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

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 ValenHong Zhang, Natalie Vokes, Daoud Meerzaman, Song Liu, Eliezer M. Van Allen, Yi Xing

Research output: Contribution to journal › Review article › peer-review

8 Scopus citations

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.

Original language	English
Article number	e009721
Journal	Journal for ImmunoTherapy of Cancer
Volume	12
Issue number	10
DOIs	https://doi.org/10.1136/jitc-2024-009721
State	Published - 26 Oct 2024

Keywords

Biomarker
Education
Immune related adverse event - irAE
Immunotherapy
Statistics

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10.1136/jitc-2024-009721

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Bao, R., Hutson, A., Madabhushi, A., Jonsson, V. D., Rosario, S. R., Barnholtz-Sloan, J. S., Fertig, E. J., Marathe, H., Harris, L., Altreuter, J., Chen, Q., Dignam, J., Gentles, A. J., Gonzalez-Kozlova, E., Gnjatic, S., Kim, E., Long, M., Morgan, M., Ruppin, E., ... Xing, Y. (2024). Ten challenges and opportunities in computational immuno-oncology. Journal for ImmunoTherapy of Cancer, 12(10), Article e009721. https://doi.org/10.1136/jitc-2024-009721

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title = "Ten challenges and opportunities in computational immuno-oncology",

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",

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

note = "Publisher Copyright: {\textcopyright} Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.",

year = "2024",

month = oct,

day = "26",

doi = "10.1136/jitc-2024-009721",

language = "English",

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journal = "Journal for ImmunoTherapy of Cancer",

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Bao, R, Hutson, A, Madabhushi, A, Jonsson, VD, Rosario, SR, Barnholtz-Sloan, JS, Fertig, EJ, Marathe, H, Harris, L, Altreuter, J, Chen, Q, Dignam, J, Gentles, AJ, Gonzalez-Kozlova, E, Gnjatic, S, Kim, E, Long, M, Morgan, M, Ruppin, E, Valen, DV, Zhang, H, Vokes, N, Meerzaman, D, Liu, S, Van Allen, EM & Xing, Y 2024, 'Ten challenges and opportunities in computational immuno-oncology', Journal for ImmunoTherapy of Cancer, vol. 12, no. 10, e009721. https://doi.org/10.1136/jitc-2024-009721

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AU - Bao, Riyue

AU - Hutson, Alan

AU - Madabhushi, Anant

AU - Jonsson, Vanessa D.

AU - Rosario, Spencer R.

AU - Barnholtz-Sloan, Jill S.

AU - Fertig, Elana J.

AU - Marathe, Himangi

AU - Harris, Lyndsay

AU - Altreuter, Jennifer

AU - Chen, Qingrong

AU - Dignam, James

AU - Gentles, Andrew J.

AU - Gonzalez-Kozlova, Edgar

AU - Gnjatic, Sacha

AU - Kim, Erika

AU - Long, Mark

AU - Morgan, Martin

AU - Ruppin, Eytan

AU - Valen, David Van

AU - Zhang, Hong

AU - Vokes, Natalie

AU - Meerzaman, Daoud

AU - Liu, Song

AU - Van Allen, Eliezer M.

AU - Xing, Yi

PY - 2024/10/26

Y1 - 2024/10/26

N2 - 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.

AB - 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.

KW - Biomarker

KW - Education

KW - Immune related adverse event - irAE

KW - Immunotherapy

KW - Statistics

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DO - 10.1136/jitc-2024-009721

M3 - Review article

C2 - 39461879

AN - SCOPUS:85208008475

SN - 2051-1426

VL - 12

JO - Journal for ImmunoTherapy of Cancer

JF - Journal for ImmunoTherapy of Cancer

IS - 10

M1 - e009721

ER -

Ten challenges and opportunities in computational immuno-oncology

Abstract

Keywords

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