The DOI matches its Crossref record; 261 of the 261 references it cites were found in a registry or an index.
Targeting glucose metabolism to suppress cancer progression: prospective of anti-glycolytic cancer therapy
Abstract
Most solid tumor cells adapt to their heterogeneous microenvironment by depending largely on aerobic glycolysis for energy production, a phenomenon called the Warburg effect, which is a hallmark of cancer. The altered energy metabolism not only provides cancer cell with ATP for cellular energy, but also generate essential metabolic intermediates that play a pivotal role in the biosynthesis of macromolecules, to support cell proliferation, invasiveness, and chemoresistance. The cellular metabolic reprogramming in cancer is regulated by several oncogenic proteins and tumor suppressors such as hypoxia-inducible factor (HIF-1), Myc, p53, and PI3K/Akt/mTOR pathway. A better understanding of the mechanisms involved in the regulation of aerobic glycolysis can help in developing glycolytic inhibitors as anticancer agents. These metabolic antiglycolytic agents could be more effective if used in drug combinations to combat cancer. Several preclinical and early clinical studies have shown the effectiveness of targeting the glycolytic pathway as a therapeutic approach to suppress cancer progression. This review aimed to present the most recent data on the emerging drug candidate targeting enzymes and intermediates involved in glucose metabolism to provide therapeutic opportunities and challenges for antiglycolytic cancer therapy.
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
1 retracted
He, T., Zhang, Y.-J., Jiang, H., Li, X.-H., Zhu, H., & Zheng, K.-L. (2015) · Medical Oncology · doi:10.1007/s12032-015-0633-8 · Cited by 130
RetractedBray, F., Ferlay, J., Soerjomataram, I., Siegel, R. L., Torre, L. A., & Jemal, A. (2018) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21492 · Cited by 84,109
Understanding the Warburg Effect: The Metabolic Requirements of Cell Proliferation
Vander Heiden, M. G., Cantley, L. C., & Thompson, C. B. (2009) · Science · doi:10.1126/science.1160809 · Cited by 16,197
Warburg, O. (1956) · Science · doi:10.1126/science.123.3191.309 · Cited by 13,425
The basics of epithelial-mesenchymal transition
Kalluri, R., & Weinberg, R. A. (2009) · Journal of Clinical Investigation · doi:10.1172/jci39104 · Cited by 10,196
Phosphorylation and regulation of Akt/PKB by the rictor-mTOR complex
Sarbassov, D. D., Guertin, D. A., Ali, S. M., & Sabatini, D. M. (2005) · Science · doi:10.1126/science.1106148 · Cited by 6,216
The tumour suppressor protein VHL targets hypoxia-inducible factors for oxygen-dependent proteolysis
Maxwell, P. H., Wiesener, M. S., Chang, G.-W., Clifford, S. C., Vaux, E. C., Cockman, M. E., Wykoff, C. C., Pugh, C. W., Maher, E. R., & Ratcliffe, P. J. (1999) · Nature · doi:10.1038/20459 · Cited by 5,180
Why Do Cancers Have High Aerobic Glycolysis?
Gatenby, R. A., & Gillies, R. J. (2004) · Nature reviews. Cancer · doi:10.1038/nrc1478 · Cited by 4,784
Kim, J.-W., Tchernyshyov, I., Semenza, G. L., & Dang, C. V. (2006) · Cell Metabolism · doi:10.1016/j.cmet.2006.02.002 · Cited by 3,905
Genomic analyses identify molecular subtypes of pancreatic cancer
Bailey, P., Chang, D. K., Nones, K., Johns, A. L., Patch, A.-M., Gingras, M.-C., Miller, D. K., Christ, A. N., Bruxner, T. J. C., Quinn, M. C., et al. (2016) · Nature · doi:10.1038/nature16965 · Cited by 3,621
Cited by
Altered metabolism in cancer: insights into energy pathways and therapeutic targets
Tufail, M., Jiang, C.-H., & Li, N. (2024) · Molecular Cancer · doi:10.1186/s12943-024-02119-3 · Cited by 534
Signaling pathways in cancer metabolism: mechanisms and therapeutic targets
You, M., Xie, Z., Zhang, N., Zhang, Y., Xiao, D., Liu, S., Zhuang, W., Li, L., & Tao, Y. (2023) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-023-01442-3 · Cited by 292
The mechanism of Warburg effect-induced chemoresistance in cancer
Liu, C., Jin, Y., & Fan, Z. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.698023 · Cited by 177
Kao, T.-W., Bai, G.-H., Wang, T.-L., Shih, I.-M., Chuang, C.-M., Lo, C.-L., Tsai, M.-C., Chiu, L.-Y., Lin, C.-C., & Shen, Y.-A. (2023) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-023-02724-y · Cited by 89
Linking Metabolic Reprogramming, Plasticity and Tumor Progression
Shuvalov, O., Daks, A., Fedorova, O., Petukhov, A., & Barlev, N. (2021) · Cancers · doi:10.3390/cancers13040762 · Cited by 63
Metadata
- Authors
- Abdel-Wahab, A. F., Mahmoud, W., & Al-Harizy, R. M.
- Venue
- Pharmacological Research
- Publisher
- Elsevier BV
- Published
- 2019-12
- Volume
- 150
- Pages
- 104511
- ISSN
- 1043-6618 (ISSN-L)
- OpenAlex
- W2985781565
- Cited by
- 591
- References
- 261
- FWCI
- 14.38
- Type
- journal article
- Language
- en
- Open access
- closed
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: Targeting glucose metabolism to suppress cancer progression: prospective of anti-glycolytic cancer therapy. https://app.cochat.ai/papers/10.1016/j.phrs.2019.104511
- The paper
- Abdel-Wahab, A. F., Mahmoud, W., & Al-Harizy, R. M. (2019). Targeting glucose metabolism to suppress cancer progression: prospective of anti-glycolytic cancer therapy. Pharmacological Research. https://doi.org/10.1016/j.phrs.2019.104511
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.