Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 323

The DOI matches its Crossref record; 118 of the 118 references it cites were found in a registry or an index.

Targeting SREBP-1-driven Lipid Metabolism to Treat Cancer

Open access
Guo, Deliang, Bell, Erica, Mischel, Paul, Chakravarti, Arnab·2014·Current Pharmaceutical Design

Abstract

Metabolic reprogramming is a hallmark of cancer. Oncogenic growth signaling regulates glucose, glutamine and lipid metabolism to meet the bioenergetics and biosynthetic demands of rapidly proliferating tumor cells. Emerging evidence indicates that sterol regulatory element-binding protein 1 (SREBP-1), a master transcription factor that controls lipid metabolism, is a critical link between oncogenic signaling and tumor metabolism. We recently demonstrated that SREBP-1 is required for the survival of mutant EGFR-containing glioblastoma, and that this pro-survival metabolic pathway is mediated, in part, by SREBP-1-dependent upregulation of the fatty acid synthesis and low density lipoprotein (LDL) receptor (LDLR). These results have identified EGFR/PI3K/Akt/SREBP-1 signaling pathway that promotes growth and survival in glioblastoma, and potentially other cancer types. Here, we summarize recent insights in the understanding of cancer lipid metabolism, and discuss the evidence linking SREBP-1 with PI3K/Akt signaling-controlled glycolysis and with Myc-regulated glutaminolysis to lipid metabolism. We also discuss the development of potential drugs targeting the SREBP-1- driven lipid metabolism as anti-cancer agents.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2174/13816128113199990486

Cites

118 of 118 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 118 references

Cited by

See all 323

Metadata

Authors
Guo, D., Bell, E., Mischel, P., & Chakravarti, A.
Venue
Current Pharmaceutical Design
Published
2014-05-12
Volume
20
Issue
15
Pages
2619-2626
ISSN
1381-6128 (ISSN-L)
OpenAlex
W2171640413
Cited by
323
References
118
FWCI
5.25
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: Targeting SREBP-1-driven Lipid Metabolism to Treat Cancer. https://app.cochat.ai/papers/10.2174/13816128113199990486
The paper
Guo, D., Bell, E., Mischel, P., & Chakravarti, A. (2014). Targeting SREBP-1-driven Lipid Metabolism to Treat Cancer. Current Pharmaceutical Design. https://doi.org/10.2174/13816128113199990486

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.