Margot F. van Spronsen, Luca L. G. Janssen, Tessa Poolman, Theresia M. Westers, Yvan Saeys, Reina E. Mebius, Arjan A. van de Loosdrecht
<p>Myelodysplastic neoplasms (MDS) are age-associated neoplasms originating from hematopoietic stem cells (HSCs). (Woll et al., <span>2014</span>) Studies have demonstrated quantitatively and functionally impaired immune cells and auto-inflammation in MDS patients, indicating that immune dysregulation contributes to MDS pathogenesis. Immunological mechanisms may partly explain the heterogeneity in MDS. Following the immune hypothesis, low-risk MDS is associated with a pro-inflammatory state and increased apoptosis. In contrast, an immunosuppressive milieu potentially enables clonal expansion and progression toward acute myeloid leukemia (AML) in high-risk MDS (Kahn et al., <span>2015</span>; Kittang et al., <span>2015</span>; Kordasti et al., <span>2009</span>). Although MDS arise from the bone marrow (BM), this hypothesis is largely based on studies focusing on single immune cell subsets in the peripheral blood (PB) rather than a comprehensive analysis of the BM microenvironment.</p><p>In this study, we performed a computational analysis of multicolor flow cytometry (FCM) data to compare immune profiles between the BM and PB and to evaluate if this method is suitable to identify immunological markers for MDS risk stratification. We analyzed BM and PB samples from 19 MDS patients and, for comparison purposes, from five chronic myelomonocytic leukemia (CMML) patients, 15 pathological controls with benign cytopenia (PCs) and seven age-matched healthy controls (HCs) (Tables S1A,B, Table S2). After data pre-processing, we applied the unsupervised algorithm FlowSOM (Figure S2). (Van Gassen et al., <span>2015</span>) Using six FCM immune panels (IP1-6), we identified 18, 16, 3, 11, 4, 12, and 25 populations respectively, with a total of 86 populations. We studied relative frequencies using the pre-gated population as reference, including white blood cells, mononuclear cells, CD3<sup>+</sup> T cells, and innate lymphoid cells (ILCs) (Table S3). We selected 45/86 populations of potential interest after excluding doublets, granulocytes, and non-immune cells (Table S4). A seventh immune panel, IP7, was compiled to identify myeloid-derived suppressor cells (MDSCs) but failed to show a reliable MDSC population. Data from IP7 were therefore excluded. Methods are described in detail in the Supplementary Information. This study was conducted following the Helsinki Declaration and approved by the Medical Ethics Committee of the Amsterdam UMC location Vrije Universiteit Amsterdam (VUmc 2014-100, VUmc 2019-3448).</p><p>We collected parallel PB and BM samples in 22/46 individuals to study whether circulatory immune cell frequencies reflect the BM immune microenvironment (Table S3). We observed significant relationships between relative frequencies of PB- and BM-derived TNFα-producing T cells, natural killer (NK)-T cells, type 1 innate lymphoid cell (ILC) subsets, and classical monocytes (statistics in Figure S2). Despite a lower frequency within the BM, there was a
