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A Community Challenge to Predict Clinical Outcomes After Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

Mike Mason, Óscar Lapuente-Santana, Anni S. Halkola, Wenyu Wang, Raghvendra Mall, Xu Xiao, Jacob Kaufman, Jingxin Fu, Jacob Pfeil, Jineta Banerjee, Verena Chung, Han Chang, Scott D. Chasalow, Hung Ying Lin, Rongrong Chai, Thomas Yu, Francesca Finotello, Tuomas Mirtti, Mikko I. Mäyränpää, Jie Bao, Emmy W. Verschuren, Eiman I. Ahmed, View ORCID ProfileMichele Ceccarelli, Lance D. Miller, Gianni Monaco, View ORCID ProfileWouter R.L. Hendrickx, Shimaa Sherif, Lin Yang, Ming Tang, Shengqing Stan Gu, Wubing Zhang, View ORCID ProfileYi Zhang, Zexian Zeng, Avinash Das Sahu, Yang Liu, Wenxian Yang, Davide Bedognetti, Jing Tang, Federica Eduati, Teemu D. Laajala, William J. Geese, Justin Guinney, Joseph D. Szustakowski, David P. Carbone, Benjamin G. Vincent
doi: https://doi.org/10.1101/2022.12.05.518667
Mike Mason
1Bristol Myers Squibb, Princeton, NJ, USA
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  • For correspondence: mike.mason@bms.com
Óscar Lapuente-Santana
2Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
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Anni S. Halkola
3Department of Mathematics and Statistics, University of Turku, Turku, Finland
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Wenyu Wang
4Faculty of Medicine, University of Helsinki, Helsinki, Finland
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Raghvendra Mall
5Qatar Computing Research Institute, Hamad Bin Khalifa University, P.O. Box 34110, Doha, Qatar
6Department of Immunology, St. Jude Children’s Research Hospital, P.O. Box 38105, Memphis, TN, USA
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Xu Xiao
7School of Informatics, Xiamen University, Xiamen, China
8National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China
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Jacob Kaufman
9Department of Medicine, Duke University, Durham, NC, USA
10The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
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Jingxin Fu
11Dana-Farber Cancer Institute, Boston, MA, USA
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Jacob Pfeil
12AbbVie, South San Francisco, CA, USA
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Jineta Banerjee
13Sage Bionetworks, Seattle, WA, USA
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Verena Chung
13Sage Bionetworks, Seattle, WA, USA
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Han Chang
1Bristol Myers Squibb, Princeton, NJ, USA
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Scott D. Chasalow
1Bristol Myers Squibb, Princeton, NJ, USA
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Hung Ying Lin
1Bristol Myers Squibb, Princeton, NJ, USA
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Rongrong Chai
13Sage Bionetworks, Seattle, WA, USA
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Thomas Yu
13Sage Bionetworks, Seattle, WA, USA
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Francesca Finotello
14Institute of Molecular Biology, University of Innsbruck, Innsbruck, Austria
15Digital Science Center (DiSC), University of Innsbruck, Innsbruck, Austria
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Tuomas Mirtti
16Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
17Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland
18iCAN-Digital Precision Cancer Medicine Flagship, Helsinki, Finland
19Department of Biomedical Engineering, School of Medicine, Emory University, Atlanta, GA, USA
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Mikko I. Mäyränpää
16Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
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Jie Bao
4Faculty of Medicine, University of Helsinki, Helsinki, Finland
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Emmy W. Verschuren
20Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
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Eiman I. Ahmed
