Cytometry Part A最新文献

{"title":"Comparison of Tissue Preparations to Identify and Phenotype T Cells in Human Colorectal Tumor Tissue","authors":"Justin F. Tirados,&nbsp;Sonya Fenton,&nbsp;Helen M. McGuire,&nbsp;Joanna M. Roberts,&nbsp;Kirsten A. Ward-Hartstonge,&nbsp;Roslyn A. Kemp","doi":"10.1002/cyto.a.70043","DOIUrl":"10.1002/cyto.a.70043","url":null,"abstract":"<p>Archived patient samples (e.g., formalin-fixed paraffin embedded (FFPE) tissue blocks, cryoembedded tissue blocks, and frozen whole tissue samples) are a source of immune information for which corresponding patient data is often collected. These precious resources present a unique opportunity to garner clinically relevant immunological insights of disease. We optimized a technique to immunophenotype T cells from archived patient samples through spectral flow cytometry. We demonstrate that frozen whole tissue samples were feasible to immunophenotype using surface markers analyzed on a spectral flow cytometer. Similar to previous findings acquired from freshly collected tissue in our laboratory, in frozen tissue samples there was a higher frequency of inhibitory receptors: CTLA4, PD1, LAG3, and TIM3, in colorectal cancer (CRC) tumors compared to adjacent non-tumor bowel from the same patients. Developing the technique further would allow us to better understand how T cell heterogeneity affects CRC patient survival and prognosis.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"109 8","pages":"567-580"},"PeriodicalIF":2.9,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.70043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148276470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CytoScan: Automated Detection of Technical Anomalies for Cytometry Quality Control","authors":"Tim R. Mocking,&nbsp;Felix Zwolle,&nbsp;Yejin Park,&nbsp;Angèle Kelder,&nbsp;Yvan Saeys,&nbsp;Jacqueline Cloos,&nbsp;Sofie van Gassen,&nbsp;Costa Bachas","doi":"10.1002/cyto.a.70052","DOIUrl":"10.1002/cyto.a.70052","url":null,"abstract":"<p>Studies evaluating cellular phenotypes by cytometry techniques are increasingly facing analytical challenges due to the multitudes of samples and parameters that are evaluated concurrently. Spurious technical effects resulting from a lack of standardization can affect marker distributions and further complicate multi-sample analyses. User-friendly tools for exploratory data analysis to identify such technical effects in large datasets are lacking. To fill this gap, we present a novel R package, CytoScan, that evaluates inter-measurement variation in cytometry datasets and allows for detecting anomalous measurements after data acquisition. CytoScan can detect two types of anomalies: files with limited similarity to others within a dataset (outliers) and files with limited similarity to previously acquired high-quality reference data (novelties). Using simulations of skewed marker distributions and real-life technical effects, we demonstrate that CytoScan can accurately detect such anomalies. CytoScan can be applied to large cytometry datasets on consumer-grade hardware with informative visualizations, providing accessible quality control for more reliable analyses.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"109 8","pages":"581-592"},"PeriodicalIF":2.9,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.70052","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148396395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coincidence Detection in Flow Cytometry Using Pulse-Shape Analysis in Polydisperse Suspensions","authors":"Alexander Putz,&nbsp;Jonas Gienger,&nbsp;Martin Hussels","doi":"10.1002/cyto.a.70053","DOIUrl":"10.1002/cyto.a.70053","url":null,"abstract":"<p>Flow cytometers, based on an optical measurement principle, are widely used for cell characterization in a variety of medical applications. Especially in hematology, high counting accuracy is crucial. Therefore, it is essential to develop accurate but also fast coincidence correction methods. We developed a procedure for post-processing the time-dependent signals (pulses) captured by the detectors during the transition of particles or cells through the flow cytometer's laser beam. These pulses are characterized by their area, maximum intensity, standard deviation, and skewness. By using standard deviation versus area, we are able to detect significantly more coincidences in monodisperse suspensions than by using the common method of area or width versus height. This demonstrates the superior sensitivity and accuracy of our approach for coincidence detection. In polydisperse suspensions and whole blood, we successfully identify and distinguish coincidences between differently sized particles (e.g., 1 and 5 μm) and particles of the same size, as well as between thrombocytes and erythrocytes based on pulse skewness and standard deviation. Unlike the current state-of-the-art method for coincidence correction in cell concentration measurements, which relies on statistical evaluation through dilution series, the developed procedure identifies a specific number of coincidences for individual measurements.