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Chi P, Jiang H, Li D, Li J, Wen X, Ding Q, Chen L, Zhang X, Huang J, Ding Y. An immune risk score predicts progression-free survival of melanoma patients in South China receiving anti-PD-1 inhibitor therapy-a retrospective cohort study examining 66 circulating immune cell subsets. Front Immunol 2022; 13:1012673. [PMID: 36569825 PMCID: PMC9768215 DOI: 10.3389/fimmu.2022.1012673] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 11/07/2022] [Indexed: 12/12/2022] Open
Abstract
Introduction Immune checkpoint blockade inhibitor (ICI) therapy offers significant survival benefits for malignant melanoma. However, some patients were observed to be in disease progression after the first few treatment cycles. As such, it is urgent to find convenient and accessible indicators that assess whether patients can benefit from ICI therapy. Methods In the training cohort, flow cytometry was used to determine the absolute values of 66 immune cell subsets in the peripheral blood of melanoma patients (n=29) before treatment with anti-PD-1 inhibitors. The least absolute shrinkage and selection operator (LASSO) Cox regression model was followed for the efficacy of each subset in predicting progression-free survival. Then we validated the performance of the selected model in validation cohorts (n=20), and developed a nomogram for clinical use. Results A prognostic immune risk score composed of CD1c+ dendritic cells and three subsets of T cells (CD8+CD28+, CD3+TCRab+HLA-DR+, CD3+TCRgd+HLA-DR+) with a higher prognostic power than individual features (AUC = 0.825). Using this model, patients in the training cohort were divided into high- and low-risk groups with significant differences in mean progression-free survival (3.6 vs. 12.3 months), including disease control rate (41.2% vs. 91.7%), and objective response rate (17.6% vs. 41.6%). Integrating four-immune cell-subset based classifiers and three clinicopathologic risk factors can help to predict which patients might benefit from anti-PD-1 antibody inhibitors and remind potential non-responders to pursue effective treatment options in a timely way. Conclusions The prognostic immune risk score including the innate immune and adaptive immune cell populations could provide an accurate prediction efficacy in malignant melanoma patients with ICI therapy.
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Affiliation(s)
- Peidong Chi
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China,Department of Clinical Laboratory, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China
| | - Hang Jiang
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China,Department of Biotherapy Center, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China
| | - Dandan Li
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China,Department of Biotherapy Center, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China
| | - Jingjing Li
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China,Department of Biotherapy Center, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China
| | - Xizhi Wen
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China,Department of Biotherapy Center, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China
| | - Qiyue Ding
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China,Department of Biotherapy Center, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China
| | - Linbin Chen
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China,Department of Biotherapy Center, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China
| | - Xiaoshi Zhang
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China,Department of Biotherapy Center, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China,*Correspondence: Ya Ding, ; Junqi Huang, ; Xiaoshi Zhang,
| | - Junqi Huang
- Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China,Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China,Guangdong Provincial International Cooperation Base of Science and Technology (Organ Transplantation), Guangzhou, China,Department of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China,*Correspondence: Ya Ding, ; Junqi Huang, ; Xiaoshi Zhang,
| | - Ya Ding
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China,Department of Biotherapy Center, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong, China,*Correspondence: Ya Ding, ; Junqi Huang, ; Xiaoshi Zhang,
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Patel VI, Booth JL, Dozmorov M, Brown BR, Metcalf JP. Anthrax Edema and Lethal Toxins Differentially Target Human Lung and Blood Phagocytes. Toxins (Basel) 2020; 12:toxins12070464. [PMID: 32698436 PMCID: PMC7405021 DOI: 10.3390/toxins12070464] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 07/14/2020] [Accepted: 07/15/2020] [Indexed: 12/26/2022] Open
Abstract
Bacillus anthracis, the causative agent of inhalation anthrax, is a serious concern as a bioterrorism weapon. The vegetative form produces two exotoxins: Lethal toxin (LT) and edema toxin (ET). We recently characterized and compared six human airway and alveolar-resident phagocyte (AARP) subsets at the transcriptional and functional levels. In this study, we examined the effects of LT and ET on these subsets and human leukocytes. AARPs and leukocytes do not express high levels of the toxin receptors, tumor endothelium marker-8 (TEM8) and capillary morphogenesis protein-2 (CMG2). Less than 20% expressed surface TEM8, while less than 15% expressed CMG2. All cell types bound or internalized protective antigen, the common component of the two toxins, in a dose-dependent manner. Most protective antigen was likely internalized via macropinocytosis. Cells were not sensitive to LT-induced apoptosis or necrosis at concentrations up to 1000 ng/mL. However, toxin exposure inhibited B. anthracis spore internalization. This inhibition was driven primarily by ET in AARPs and LT in leukocytes. These results support a model of inhalation anthrax in which spores germinate and produce toxins. ET inhibits pathogen phagocytosis by AARPs, allowing alveolar escape. In late-stage disease, LT inhibits phagocytosis by leukocytes, allowing bacterial replication in the bloodstream.
