Community assessment of methods to deconvolve cellular composition from bulk gene expression

Brian S. White, Aurélien Reyniès, Aaron M. Newman, Joshua J. Waterfall, Andrew Lamb, Florent Petitprez, Yating Lin, Rongshan Yu, Martin E. Guerrero-Gimenez, Sergii Domanskyi, Gianni Monaco, Verena Chung, Jineta Banerjee, Daniel Derrick, Alberto Valdeolivas, Haojun Li, Xu Xiao, Shun Wang, Frank Zheng, Wenxian Yang, Carlos A. Catania, Benjamin J. Lang, Thomas J. Bertus, Carlo Piermarocchi, Francesca P. Caruso, Michele Ceccarelli, Thomas Yu, Xindi Guo, Julie Bletz, John Coller, Holden Maecker, Caroline Duault, Vida Shokoohi, Shailja Patel, Joanna E. Liliental, Stockard Simon, Julio Saez-Rodriguez, Laura M. Heiser, Justin Guinney and Andrew J. Gentles ()
Additional contact information
Brian S. White: Sage Bionetworks
Aurélien Reyniès: INSERM U1138, Université Paris Cité
Aaron M. Newman: Stanford University
Joshua J. Waterfall: PSL Research University
Andrew Lamb: Sage Bionetworks
Florent Petitprez: Ligue Nationale Contre le Cancer
Yating Lin: Xiamen University
Rongshan Yu: Xiamen University
Martin E. Guerrero-Gimenez: National University of Cuyo
Sergii Domanskyi: Michigan State University
Gianni Monaco: BIOGEM Institute of Molecular Biology and Genetics
Verena Chung: Sage Bionetworks
Jineta Banerjee: Sage Bionetworks
Daniel Derrick: Oregon Health & Science University
Alberto Valdeolivas: Institute for Computational Biomedicine
Haojun Li: Xiamen University
Xu Xiao: Xiamen University
Shun Wang: Cancer Hospital, Chinese Aacdemy of Medical Science
Frank Zheng: AmoyDx
Wenxian Yang: Aginome Scientific
Carlos A. Catania: National University of Cuyo
Benjamin J. Lang: Harvard Medical School
Thomas J. Bertus: Michigan State University
Carlo Piermarocchi: Michigan State University
Francesca P. Caruso: BIOGEM Institute of Molecular Biology and Genetics
Michele Ceccarelli: BIOGEM Institute of Molecular Biology and Genetics
Thomas Yu: Sage Bionetworks
Xindi Guo: Sage Bionetworks
Julie Bletz: Sage Bionetworks
John Coller: Stanford University School of Medicine
Holden Maecker: Stanford University School of Medicine
Caroline Duault: Stanford University School of Medicine
Vida Shokoohi: Stanford University School of Medicine
Shailja Patel: Stanford University School of Medicine
Joanna E. Liliental: Stanford University School of Medicine
Stockard Simon: Sage Bionetworks
Julio Saez-Rodriguez: Institute for Computational Biomedicine
Laura M. Heiser: Oregon Health & Science University
Justin Guinney: Sage Bionetworks
Andrew J. Gentles: Stanford University

Nature Communications, 2024, vol. 15, issue 1, 1-22

Abstract: Abstract We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.

Date: 2024
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DOI: 10.1038/s41467-024-50618-0

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