Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,056

The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.

Serine and glycine metabolism in cancer

Open access
Amelio, Ivano, Cutruzzolá, Francesca, Antonov, Alexey, Agostini, Massimiliano, Melino, Gerry·2014·Trends in Biochemical Sciences

Abstract

Serine and glycine are biosynthetically linked, and together provide the essential precursors for the synthesis of proteins, nucleic acids, and lipids that are crucial to cancer cell growth. Moreover, serine/glycine biosynthesis also affects cellular antioxidative capacity, thus supporting tumour homeostasis. A crucial contribution of serine/glycine to cellular metabolism is through the glycine cleavage system, which refuels one-carbon metabolism; a complex cyclic metabolic network based on chemical reactions of folate compounds. The importance of serine/glycine metabolism is further highlighted by genetic and functional evidence indicating that hyperactivation of the serine/glycine biosynthetic pathway drives oncogenesis. Recent developments in our understanding of these pathways provide novel translational opportunities for drug development, dietary intervention, and biomarker identification of human cancers.

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 · 10.1016/j.tibs.2014.02.004

Cites

16 of 16 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 16 references

Cited by

See all 1,056

Metadata

Authors
Amelio, I., Cutruzzolá, F., Antonov, A., Agostini, M., & Melino, G.
Venue
Trends in Biochemical Sciences
Publisher
Elsevier BV
Published
2014-04
Volume
39
Issue
4
Pages
191-198
ISSN
0968-0004 (ISSN-L)
OpenAlex
W2051522090
Cited by
1,056
References
16
FWCI
4.21
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: Serine and glycine metabolism in cancer. https://app.cochat.ai/papers/10.1016/j.tibs.2014.02.004
The paper
Amelio, I., Cutruzzolá, F., Antonov, A., Agostini, M., & Melino, G. (2014). Serine and glycine metabolism in cancer. Trends in Biochemical Sciences. https://doi.org/10.1016/j.tibs.2014.02.004

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.