis also because once defined; it provides significant contributions to the overall FC MDS score. Methods: We elected to investigate inter-analyst agreement for the most fundamental parameter of the FC MDS diagnostic score: the MyP count. A common gating strategy was agreed and used by seven cytometrists for blind analysis of 34 routine bone marrows sent for MDS work-up. Additionally, we compared the results with a computational approach. Results: Concordance was excellent: Intraclass correlation was 0.993 whether measuring %MyP of total cells or CD45+ cells, and no significant difference was observed between files from different centers or for samples with abnormal MyP phenotypes. Computational and manual results were similar. Applying the common strategy to individual laboratories' control cohorts produced similar MyP reference ranges across centers. Conclusion: The FC MyP count offers a reliable diagnostic and prognostic measurement in MDS. The use of manual and computational approaches side by side may allow for optimizing both strategies. Considering its known prognostic power, the MyP count could be considered a useful and reliable addition to existing prognostic scoring systems

Flow cytometric evaluation of peripheral blood for suspected Sézary syndrome or mycosis fungoides: International guidelines for assay characteristics

A peripheral blood flow cytometric assay for Sézary syndrome (SS) or circulating mycosis fungoides (MF) cells must be able to reliably identify, characterize, and enumerate T‐cells with an immunophenotype that differs from non‐neoplastic T‐cells. Although it is also important to distinguish SS and MF from other subtypes of T‐cell neoplasm, this usually requires information in addition to the immunophenotype, such as clinical and morphologic features. This article outlines the approach recommended by an international group with experience and expertise in this area. The following key points are discussed: (a) At a minimum, a flow cytometric assay for SS and MF should include the following six antibodies: CD3, CD4, CD7, CD8, CD26, and CD45. (b) An analysis template must reliably detect abnormal T‐cells, even when they lack staining for CD3 or CD45, or demonstrate a phenotype that is not characteristic of normal T‐cells. (c) Gating strategies to identify abnormal T‐cells should be based on the identification of subsets with distinctly homogenous immunophenotypic properties that are different from those expected for normal T‐cells. (d) The blood concentration of abnormal cells, based on any immunophenotypic abnormalities indicative of MF or SS, should be calculated by either direct enumeration or a dual‐platform method, and reported.Peer reviewe

Kinetics of Immune Subsets in COVID-19 Patients Treated with Corticosteroids

Rationale: Changes in anti-SARS-CoV-2 defense immune subsets in patients treated with dexamethasone (DXM) for severe COVID-19 and their relation to disease outcomes are poorly understood. Methods: Blood-lymphocyte subsets of 110 hospitalized COVID-19 patients were prospectively examined. A first sample was taken at enrollment and a second one 7–10 days later. Total B-, T-lymphocytes, CD4+, CD8+, T-regulatory (Treg), Natural-Killer (NK) and NK T-cells were counted using flow cytometry. Results: At enrollment, patients with respiratory failure, characterized by DXM failure (intubation/death) or DXM success (hospital discharge) exhibited significantly fewer CD3+, CD4+ and CD8+ cells and B-lymphocytes compared to the control group (no respiratory failure/no DXM). At the time of treatment completion, the DXM-failure group exhibited significantly fewer CD3+, CD4+ and CD8+ cells, memory CD4+ and CD8+ T-lymphocytes, compared to the control and the DXM-success groups and fewer activated CD4+ T-lymphocytes, Tregs and NK cells compared to the control group. At the time of treatment completion, the number of all investigated lymphocyte subsets increased in the DXM-success group and was similar to those of the control group. NK cells significantly decreased over time in the DXM-failure group. Conclusion: The lymphocyte kinetics differ between DXM-treated and control COVID-19 patients and are associated with clinical outcomes