A community challenge to predict clinical outcomes after immune checkpoint blockade in non-small cell lung cancer.

Autor: Mason M; Bristol Myers Squibb, Princeton, NJ, USA., Lapuente-Santana Ó; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands., Halkola AS; Department of Mathematics and Statistics, University of Turku, Turku, Finland., Wang W; Faculty of Medicine, Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland., Mall R; Qatar Computing Research Institute, Hamad Bin Khalifa University, P.O. Box 34110, Doha, Qatar.; Department of Immunology, St. Jude Children's Research Hospital, P.O. Box 38105, Memphis, TN, USA.; Biotechnology Research Center, Technology Innovation Institute, P.O. Box 9639, Abu Dhabi, United Arab Emirates., Xiao X; School of Informatics, Xiamen University, Xiamen, China.; National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China., Kaufman J; Department of Medicine, Duke University, Durham, NC, USA.; The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA., Fu J; Dana-Farber Cancer Institute, Boston, MA, USA., Pfeil J; AbbVie, South San Francisco, CA, USA., Banerjee J; Sage Bionetworks, Seattle, WA, USA., Chung V; Sage Bionetworks, Seattle, WA, USA., Chang H; Bristol Myers Squibb, Princeton, NJ, USA., Chasalow SD; Bristol Myers Squibb, Princeton, NJ, USA., Lin HY; Bristol Myers Squibb, Princeton, NJ, USA., Chai R; Sage Bionetworks, Seattle, WA, USA., Yu T; Sage Bionetworks, Seattle, WA, USA., Finotello F; Institute of Molecular Biology, University of Innsbruck, Innsbruck, Austria.; Digital Science Center (DiSC), University of Innsbruck, Innsbruck, Austria., Mirtti T; Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.; Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland.; iCAN-Digital Precision Cancer Medicine Flagship, Helsinki, Finland.; Department of Biomedical Engineering, School of Medicine, Emory University, Atlanta, GA, USA., Mäyränpää MI; Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland., Bao J; Faculty of Medicine, Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland., Verschuren EW; Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland., Ahmed EI; Human Immunology Department, Sidra Medicine, P.O. Box 26999, Doha, Qatar., Ceccarelli M; Department of Electrical Engineering and Information Technology (DIETI), University of Naples 'Federico II', 80125, Naples, Italy.; BIOGEM Institute of Molecular Biology and Genetics, Via Camporeale, Ariano Irpino, Italy., Miller LD; Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, NC, USA.; Atrium Health Wake Forest Baptist Comprehensive Cancer Center, Winston-Salem, NC, USA., Monaco G; BIOGEM Institute of Molecular Biology and Genetics, Via Camporeale, Ariano Irpino, Italy., Hendrickx WRL; Human Immunology Department, Sidra Medicine, P.O. Box 26999, Doha, Qatar.; College of Health and Life Sciences, Hamad Bin Khalifa University, P.O. Box 26999, Doha, Qatar., Sherif S; Human Immunology Department, Sidra Medicine, P.O. Box 26999, Doha, Qatar.; College of Health and Life Sciences, Hamad Bin Khalifa University, P.O. Box 26999, Doha, Qatar., Yang L; Dana-Farber Cancer Institute, Boston, MA, USA., Tang M; Dana-Farber Cancer Institute, Boston, MA, USA., Gu SS; Dana-Farber Cancer Institute, Boston, MA, USA., Zhang W; Dana-Farber Cancer Institute, Boston, MA, USA., Zhang Y; Dana-Farber Cancer Institute, Boston, MA, USA., Zeng Z; Dana-Farber Cancer Institute, Boston, MA, USA., Das Sahu A; Dana-Farber Cancer Institute, Boston, MA, USA., Liu Y; Dana-Farber Cancer Institute, Boston, MA, USA., Yang W; Aginome Scientific, Xiamen, China., Bedognetti D; Human Immunology Department, Sidra Medicine, P.O. Box 26999, Doha, Qatar.; College of Health and Life Sciences, Hamad Bin Khalifa University, P.O. Box 26999, Doha, Qatar.; Department of Internal Medicine and Medical Specialties, University of Genoa, Genoa, Italy., Tang J; Faculty of Medicine, Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland.; Department of Biochemistry and Developmental Biology, Faculty of Medicine, University of Helsinki, Helsinki, Finland., Eduati F; Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.; Institute for Complex Molecular Systems (ICMS), Eindhoven University of Technology, Eindhoven, The Netherlands., Laajala TD; Department of Mathematics and Statistics, University of Turku, Turku, Finland.; Department of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.; Research Program in Systems Oncology, University of Helsinki, Helsinki, Finland.; iCAN-Digital Precision Cancer Medicine Flagship, Helsinki, Finland.; FICAN West Cancer Centre, University of Turku and Turku University Hospital, Turku, Finland.; Department of Pharmacology, Anschutz Medical Campus, University of Colorado, Denver, CO, USA., Geese WJ; Bristol Myers Squibb, Princeton, NJ, USA., Guinney J; Tempus Labs, Chicago, IL, USA., Szustakowski JD; Bristol Myers Squibb, Princeton, NJ, USA., Vincent BG; Department 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., Carbone DP; The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA. david.p.carbone@gmail.com.
Jazyk: angličtina
Zdroj: Journal of translational medicine [J Transl Med] 2024 Feb 21; Vol. 22 (1), pp. 190. Date of Electronic Publication: 2024 Feb 21.
DOI: 10.1186/s12967-023-04705-3
Abstrakt: Background: Predictive biomarkers of immune checkpoint inhibitor (ICI) 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 best-performing models showed improved predictive power over reference variables, including TMB or PD-L1.
Conclusions: This DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICI 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 ICI efficacy.
Trial Registration: CheckMate 026; NCT02041533, registered January 22, 2014. CheckMate 227; NCT02477826, registered June 23, 2015.
(© 2024. The Author(s).)
Databáze: MEDLINE
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