骨髓增生异常肿瘤(MDS)是起源于造血干细胞(hsc)的年龄相关性肿瘤。(Woll et al., 2014)研究证实MDS患者免疫细胞和自身炎症在数量上和功能上受损,表明免疫失调与MDS发病机制有关。免疫机制可能部分解释MDS的异质性。根据免疫假说,低风险MDS与促炎状态和细胞凋亡增加有关。相反,免疫抑制环境可能使高危MDS的克隆扩增和向急性髓系白血病(AML)发展(Kahn等,2015;Kittang等,2015;Kordasti等,2009)。虽然MDS起源于骨髓(BM),但这一假设主要基于对外周血(PB)中单一免疫细胞亚群的研究,而不是对骨髓微环境的全面分析。在这项研究中,我们对多色流式细胞术(FCM)数据进行了计算分析,以比较BM和PB之间的免疫谱,并评估该方法是否适用于识别MDS风险分层的免疫标志物。我们分析了19名MDS患者的BM和PB样本,以及5名慢性髓细胞白血病(CMML)患者、15名良性细胞减少症(PCs)病理对照和7名年龄匹配的健康对照(hc)样本进行比较(表S1A,B,表S2)。数据预处理后,我们采用无监督算法FlowSOM(图S2)。(Van Gassen et al., 2015)使用6个FCM免疫板(IP1-6),我们分别鉴定了18、16、3、11、4、12和25个群体,共86个群体。我们研究了以预门控人群为参考的相对频率,包括白细胞、单核细胞、CD3+ T细胞和先天淋巴样细胞(ILCs)(表S3)。在排除双胎、粒细胞和非免疫细胞后,我们选择了45/86个潜在兴趣群体(表S4)。第七免疫组IP7被用于鉴定髓源性抑制细胞(MDSCs),但未能显示可靠的MDSCs群体。因此,IP7的数据被排除在外。方法在补充信息中有详细说明。本研究遵循《赫尔辛基宣言》进行,并经阿姆斯特丹UMC所在地阿姆斯特丹自由大学医学伦理委员会批准(VUmc 2014-100, VUmc 2019-3448)。我们收集了22/46个人的平行PB和BM样本,以研究循环免疫细胞频率是否反映BM免疫微环境(表S3)。我们观察到PB和bm来源的产生tnf α的T细胞、自然杀伤(NK)-T细胞、1型先天淋巴样细胞(ILC)亚群和经典单核细胞的相对频率之间存在显著关系(统计数据见图S2)。尽管BM内的频率较低,但PB-和BM来源的6-sulfo lacnac阳性(Slan+)单核细胞之间存在线性相关。相反,我们发现PB和bm来源的产生ifn γ的T细胞、γδ T细胞和调节性T细胞的百分比之间没有明显的关系。这些数据挑战了假设,即PB提供了BM内所有不同免疫亚群的准确反映。因此,进一步的分析集中在骨髓样本上,以探索MDS患者和对照组的免疫微环境。为了探索整个诊断过程中免疫微环境的差异,我们同时对所有样本的种群频率进行了主成分分析(PCA)。不同面板的PCA图,测量B和T细胞亚群,NK细胞,ILCs和树突状细胞(dc),聚集HC和CMML样本在不同的区域,但分散PC和MDS样本,并将PC样本定位在hcc和MDS患者之间(图1a)。此外,人口频率的热图总结将pc与MDS患者聚集在一起,而不是hc(图1b)。与hcc相比,PC样品显示中央记忆(CM) CD4+ T细胞百分比增加(IP2_7: p = 0.007), naïve CD4+ T细胞百分比减少(IP2_1: p = 0.003),祖细胞,未成熟和成熟B细胞百分比减少(IP1_17: p = 0.044, IP1_16: p = 0.027, IP1_18: p = 0.035)。同时分析所有BM样本时,祖细胞B细胞频率与年龄呈负相关(IP1_17: p = 0.039, R2 = 0.104)。这一发现表明,正如之前所描述的那样,祖B细胞与年龄相关的衰退(Weksler & Szabo, 2000)。在建立了非恶性血液病的参考免疫谱后,我们通过将MDS和CMML样本与hc进行比较,探讨了肿瘤造血中的免疫微环境。将MDS和CMML从对照组中分离出来的群体频率方差可视化,表明免疫谱可能有助于区分诊断(图1a,b)。与pc相似,MDS和CMML的B细胞亚群减少(IP1_16-18: MDS均p <; 0.001; CMML均p≤0)。 005) CM CD4+ T细胞扩增(IP2_1: p = 0.028, p = 0.024), naïve CD4+ T细胞减少(IP2_1: p = 0.016, p = 0.024)(图1c,图S3)。来自CMML患者的样本含有更高频率的naïve和效应CD8+ T细胞(IP2_5: p = 0.024, IP2_12: p = 0.042),如先前报道的,经典单核细胞(IP6_2和IP6_11: p = 0.004)比hc。(Tarfi et al., 2020)与hcc相比,MDS和CMML患者的γδ T细胞(IP2_11: p = 0.019, p = 0.042)增加,浆细胞样DCs (pDCs, IP6_16: p = 0.022, p = 0.030)、6-sulfo lacnac阳性(Slan+)单核细胞(IP6_6: p = 0.033, p = 0.017)和NK-T细胞(IP1_5: p = 0.002, p = 0.003)减少。此外,与hc相比,MDS患者的ILCs频率相似,但ILC1s (T5.5iii, p = 0.009)相对扩大,而ILC3s (IP5_5v, p = 0.007, IP5_5vii: p = 0.009)相对减少。有趣的是,先前的研究表明,在高危MDS中存在异常的γδ T细胞受体库,并且在AML中ILCs1的富集以ILC3s为代价。(Geng et al., 2012; Trabanelli et al., 2015)因此,未来的研究有必要探索这些亚群在MDS发病机制和白血病进展中的作用。我们观察到MDS患者pDC和Slan+单核细胞百分比降低,这证实了先前关于MDS患者pDC和Slan+亚群风险相关降低的报道。(Chan et al., 2022; Van Leeuwen-Kerkhoff et al., 2022)尽管关于MDS中NK-T细胞的文献存在矛盾,但不变的NK-T细胞缺陷小鼠(即造血功能受损和细胞减少)的表型以及我们揭示MDS中NK-T细胞减少的数据也可能促使进一步的研究。(Aggarwal等人,2016;Chan等人,2010;Kotsianidis等人,2006)。最后,我们将重点放在MDS患者身上,在我们的数据集中检验免疫假设,该数据集包括计算分析的BM样本。综上所述,该假说认为低风险MDS和高风险MDS分别以免疫监视和免疫逃避为特征。根据修订后的国际预后评分系统(IPSS-R), 19例患者中,12例(63%)为极低至低风险,7例(37%)为中至高风险(表S1A)。一般来说,具有不良临床特征的患者未成熟B细胞、效应T细胞和Slan+单核细胞的频率较低。特别是,我们观察到CD4+ T细胞减少的患者生存时间较短(IP2_2: p = 0.046),与文献一致,未成熟B细胞减少(IP1_16: p = 0.035,图2a)。(Kahn
