Cytometry Part B: Clinical Cytometry最新文献

The gut-liver axis includes the bidirectional communication between the gut and the liver, and thus covers signals from liver-to-gut and from gut-to-liver. Disruptions of the gut-liver axis have been associated with the progression of chronic liver diseases, including alcohol-related and metabolic dysfunction-associated steatotic liver disease and cholangiopathies. Immune cells and their expression of pattern recognition receptors, activation markers or immune checkpoints might play an active role in the communication between gut and liver. Here, we present a 26-color full spectrum flow cytometry panel for human cells to decipher the role of circulating immune cells in gut-liver communication during the progression of chronic liver diseases in a non-invasive manner, which has been optimized to be used on patient-derived whole blood samples, the most abundantly available clinical material. Our panel focuses on changes in pattern recognition receptors, including toll-like receptors (TLRs) or Dectin-1, and also includes other immunomodulatory molecules such as bile acid receptors and checkpoint molecules. Moreover, this panel can be utilized to follow the progression of chronic liver diseases and could be used as a tool to evaluate the efficiency of therapeutic targets directed against microbial mediators or modulating immune cell activation.

The most important reason for dismal outcomes in acute myeloid leukemia (AML) is the development of relapse. Leukemia stem cells (LSCs) are hypothesized to initiate relapse, and high CD34+CD38− LSC load is associated with poor prognosis. In 10% of AML patients, CD34 is not or is low expressed on the leukemic cells (<1%), and CD34+CD38− LSCs are absent. These patients are classified as CD34-negative. We aimed to determine whether the primitive marker CD133 can detect LSCs in CD34-negative AML. We retrospectively quantified 148 CD34-negative patients for proportions of CD34−CD133+ and CD133+CD38− cell fractions in the diagnostic samples of CD34-negative patients in the HOVON102 and HOVON132 trials. No prognostic difference was found between patients with high or low proportions of CD34−CD133+, which is found to be aberrantly expressed in AML. A high level of CD133+CD38− cells was not associated with poor overall survival, and expression in AML was similar to normal bone marrow. To conclude, CD133 is useful as an additional primitive marker for the detection of leukemic blast cells in CD34-negative AML. However, CD133+CD38 alone is not suitable for the detection of LSCs at diagnosis.

The Clinical and Laboratory Standards Institute (CLSI) H62—Validation of Assays Performed by Flow Cytometry guideline, released in 2021, provides recommendations for platform workflow and quality system essentials, instrument setup and standardization, assay development and optimization and fit-for-purpose analytical method validation. In addition, CLSI H62 includes some recommendations for the validation strategies after a validated flow cytometric method has been modified. This manuscript builds on those recommendations and discusses the impact of different types of assay modifications on assay performance. Recommendations regarding which validation parameters to evaluate depending on the type of modification are provided. The impact of assay modification on the assay's intended use is discussed. When recommending minor deviations from the CLSI H62 process for a laboratory-initiated assay revision (e.g., specimen numbers for sensitivity, specificity, or precision studies), a rationale based on expert opinion is provided with the understanding that not every laboratory, assay type, and circumstance can be comprehensively addressed in this paper. These recommendations are meant as a practical recommendation and are not intended to be restrictive, prescriptive, or understood as necessarily sufficient to meet every specific requirement from regulatory bodies (e.g., FDA or New York State Department of Health).

Measurable residual disease (MRD) is detected in approximately a quarter of AML chemotherapy responders, serving as a predictor for relapse and shorter survival. Immunological control of residual disease is suggested to prevent relapse, but the mechanisms involved are not fully understood. We present a peripheral blood single cell immune profiling by mass cytometry using a 42-antibody panel with particular emphasis on markers of cellular immune response. Six healthy donors were compared with four AML patients with MRD (MRD⁺) in first complete remission (CR1_MRD+). Three of four patients demonstrated a favorable genetic risk profile, while the fourth patient had an unfavorable risk profile (complex karyotype, TP53-mutation) and a high level of MRD. Unsupervised clustering using self-organizing maps and dimensional reduction analysis was performed for visualization and analysis of immune cell subsets. CD57⁺ natural killer (NK)-cell subsets were found to be less abundant in patients than in healthy donors. Both T and NK cells demonstrated elevated expression of activity and maturation markers (CD44, granzyme B, and phosho-STAT5 Y694) in patients. Although mass cytometry remains an expensive method with limited scalability, our data suggest the utility for employing a 42-plex profiling for cellular immune surveillance in whole blood, and possibly as a biomarker platform in future clinical trials. The findings encourage further investigations of single cell immune profiling in CR1_MRD+ AML-patients.

The publication of Clinical and Laboratory Standards Institute's guideline H62 has provided the flow cytometry community with much-needed guidance on development and validation of flow cytometric assays (CLSI, 2021). It has also paved the way for additional exploration of certain topics requiring additional guidance. Flow cytometric analysis of rare matrices, or unique and/or less frequently encountered specimen types, is one such topic and is the focus of this manuscript. This document is the result of a collaboration subject matter experts from a diverse range of backgrounds and seeks to provide best practice consensus guidance regarding these types of specimens. Herein, we define rare matrix samples in the setting of flow cytometric analysis, address validation implications and challenges with these samples, and describe important considerations of using these samples in both clinical and research settings.

The advent of high-dimensional imaging offers new opportunities to molecularly characterize diagnostic cells in disorders that have previously relied on histopathological definitions. One example case is found in tuberous sclerosis complex (TSC), a developmental disorder characterized by systemic growth of benign tumors. Within resected brain tissues from patients with TSC, detection of abnormally enlarged balloon cells (BCs) is pathognomonic for this disorder. Though BCs can be identified by an expert neuropathologist, little is known about the specificity and broad applicability of protein markers for these cells, complicating classification of proposed BCs identified in experimental models of this disorder. Here, we report the development of a customized machine learning pipeline (BAlloon IDENtifier; BAIDEN) that was trained to prospectively identify BCs in tissue sections using a histological stain compatible with high-dimensional cytometry. This approach was coupled to a custom 36-antibody panel and imaging mass cytometry (IMC) to explore the expression of multiple previously proposed BC marker proteins and develop a descriptor of BC features conserved across multiple tissue samples from patients with TSC. Here, we present a modular workflow encompassing BAIDEN, a custom antibody panel, a control sample microarray, and analysis pipelines—both open-source and in-house—and apply this workflow to understand the abundance, structure, and signaling activity of BCs as an example case of how high-dimensional imaging can be applied within human tissues.