The DOI matches its Crossref record; 74 of the 74 references it cites were found in a registry or an index.
Cellular Senescence Is Immunogenic and Promotes Antitumor Immunity
Open accessAbstract
Cellular senescence is a stress response that activates innate immune cells, but little is known about its interplay with the adaptive immune system. Here, we show that senescent cells combine several features that render them highly efficient in activating dendritic cells (DC) and antigen-specific CD8 T cells. This includes the release of alarmins, activation of IFN signaling, enhanced MHC class I machinery, and presentation of senescence-associated self-peptides that can activate CD8 T cells. In the context of cancer, immunization with senescent cancer cells elicits strong antitumor protection mediated by DCs and CD8 T cells. Interestingly, this protection is superior to immunization with cancer cells undergoing immunogenic cell death. Finally, the induction of senescence in human primary cancer cells also augments their ability to activate autologous antigen-specific tumor-infiltrating CD8 lymphocytes. Our study indicates that senescent cancer cells can be exploited to develop efficient and protective CD8-dependent antitumor immune responses. Significance: Our study shows that senescent cells are endowed with a high immunogenic potential—superior to the gold standard of immunogenic cell death. We harness these properties of senescent cells to trigger efficient and protective CD8-dependent antitumor immune responses. See related article by Chen et al., p. 432. This article is highlighted in the In This Issue feature, p. 247
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
STAR: ultrafast universal RNA-seq aligner
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/bts635 · Cited by 51,709
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458
Cutadapt removes adapter sequences from high-throughput sequencing reads
Martin, M. (2011) · EMBnet.journal · doi:10.14806/ej.17.1.200 · Cited by 33,889
The Molecular Signatures Database Hallmark Gene Set Collection
Liberzon, A., Birger, C., Thorvaldsdóttir, H., Ghandi, M., Mesirov, J. P., & Tamayo, P. (2015) · Cell Systems · doi:10.1016/j.cels.2015.12.004 · Cited by 13,807
Hallmarks of Cancer: New Dimensions
Hanahan, D. (2022) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-1059 · Cited by 9,887
QuPath: Open source software for digital pathology image analysis
Bankhead, P., Loughrey, M. B., Fernández, J. A., Dombrowski, Y., McArt, D. G., Dunne, P. D., McQuaid, S., Gray, R. T., Murray, L. J., Coleman, H. G., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-17204-5 · Cited by 8,908
The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidences
Perez-Riverol, Y., Bai, J., Bandla, C., García-Seisdedos, D., Hewapathirana, S., Kamatchinathan, S., Kundu, D. J., Prakash, A., Frericks-Zipper, A., Eisenacher, M., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkab1038 · Cited by 6,125
Oncogenic ras provokes premature cell senescence associated with accumulation of p53 and p16INK4a
Serrano, M., Lin, A. W., McCurrach, M. E., Beach, D., & Lowe, S. W. (1997) · Cell · doi:10.1016/s0092-8674(00)81902-9 · Cited by 5,218 · cited 1×
“Proteins were dissolved in UT buffer (8 mol/L urea, 2 mol/L thiourea, 100 mmol/L Tris– pH 8) and digested by means of the standard FASP protocol.”
MethodSelf-citationThe senescence-associated secretory phenotype: the dark side of tumor suppression
Coppé, J.-P., Desprez, P.-Y., Krtolica, A., & Campisi, J. (2010) · Annual Review of Pathology: Mechanisms of Disease · doi:10.1146/annurev-pathol-121808-102144 · Cited by 5,206
GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists
Eden, E., Navon, R., Steinfeld, I., Lipson, D., & Yakhini, Z. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-48 · Cited by 3,356
Cited by
SenNet recommendations for detecting senescent cells in different tissues
Suryadevara, V., Hudgins, A. D., Rajesh, A., Pappalardo, A., Karpova, A., Dey, A. K., Hertzel, A., Agudelo, A., Rocha, A., Soygur, B., et al. (2024) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-024-00738-8 · Cited by 408
“10,36), PDL2 and MHC class I molecules 37,38 .”
Senescence as a therapeutic target in cancer and age-related diseases
McHugh, D., Durán, I., & Gil, J. (2025) · Nature Reviews Drug Discovery · doi:10.1038/s41573-024-01074-4 · Cited by 197
Lelarge, V., Capelle, R., Oger, F., Mathieu, T., & Le Calvé, B. (2024) · npj Aging · doi:10.1038/s41514-024-00138-4 · Cited by 140
The efficacy of chemotherapy is limited by intratumoral senescent cells expressing PD-L2
Chaib, S., López-Domínguez, J. A., Lalinde-Gutiérrez, M., Prats, N., Marin, I., Boix, O., García-Garijo, A., Meyer, K., Muñoz, M. I., Aguilera, M., et al. (2024) · Nature Cancer · doi:10.1038/s43018-023-00712-x · Cited by 114
Self-citationTargeting aging and age-related diseases with vaccines
Wu, R., Sun, F., Zhang, W., Ren, J., & Liu, G.-H. (2024) · Nature Aging · doi:10.1038/s43587-024-00597-0 · Cited by 66
Metadata
- Authors
- Marin, I., Boix, O., Garcia-Garijo, A., Sirois, I., Caballe, A., Zarzuela, E., Ruano, I., Attolini, C. S.-O., Prats, N., López-Domínguez, J. A., Kovatcheva, M., Garralda, E., Muñoz, J., Caron, E., Abad, M., Gros, A., Pietrocola, F., & Serrano, M.
- Venue
- Cancer Discovery
- Published
- 2022-10-27
- Volume
- 13
- Issue
- 2
- Pages
- 410-431
- ISSN
- 2159-8274 (ISSN-L)
- 2159-8290
- OpenAlex
- W4307493936
- Cited by
- 346
- References
- 74
- FWCI
- 21.18
- 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: Cellular Senescence Is Immunogenic and Promotes Antitumor Immunity. https://app.cochat.ai/papers/10.1158/2159-8290.cd-22-0523
- The paper
- Marin, I., Boix, O., Garcia-Garijo, A., Sirois, I., Caballe, A., Zarzuela, E., Ruano, I., Attolini, C. S.-O., Prats, N., López-Domínguez, J. A., Kovatcheva, M., Garralda, E., Muñoz, J., Caron, E., Abad, M., Gros, A., Pietrocola, F., & Serrano, M. (2023). Cellular Senescence Is Immunogenic and Promotes Antitumor Immunity. Cancer Discovery. https://doi.org/10.1158/2159-8290.cd-22-0523
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.