Journal for ImmunoTherapy of Cancer (Oct 2024)
Ten challenges and opportunities in computational immuno-oncology
- Hong Zhang,
- Riyue Bao,
- Song Liu,
- Mark Long,
- Sacha Gnjatic,
- Yi Xing,
- Elana J Fertig,
- Alan Hutson,
- Martin Morgan,
- Eytan Ruppin,
- Anant Madabhushi,
- Natalie Vokes,
- Daoud Meerzaman,
- Edgar Gonzalez-Kozlova,
- Vanessa D Jonsson,
- Eliezer M Van Allen,
- Spencer R Rosario,
- Jennifer Altreuter,
- Himangi Marathe,
- Jill S Barnholtz-Sloan,
- Lyndsay Harris,
- Qingrong Chen,
- James Dignam,
- Andrew J Gentles,
- Erika Kim,
- David Van Valen
Affiliations
- Hong Zhang
- 11 Institute of Cardiovascular Sciences and Key Laboratory of Molecular Cardiovascular Sciences, Peking University Health Science Centre, Beijing, China
- Riyue Bao
- 1 UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Song Liu
- 3 Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, New York, USA
- Mark Long
- 3 Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, New York, USA
- Sacha Gnjatic
- 19 Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Yi Xing
- 33 Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Elana J Fertig
- 11 Department of Oncology, Johns Hopkins University, Baltimore, Maryland, USA
- Alan Hutson
- 3 Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, New York, USA
- Martin Morgan
- 3 Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, New York, USA
- Eytan Ruppin
- 23 Cancer Data Science Laboratory, National Cancer Institute, Bethesda, Maryland, USA
- Anant Madabhushi
- 6 Atlanta Veterans Affairs Medical Center, Atlanta, Georgia, USA
- Natalie Vokes
- 26 Department of Thoracic and Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- Daoud Meerzaman
- 16 Center for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, Maryland, USA
- Edgar Gonzalez-Kozlova
- 19 Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Vanessa D Jonsson
- 7 Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, USA
- Eliezer M Van Allen
- 31 Cancer Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Spencer R Rosario
- 3 Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, New York, USA
- Jennifer Altreuter
- 15 Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Himangi Marathe
- 3 Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, New York, USA
- Jill S Barnholtz-Sloan
- 9 Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
- Lyndsay Harris
- 14 Cancer Diagnosis Program, National Cancer Institute Division of Cancer Treatment and Diagnosis, Bethesda, Maryland, USA
- Qingrong Chen
- 16 Center for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, Maryland, USA
- James Dignam
- 17 Department of Public Health Sciences, University of Chicago Division of the Biological Sciences, Chicago, Illinois, USA
- Andrew J Gentles
- 18 Department of Pathology, Stanford University, Stanford, California, USA
- Erika Kim
- 22 Informatics and Data Science Program, Center for Biomedical Informatics and Information Technology, National Cancer Institute, Bethesda, Maryland, USA
- David Van Valen
- 24 Division of Computing and Mathematical Science, Caltech, Pasadena, California, USA
- DOI
- https://doi.org/10.1136/jitc-2024-009721
- Journal volume & issue
-
Vol. 12,
no. 10
Abstract
Immuno-oncology has transformed the treatment of cancer, with several immunotherapies becoming the standard treatment across histologies. Despite these advancements, the majority of patients do not experience durable clinical benefits, highlighting the imperative for ongoing advancement in immuno-oncology. Computational immuno-oncology emerges as a forefront discipline that draws on biomedical data science and intersects with oncology, immunology, and clinical research, with the overarching goal to accelerate the development of effective and safe immuno-oncology treatments from the laboratory to the clinic. In this review, we outline 10 critical challenges and opportunities in computational immuno-oncology, emphasizing the importance of robust computational strategies and interdisciplinary collaborations amid the constantly evolving interplay between clinical needs and technological innovation.
