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Pan-cancer single-cell RNA-seq identifies recurring programs of cellular heterogeneity

Authors :
Kinker, Gabriela S
Greenwald, Alissa C
Tal, Rotem
Orlova, Zhanna
Cuoco, Michael S
McFarland, James M
Warren, Allison
Rodman, Christopher
Roth, Jennifer A
Bender, Samantha A
Kumar, Bhavna
Rocco, James W
Fernandes, Pedro ACM
Mader, Christopher C
Keren-Shaul, Hadas
Plotnikov, Alexander
Barr, Haim
Tsherniak, Aviad
Rozenblatt-Rosen, Orit
Krizhanovsky, Valery
Puram, Sidharth V
Regev, Aviv
Tirosh, Itay
Kinker, Gabriela S
Greenwald, Alissa C
Tal, Rotem
Orlova, Zhanna
Cuoco, Michael S
McFarland, James M
Warren, Allison
Rodman, Christopher
Roth, Jennifer A
Bender, Samantha A
Kumar, Bhavna
Rocco, James W
Fernandes, Pedro ACM
Mader, Christopher C
Keren-Shaul, Hadas
Plotnikov, Alexander
Barr, Haim
Tsherniak, Aviad
Rozenblatt-Rosen, Orit
Krizhanovsky, Valery
Puram, Sidharth V
Regev, Aviv
Tirosh, Itay
Source :
PMC
Publication Year :
2021

Abstract

© 2020, The Author(s), under exclusive licence to Springer Nature America, Inc. Cultured cell lines are the workhorse of cancer research, but the extent to which they recapitulate the heterogeneity observed among malignant cells in tumors is unclear. Here we used multiplexed single-cell RNA-seq to profile 198 cancer cell lines from 22 cancer types. We identified 12 expression programs that are recurrently heterogeneous within multiple cancer cell lines. These programs are associated with diverse biological processes, including cell cycle, senescence, stress and interferon responses, epithelial–mesenchymal transition and protein metabolism. Most of these programs recapitulate those recently identified as heterogeneous within human tumors. We prioritized specific cell lines as models of cellular heterogeneity and used them to study subpopulations of senescence-related cells, demonstrating their dynamics, regulation and unique drug sensitivities, which were predictive of clinical response. Our work describes the landscape of heterogeneity within diverse cancer cell lines and identifies recurrent patterns of heterogeneity that are shared between tumors and specific cell lines.

Details

Database :
OAIster
Journal :
PMC
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1286405201
Document Type :
Electronic Resource