The DOI matches its Crossref record; 89 of the 89 references it cites were found in a registry or an index.
Adenosine Metabolism: Emerging Concepts for Cancer Therapy
Open accessAbstract
Summary Adenosine is a key metabolic and immune checkpoint regulator implicated in the tumor escape from the host immune system. Major gaps in knowledge that impede the development of effective adenosine-based therapeutics include: (1) Lack of consideration of redundant pathways controlling ATP and adenosine levels; (2) lack of distinction between receptor-dependent and - independent effects of adenosine, and (3) focus on extracellular adenosine without consideration of intracellular metabolism and compartmentalization. In light of current clinical trials, we provide an overview of adenosine metabolism and point out the need for a more careful evaluation of the entire purinome in emerging cancer therapies.
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
Receptors for Purines and Pyrimidines
Burnstock, G., & Verkhratsky, A. (2012) · Purinergic Signalling and the Nervous System · doi:10.1007/978-3-642-28863-0_5 · Cited by 3,958
On Respiratory Impairment in Cancer Cells
Warburg, O. (1956) · Science · doi:10.1126/science.124.3215.269 · Cited by 3,468
Defining T Cell States Associated with Response to Checkpoint Immunotherapy in Melanoma
Sade-Feldman, M., Yizhak, K., Bjorgaard, S. L., Ray, J. P., de Boer, C. G., Jenkins, R. W., Lieb, D. J., Chen, J. H., Frederick, D. T., Barzily-Rokni, M., et al. (2018) · Cell · doi:10.1016/j.cell.2018.10.038 · Cited by 2,053
Cancer metabolism: a therapeutic perspective
Martinez-Outschoorn, U. E., Peiris-Pagés, M., Pestell, R. G., Sotgia, F., & Lisanti, M. P. (2017) · Nature Reviews Clinical Oncology · doi:10.1038/nrclinonc.2016.60 · Cited by 1,505
Autophagy-Dependent Anticancer Immune Responses Induced by Chemotherapeutic Agents in Mice
Michaud, M., Martins, I., Sukkurwala, A. Q., Adjemian, S., Ma, Y., Pellegatti, P., Shen, S., Kepp, O., Scoazec, M., Mignot, G., et al. (2011) · Science · doi:10.1126/science.1208347 · Cited by 1,377
Bystander CD8+ T cells are abundant and phenotypically distinct in human tumour infiltrates
Simoni, Y., Becht, E., Fehlings, M., Loh, C. Y., Koo, S.-L., Teng, K. W. W., Yeong, J. P. S., Nahar, R., Zhang, T., Kared, H., et al. (2018) · Nature · doi:10.1038/s41586-018-0130-2 · Cited by 1,370
Ohta, A., & Sitkovsky, M. (2001) · Nature · doi:10.1038/414916a · Cited by 1,334
Combination cancer immunotherapy and new immunomodulatory targets
Mahoney, K. M., Rennert, P. D., & Freeman, G. J. (2015) · Nature Reviews Drug Discovery · doi:10.1038/nrd4591 · Cited by 1,294
Yegutkin, G. G. (2008) · Biochimica et Biophysica Acta (BBA) - Molecular Cell Research · doi:10.1016/j.bbamcr.2008.01.024 · Cited by 1,154
Self-citationA2A adenosine receptor protects tumors from antitumor T cells
Ohta, A., Gorelik, E., Prasad, S. J., Ronchese, F., Lukashev, D., Wong, M. K. K., Huang, X., Caldwell, S., Liu, K., Smith, P., et al. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605251103 · Cited by 1,065
Cited by
Unveiling the mechanisms and challenges of cancer drug resistance
Khan, S. U., Fatima, K., Aisha, S., & Malik, F. (2024) · Cell Communication and Signaling · doi:10.1186/s12964-023-01302-1 · Cited by 417
CD39/CD73/A2AR pathway and cancer immunotherapy
Xia, C., Yin, S., To, K. K. W., & Fu, L. (2023) · Molecular Cancer · doi:10.1186/s12943-023-01733-x · Cited by 399
Moesta, A. K., Li, X.-Y., & Smyth, M. J. (2020) · Nature Reviews Immunology · doi:10.1038/s41577-020-0376-4 · Cited by 322
Hypoxia drives CD39-dependent suppressor function in exhausted T cells to limit antitumor immunity
Vignali, P. D. A., DePeaux, K., Watson, M. J., Ye, C., Ford, B. R., Lontos, K., McGaa, N. K., Scharping, N. E., Menk, A. V., Robson, S. C., et al. (2023) · Nature Immunology · doi:10.1038/s41590-022-01379-9 · Cited by 269
Astrocytes in the initiation and progression of epilepsy
Vezzani, A., Ravizza, T., Bedner, P., Aronica, E., Steinhäuser, C., & Boison, D. (2022) · Nature Reviews Neurology · doi:10.1038/s41582-022-00727-5 · Cited by 272
Self-citation
Metadata
- Authors
- Boison, D., & Yegutkin, G. G.
- Venue
- Cancer Cell
- Publisher
- Elsevier BV
- Published
- 2019-12
- Volume
- 36
- Issue
- 6
- Pages
- 582-596
- ISSN
- 1535-6108 (ISSN-L)
- OpenAlex
- W2994080338
- Cited by
- 336
- References
- 89
- FWCI
- 20.45
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Adenosine Metabolism: Emerging Concepts for Cancer Therapy. https://app.cochat.ai/papers/10.1016/j.ccell.2019.10.007
- The paper
- Boison, D., & Yegutkin, G. G. (2019). Adenosine Metabolism: Emerging Concepts for Cancer Therapy. Cancer Cell. https://doi.org/10.1016/j.ccell.2019.10.007
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.