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Affiliation(s)
- Vineet I. Patel
- Department of Medicine, Pulmonary, Critical Care & Sleep Medicine, the University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (V.I.P.); (J.L.B.); (B.R.B.)
| | - J. Leland Booth
- Department of Medicine, Pulmonary, Critical Care & Sleep Medicine, the University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (V.I.P.); (J.L.B.); (B.R.B.)
| | - Mikhail Dozmorov
- Department of Biostatistics, Virginia Commonwealth University, Richmond, VA 23298, USA;
| | - Brent R. Brown
- Department of Medicine, Pulmonary, Critical Care & Sleep Medicine, the University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (V.I.P.); (J.L.B.); (B.R.B.)
| | - Jordan P. Metcalf
- Department of Medicine, Pulmonary, Critical Care & Sleep Medicine, the University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA; (V.I.P.); (J.L.B.); (B.R.B.)
- Department of Microbiology and Immunology, the University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA
- Veterans Affairs Medical Center, Oklahoma City, OK 73104, USA
- Correspondence:
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Self-Learning Microfluidic Platform for Single-Cell Imaging and Classification in Flow. MICROMACHINES 2019; 10:mi10050311. [PMID: 31075890 PMCID: PMC6563144 DOI: 10.3390/mi10050311] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Accepted: 05/06/2019] [Indexed: 02/07/2023]
Abstract
Single-cell analysis commonly requires the confinement of cell suspensions in an analysis chamber or the precise positioning of single cells in small channels. Hydrodynamic flow focusing has been broadly utilized to achieve stream confinement in microchannels for such applications. As imaging flow cytometry gains popularity, the need for imaging-compatible microfluidic devices that allow for precise confinement of single cells in small volumes becomes increasingly important. At the same time, high-throughput single-cell imaging of cell populations produces vast amounts of complex data, which gives rise to the need for versatile algorithms for image analysis. In this work, we present a microfluidics-based platform for single-cell imaging in-flow and subsequent image analysis using variational autoencoders for unsupervised characterization of cellular mixtures. We use simple and robust Y-shaped microfluidic devices and demonstrate precise 3D particle confinement towards the microscope slide for high-resolution imaging. To demonstrate applicability, we use these devices to confine heterogeneous mixtures of yeast species, brightfield-image them in-flow and demonstrate fully unsupervised, as well as few-shot classification of single-cell images with 88% accuracy.