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"109 8","pages":"593-604"},"PeriodicalIF":2.9,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.70053","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148520201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spectral, Semi-Spectral, and Bandwidth Flow Cytometric Implementation of Multiplex Cytokine Bead Assays","authors":"Jacob Laster,&nbsp;Jenny Hernandez-Davies,&nbsp;D. Huw Davies,&nbsp;Egest J. Pone","doi":"10.1002/cyto.a.70057","DOIUrl":"10.1002/cyto.a.70057","url":null,"abstract":"<p>Multiplex cytokine bead assays (MCBA) have previously been carried out on conventional (aka classical, or bandwidth) flow cytometers, and issues involving unmixing distortions were encountered when using the manufacturer's set-up beads for unmixing full-spectrum data. After resolving such issues, we introduce and characterize the first full-spectrum flow cytometry implementation of MCBAs. In more detail, the set-up beads were originally produced for conventional cytometers, and a temporary work-around was issued for the semi-spectral mode only: spectral acquisition but bandwidth data display and analysis. We proceeded to make our own reference fluorophore controls (RFCs), starting with polystyrene beads derivatized with carboxyl functional groups that were first conjugated with streptavidin and then titrated with PE-biotin. The autofluorescence profile of the in-house conjugated PE beads matched that of the kit beads, and proper use of PE and “APC” RFCs enabled normal spectral unmixing without any distortions. Comparison of the three modes, namely spectral, semi-spectral, and bandwidth, illustrated the advantages of the spectral mode, including precision and resolution. In addition to enabling proper spectral implementation of the MCBA, a full-spectrum approach opens the door for various types of more complex multi-analyte bead assays yielding richer information, which have previously remained out of reach in conventional cytometry.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"109 8","pages":"605-616"},"PeriodicalIF":2.9,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.70057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148629786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Volume 109A, Number 8, August 2026 Cover Image","authors":"","doi":"10.1002/cyto.a.70063","DOIUrl":"https://doi.org/10.1002/cyto.a.70063","url":null,"abstract":"","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"109 8","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.70063","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148965657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decoding Immune Cell Doublets in Humans: From Artifacts to Insights","authors":"Ningxin Kang,&nbsp;Cheryl Kim,&nbsp;Bjoern Peters,&nbsp;Julie G. Burel","doi":"10.1002/cyto.a.70060","DOIUrl":"10.1002/cyto.a.70060","url":null,"abstract":"<div>\u0000 \u0000 <p>Although routinely detected in human blood and tissue samples, immune cell doublets are typically discarded during data acquisition or analysis, often dismissed as technical artifacts arising from ex vivo cell handling. However, emerging evidence suggests that these immune cell doublets reflect biologically meaningful interactions, offering critical insights into immune communication during health and disease. In this review, we evaluate the current evidence supporting the existence of biological immune cell doublets across various human tissues, highlighting their diverse phenotypes and functions that distinguish them from technical noise. We explore how existing single-cell datasets and analytical frameworks can be repurposed to study doublets, and we examine the primary challenge in the field, which is the lack of definitive markers to distinguish biological doublets from artifacts. Finally, we examine how novel technologies, namely high-throughput image-enabled sorting, are facilitating the next generation of research on this topic.