21Human Immunology Department, Sidra Medicine, P.O. Box 26999, Doha, Qatar
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Michele Ceccarelli
22Department of Electrical Engineering and Information Technology (DIETI), University of Naples “Federico II”, 80125 Naples, Italy
23BIOGEM Institute of Molecular Biology and Genetics, Via Camporeale, Ariano Irpino, Italy
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  • ORCID record for Michele Ceccarelli
Lance D. Miller
24Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, USA
25Atrium Health Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC, USA
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Gianni Monaco
23BIOGEM Institute of Molecular Biology and Genetics, Via Camporeale, Ariano Irpino, Italy
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Wouter R.L. Hendrickx
21Human Immunology Department, Sidra Medicine, P.O. Box 26999, Doha, Qatar
26College of Health and Life Sciences, Hamad Bin Khalifa University, P.O. Box 26999, Doha, Qatar
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Shimaa Sherif
21Human Immunology Department, Sidra Medicine, P.O. Box 26999, Doha, Qatar
26College of Health and Life Sciences, Hamad Bin Khalifa University, P.O. Box 26999, Doha, Qatar
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Lin Yang
11Dana-Farber Cancer Institute, Boston, MA, USA
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Ming Tang
11Dana-Farber Cancer Institute, Boston, MA, USA
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Shengqing Stan Gu
11Dana-Farber Cancer Institute, Boston, MA, USA
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Wubing Zhang
11Dana-Farber Cancer Institute, Boston, MA, USA
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Yi Zhang
11Dana-Farber Cancer Institute, Boston, MA, USA
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Zexian Zeng
11Dana-Farber Cancer Institute, Boston, MA, USA
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Avinash Das Sahu
11Dana-Farber Cancer Institute, Boston, MA, USA
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Yang Liu
11Dana-Farber Cancer Institute, Boston, MA, USA
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Wenxian Yang
27Aginome Scientific, Xiamen, China
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Davide Bedognetti
21Human Immunology Department, Sidra Medicine, P.O. Box 26999, Doha, Qatar
26College of Health and Life Sciences, Hamad Bin Khalifa University, P.O. Box 26999, Doha, Qatar
28Department of Internal Medicine and Medical Specialties, University of Genoa, Genoa, Italy
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Jing Tang
29University of Helsinki, Helsinki, Finland
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Federica Eduati
2Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
30Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, The Netherlands
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Teemu D. Laajala
3Department of Mathematics and Statistics, University of Turku, Turku, Finland
31FICAN West Cancer Centre, University of Turku and Turku University Hospital, Turku, Finland
32Department of Pharmacology, Anschutz Medical Campus, University of Colorado, Denver, CO, USA
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William J. Geese
1Bristol Myers Squibb, Princeton, NJ, USA
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Justin Guinney
33Tempus Labs, Chicago, IL, USA
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Joseph D. Szustakowski
1Bristol Myers Squibb, Princeton, NJ, USA
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David P. Carbone
10The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
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Benjamin G. Vincent
34Department of Medicine, Division of Hematology, Department of Microbiology and Immunology, Curriculum in Bioinformatics and Computational Biology, Computational Medicine Program, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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Abstract

