MANIFEST: Multiomic Platform for Cancer Immunotherapy

Immunotherapy has revolutionized survival outcomes for many patients diagnosed with cancer. However, biomarkers that can reliably distinguish treatment responders from nonresponders, predict potential life-threatening and life-changing drug-induced toxicities, or rationalize treatment choices are still lacking. In response to this unmet clinical need, we introduce Multiomic ANalysis of Immunotherapy Features Evidencing Success and Toxicity, a tumor type-agnostic platform to provide deep profiling of patients receiving immunotherapy that will enable integrative identification of biomarkers and discovery of novel targets using artificial intelligence and machine learning.

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Publication Details

Journal
Cancer Discovery
Published
2025-05-02
DOI
https://doi.org/10.1158/2159-8290.cd-25-0099
Citations
5
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
4.03
Controls
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article

MANIFEST: Multiomic Platform for Cancer Immunotherapy

Darren Treanor, Corinne Faivre‐Finn, Kairbaan Hodivala‐Dilke, Javier A. Alfaro et al.
5 citations
Cancer Discovery
vaccines and immunoinformatics approaches
4.03
article

MANIFEST: Multiomic Platform for Cancer Immunotherapy

Darren Treanor, Corinne Faivre‐Finn, Kairbaan Hodivala‐Dilke, Javier A. Alfaro, Bristi Basu, Inês Sequeira, Fiona Thistlethwaite, Matthew P. Humphries, Andrew Riddell, Michael Hubank, Santiago Zelenay, Emma Nye, Christopher R. S. Banerji, Trevor A. Graham, Benny Chain, Caroline Dive, Fiona Collinson, Samra Turajlic, Ananya Choudhury, Trevor D. Lawley, Manuel Salto‐Tellez, Robert Anthony Huddart, Christina Messiou, Stefan N. Symeonides, Andrew J.S. Furness, Naveen Vasudev, Gavin Kelly, Anne Caroline Armstrong, Will Ince, George Kassiotis, Bernadett Szabados, Nicholas C. Turner, Pippa Corrie, Peter Schmid, James O. Jones, Brent O’Carrigan, Juanita Suzanne Lopez, Jennifer Hay, Alicia Okines, Xiao Fu, Florent Moulière, Paul C. Lorigan, Alan A. Melcher, Natalie Cook, Dimitris Lagos, Kathryn Simpson, Karen Ambrose, James Larkin, Ajitha Rajan, Jean‐Baptiste Cazier, Grant Duncan Stewart, Kok Haw Jonathan Lim, Mark Stares, Zayd Tippu, Alexander Laird, Peter E. Hall, Véronique Birault, Thomas B. Powles, Rebecca Lee, Ali Raza, Pedro Oliveira, David J. Harrison, Tom Waddell, Stuart McDonald, Amy Strange, J.D.B. De Bono, Jyoti Choudhary, Christopher Twelves, James W. Fleming, T. Chakraborty, Brandon Witcher
article en
5 citations

Abstract

Immunotherapy has revolutionized survival outcomes for many patients diagnosed with cancer. However, biomarkers that can reliably distinguish treatment responders from nonresponders, predict potential life-threatening and life-changing drug-induced toxicities, or rationalize treatment choices are still lacking. In response to this unmet clinical need, we introduce Multiomic ANalysis of Immunotherapy Features Evidencing Success and Toxicity, a tumor type-agnostic platform to provide deep profiling of patients receiving immunotherapy that will enable integrative identification of biomarkers and discovery of novel targets using artificial intelligence and machine learning.

Cancer DiscoveryVol. 15(5)
Queen's University Belfast (GB), NHS Lothian (GB), Royal Marsden NHS Foundation Trust (GB), Institute of Cancer Research (GB), Queen Mary University of London (GB), University of Cambridge (GB), Manchester Academic Health Science Centre (GB), Breast Cancer Now (GB), The Francis Crick Institute (GB), Cambridge University Hospitals NHS Foundation Trust (GB), Wellcome Sanger Institute (GB), Edinburgh Cancer Research (GB), University of Manchester (GB), Cambridge School (PT), Bridge University (SS), Space Research Institute (UA), AMS (United Kingdom) (GB), Cancer Research UK Manchester Institute (GB), The Christie NHS Foundation Trust (GB), Genomics England (GB), Centre for Inflammation Research (GB), National Computing Centre (United Kingdom) (GB), University of Edinburgh (GB)
Good health and well-being
Openalex Percentile: Top 6%
vaccines and immunoinformatics approaches
4.03
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