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

View ORCID ProfileBrian S. White, View ORCID ProfileAurélien de Reyniès, View ORCID ProfileAaron M. Newman, View ORCID ProfileJoshua J. Waterfall, Andrew Lamb, View ORCID ProfileFlorent Petitprez, View ORCID ProfileAlberto Valdeolivas, Yating Lin, Haojun Li, Xu Xiao, Shun Wang, Frank Zheng, View ORCID ProfileWenxian Yang, View ORCID ProfileRongshan Yu, View ORCID ProfileMartin E Guerrero-Gimenez, Carlos A Catania, View ORCID ProfileBenjamin J Lang, View ORCID ProfileSergii Domanskyi, Thomas J Bertus, View ORCID ProfileCarlo Piermarocchi, View ORCID ProfileGianni Monaco, Francesca P Caruso, View ORCID ProfileMichele Ceccarelli, Thomas Yu, Xindi Guo, John Coller, Holden Maecker, Caroline Duault, Vida Shokoohi, Shailja Patel, Joanna E Liliental, Stockard Simon, Tumor Deconvolution DREAM Challenge consortium, View ORCID ProfileJulio Saez-Rodriguez, Laura M. Heiser, View ORCID ProfileJustin Guinney, View ORCID ProfileAndrew J. Gentles
doi: https://doi.org/10.1101/2022.06.03.494221
Brian S. White
1Computational Oncology, Sage Bionetworks, Seattle, WA, USA
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Aurélien de Reyniès
2Centre de Recherche des Cordeliers, INSERM U1138, Université Paris Cité, Paris, France
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Aaron M. Newman
3Institute for Stem Cell Biology and Regenerative Medicine and Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
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Joshua J. Waterfall
4INSERM U830 and Translational Research Department, Institut Curie, PSL Research University, Paris, France
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Andrew Lamb
1Computational Oncology, Sage Bionetworks, Seattle, WA, USA
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Florent Petitprez
5Programme Cartes d’Identité des Tumeurs, Ligue Nationale Contre le Cancer, Paris, France and MRC Centre for Reproductive Health, the Queen’s Medical Research Institute, University of Edinburgh, United Kingdom
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Alberto Valdeolivas
6Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany
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Yating Lin
7Xiamen University, Xiamen, Fujian, China
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Haojun Li
7Xiamen University, Xiamen, Fujian, China
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Xu Xiao
7Xiamen University, Xiamen, Fujian, China
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Shun Wang
8Aginome Scientific, Xiamen, Fujian, China
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Frank Zheng
9AmoyDx, Xiamen, Fujian, China
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Wenxian Yang
8Aginome Scientific, Xiamen, Fujian, China
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Rongshan Yu
7Xiamen University, Xiamen, Fujian, China
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Martin E Guerrero-Gimenez
10Institute of Biochemistry and Biotechnology, School of Medicine, National University of Cuyo, Mendoza, Argentina
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Carlos A Catania
11Laboratory of Intelligent Systems (LABSIN), Engineering School, National University of Cuyo, Mendoza, Argentina
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Benjamin J Lang
12Department of Radiation Oncology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
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Sergii Domanskyi
13Michigan State University, East Lansing, MI, USA
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Thomas J Bertus
13Michigan State University, East Lansing, MI, USA
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Carlo Piermarocchi
13Michigan State University, East Lansing, MI, USA
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Gianni Monaco
14BIOGEM Institute of Molecular Biology and Genetics, Ariano Irpino, AV, Italy
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Francesca P Caruso
14BIOGEM Institute of Molecular Biology and Genetics, Ariano Irpino, AV, Italy
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Michele Ceccarelli
15BIOGEM Institute of Molecular Biology and Genetics, Department of Electrical Engineering and Information Technology (DIETI), University of Naples “Federico II”, Ariano Irpino, AV, Italy
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Thomas Yu
16Computational Oncology, Sage Bionetworks, Seattle, WA, USA
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Xindi Guo
16Computational Oncology, Sage Bionetworks, Seattle, WA, USA
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John Coller
17Stanford Functional Genomics Facility, Stanford University School of Medicine, Stanford, CA
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Holden Maecker
18Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA
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Caroline Duault
18Institute for Immunity, Transplantation, and Infection, Stanford University School of Medicine, Stanford, CA
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Vida Shokoohi
19Stanford Functional Genomics Facility, Stanford University School of Medicine, Stanford, CA
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Shailja Patel
20Translational Applications Service Center, Stanford University School of Medicine, Stanford, CA
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Joanna E Liliental
20Translational Applications Service Center, Stanford University School of Medicine, Stanford, CA
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Stockard Simon
21Sage Bionetworks, Seattle, WA, USA
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Julio Saez-Rodriguez
22Heidelberg University, Faculty of Medicine, and Heidelberg University Hospital, Institute for Computational Biomedicine, Bioquant, Heidelberg, Germany
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Laura M. Heiser
23Department of Biomedical Engineering, Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA
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Justin Guinney
16Computational Oncology, Sage Bionetworks, Seattle, WA, USA
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Andrew J. Gentles
24Departments of Medicine, and Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
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  • For correspondence: andrewg@stanford.edu
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Abstract

