Ten challenges and opportunities in computational immuno-oncology

Riyue Bao; Alan Hutson; Anant Madabhushi; Vanessa D Jonsson; Spencer R Rosario; Jill S Barnholtz-Sloan; Elana J Fertig; Himangi Marathe; Lyndsay Harris; Jennifer Altreuter; Qingrong Chen; James Dignam; Andrew J Gentles; Edgar Gonzalez-Kozlova; Sacha Gnjatic; Erika Kim; Mark Long; Martin Morgan; Eytan Ruppin; David Van Valen; Hong Zhang; Natalie Vokes; Daoud Meerzaman; Song Liu; Eliezer M Van Allen; Yi Xing

doi:10.1136/jitc-2024-009721

Ten challenges and opportunities in computational immuno-oncology

J Immunother Cancer. 2024 Oct 26;12(10):e009721. doi: 10.1136/jitc-2024-009721.

Authors

Riyue Bao^#^{1

2}, Alan Hutson^#³, Anant Madabhushi^#^{4

5

6}, Vanessa D Jonsson^#^{7

8}, Spencer R Rosario^#⁹, Jill S Barnholtz-Sloan^#^{10

11}, Elana J Fertig^#^{12

13

14}, Himangi Marathe⁹, Lyndsay Harris¹⁵, Jennifer Altreuter¹⁶, Qingrong Chen¹⁷, James Dignam¹⁸, Andrew J Gentles¹⁹, Edgar Gonzalez-Kozlova^{20

21

22}, Sacha Gnjatic^{20

21

22}, Erika Kim²³, Mark Long⁹, Martin Morgan⁹, Eytan Ruppin²⁴, David Van Valen^{25

26}, Hong Zhang⁹, Natalie Vokes^{27

28}, Daoud Meerzaman²⁹, Song Liu³, Eliezer M Van Allen^{30

31

32

33}, Yi Xing^{34

35

36}

Affiliations

¹ UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected].
² Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
³ Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, New York, USA [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected].
⁴ Emory University, Atlanta, Georgia, USA [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected].
⁵ Georgia Institute of Technology, Atlanta, Georgia, USA.
⁶ Atlanta Veterans Affairs Medical Center, Atlanta, Georgia, USA.
⁷ Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, California, USA.
⁸ Genomics Institute, University of California Santa Cruz, Santa Cruz, California, USA.
⁹ Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, New York, USA.
¹⁰ Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.
¹¹ Center for Biomedical Informatics & Information Technology, National Cancer Institute, Bethesda, Maryland, USA.
¹² Department of Oncology, Johns Hopkins University, Baltimore, Maryland, USA.
¹³ Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.
¹⁴ Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Maryland, USA.
¹⁵ Cancer Diagnosis Program, National Cancer Institute Division of Cancer Treatment and Diagnosis, Bethesda, Maryland, USA.
¹⁶ Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
¹⁷ Center for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, Maryland, USA.
¹⁸ Department of Public Health Sciences, University of Chicago Division of the Biological Sciences, Chicago, Illinois, USA.
¹⁹ Department of Pathology, Stanford University, Stanford, California, USA.
²⁰ Precision Immunology Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
²¹ Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
²² Department of Immunology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
²³ Informatics and Data Science Program, Center for Biomedical Informatics and Information Technology, National Cancer Institute, Bethesda, Maryland, USA.
²⁴ Cancer Data Science Laboratory, National Cancer Institute, Bethesda, Maryland, USA.
²⁵ Division of Computing and Mathematical Science, Caltech, Pasadena, California, USA.
²⁶ Howard Hughes Medical Institute, Chevy Chase, Maryland, USA.
²⁷ Department of Thoracic and Head and Neck Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
²⁸ Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
²⁹ Center for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, Maryland, USA [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected].
³⁰ Harvard Medical School, Boston, Massachusetts, USA [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected].
³¹ Division of Population Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
³² Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
³³ Cancer Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
³⁴ Center for Computational and Genomic Medicine, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA [email protected] [email protected] [email protected] [email protected] [email protected] [email protected] [email protected].
³⁵ Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
³⁶ Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.

^# Contributed equally.

PMID: 39461879
DOI: 10.1136/jitc-2024-009721

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.

Keywords: Biomarker; Education; Immune related adverse event - irAE; Immunotherapy; Statistics.

Publication types

Review

MeSH terms

Computational Biology / methods
Humans
Immunotherapy* / methods
Medical Oncology* / methods
Neoplasms* / immunology
Neoplasms* / therapy