{"title":"Toward immunoprofiling in MDS: A computational study of the bone marrow immune microenvironment","authors":"Margot F. van Spronsen, Luca L. G. Janssen, Tessa Poolman, Theresia M. Westers, Yvan Saeys, Reina E. Mebius, Arjan A. van de Loosdrecht","doi":"10.1002/cyto.b.22244","DOIUrl":"10.1002/cyto.b.22244","url":null,"abstract":"<p>Myelodysplastic neoplasms (MDS) are age-associated neoplasms originating from hematopoietic stem cells (HSCs). (Woll et al., <span>2014</span>) Studies have demonstrated quantitatively and functionally impaired immune cells and auto-inflammation in MDS patients, indicating that immune dysregulation contributes to MDS pathogenesis. Immunological mechanisms may partly explain the heterogeneity in MDS. Following the immune hypothesis, low-risk MDS is associated with a pro-inflammatory state and increased apoptosis. In contrast, an immunosuppressive milieu potentially enables clonal expansion and progression toward acute myeloid leukemia (AML) in high-risk MDS (Kahn et al., <span>2015</span>; Kittang et al., <span>2015</span>; Kordasti et al., <span>2009</span>). Although MDS arise from the bone marrow (BM), this hypothesis is largely based on studies focusing on single immune cell subsets in the peripheral blood (PB) rather than a comprehensive analysis of the BM microenvironment.</p><p>In this study, we performed a computational analysis of multicolor flow cytometry (FCM) data to compare immune profiles between the BM and PB and to evaluate if this method is suitable to identify immunological markers for MDS risk stratification. We analyzed BM and PB samples from 19 MDS patients and, for comparison purposes, from five chronic myelomonocytic leukemia (CMML) patients, 15 pathological controls with benign cytopenia (PCs) and seven age-matched healthy controls (HCs) (Tables S1A,B, Table S2). After data pre-processing, we applied the unsupervised algorithm FlowSOM (Figure S2). (Van Gassen et al., <span>2015</span>) Using six FCM immune panels (IP1-6), we identified 18, 16, 3, 11, 4, 12, and 25 populations respectively, with a total of 86 populations. We studied relative frequencies using the pre-gated population as reference, including white blood cells, mononuclear cells, CD3<sup>+</sup> T cells, and innate lymphoid cells (ILCs) (Table S3). We selected 45/86 populations of potential interest after excluding doublets, granulocytes, and non-immune cells (Table S4). A seventh immune panel, IP7, was compiled to identify myeloid-derived suppressor cells (MDSCs) but failed to show a reliable MDSC population. Data from IP7 were therefore excluded. Methods are described in detail in the Supplementary Information. This study was conducted following the Helsinki Declaration and approved by the Medical Ethics Committee of the Amsterdam UMC location Vrije Universiteit Amsterdam (VUmc 2014-100, VUmc 2019-3448).</p><p>We collected parallel PB and BM samples in 22/46 individuals to study whether circulatory immune cell frequencies reflect the BM immune microenvironment (Table S3). We observed significant relationships between relative frequencies of PB- and BM-derived TNFα-producing T cells, natural killer (NK)-T cells, type 1 innate lymphoid cell (ILC) subsets, and classical monocytes (statistics in Figure S2). Despite a lower frequency within the BM, there was a","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"108 6","pages":"466-470"},"PeriodicalIF":2.7,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.b.22244","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144717715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vandana Panakkal, Raniah Al Amri, Stacey Mamatas, Wendy Shallenberger, Sara A. Monaghan, Ahmad Al-Attar