Deconvolution methods infer levels of immune and stromal infiltration from bulk expression of tumor samples. These methods allow projection of characteristics of the tumor microenvironment, known to affect patient outcome and therapeutic response, onto the millions of bulk transcriptional profiles in public databases, many focused on uniquely valuable and clinically-annotated cohorts. Despite the wide development of such methods, a standardized dataset with ground truth to evaluate their performance has been lacking. We generated and sequenced in vitro and in silico admixtures of tumor, immune, and stromal cells and used them as ground truth in a community-wide DREAM Challenge that provided an objective, unbiased assessment of six widely-used published deconvolution methods and of 22 new analytical approaches developed by international teams. Our results demonstrate that existing methods predict many cell types well, while team-contributed methods highlight the potential to resolve functional states of T cells that were either not covered by published reference signatures or estimated poorly by some published methods. Our assessment and the open-source implementations of top-performing methods will allow researchers to apply the deconvolution approach most appropriate to querying their cell type of interest. Further, our publicly-available admixed and purified expression profiles will be a valuable resource to those developing deconvolution methods, including in non-malignant settings involving immune cells.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Revised methods for IZI deconvolution method Fixed equations in methods

  • https://www.synapse.org/#!Synapse:syn15589870/wiki/582446

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Community assessment of methods to deconvolve cellular composition from bulk gene expression
Brian S. White, Aurélien de Reyniès, Aaron M. Newman, Joshua J. Waterfall, Andrew Lamb, Florent Petitprez, Alberto Valdeolivas, Yating Lin, Haojun Li, Xu Xiao, Shun Wang, Frank Zheng, Wenxian Yang, Rongshan Yu, Martin E Guerrero-Gimenez, Carlos A Catania, Benjamin J Lang, Sergii Domanskyi, Thomas J Bertus, Carlo Piermarocchi, Gianni Monaco, Francesca P Caruso, Michele Ceccarelli, Thomas Yu, Xindi Guo, John Coller, Holden Maecker, Caroline Duault, Vida Shokoohi, Shailja Patel, Joanna E Liliental, Stockard Simon, Tumor Deconvolution DREAM Challenge consortium, Julio Saez-Rodriguez, Laura M. Heiser, Justin Guinney, Andrew J. Gentles
bioRxiv 2022.06.03.494221; doi: https://doi.org/10.1101/2022.06.03.494221
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Community assessment of methods to deconvolve cellular composition from bulk gene expression
Brian S. White, Aurélien de Reyniès, Aaron M. Newman, Joshua J. Waterfall, Andrew Lamb, Florent Petitprez, Alberto Valdeolivas, Yating Lin, Haojun Li, Xu Xiao, Shun Wang, Frank Zheng, Wenxian Yang, Rongshan Yu, Martin E Guerrero-Gimenez, Carlos A Catania, Benjamin J Lang, Sergii Domanskyi, Thomas J Bertus, Carlo Piermarocchi, Gianni Monaco, Francesca P Caruso, Michele Ceccarelli, Thomas Yu, Xindi Guo, John Coller, Holden Maecker, Caroline Duault, Vida Shokoohi, Shailja Patel, Joanna E Liliental, Stockard Simon, Tumor Deconvolution DREAM Challenge consortium, Julio Saez-Rodriguez, Laura M. Heiser, Justin Guinney, Andrew J. Gentles
bioRxiv 2022.06.03.494221; doi: https://doi.org/10.1101/2022.06.03.494221

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