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Galkowski D, Ratajczak MZ, Kocki J, Darzynkiewicz Z. Of Cytometry, Stem Cells and Fountain of Youth. Stem Cell Rev Rep 2018; 13:465-481. [PMID: 28364326 DOI: 10.1007/s12015-017-9733-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Outlined are advances of cytometry applications to identify and sort stem cells, of laser scanning cytometry and ImageStream imaging instrumentation to further analyze morphometry of these cells, and of mass cytometry to classify a multitude of cellular markers in large cell populations. Reviewed are different types of stem cells, including potential candidates for cancer stem cells, with respect to their "stemness", and other characteristics. Appraised is further progress in identification and isolation of the "very small embryonic-like stem cells" (VSELs) and their autogenous transplantation for tissue repair and geroprotection. Also assessed is a function of hyaluronic acid, the major stem cells niche component, as a guardian and controller of stem cells. Briefly appraised are recent advances and challenges in the application of stem cells in regenerative medicine and oncology and their future role in different disciplines of medicine, including geriatrics.
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Affiliation(s)
| | - Mariusz Z Ratajczak
- Stem Cell Institute at James Graham Brown Cancer Center, University of Louisville, Louisville, KY, 40202, USA
| | - Janusz Kocki
- Department of Clinical Genetics, Medical University in Lublin, 20-080, Lublin, Poland
| | - Zbigniew Darzynkiewicz
- Brander Cancer Research Institute and Department of Pathology, New York Medical College, Valhalla, NY, 10095, USA.
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Rubbens P, Props R, Boon N, Waegeman W. Flow Cytometric Single-Cell Identification of Populations in Synthetic Bacterial Communities. PLoS One 2017; 12:e0169754. [PMID: 28122063 PMCID: PMC5266259 DOI: 10.1371/journal.pone.0169754] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2016] [Accepted: 12/21/2016] [Indexed: 01/14/2023] Open
Abstract
Bacterial cells can be characterized in terms of their cell properties using flow cytometry. Flow cytometry is able to deliver multiparametric measurements of up to 50,000 cells per second. However, there has not yet been a thorough survey concerning the identification of the population to which bacterial single cells belong based on flow cytometry data. This paper not only aims to assess the quality of flow cytometry data when measuring bacterial populations, but also suggests an alternative approach for analyzing synthetic microbial communities. We created so-called in silico communities, which allow us to explore the possibilities of bacterial flow cytometry data using supervised machine learning techniques. We can identify single cells with an accuracy >90% for more than half of the communities consisting out of two bacterial populations. In order to assess to what extent an in silico community is representative for its synthetic counterpart, we created so-called abundance gradients, a combination of synthetic (i.e., in vitro) communities containing two bacterial populations in varying abundances. By showing that we are able to retrieve an abundance gradient using a combination of in silico communities and supervised machine learning techniques, we argue that in silico communities form a viable representation for synthetic bacterial communities, opening up new opportunities for the analysis of synthetic communities and bacterial flow cytometry data in general.
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Affiliation(s)
- Peter Rubbens
- KERMIT, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Ghent, Belgium
- * E-mail:
| | - Ruben Props
- Center for Microbial Technology and Ecology (CMET), Ghent University, Ghent, Belgium
| | - Nico Boon
- Center for Microbial Technology and Ecology (CMET), Ghent University, Ghent, Belgium
| | - Willem Waegeman
- KERMIT, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Ghent, Belgium
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Balakrishnan KR, Whang JC, Hwang R, Hack JH, Godley LA, Sohn LL. Node-pore sensing enables label-free surface-marker profiling of single cells. Anal Chem 2015; 87:2988-95. [PMID: 25625182 PMCID: PMC4350414 DOI: 10.1021/ac504613b] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
![]()
Flow cytometry is a ubiquitous, multiparametric
method for characterizing
cellular populations. However, this method can grow increasingly complex
with the number of proteins that need to be screened simultaneously:
spectral emission overlap of fluorophores and the subsequent need
for compensation, lengthy sample preparation, and multiple control
tests that need to be performed separately must all be considered.
These factors lead to increased costs, and consequently, flow cytometry
is performed in core facilities with a dedicated technician operating
the instrument. Here, we describe a low-cost, label-free microfluidic
method that can determine the phenotypic profiles of single cells.