{"title":"An unusual pattern observed upon the addition of CD79b to a flow cytometry B-cell lymphoma panel","authors":"Vandana Panakkal, Raniah Al Amri, Stacey Mamatas, Wendy Shallenberger, Sara A. Monaghan, Ahmad Al-Attar","doi":"10.1002/cyto.b.22246","DOIUrl":"10.1002/cyto.b.22246","url":null,"abstract":"","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"108 6","pages":"488-489"},"PeriodicalIF":2.7,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144625560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bettina Palicskó, Luca Janovák, László Rejtő, László Váróczy, Zsuzsanna Hevessy, Bettina Kárai
Central nervous system (CNS) involvement in multiple myeloma (MM) is a rare but severe complication with a poor prognosis. The identification of malignant plasma cells in cerebrospinal fluid (CSF) is essential for early diagnosis and intervention. However, the sensitivity of traditional diagnostic methods like cytology is low, especially in samples with low-cell counts. This study aimed to develop a multidimensional radar dot-plot analysis using Kaluza software to enhance the sensitivity and specificity of flow cytometry for detecting abnormal plasma cells in CSF. One hundred and twenty-five CSF samples were sent for flow cytometric testing to investigate the central nervous system involvement of MM. Finally, 89 samples from 40 patients were included in our study. Multicolor flow cytometry was performed using an 8-color labeling method, and radar dot-plot analysis was developed using diagnostic bone marrow samples to distinguish normal plasma cells, abnormal plasma cells, and cellular debris. The sensitivity of the novel method was evaluated by diluting myeloma bone marrow cells in pooled CSF samples to simulate low cell counts. Of the 125 CSF specimens, 16 samples from 4 patients showed abnormal plasma cells using both conventional and multidimensional flow cytometry analysis. Discordant results were found in 32 samples (25%), where conventional analysis suggested the presence of abnormal cells, but these were ruled out by multidimensional analysis. Sensitivity testing showed that the multidimensional dot-plot method outperforms conventional two-dimensional dot-plot analysis, as the radar dot plot can be used to identify abnormal cells in samples diluted to 5 WBC/μL, where the cell count of abnormal plasma cells is < 1 cell/μL. Our results showed that the new radar dot-plot analysis can increase the sensitivity and specificity of flow cytometry in MM for the detection of CNS involvement, even in low-cell-count CSF samples, regardless of whether the sample was obtained in a tube containing special reagent or not (TransFix/EDTA CSF Sample Storage tubes). This approach improves diagnostic accuracy, reduces the number of false positive cases caused by antibodies adhering to cell debris, and provides a reliable tool for assessing neurological complications in MM. Further validation is needed in a larger number of cases and testing of the method on different antibody panels.