Purpose Predictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti–PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC.

Methods Participants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials.

Results A total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression–based signatures. The bestperforming models showed improved predictive power over reference variables, including TMB or PD-L1.

Conclusion This DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICIs clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICIs efficacy.

Key objective Not all patients with non-small cell lung cancer (NSCLC) eligible for immune checkpoint inhibitor (ICIs) respond to treatment, but accurate predictive biomarkers of ICIs clinical outcomes are currently lacking. This crowdsourced initiative enabled the robust assessment of predictive models using data from two randomized clinical trials of first-line ICI in metastatic NSCLC.

Knowledge generated Models submitted indicate that a combination of programmed death ligand 1 (PD-L1), tumor mutational burden (TMB), and immune gene signatures might be able to identify patients more likely to respond to ICIs. TMB and PD-L1 seemed important to predict progression-free survival and overall survival. Mechanisms including apoptosis, T-cell crosstalk, and adaptive immune resistance appeared essential to predict response.

Competing Interest Statement

Han Chang and Hung Ying Lin are employees of Bristol Myers Squibb. Mikko I. Mayranpaa has received lecture and/or advisory board fees from Boehringer Ingelheim, Bristol Myers Squibb, MSD, Takeda, Bayer, Amgen, Roche, and Aiforia Technologies Oy. Wenxian Yang is a shareholder of Aginome Scientific. Justin Guinney is an employee of Tempus Labs. Shengqing Stan Gu is the recipient of a fellowship from the Sara Elizabeth O Brien Trust. Joseph Szustakowski, Scott Chasalow, and William Geese are employees and shareholders of Bristol Myers Squibb. Benjamin G. Vincent received consulting fees from GeneCentric Therapeutics. David Carbone has received advisory board fees, consulting fees, presentation fees, or consulting fees from Regeneron, Novartis, AbbVie, AstraZeneca, Bristol Myers Squibb, Roche, Arcus Biosciences, Mirati, Iovance Biotherapeutics, Pfizer, Onc Live, InThought, Glaxo-Smith Kline, Intellisphere, Sanofi, Merck KGgA, Merck/EMD Serono, Johnson & Johnson, Jazz, Janssen, Curio Science, PDD development, G1 Therapeutics, OncoHost, Eisai, Flame Biosciences, Novocure, Merck, DaiiChi Sankyo, and Boehringer Ingelheim. Other authors do not have competing interests.

Footnotes

  • ↵* Co-senior authors from the Anti–PD-1 Response Prediction DREAM Challenge steering committee

  • Previous presentation: Results from this study have been presented, in part, at the 14th annual RECOMB/ISCB Conference on Regulatory and Systems Genomics with DREAM Challenges RSGDREAM 2022), November 8–9, 2022, Las Vegas, Nevada, USA.

  • https://www.synapse.org/#!Synapse:syn18404605/wiki/589611

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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A Community Challenge to Predict Clinical Outcomes After Immune Checkpoint Blockade in Non-Small Cell Lung Cancer
Mike Mason, Óscar Lapuente-Santana, Anni S. Halkola, Wenyu Wang, Raghvendra Mall, Xu Xiao, Jacob Kaufman, Jingxin Fu, Jacob Pfeil, Jineta Banerjee, Verena Chung, Han Chang, Scott D. Chasalow, Hung Ying Lin, Rongrong Chai, Thomas Yu, Francesca Finotello, Tuomas Mirtti, Mikko I. Mäyränpää, Jie Bao, Emmy W. Verschuren, Eiman I. Ahmed, Michele Ceccarelli, Lance D. Miller, Gianni Monaco, Wouter R.L. Hendrickx, Shimaa Sherif, Lin Yang, Ming Tang, Shengqing Stan Gu, Wubing Zhang, Yi Zhang, Zexian Zeng, Avinash Das Sahu, Yang Liu, Wenxian Yang, Davide Bedognetti, Jing Tang, Federica Eduati, Teemu D. Laajala, William J. Geese, Justin Guinney, Joseph D. Szustakowski, David P. Carbone, Benjamin G. Vincent
bioRxiv 2022.12.05.518667; doi: https://doi.org/10.1101/2022.12.05.518667
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A Community Challenge to Predict Clinical Outcomes After Immune Checkpoint Blockade in Non-Small Cell Lung Cancer
Mike Mason, Óscar Lapuente-Santana, Anni S. Halkola, Wenyu Wang, Raghvendra Mall, Xu Xiao, Jacob Kaufman, Jingxin Fu, Jacob Pfeil, Jineta Banerjee, Verena Chung, Han Chang, Scott D. Chasalow, Hung Ying Lin, Rongrong Chai, Thomas Yu, Francesca Finotello, Tuomas Mirtti, Mikko I. Mäyränpää, Jie Bao, Emmy W. Verschuren, Eiman I. Ahmed, Michele Ceccarelli, Lance D. Miller, Gianni Monaco, Wouter R.L. Hendrickx, Shimaa Sherif, Lin Yang, Ming Tang, Shengqing Stan Gu, Wubing Zhang, Yi Zhang, Zexian Zeng, Avinash Das Sahu, Yang Liu, Wenxian Yang, Davide Bedognetti, Jing Tang, Federica Eduati, Teemu D. Laajala, William J. Geese, Justin Guinney, Joseph D. Szustakowski, David P. Carbone, Benjamin G. Vincent
bioRxiv 2022.12.05.518667; doi: https://doi.org/10.1101/2022.12.05.518667

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