The DOI matches its Crossref record; 197 of the 197 references it cites were found in a registry or an index.
Lipids in the tumor microenvironment: From cancer progression to treatment
Open accessAbstract
Over the past decade, the study of metabolic abnormalities in cancer cells has risen dramatically. Cancer cells can thrive in challenging environments, be it the hypoxic and nutrient-deplete tumor microenvironment or a distant tissue following metastasis. The ways in which cancer cells utilize lipids are often influenced by the complex interactions within the tumor microenvironment and adjacent stroma. Adipocytes can be activated by cancer cells to lipolyze their triglyceride stores, delivering secreted fatty acids to cancer cells for uptake through numerous fatty acid transporters. Cancer-associated fibroblasts are also implicated in lipid secretion for cancer cell catabolism and lipid signaling leading to activation of mitogenic and migratory pathways. As these cancer-stromal interactions are exacerbated during tumor progression, fatty acids secreted into the microenvironment can impact infiltrating immune cell function and phenotype. Lipid metabolic abnormalities such as increased fatty acid oxidation and de novo lipid synthesis can provide survival advantages for the tumor to resist chemotherapeutic and radiation treatments and alleviate cellular stresses involved in the metastatic cascade. In this review, we highlight recent literature that demonstrates how lipids can shape each part of the cancer lifecycle and show that there is significant potential for therapeutic intervention surrounding lipid metabolic and signaling pathways.
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
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 emerging hallmarks of cancer metabolism
Pavlova, N. N., & Thompson, C. B. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2015.12.006 · Cited by 5,926
Obesity: global epidemiology and pathogenesis
Blüher, M. (2019) · Nature Reviews Endocrinology · doi:10.1038/s41574-019-0176-8 · Cited by 5,126
Tumor-Associated Macrophages: From Mechanisms to Therapy
Noy, R., & Pollard, J. W. (2014) · Immunity · doi:10.1016/j.immuni.2014.06.010 · Cited by 4,089
Macrophage activation and polarization
Martinez, F. O. (2008) · Frontiers in Bioscience · doi:10.2741/2692 · Cited by 3,160
Adipocytes promote ovarian cancer metastasis and provide energy for rapid tumor growth
Nieman, K. M., Kenny, H. A., Penicka, C. V., Ladanyi, A., Buell-Gutbrod, R., Zillhardt, M. R., Romero, I. L., Carey, M. S., Mills, G. B., Hotamisligil, G. S., et al. (2011) · Nature Medicine · doi:10.1038/nm.2492 · Cited by 2,279
Metastatic colonization by circulating tumour cells
Massagué, J., & Obenauf, A. C. (2016) · Nature · doi:10.1038/nature17038 · Cited by 2,062
Myeloid-Derived Suppressor Cells
Gabrilovich, D. I. (2017) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-16-0297 · Cited by 1,882
Cited by
The role of lipid metabolic reprogramming in tumor microenvironment
Yang, K., Wang, X., Song, C., He, Z., Wang, R., Xu, Y., Jiang, G., Wan, Y., Mei, J., & Mao, W. (2023) · Theranostics · doi:10.7150/thno.82920 · Cited by 270
Mitochondrial CPT1A: Insights into structure, function, and basis for drug development
Liang, K. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1160440 · Cited by 156
“One indicator of RT and CT resistant tumor cells is thought to be the abnormal upregulation of CPT1A-dependent FAO (Corn et al., 2020).”
BackgroundHu, D., Li, Y., Li, R., Wang, M., Zhou, K., He, C., Wei, Q., & Qian, Z. (2024) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2024.10.015 · Cited by 153
Rodriguez-Gonzalez, J. C., Hernández-Balmaseda, I., Declerck, K., Pérez-Novo, C., Logie, E., Theys, C., Jakubek, P., Quiñones-Maza, O. L., Dantas-Cassali, G., Carlos dos Reis, D., et al. (2021) · Frontiers in Pharmacology · doi:10.3389/fphar.2021.670167 · Cited by 19
Metadata
- Authors
- Corn, K. C., Windham, M. A., & Rafat, M.
- Venue
- Progress in Lipid Research
- Publisher
- Elsevier BV
- Published
- 2020-11
- Volume
- 80
- Pages
- 101055
- ISSN
- 0163-7827 (ISSN-L)
- OpenAlex
- W3048456013
- Cited by
- 469
- References
- 197
- FWCI
- 13.16
- 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: Lipids in the tumor microenvironment: From cancer progression to treatment. https://app.cochat.ai/papers/10.1016/j.plipres.2020.101055
- The paper
- Corn, K. C., Windham, M. A., & Rafat, M. (2020). Lipids in the tumor microenvironment: From cancer progression to treatment. Progress in Lipid Research. https://doi.org/10.1016/j.plipres.2020.101055
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.