{"title":"Enhancing detection of central nervous system involvement in multiple myeloma: A novel multidimensional dot-plot based analysis for flow cytometry","authors":"Bettina Palicskó, Luca Janovák, László Rejtő, László Váróczy, Zsuzsanna Hevessy, Bettina Kárai","doi":"10.1002/cyto.b.22245","DOIUrl":"10.1002/cyto.b.22245","url":null,"abstract":"<p>Central nervous system (CNS) involvement in multiple myeloma (MM) is a rare but severe complication with a poor prognosis. The identification of malignant plasma cells in cerebrospinal fluid (CSF) is essential for early diagnosis and intervention. However, the sensitivity of traditional diagnostic methods like cytology is low, especially in samples with low-cell counts. This study aimed to develop a multidimensional radar dot-plot analysis using Kaluza software to enhance the sensitivity and specificity of flow cytometry for detecting abnormal plasma cells in CSF. One hundred and twenty-five CSF samples were sent for flow cytometric testing to investigate the central nervous system involvement of MM. Finally, 89 samples from 40 patients were included in our study. Multicolor flow cytometry was performed using an 8-color labeling method, and radar dot-plot analysis was developed using diagnostic bone marrow samples to distinguish normal plasma cells, abnormal plasma cells, and cellular debris. The sensitivity of the novel method was evaluated by diluting myeloma bone marrow cells in pooled CSF samples to simulate low cell counts. Of the 125 CSF specimens, 16 samples from 4 patients showed abnormal plasma cells using both conventional and multidimensional flow cytometry analysis. Discordant results were found in 32 samples (25%), where conventional analysis suggested the presence of abnormal cells, but these were ruled out by multidimensional analysis. Sensitivity testing showed that the multidimensional dot-plot method outperforms conventional two-dimensional dot-plot analysis, as the radar dot plot can be used to identify abnormal cells in samples diluted to 5 WBC/μL, where the cell count of abnormal plasma cells is < 1 cell/μL. Our results showed that the new radar dot-plot analysis can increase the sensitivity and specificity of flow cytometry in MM for the detection of CNS involvement, even in low-cell-count CSF samples, regardless of whether the sample was obtained in a tube containing special reagent or not (TransFix/EDTA CSF Sample Storage tubes). This approach improves diagnostic accuracy, reduces the number of false positive cases caused by antibodies adhering to cell debris, and provides a reliable tool for assessing neurological complications in MM. Further validation is needed in a larger number of cases and testing of the method on different antibody panels.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"108 4","pages":"275-281"},"PeriodicalIF":2.7,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.b.22245","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144575004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qi Gao, Jingping Zhang, Krasimira Rozenova, Xiaotian Sun, Amanda Burke, Olivia Miu, Nghia Nguyen, Shu Jie Zhang, Mikhail Roshal
T-lineage acute lymphoblastic leukemia (T-ALL) is an aggressive neoplasm of immature T cells. Flow cytometry plays a critical role in the diagnosis and management of the disease. It is used to establish the abnormal immature T-cell phenotype and to distinguish the early T-cell precursor (ETP)-ALL from more mature types at diagnosis. The evaluation of mediastinal disease is often complicated by the difficulty of the phenotypic distinction between the normal thymic precursors and the abnormal T lymphoblasts. Follow-up measurements of minimal/measurable residual disease (MRD) are critical for therapy decision-making and prognostication. In the MRD setting, flow cytometry requires a high degree of analytical expertise and assessment of numerous antigens. To address the diagnostic and monitoring challenges, we developed a single-tube 21-antigen assessment with simplified analysis. The assay distinguishes between normal thymic precursors and T lymphoblasts in tissue samples, enables evaluation of ETP versus non-ETP phenotypes, and allows for MRD assessment below 0.01% robust to antigenic changes.
