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Cited by 850

The DOI matches its Crossref record; 269 of the 269 references it cites were found in a registry or an index.

Lipid metabolism reprogramming and its potential targets in cancer

Open access
Cheng, Chunming, Geng, Feng, Cheng, Xiang, Guo, Deliang·2018·Cancer Communications

Abstract

Reprogramming of lipid metabolism is a newly recognized hallmark of malignancy. Increased lipid uptake, storage and lipogenesis occur in a variety of cancers and contribute to rapid tumor growth. Lipids constitute the basic structure of membranes and also function as signaling molecules and energy sources. Sterol regulatory element‐binding proteins (SREBPs), a family of membrane‐bound transcription factors in the endoplasmic reticulum, play a central role in the regulation of lipid metabolism. Recent studies have revealed that SREBPs are highly up‐regulated in various cancers and promote tumor growth. SREBP cleavage‐activating protein is a key transporter in the trafficking and activation of SREBPs as well as a critical glucose sensor, thus linking glucose metabolism and de novo lipid synthesis. Targeting altered lipid metabolic pathways has become a promising anti‐cancer strategy. This review summarizes recent progress in our understanding of lipid metabolism regulation in malignancy, and highlights potential molecular targets and their inhibitors for cancer treatment.

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Crossref · 10.1186/s40880-018-0301-4

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Metadata

Authors
Cheng, C., Geng, F., Cheng, X., & Guo, D.
Venue
Cancer Communications
Published
2018-05-21
Volume
38
Issue
1
Pages
1-14
ISSN
  • 1000-467X (ISSN-L)
  • 2523-3548
OpenAlex
W2805393256
Cited by
850
References
269
FWCI
12.53
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Lipid metabolism reprogramming and its potential targets in cancer. https://app.cochat.ai/papers/10.1186/s40880-018-0301-4
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Cheng, C., Geng, F., Cheng, X., & Guo, D. (2018). Lipid metabolism reprogramming and its potential targets in cancer. Cancer Communications. https://doi.org/10.1186/s40880-018-0301-4

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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.