Single-cell mapping of human brain cancer reveals tumor-specific instruction of tissue invading leukocytes

Published: 18-11-2020| Version 1 | DOI: 10.17632/jk8c3c3nmz.1
Contributor:
Ekaterina Friebel

Description

Ekaterina Friebel, Konstantina Kapolou, Susanne Unger, Nicolás Gonzalo Núñez, Sebastian Utz, Elisabeth Jane Rushing, Luca Regli, Michael Weller, Melanie Greter, Sonia Tugues, Marian Christoph Neidert, Burkhard Becher* *Correspondence: becher@immunology.uzh.ch

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The normalized mass cytometry data containing living cells from every individual patient were manually exported from FlowJo Software (Tree Star) and imported into R studio of R (R Foundation for Statistical Computing). Before automated high-dimensional data analysis, the mass cytometry data were transformed with a cofactor from 5 to 60 using an inverse hyperbolic sine (arcsinh) function. For flow cytometry data, the compensation matrix was corrected using FlowJo software (Tree Star). After live, single, CD45 positive and compensated cells were exported and imported into R Studio. Before automated high-dimensional data analysis, flow cytometry data were transformed using an inverse hyperbolic sine (arcsinh) function with a cofactor from 300 to 600. Every animal got an ID code. “C” in the animal ID marked the control animals, the one did not have the injection of tumor cells, but had Sall1/YFP expression. Samples LH60, LV57, L57, RV58, RH57, RH58 and RV57 developed a big tumor, and the rest had an intermediate to a small tumor. Samples RV58, LH60, L57 and RH60 were wild type control animals (YFP-) with the injection of tumor cells.