{"title":"A 20-color 21-antigen flow cytometric assay for disease monitoring of T-cell lymphoblastic leukemia","authors":"Qi Gao, Jingping Zhang, Krasimira Rozenova, Xiaotian Sun, Amanda Burke, Olivia Miu, Nghia Nguyen, Shu Jie Zhang, Mikhail Roshal","doi":"10.1002/cyto.b.22242","DOIUrl":"10.1002/cyto.b.22242","url":null,"abstract":"<p>T-lineage acute lymphoblastic leukemia (T-ALL) is an aggressive neoplasm of immature T cells. Flow cytometry plays a critical role in the diagnosis and management of the disease. It is used to establish the abnormal immature T-cell phenotype and to distinguish the early T-cell precursor (ETP)-ALL from more mature types at diagnosis. The evaluation of mediastinal disease is often complicated by the difficulty of the phenotypic distinction between the normal thymic precursors and the abnormal T lymphoblasts. Follow-up measurements of minimal/measurable residual disease (MRD) are critical for therapy decision-making and prognostication. In the MRD setting, flow cytometry requires a high degree of analytical expertise and assessment of numerous antigens. To address the diagnostic and monitoring challenges, we developed a single-tube 21-antigen assessment with simplified analysis. The assay distinguishes between normal thymic precursors and T lymphoblasts in tissue samples, enables evaluation of ETP versus non-ETP phenotypes, and allows for MRD assessment below 0.01% robust to antigenic changes.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"108 4","pages":"299-311"},"PeriodicalIF":2.7,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.b.22242","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144552552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nirupama D. Verma, Ranje Al-atiyah, Prateek Rakesh, Andrew D. Lam, Christopher Chiu, Giang T. Tran, Bruce M. Hall, Suzanne J. Hodgkinson
Monitoring subpopulations of CD4+ T cells in blood, especially regulatory CD4+CD25+Foxp3+CD127loT cells, has the potential to identify tolerance to transplants and defects that cause autoimmunity. CD45RA is expressed by naïve/resting CD4+, not by activated cells. Staining CD45RA with CD25 or Foxp3 identifies five populations of CD4+ T cells, three Treg, and two CD4+Foxp3−T cells. CD25 is induced on activation of effector cells and is constitutively expressed by Treg. Examining Foxp3+ cells in CD4+CD25+CD127lo, identified three Treg populations. It is not known how stable these populations of CD4+T cells are within individuals and between individuals. Repeated estimations over 3 years in 10 HV showed the proportion of cells in the three Treg populations was stable, whereas the two Foxp3− populations varied. In a larger cohort of 110 samples, females had higher numbers of CD4+ cells than males. As a percentage of lymphocytes, there was no sex difference in the proportion of cells in the five populations. With age, there were fewer total Treg, with fewer resting Treg but an increase in activated Treg. Activation of both naïve CD4+ T cells and Treg induces expression of chemokine receptors associated with Th1, Th17, and Th2 responses that promote their infiltration into sites of inflammation. Activated Treg expressed CCR4 and, in addition, expressed CXCR3 (Th1), CCR6 (Th17), or neither CXCR3 nor CCR6 (Th2). Some Treg expressed both CCR6 and CXCR3. HLA-DR and CD39 were expressed by activated Treg, and many cells expressed both. There was low PD-1 expression. The stability of the major Treg populations suggested it could be feasible to establish normal ranges for the three Treg populations. Staining for chemokine receptors and Treg effector molecules in activated Treg populations may detect changes in immune homeostasis and tolerance.
