The DOI matches its Crossref record; 74 of the 74 references it cites were found in a registry or an index.
Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy
Open accessAbstract
Chromosomal chaos and tumor immunity: Cancer immunotherapy produces durable clinical responses in only a subset of patients. Identification of tumor characteristics that correlate with responses could lead to predictive biomarkers and shed light on causal mechanisms. Davoli et al. found that human tumors with extensive aneuploidy—i.e., that display a highly abnormal number of chromosomes and chromosomal segments—express fewer markers of the immune cells responsible for tumor destruction. In a retrospective analysis of clinical trial data, they found that melanoma patients with highly aneuploid tumors were less likely to benefit from immune checkpoint blockade therapy than patients whose tumors had a more normal karyotype. Thus, aneuploidy appears to enhance the ability of tumors to evade the immune system. Science , this issue p. 10.1126/science.aaf8399
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
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482
Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp616 · Cited by 41,364
PD-1 and PD-L1 Immune Checkpoint Blockade to Treat Breast Cancer
Hartkopf, A. D., Taran, F.-A., Wallwiener, M., Walter, C. B., Krämer, B., Grischke, E.-M., & Brucker, S. Y. (2016) · Breast Care · doi:10.1159/000453569 · Cited by 30,845
Regularization and Variable Selection Via the Elastic Net
Zou, H., & Hastie, T. (2005) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2005.00503.x · Cited by 20,957
Regularization Paths for Generalized Linear Models via Coordinate Descent
Friedman, J., Hastie, T., & Tibshirani, R. (2010) · Journal of Statistical Software · doi:10.18637/jss.v033.i01 · Cited by 19,927
The blockade of immune checkpoints in cancer immunotherapy
Pardoll, D. M. (2012) · Nature Reviews Cancer · doi:10.1038/nrc3239 · Cited by 13,838
pROC: an open-source package for R and S+ to analyze and compare ROC curves
Robin, X., Turck, N., Hainard, A., Tiberti, N., Lisacek, F., Sanchez, J.-C., & Müller, M. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-77 · Cited by 13,697
Robust enumeration of cell subsets from tissue expression profiles
Newman, A. M., Liu, C. L., Green, M. R., Gentles, A. J., Feng, W., Xu, Y., Hoang, C. D., Diehn, M., & Alizadeh, A. A. (2015) · Nature Methods · doi:10.1038/nmeth.3337 · Cited by 13,224
A method and server for predicting damaging missense mutations.
Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., Kondrashov, A. S., & Sunyaev, S. R. (2010) · Nature Methods · doi:10.1038/nmeth0410-248 · Cited by 13,194
Mutational landscape determines sensitivity to PD-1 blockade in non–small cell lung cancer
Rizvi, N. A., Hellmann, M. D., Snyder, A., Kvistborg, P., Makarov, V., Havel, J. J., Lee, W., Yuan, J., Wong, P., Ho, T. S., et al. (2015) · Science · doi:10.1126/science.aaa1348 · Cited by 7,802
Cited by
Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response
Jiang, P., Gu, S., Pan, D., Fu, J., Sahu, A., Hu, X., Li, Z., Traugh, N., Bu, X., Li, B., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0136-1 · Cited by 5,179
Approaches to treat immune hot, altered and cold tumours with combination immunotherapies
Galon, J., & Bruni, D. (2019) · Nature Reviews Drug Discovery · doi:10.1038/s41573-018-0007-y · Cited by 3,409
Chen, Y.-P., Chan, A. T. C., Le, Q.-T., Blanchard, P., Sun, Y., & Ma, J. (2019) · The Lancet · doi:10.1016/s0140-6736(19)30956-0 · Cited by 3,077
Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab
Riaz, N., Havel, J. J., Makarov, V., Desrichard, A., Urba, W. J., Sims, J. S., Hodi, F. S., Martín-Algarra, S., Mandal, R., Sharfman, W. H., et al. (2017) · Cell · doi:10.1016/j.cell.2017.09.028 · Cited by 2,401
The immune contexture in cancer prognosis and treatment
Fridman, W. H., Zitvogel, L., Sautès–Fridman, C., & Kroemer, G. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2017.101 · Cited by 2,263
Metadata
- Authors
- Davoli, T., Uno, H., Wooten, E. C., & Elledge, S. J.
- Venue
- Science
- Published
- 2017-01-20
- Volume
- 355
- Issue
- 6322
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2574604975
- Cited by
- 1,360
- References
- 74
- FWCI
- 46.10
- Type
- journal article
- Language
- en
- Open access
- green
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: Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy. https://app.cochat.ai/papers/10.1126/science.aaf8399
- The paper
- Davoli, T., Uno, H., Wooten, E. C., & Elledge, S. J. (2017). Tumor aneuploidy correlates with markers of immune evasion and with reduced response to immunotherapy. Science. https://doi.org/10.1126/science.aaf8399
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.
