Preliminary study for a fully automated pre-gating method for high-dimensional mass cytometry data

Author(s):  
Aleksandra Suwalska ◽  
Joanna Polanska
2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Christos Nikolaou ◽  
Kerstin Muehle ◽  
Stephan Schlickeiser ◽  
Alberto Sada Japp ◽  
Nadine Matzmohr ◽  
...  

An amendment to this paper has been published and can be accessed via the original article.


Author(s):  
Jacobus Herderschee ◽  
Tytti Heinonen ◽  
Craig Fenwick ◽  
Irene T. Schrijver ◽  
Khalid Ohmiti ◽  
...  

2019 ◽  
Vol 200 ◽  
pp. 24-30 ◽  
Author(s):  
Min Sun Shin ◽  
Kristina Yim ◽  
Kevin Moon ◽  
Hong-Jai Park ◽  
Subhasis Mohanty ◽  
...  

2019 ◽  
Vol 35 (20) ◽  
pp. 4063-4071 ◽  
Author(s):  
Tamim Abdelaal ◽  
Thomas Höllt ◽  
Vincent van Unen ◽  
Boudewijn P F Lelieveldt ◽  
Frits Koning ◽  
...  

Abstract Motivation High-dimensional mass cytometry (CyTOF) allows the simultaneous measurement of multiple cellular markers at single-cell level, providing a comprehensive view of cell compositions. However, the power of CyTOF to explore the full heterogeneity of a biological sample at the single-cell level is currently limited by the number of markers measured simultaneously on a single panel. Results To extend the number of markers per cell, we propose an in silico method to integrate CyTOF datasets measured using multiple panels that share a set of markers. Additionally, we present an approach to select the most informative markers from an existing CyTOF dataset to be used as a shared marker set between panels. We demonstrate the feasibility of our methods by evaluating the quality of clustering and neighborhood preservation of the integrated dataset, on two public CyTOF datasets. We illustrate that by computationally extending the number of markers we can further untangle the heterogeneity of mass cytometry data, including rare cell-population detection. Availability and implementation Implementation is available on GitHub (https://github.com/tabdelaal/CyTOFmerge). Supplementary information Supplementary data are available at Bioinformatics online.


2018 ◽  
Vol 13 (10) ◽  
pp. 2121-2148 ◽  
Author(s):  
Guojun Han ◽  
Matthew H. Spitzer ◽  
Sean C. Bendall ◽  
Wendy J. Fantl ◽  
Garry P. Nolan

2019 ◽  
Vol 13 (Supplement_1) ◽  
pp. S020-S020
Author(s):  
V van Unen ◽  
N Li ◽  
T Abdelaal ◽  
Y Kooy-Winkelaar ◽  
L Ouboter ◽  
...  

2015 ◽  
Vol 9 (1) ◽  
pp. 68-82 ◽  
Author(s):  
N Nair ◽  
E W Newell ◽  
C Vollmers ◽  
S R Quake ◽  
J M Morton ◽  
...  

2017 ◽  
Vol 114 (29) ◽  
pp. E5900-E5909 ◽  
Author(s):  
Valerie Chew ◽  
Liyun Lai ◽  
Lu Pan ◽  
Chun Jye Lim ◽  
Juntao Li ◽  
...  

The recent development of immunotherapy as a cancer treatment has proved effective over recent years, but the precise dynamics between the tumor microenvironment (TME), nontumor microenvironment (NTME), and the systemic immune system remain elusive. Here, we interrogated these compartments in hepatocellular carcinoma (HCC) using high-dimensional proteomic and transcriptomic analyses. By time-of-flight mass cytometry, we found that the TME was enriched in regulatory T cells (Tregs), tissue resident memory CD8+ T cells (TRMs), resident natural killer cells (NKRs), and tumor-associated macrophages (TAMs). This finding was also validated with immunofluorescence staining on Foxp3+CD4+ and PD-1+CD8+ T cells. Interestingly, Tregs and TRMs isolated from the TME expressed multiple markers for T-cell exhaustion, including PD-1, Lag-3, and Tim-3 compared with Tregs and TRMs isolated from the NTME. We found PD-1+ TRMs were the predominant T-cell subset responsive to anti–PD-1 treatment and significantly reduced in number with increasing HCC tumor progression. Furthermore, T-bet was identified as a key transcription factor, negatively correlated with PD-1 expression on memory CD8+ T cells, and the PD-1:T-bet ratio increased upon exposure to tumor antigens. Finally, transcriptomic analysis of tumor and adjacent nontumor tissues identified a chemotactic gradient for recruitment of TAMs and NKRs via CXCR3/CXCL10 and CCR6/CCL20 pathways, respectively. Taken together, these data confirm the existence of an immunosuppressive gradient across the TME, NTME, and peripheral blood in primary HCC that manipulates the activation status of tumor-infiltrating leukocytes and renders them immunocompromised against tumor cells. By understanding the immunologic composition of this gradient, more effective immunotherapeutics for HCC may be designed.


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