{"title":"Frequency and stability of populations of CD4+ and CD4+CD25+Foxp3+CD127lo Treg in healthy adults defined by cytometry using monoclonal antibodies to T cell associated molecules","authors":"Nirupama D. Verma, Ranje Al-atiyah, Prateek Rakesh, Andrew D. Lam, Christopher Chiu, Giang T. Tran, Bruce M. Hall, Suzanne J. Hodgkinson","doi":"10.1002/cyto.b.22241","DOIUrl":"10.1002/cyto.b.22241","url":null,"abstract":"<p>Monitoring subpopulations of CD4<sup>+</sup> T cells in blood, especially regulatory CD4<sup>+</sup>CD25<sup>+</sup>Foxp3<sup>+</sup>CD127<sup>lo</sup>T cells, has the potential to identify tolerance to transplants and defects that cause autoimmunity. CD45RA is expressed by naïve/resting CD4<sup>+</sup>, not by activated cells. Staining CD45RA with CD25 or Foxp3 identifies five populations of CD4<sup>+</sup> T cells, three Treg, and two CD4<sup>+</sup>Foxp3<sup>−</sup>T cells. CD25 is induced on activation of effector cells and is constitutively expressed by Treg. Examining Foxp3<sup>+</sup> cells in CD4<sup>+</sup>CD25<sup>+</sup>CD127<sup>lo</sup>, identified three Treg populations. It is not known how stable these populations of CD4<sup>+</sup>T cells are within individuals and between individuals. Repeated estimations over 3 years in 10 HV showed the proportion of cells in the three Treg populations was stable, whereas the two Foxp3<sup>−</sup> populations varied. In a larger cohort of 110 samples, females had higher numbers of CD4<sup>+</sup> cells than males. As a percentage of lymphocytes, there was no sex difference in the proportion of cells in the five populations. With age, there were fewer total Treg, with fewer resting Treg but an increase in activated Treg. Activation of both naïve CD4<sup>+</sup> T cells and Treg induces expression of chemokine receptors associated with Th1, Th17, and Th2 responses that promote their infiltration into sites of inflammation. Activated Treg expressed CCR4 and, in addition, expressed CXCR3 (Th1), CCR6 (Th17), or neither CXCR3 nor CCR6 (Th2). Some Treg expressed both CCR6 and CXCR3. HLA-DR and CD39 were expressed by activated Treg, and many cells expressed both. There was low PD-1 expression. The stability of the major Treg populations suggested it could be feasible to establish normal ranges for the three Treg populations. Staining for chemokine receptors and Treg effector molecules in activated Treg populations may detect changes in immune homeostasis and tolerance.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"108 4","pages":"282-298"},"PeriodicalIF":2.7,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.b.22241","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144215202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Remembering Dr. Bruce H. Davis: A passionate leader in clinical flow cytometry","authors":"","doi":"10.1002/cyto.b.22240","DOIUrl":"https://doi.org/10.1002/cyto.b.22240","url":null,"abstract":"","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"108 3","pages":"189-194"},"PeriodicalIF":2.3,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144179067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Thulasi Raman Ramalingam, Bharaneedharan Marimuthu, Harsha N Rasheed, Archana Lakshmanan, Swetha Lakshmi Narla, Lakshman Vaidhyanathan, Ajit Pai
The free carcinoma cells (FCC) in peritoneal lavage fluid are an independent adverse prognostic factor in patients with gastric carcinoma. Detection of FCC in the pre-operative peritoneal lavage fluid is critical, as patients with FCC do not have a survival advantage with curative cytoreductive (CCR) surgery. Cytology is currently used to assess FCC, but its sensitivity is poor and there is a need for better sensitive techniques. We attempted to study the efficiency of intra-operative flow cytometry (FCM) in detecting FCC in peritoneal lavage fluid of gastric carcinoma patients. In this prospective study, 32 peritoneal lavage fluids were analyzed intra-operatively by cytology and FCM. The median time taken for sample processing was 47 min. The concordance was achieved in 84% (27/32) of samples. FCM detected FCC in 17 peritoneal lavage fluids, of which only 12 were reported positive by cytology. Five cases that had a FCC burden of less than 0.01% were reported negative by cytology. FCC with programmed death-ligand 1 (PD-L1) expression of greater than 50% was noted in 12 cases. Intra-operative FCM improves the detection of FCC in peritoneal lavage fluid compared to cytology. Due to higher sensitivity, flow cytometry offers a promising adjuvant to cytology and helps in deciding on judicious radical CCR.
