The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Ketones and lactate increase cancer cell “stemness,” driving recurrence, metastasis and poor clinical outcome in breast cancer: Achieving personalized medicine via Metabolo-Genomics
Open accessAbstract
Previously, we showed that high-energy metabolites (lactate and ketones) "fuel" tumor growth and experimental metastasis in an in vivo xenograft model, most likely by driving oxidative mitochondrial metabolism in breast cancer cells. To mechanistically understand how these metabolites affect tumor cell behavior, here we used genome-wide transcriptional profiling. Briefly, human breast cancer cells (MCF7) were cultured with lactate or ketones, and then subjected to transcriptional analysis (exon-array). Interestingly, our results show that treatment with these high-energy metabolites increases the transcriptional expression of gene profiles normally associated with "stemness," including genes upregulated in embryonic stem (ES) cells. Similarly, we observe that lactate and ketones promote the growth of bonafide ES cells, providing functional validation. The lactate- and ketone-induced "gene signatures" were able to predict poor clinical outcome (including recurrence and metastasis) in a cohort of human breast cancer patients. Taken together, our results are consistent with the idea that lactate and ketone utilization in cancer cells promotes the "cancer stem cell" phenotype, resulting in significant decreases in patient survival. One possible mechanism by which these high-energy metabolites might induce stemness is by increasing the pool of Acetyl-CoA, leading to increased histone acetylation, and elevated gene expression. Thus, our results mechanistically imply that clinical outcome in breast cancer could simply be determined by epigenetics and energy metabolism, rather than by the accumulation of specific "classical" gene mutations. We also suggest that high-risk cancer patients (identified by the lactate/ketone gene signatures) could be treated with new therapeutics that target oxidative mitochondrial metabolism, such as the anti-oxidant and "mitochondrial poison" metformin. Finally, we propose that this new approach to personalized cancer medicine be termed "Metabolo-Genomics," which incorporates features of both 1) cell metabolism and 2) gene transcriptional profiling. Importantly, this powerful new approach directly links cancer cell metabolism with clinical outcome, and new therapeutic strategies for inhibiting the TCA cycle and mitochondrial oxidative phosphorylation in cancer cells.
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
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Martinez-Outschoorn, U. E., Pavlides, S., Howell, A., Pestell, R. G., Tanowitz, H. B., Sotgia, F., & Lisanti, M. P. (2011) · The International Journal of Biochemistry & Cell Biology · doi:10.1016/j.biocel.2011.01.023 · Cited by 248
Self-citationMetformin and Other Biguanides in Oncology: Advancing the Research Agenda
Pollak, M. (2010) · Cancer Prevention Research · doi:10.1158/1940-6207.capr-10-0175 · Cited by 240
Dykens, J. A., Jamieson, J., Marroquin, L., Nadanaciva, S., Billis, P. A., & Will, Y. (2008) · Toxicology and Applied Pharmacology · doi:10.1016/j.taap.2008.08.013 · Cited by 220
Lisanti, M. P., Martinez-Outschoorn, U. E., Chiavarina, B., Pavlides, S., Whitaker-Menezes, D., Tsirigos, A., Witkiewicz, A. K., Lin, Z., Balliet, R. M., Howell, A., et al. (2010) · Cancer Biology & Therapy · doi:10.4161/cbt.10.6.13370 · Cited by 199
Self-citation
Cited by
Metabolic regulation of gene expression by histone lactylation
Zhang, D., Tang, Z., Huang, H., Zhou, G., Cui, C., Weng, Y., Liu, W., Kim, S., Lee, S., Perez-Neut, M., et al. (2019) · Nature · doi:10.1038/s41586-019-1678-1 · Cited by 4,371
The Science and Translation of Lactate Shuttle Theory
Brooks, G. A. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.03.008 · Cited by 1,486
Metabolic Regulation of Gene Expression by Histone Lysine β-Hydroxybutyrylation
Xie, Z., Zhang, D., Chung, D., Tang, Z., Huang, H., Dai, L., Qi, S., Li, J., Colak, G., Chen, Y., et al. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.03.036 · Cited by 744
Henry, B. M., Aggarwal, G., Wong, J., Benoit, S., Vikse, J., Plebani, M., & Lippi, G. (2020) · The American Journal of Emergency Medicine · doi:10.1016/j.ajem.2020.05.073 · Cited by 608
Peiris-Pagès, M., Martinez-Outschoorn, U. E., Pestell, R. G., Sotgia, F., & Lisanti, M. P. (2016) · Breast Cancer Research · doi:10.1186/s13058-016-0712-6 · Cited by 465
Self-citation
Metadata
- Authors
- Martinez-Outschoorn, U. E., Prisco, M., Ertel, A., Tsirigos, A., Lin, Z., Pavlides, S., Wang, C., Flomenberg, N., Knudsen, E. S., Howell, A., Pestell, R. G., Sotgia, F., & Lisanti, M. P.
- Venue
- Cell Cycle
- Publisher
- Informa UK Limited
- Published
- 2011-04-15
- Volume
- 10
- Issue
- 8
- Pages
- 1271-1286
- ISSN
- 1538-4101 (ISSN-L)
- 1551-4005
- OpenAlex
- W2004045970
- Cited by
- 338
- References
- 5
- FWCI
- 8.34
- 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: Ketones and lactate increase cancer cell “stemness,” driving recurrence, metastasis and poor clinical outcome in breast cancer: Achieving personalized medicine via Metabolo-Genomics. https://app.cochat.ai/papers/10.4161/cc.10.8.15330
- The paper
- Martinez-Outschoorn, U. E., Prisco, M., Ertel, A., Tsirigos, A., Lin, Z., Pavlides, S., Wang, C., Flomenberg, N., Knudsen, E. S., Howell, A., Pestell, R. G., Sotgia, F., & Lisanti, M. P. (2011). Ketones and lactate increase cancer cell “stemness,” driving recurrence, metastasis and poor clinical outcome in breast cancer: Achieving personalized medicine via Metabolo-Genomics. Cell Cycle. https://doi.org/10.4161/cc.10.8.15330
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.