Assessing the interactions between radiotherapy and antitumour immunity
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Immunotherapy, specifically the introduction of immune checkpoint inhibitors, has transformed the treatment of cancer, enabling long-term tumour control even in individuals with advanced-stage disease. Unfortunately, only a small subset of patients show a response to currently available immunotherapies. Despite a growing consensus that combining immune checkpoint inhibitors with radiotherapy can increase response rates, this approach might be limited by the development of persistent radiation-induced immunosuppression. The ultimate goal of combining immunotherapy with radiotherapy is to induce a shift from an ineffective, pre-existing immune response to a long-lasting, therapy-induced immune response at all sites of disease. To achieve this goal and enable the adaptation and monitoring of individualized treatment approaches, assessment of the dynamic changes in the immune system at the patient level is essential. In this Review, we summarize the available clinical data, including forthcoming methods to assess the immune response to radiotherapy at the patient level, ranging from serum biomarkers to imaging techniques that enable investigation of immune cell dynamics in patients. Furthermore, we discuss modelling approaches that have been developed to predict the interaction of immunotherapy with radiotherapy, and highlight how they could be combined with biomarkers of antitumour immunity to optimize radiotherapy regimens and maximize their synergy with immunotherapy.
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Radiotherapy in combination with immunotherapy can maximize the antitumor immune response and promote durable disease control.
“In combination with immunotherapy, radiotherapy can maximize the antitumor immune response and promote durable disease control16,17.”
From Gut microbiome diversity is an independent predictor of survival in cervical cancer patients receiving chemoradiation (2021) · cites this paper as [17]
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- Authors
- Grassberger, C., Ellsworth, S. G., Wilks, M. Q., Keane, F. K., & Loeffler, J. S.
- Affiliations
- Harvard University (US)
- Indiana University School of Medicine (US)
- Gordon Center for Medical Imaging (US)
- Corresponding author
- Grassberger, Clemens
- Venue
- Nature Reviews Clinical Oncology
- Published
- 2019-06-26
- Volume
- 16
- Issue
- 12
- Pages
- 729-745
- ISSN
- 1759-4774 (ISSN-L)
- 1759-4782
- PMC
- PMC13492067
- OpenAlex
- W2954542121
- Cited by
- 244
- References
- 216
- Citations by year
- 2026: 14 · 2025: 26 · 2024: 25 · 2023: 45 · 2022: 53 · 2021: 36 · 2020: 40 · 2019: 5
- FWCI
- 3.19
- Type
- journal article
- Language
- en
- Open access
- green
- pmc.ncbi.nlm.nih.gov
- Locations
- Nature Reviews Clinical Oncology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion)
- Funders
- Massachusetts General Hospital
- National Cancer Institute (R21CA241918, P01CA021239)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Life Sciences › Immunology and Microbiology › Immunology › Immunotherapy and Immune Responses
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Keywords
- radiotherapy, antitumor immunity, immune checkpoint inhibitors, radiation-induced immunosuppression, immune response assessment, serum biomarkers, immune cell imaging, personalized radiotherapy, predictive biomarkers
- MeSH terms
- Combined Modality Therapy, Humans, Immune System, Immunotherapy, Neoplasms, Radiotherapy, Precision Medicine
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