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Article ; Online: Precise reconstruction of the TME using bulk RNA-seq and a machine learning algorithm trained on artificial transcriptomes.

Zaitsev, Aleksandr / Chelushkin, Maksim / Dyikanov, Daniiar / Cheremushkin, Ilya / Shpak, Boris / Nomie, Krystle / Zyrin, Vladimir / Nuzhdina, Ekaterina / Lozinsky, Yaroslav / Zotova, Anastasia / Degryse, Sandrine / Kotlov, Nikita / Baisangurov, Artur / Shatsky, Vladimir / Afenteva, Daria / Kuznetsov, Alexander / Paul, Susan Raju / Davies, Diane L / Reeves, Patrick M /
Lanuti, Michael / Goldberg, Michael F / Tazearslan, Cagdas / Chasse, Madison / Wang, Iris / Abdou, Mary / Aslanian, Sharon M / Andrewes, Samuel / Hsieh, James J / Ramachandran, Akshaya / Lyu, Yang / Galkin, Ilia / Svekolkin, Viktor / Cerchietti, Leandro / Poznansky, Mark C / Ataullakhanov, Ravshan / Fowler, Nathan / Bagaev, Alexander

Cancer cell

2022  Volume 40, Issue 8, Page(s) 879–894.e16

Abstract: Cellular deconvolution algorithms virtually reconstruct tissue composition by analyzing the gene expression of complex tissues. We present the decision tree machine learning algorithm, Kassandra, trained on a broad collection of >9,400 tissue and blood ... ...

Abstract Cellular deconvolution algorithms virtually reconstruct tissue composition by analyzing the gene expression of complex tissues. We present the decision tree machine learning algorithm, Kassandra, trained on a broad collection of >9,400 tissue and blood sorted cell RNA profiles incorporated into millions of artificial transcriptomes to accurately reconstruct the tumor microenvironment (TME). Bioinformatics correction for technical and biological variability, aberrant cancer cell expression inclusion, and accurate quantification and normalization of transcript expression increased Kassandra stability and robustness. Performance was validated on 4,000 H&E slides and 1,000 tissues by comparison with cytometric, immunohistochemical, or single-cell RNA-seq measurements. Kassandra accurately deconvolved TME elements, showing the role of these populations in tumor pathogenesis and other biological processes. Digital TME reconstruction revealed that the presence of PD-1-positive CD8
MeSH term(s) Algorithms ; CD8-Positive T-Lymphocytes ; Humans ; Machine Learning ; Neoplasms/genetics ; RNA-Seq ; Sequence Analysis, RNA ; Transcriptome ; Tumor Microenvironment/genetics
Language English
Publishing date 2022-07-06
Publishing country United States
Document type Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID 2078448-X
ISSN 1878-3686 ; 1535-6108
ISSN (online) 1878-3686
ISSN 1535-6108
DOI 10.1016/j.ccell.2022.07.006
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