</p>\u0000 </div>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"109 8","pages":"553-566"},"PeriodicalIF":2.9,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148759337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Publication Guidelines for Optimized Multiparameter Immunolabeling Panels (OMIPs)","authors":"Antonio Cosma,&nbsp;Tess M. Brodie,&nbsp;Andrew Filby,&nbsp;Maria C. Jaimes,&nbsp;Raluca A. Niesner,&nbsp;Alfonso J. Schmidt,&nbsp;Yolanda D. Mahnke","doi":"10.1002/cyto.a.70045","DOIUrl":"10.1002/cyto.a.70045","url":null,"abstract":"&lt;p&gt;Those with a keen eye will immediately notice a “mistake” in the title. The expected term Optimized Multicolor Immunofluorescence Panel has been replaced with Optimized Multiparameter Immunolabeling Panel, while retaining the familiar acronym OMIP. This change clarifies that OMIPs encompass panels for technologies that use fluorescence, as they have since 2010, other optical emissions such as those used in intravital multiphoton microscopy, and mass cytometry, as they have since 2017. OMIPs may also include other methods of labeling molecules, such as genetically encoded fluorochromes and dyes, and the measured parameters may include endogenous fluorescence, such as that of NAD(P)H. These panels typically include at least a few labeled antibodies (Abs) used to detect their target molecules. The new name is therefore appropriate for all such panels.&lt;/p&gt;&lt;p&gt;When OMIPs were first introduced in 2010, primarily with flow cytometry in mind, the highest multiplexing achievable with conventional flow cytometry (CFC) was 18 distinct fluorochromes [&lt;span&gt;1&lt;/span&gt;]. Mass cytometry (MC), which enables multiplexing beyond 30 parameters, was adopted more widely in the years that followed. The field has since advanced to the point where 60+ fluorescent parameters can be measured with spectral flow cytometry (SFC), and higher levels of multiplexing are likely to emerge. This progress has driven a new wave of fluorochrome design aimed at narrowing excitation and emission windows to reduce spillover-spreading between reagents. These tools are crucial for building reliable high-parameter panels, but the task remains far from trivial. OMIPs are therefore increasingly important for sharing optimized panels with the research community and for communicating the advantages and limitations of different procedures, protocols, and reagent combinations. They have also proven relevant in veterinary applications, where even small panels can be challenging because of limited species-specific resources. All existing OMIPs can be queried in a database developed and maintained by Antonio Cosma and colleagues, available via the ISAC website.\u0000 &lt;sup&gt;1&lt;/sup&gt;\u0000 \u0000 &lt;/p&gt;&lt;p&gt;OMIPs have been adopted beyond CFC and now include panels for MC, SFC, and imaging mass cytometry (IMC) (Graphic 1). They will hopefully soon also feature panels for imaging flow cytometry (IFC), fluorescence microscopy (FM), and intravital microscopy (IVM), as well as panels used for clinical applications. Although the original OMIP publication guidelines remain valid [&lt;span&gt;1&lt;/span&gt;], authors who submit panels for these different technologies and applications require more specific guidance. In addition, the full OMIP will henceforth be published as a single document within the printed journal. OMIPs were initially designed to consist of a brief section presenting the panel in the printed journal and a more elaborate online section presenting the technical details and discussion","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"109 7","pages":"465-481"},"PeriodicalIF":2.9,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.70045","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148367304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantitative Detection of Entotic Cell-In-Cell Structures Using Deformable Segmentation and Deep Learning","authors":"Maria V. Leyba-Mesa,&nbsp;Mikołaj Biegański,&nbsp;Elijah Ray,&nbsp;Izabela Młynarczuk-Bialy,&nbsp;Buket D. Barkana","doi":"10.1002/cyto.a.70046","DOIUrl":"10.1002/cyto.a.70046","url":null,"abstract":"<p>Cell-in-cell (CIC) structures are among the most intriguing cellular phenomena occasionally observed in human cancer specimens. Once regarded as incidental findings, accumulating evidence has linked specific CIC subtypes, particularly entosis, to tumor progression and patient prognosis. Despite growing interest, systematic investigation of entosis remains limited due to the labor-intensive nature of manual identification and analysis. Computational approaches are, therefore, needed to enable scalable and reproducible entosis detection. In this study, we developed and evaluated five morphology-driven deformable segmentation models alongside a YOLOv8 deep learning–based detection framework for automated entotic cell identification in BxPC3 (pancreatic) and MCF7 (breast) cancer cell lines. The deformable models were designed to capture complementary morphological characteristics, including entropy, spatial proximity, contour topology, and circularity. Comparative evaluation showed that deformable Models A and C achieved the