The DOI matches its Crossref record; 140 of the 140 references it cites were found in a registry or an index.
The PI3K-Akt-mTOR Signaling Pathway in Human Acute Myeloid Leukemia (AML) Cells
Open accessAbstract
Acute myeloid leukemia (AML) is a heterogeneous group of diseases characterized by uncontrolled proliferation of hematopoietic stem cells in the bone marrow. Malignant cell growth is characterized by disruption of normal intracellular signaling, caused by mutations or aberrant external signaling. The phosphoinositide 3-kinase (PI3K)-Akt-mammalian target of rapamycin (mTOR) pathway (PI3K-Akt-mTOR pathway) is among one of the intracellular pathways aberrantly upregulated in cancers including AML. Activation of this pathway seems important in leukemogenesis, and given the central role of this pathway in metabolism, the bioenergetics of AML cells may depend on downstream signaling within this pathway. Furthermore, observations suggest that constitutive activation of the PI3K-Akt-mTOR pathway differs between patients, and that increased activity within this pathway is an adverse prognostic parameter in AML. Pharmacological targeting of the PI3K-Akt-mTOR pathway with specific inhibitors results in suppression of leukemic cell growth. However, AML patients seem to differ regarding their susceptibility to various small-molecule inhibitors, reflecting biological heterogeneity in the intracellular signaling status. These findings should be further investigated in both preclinical and clinical settings, along with the potential use of this pathway as a prognostic biomarker, both in patients receiving intensive curative AML treatment and in elderly/unfit receiving AML-stabilizing treatment.
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
Hallmarks of Cancer: The Next Generation
Hanahan, D., & Weinberg, R. A. (2011) · Cell · doi:10.1016/j.cell.2011.02.013 · Cited by 66,590
Hanahan, D., & Weinberg, R. A. (2000) · Cell · doi:10.1016/s0092-8674(00)81683-9 · Cited by 29,219
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
Arber, D. A., Orazi, A., Hasserjian, R., Thiele, J., Borowitz, M. J., Le Beau, M. M., Bloomfield, C. D., Cazzola, M., & Vardiman, J. W. (2016) · Blood · doi:10.1182/blood-2016-03-643544 · Cited by 10,119
mTOR Signaling in Growth, Metabolism, and Disease
Saxton, R. A., & Sabatini, D. M. (2017) · Cell · doi:10.1016/j.cell.2017.02.004 · Cited by 7,555
AKT/PKB signaling: navigating downstream
Manning, B. D., & Cantley, L. C. (2007) · Cell · doi:10.1016/j.cell.2007.06.009 · Cited by 6,115
Bonnet, D., & Dick, J. E. (1997) · Nature Medicine · doi:10.1038/nm0797-730 · Cited by 5,864
Döhner, H., Estey, E., Grimwade, D., Amadori, S., Appelbaum, F. R., Büchner, T., Dombret, H., Ebert, B. L., Fenaux, P., Larson, R. A., et al. (2017) · Blood · doi:10.1182/blood-2016-08-733196 · Cited by 5,775
Genomic and Epigenomic Landscapes of Adult De Novo Acute Myeloid Leukemia
The Cancer Genome Atlas Research Network (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1301689 · Cited by 5,078
Mutational landscape and significance across 12 major cancer types
Kandoth, C., McLellan, M. D., Vandin, F., Ye, K., Niu, B., Lu, C., Xie, M., Zhang, Q., McMichael, J. F., Wyczalkowski, M. A., et al. (2013) · Nature · doi:10.1038/nature12634 · Cited by 4,419
Cited by
Sanz, M. A., Fenaux, P., Tallman, M. S., Estey, E. H., Löwenberg, B., Naoe, T., Lengfelder, E., Döhner, H., Burnett, A. K., Chen, S.-J., et al. (2019) · Blood · doi:10.1182/blood-2019-01-894980 · Cited by 664
The role of PD-1/PD-L1 and application of immune-checkpoint inhibitors in human cancers
Tang, Q., Chen, Y., Li, X., Long, S., Shi, Y., Yu, Y., Wu, W., Han, L., & Wang, S. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.964442 · Cited by 561
Metadata
- Authors
- Nepstad, I., Hatfield, K. J., Grønningsæter, I. S., & Reikvam, H.
- Venue
- International Journal of Molecular Sciences
- Publisher
- MDPI AG
- Published
- 2020-04-21
- Volume
- 21
- Issue
- 8
- Pages
- 2907
- ISSN
- 1422-0067 (ISSN-L)
- OpenAlex
- W3020803734
- Cited by
- 348
- References
- 140
- FWCI
- 12.59
- Type
- journal article
- Language
- en
- Open access
- gold
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 PI3K-Akt-mTOR Signaling Pathway in Human Acute Myeloid Leukemia (AML) Cells. https://app.cochat.ai/papers/10.3390/ijms21082907
- The paper
- Nepstad, I., Hatfield, K. J., Grønningsæter, I. S., & Reikvam, H. (2020). The PI3K-Akt-mTOR Signaling Pathway in Human Acute Myeloid Leukemia (AML) Cells. International Journal of Molecular Sciences. https://doi.org/10.3390/ijms21082907
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.