The DOI matches its Crossref record; 145 of the 145 references it cites were found in a registry or an index.
The cancer-immunity cycle: Indication, genotype, and immunotype
Open accessAbstract
The cancer-immunity cycle provides a framework to understand the series of events that generate anti-cancer immune responses. It emphasizes the iterative nature of the response where the killing of tumor cells by T cells initiates subsequent rounds of antigen presentation and T cell stimulation, maintaining active immunity and adapting it to tumor evolution. Any step of the cycle can become rate-limiting, rendering the immune system unable to control tumor growth. Here, we update the cancer-immunity cycle based on the remarkable progress of the past decade. Understanding the mechanism of checkpoint inhibition has evolved, as has our view of dendritic cells in sustaining anti-tumor immunity. We additionally account for the role of the tumor microenvironment in facilitating, not just suppressing, the anti-cancer response, and discuss the importance of considering a tumor's immunological phenotype, the "immunotype". While these new insights add some complexity to the cycle, they also provide new targets for research and therapeutic intervention.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Oncology meets immunology: the cancer-immunity cycle.
Chen, D. S., & Mellman, I. (2013) · Immunity · doi:10.1016/j.immuni.2013.07.012 · Cited by 6,929
Self-citationPembrolizumab plus chemotherapy in metastatic non–small-cell lung cancer
Gandhi, L., Rodríguez-Abreu, D., Gadgeel, S., Esteban, E., Felip, E., De Angelis, F., Domine, M., Clingan, P., Hochmair, M. J., Powell, S. F., et al. (2018) · New England Journal of Medicine · doi:10.1056/nejmoa1801005 · Cited by 6,607
TGFβ attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells
Mariathasan, S., Turley, S. J., Nickles, D., Castiglioni, A., Yuen, K., Wang, Y., Kadel III, E. E., Koeppen, H., Astarita, J. L., Cubas, R., et al. (2018) · Nature · doi:10.1038/nature25501 · Cited by 5,400
Self-citationElements of cancer immunity and the cancer–immune set point
Chen, D. S., & Mellman, I. (2017) · Nature · doi:10.1038/nature21349 · Cited by 5,352
Self-citationPredictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients
Herbst, R. S., Soria, J.-C., Kowanetz, M., Fine, G. D., Hamid, O., Gordon, M. S., Sosman, J. A., McDermott, D. F., Powderly, J. D., Gettinger, S. N., et al. (2014) · Nature · doi:10.1038/nature14011 · Cited by 5,231
Self-citationMolecular and cellular insights into T cell exhaustion
Wherry, E. J., & Kurachi, M. (2015) · Nature Reviews Immunology · doi:10.1038/nri3862 · Cited by 4,652
Wherry, E. J. (2011) · Nature Immunology · doi:10.1038/ni.2035 · Cited by 4,062
A framework for advancing our understanding of cancer-associated fibroblasts
Sahai, E., Astsaturov, I., Cukierman, E., DeNardo, D. G., Egeblad, M., Evans, R. M., Fearon, D., Greten, F. R., Hingorani, S. R., Hunter, T., et al. (2020) · Nature Reviews Cancer · doi:10.1038/s41568-019-0238-1 · Cited by 3,863
Melanoma-intrinsic β-catenin signalling prevents anti-tumour immunity
Spranger, S., Bao, R., & Gajewski, T. F. (2015) · Nature · doi:10.1038/nature14404 · Cited by 2,830
B cells and tertiary lymphoid structures promote immunotherapy response
Helmink, B. A., Reddy, S. M., Gao, J., Zhang, S., Basar, R., Thakur, R., Yizhak, K., Sade-Feldman, M., Blando, J., Han, G., et al. (2020) · Nature · doi:10.1038/s41586-019-1922-8 · Cited by 2,731
Cited by
Breast cancer: pathogenesis and treatments
Xiong, X., Zheng, L.-W., Ding, Y., Chen, Y.-F., Cai, Y.-W., Wang, L.-P., Huang, L., Liu, C.-C., Shao, Z.-M., & Yu, K.-D. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-02108-4 · Cited by 958
Cancer immune evasion, immunoediting and intratumour heterogeneity
Roerden, M., & Spranger, S. (2025) · Nature Reviews Immunology · doi:10.1038/s41577-024-01111-8 · Cited by 265
Metabolic reprogramming in the tumor microenvironment of liver cancer
Lin, J., Rao, D., Zhang, M., & Gao, Q. (2024) · Journal of Hematology & Oncology · doi:10.1186/s13045-024-01527-8 · Cited by 251
“Metabolic derangements within the TME are increasingly recognized as one of the most important factors halting the CIC [94].”
BackgroundAdvances in molecular pathology and therapy of non-small cell lung cancer
Huang, Q., Li, Y., Huang, Y., Wu, J., Bao, W., Xue, C., Li, X., Dong, S., Dong, Z., & Hu, S. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-025-02243-6 · Cited by 197
Wang, H., Arulraj, T., Ippolito, A., & Popel, A. S. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01188-4 · Cited by 122
Metadata
- Authors
- Mellman, I., Chen, D. S., Powles, T., & Turley, S. J.
- Venue
- Immunity
- Publisher
- Elsevier BV
- Published
- 2023-10
- Volume
- 56
- Issue
- 10
- Pages
- 2188-2205
- ISSN
- 1074-7613 (ISSN-L)
- OpenAlex
- W4387494986
- Cited by
- 953
- References
- 145
- FWCI
- 98.77
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The cancer-immunity cycle: Indication, genotype, and immunotype. https://app.cochat.ai/papers/10.1016/j.immuni.2023.09.011
- The paper
- Mellman, I., Chen, D. S., Powles, T., & Turley, S. J. (2023). The cancer-immunity cycle: Indication, genotype, and immunotype. Immunity. https://doi.org/10.1016/j.immuni.2023.09.011
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.