highest sensitivity, with recall values ranging from 0.91 to 0.94 and F1-scores between 0.81 and 0.83, demonstrating robust performance across heterogeneous entotic morphologies. YOLOv8 achieved high overall accuracy (0.97) and specificity (0.98), indicating strong background discrimination, but exhibited lower recall (0.65) and <i>F</i>1-score (0.59), reflecting a conservative detection profile under extreme class imbalance, where entotic events comprised approximately 1% of all observed cells. While deformable models provided higher sensitivity and detailed morphological segmentation, YOLOv8 offered advantages in computational efficiency and rapid inference. Together, these findings highlight the complementary strengths of morphology-driven segmentation and deep learning–based detection, and support the future development of scalable hybrid frameworks for automated entosis analysis.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"109 7","pages":"513-531"},"PeriodicalIF":2.9,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.70046","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148301285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Modular High-Parameter Flow Cytometry Framework: Pre-Analytical Optimization and Validation for Clinical Research","authors":"Jennifer Scott,&nbsp;Iva Lelios,&nbsp;Tobias Rutishauser,&nbsp;Stefan Ganter,&nbsp;Megan M. McCausland,&nbsp;Karen Smith,&nbsp;Alistair Watt,&nbsp;Enrique Gómez","doi":"10.1002/cyto.a.70049","DOIUrl":"10.1002/cyto.a.70049","url":null,"abstract":"<div>\u0000 \u0000 <p>High-parameter flow cytometry (hpFCM) enables powerful immune profiling and biomarker discovery in clinical trials. However, its clinical adoption is hindered by assay variability, logistical challenges, and technical complexity. Ensuring data reproducibility and robustness requires stringent quality controls and standardized validation. We introduce a new concept for implementing hpFCM in drug development, a modular hpFCM approach. It features a 12-marker core panel with 21 additional markers distributed in five interchangeable modules, enabling flexible assay customization throughout clinical studies. This innovative design allows for dynamic modifications during clinical development, facilitating evolving immunophenotyping of T and NK cells and comprehensive biomarker analysis. Validation in accordance with CLSI H62 guidelines confirmed the assay's reliability across exploratory and secondary endpoints, demonstrating high accuracy, selectivity, repeatability, and reproducibility independent of the applied assay configuration. Key secondary endpoints, including CD8+ cytotoxic and regulatory T cells, achieved precision, with repeatability and inter-operator variability under 20% coefficient of variation (CV), while specimen stability was maintained over 4 days of ambient storage. For exploratory endpoints, 90% of analytes met repeatability criteria, with 55% remaining stable over 4 days. The modular approach enhances end-to-end solutions and assay adaptability, supporting both targeted and exploratory strategies for clinical biomarker analysis. Importantly, robust performance and data comparability among different assay configurations were confirmed in both whole blood and frozen PBMC samples. By addressing key limitations in current hpFCM workflows, this modular approach provides a scalable, agile, and cost-effective framework designed to support biomarker strategies during drug development. This framework was conceptualized to increase operational efficiency and enable reverse translational approaches by allowing the rapid integration of emerging markers. Consequently, this design facilitates dynamic immunophenotyping and biomarker discovery, streamlining the path from exploratory research to clinical implementation. Importantly, while the assay is designed for biomarker discovery and exploratory immune monitoring in clinical trials, its clinical utility, therapeutic-response performance, and feasibility in multi-site real-world trial logistics remain to be established in ongoing studies involving specific disease cohorts.</p>\u0000 </div>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"109 7","pages":"532-547"},"PeriodicalIF":2.9,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148338146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Volume 109A, Number 7, July 2026 Cover Image","authors":"","doi":"10.1002/cyto.a.70056","DOIUrl":"https://doi.org/10.1002/cyto.a.70056","url":null,"abstract":"","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"109 7","pages":""},"PeriodicalIF":2.9,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.70056","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148616405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}