Our method employs Node-Pore Sensing to measure the transit times
of cells as they interact with a series of different antibodies, each
corresponding to a specific cell-surface antigen, that have been functionalized
in a single microfluidic channel. We demonstrate the capabilities
of our method not only by screening two acute promyelocytic leukemia
human cells lines (NB4 and AP-1060) for myeloid antigens, CD13, CD14,
CD15, and CD33, simultaneously, but also by distinguishing a mixture
of cells of similar size—AP-1060 and NALM-1—based on
surface markers CD13 and HLA-DR. Furthermore, we show that our method
can screen complex subpopulations in clinical samples: we successfully
identified the blast population in primary human bone marrow samples
from patients with acute myeloid leukemia and screened these cells
for CD13, CD34, and HLA-DR. We show that our label-free method is
an affordable, highly sensitive, and user-friendly technology that
has the potential to transform cellular screening at the benchside.
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Affiliation(s)
- Karthik R Balakrishnan
- Department of Mechanical Engineering, University of California , Berkeley, California 94720, United States
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Donnenberg VS, Landreneau RJ, Pfeifer ME, Donnenberg AD. Flow cytometric determination of stem/progenitor content in epithelial tissues: an example from nonsmall lung cancer and normal lung. Cytometry A 2013; 83:141-9. [PMID: 23081669 PMCID: PMC4162487 DOI: 10.1002/cyto.a.22156] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2012] [Revised: 05/18/2012] [Accepted: 07/20/2012] [Indexed: 12/27/2022]
Abstract
Single cell analysis and cell sorting has enabled the study of development, growth, differentiation, repair and maintenance of "liquid" tissues and their cancers. The application of these methods to solid tissues is equally promising, but several unique technical challenges must be addressed. This report illustrates the application of multidimensional flow cytometry to the identification of candidate stem/progenitor populations in non-small cell lung cancer and paired normal lung tissue. Seventeen paired tumor/normal lung samples were collected at the time of surgical excision and processed immediately. Tissues were mechanically and enzymatically dissociated into single cell suspension and stained with a panel of antibodies used for negative gating (CD45, CD14, CD33, glycophorin A), identification of epithelial cells (intracellular cytokeratin), and detection of stem/progenitor markers (CD44, CD90, CD117, CD133). DAPI was added to measure DNA content. Formalin fixed paraffin embedded tissue samples were stained with key markers (cytokeratin, CD117, DAPI) for immunofluorescent tissue localization of populations detected by flow cytometry. Disaggregated tumor and lung preparations contained a high proportion of events that would interfere with analysis, were they not eliminated by logical gating. We demonstrate how inclusion of doublets, events with hypodiploid DNA, and cytokeratin+ events also staining for hematopoietic markers reduces the ability to quantify epithelial cells and their precursors. Using the lung cancer/normal lung data set, we present an approach to multidimensional data analysis that consists of artifact removal, identification of classes of cells to be studied further (classifiers) and the measurement of outcome variables on these cell classes. The results of bivariate analysis show a striking similarity between the expression of stem/progenitor markers on lung tumor and adjacent tumor-free lung.
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Affiliation(s)
- Vera S. Donnenberg
- Department of Cardiothoracic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
- University of Pittsburgh Cancer Center, Pittsburgh, PA USA
- McGowan Institute of Regenerative Medicine, Pittsburgh PA USA
| | - Rodney J. Landreneau
- Department of Cardiothoracic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA USA
- University of Pittsburgh Cancer Center, Pittsburgh, PA USA
| | | | - Albert D. Donnenberg
- University of Pittsburgh Cancer Center, Pittsburgh, PA USA
- McGowan Institute of Regenerative Medicine, Pittsburgh PA USA
- University of Pittsburgh School of Medicine, Dept. of Medicine, Pittsburgh, PA USA
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