{"title":"Intraoperative flow cytometry in detecting free carcinoma cells in peritoneal lavage fluid of gastric carcinoma cases.","authors":"Thulasi Raman Ramalingam, Bharaneedharan Marimuthu, Harsha N Rasheed, Archana Lakshmanan, Swetha Lakshmi Narla, Lakshman Vaidhyanathan, Ajit Pai","doi":"10.1002/cyto.b.22238","DOIUrl":"https://doi.org/10.1002/cyto.b.22238","url":null,"abstract":"<p><p>The free carcinoma cells (FCC) in peritoneal lavage fluid are an independent adverse prognostic factor in patients with gastric carcinoma. Detection of FCC in the pre-operative peritoneal lavage fluid is critical, as patients with FCC do not have a survival advantage with curative cytoreductive (CCR) surgery. Cytology is currently used to assess FCC, but its sensitivity is poor and there is a need for better sensitive techniques. We attempted to study the efficiency of intra-operative flow cytometry (FCM) in detecting FCC in peritoneal lavage fluid of gastric carcinoma patients. In this prospective study, 32 peritoneal lavage fluids were analyzed intra-operatively by cytology and FCM. The median time taken for sample processing was 47 min. The concordance was achieved in 84% (27/32) of samples. FCM detected FCC in 17 peritoneal lavage fluids, of which only 12 were reported positive by cytology. Five cases that had a FCC burden of less than 0.01% were reported negative by cytology. FCC with programmed death-ligand 1 (PD-L1) expression of greater than 50% was noted in 12 cases. Intra-operative FCM improves the detection of FCC in peritoneal lavage fluid compared to cytology. Due to higher sensitivity, flow cytometry offers a promising adjuvant to cytology and helps in deciding on judicious radical CCR.</p>","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144141761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nikiforova Kseniya Alexandrovna, Kapranov Nikolai Mikhailovich, Davydova Yulia Olegovna, Fidarova Zalina Taymurazovna, Galtseva Irina Vladimirovna, Parovnichnikova Elena Nikolaevna
{"title":"Comparison of monoclonal antibody to CD59 for the diagnosis of paroxysmal nocturnal hemoglobinuria by flow cytometry","authors":"Nikiforova Kseniya Alexandrovna, Kapranov Nikolai Mikhailovich, Davydova Yulia Olegovna, Fidarova Zalina Taymurazovna, Galtseva Irina Vladimirovna, Parovnichnikova Elena Nikolaevna","doi":"10.1002/cyto.b.22237","DOIUrl":"10.1002/cyto.b.22237","url":null,"abstract":"","PeriodicalId":10883,"journal":{"name":"Cytometry Part B: Clinical Cytometry","volume":"108 6","pages":"481-483"},"PeriodicalIF":2.7,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143994072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}