YAP/TAZ-mediated activation of serine metabolism and methylation regulation is critical for LKB1-deficient breast cancer progression
Open accessAbstract
The crucial interplay between metabolic remodeling and the epigenetics could contribute to promote cancer progression. A remarkable association within interaction, LKB1 has been reported, suggesting that the expression of key enzymes involving de novo serine synthesis and DNA methyltransferases like DNMT1 and DNMT3A increase LKB1-deficiency cells. However, the complex interactional link between metabolic remodeling and the epigenetics is still unclear. Hence, we focus on the relationship between YAP/TAZ and serine metabolism to control methylation of DNA or histone in breast cancer with LKB1 deficiency. We hypothesize that YAP/TAZ may have the function to activate key enzymes involving serine metabolism like PSPH and up-regulate the amino acid transporters to supply sources of serine synthesis through activation of C-MYC with TEAD1. Further, we speculate that YAP/TAZ in dependent of FOS may promote DNMT1 and subsequently mediate DNMT1–G9A complex involving serine metabolism and the methylation of DNA and histone. We hope that our study will stimulate further studies and a new targeted therapy and early medical intervention for YAP/TAZ could be a useful option for breast cancer cases complicated with LKB1 deficiency.
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Augmented PSPH level is correlated with prognosis in multiple cancers including cutaneous squamous cell carcinoma, breast cancer, non-small cell lung cancer, colorectal cancer, and hepatocellular carcinoma.
“Additionally, several studies reported that augmented PSPH level is correlated with the prognosis in multiple cancers including cutaneous squamous cell carcinoma [9], breast cancer [10], non-small cell lung cancer [11], colorectal cancer [12] and hepatocellular carcinoma [13].”
From Phosphoserine phosphatase as a prognostic biomarker in patients with gastric cancer and its potential association with immune cells (2022) · cites this paper as [10]
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- Authors
- Wu, Q., Li, J., Sun, S., Chen, X., Zhang, H., Li, B., & Sun, S.
- Affiliations
- Renmin Hospital of Wuhan University (CN)
- Corresponding author
- Sun, Shengrong
- Venue
- Bioscience Reports
- Publisher
- Portland Press Ltd.
- Published
- 2017-10-24
- Volume
- 37
- Issue
- 5
- ISSN
- 0144-8463 (ISSN-L)
- 1573-4935
- PMC
- PMC5653917
- OpenAlex
- W2755496433
- Cited by
- 38
- References
- 41
- Citations by year
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- FWCI
- 0.38
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Bioscience Reports (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (81302314, 81471781)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Hippo pathway signaling and YAP/TAZ
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer, Hypoxia, and Metabolism
- Keywords
- YAP/TAZ, LKB1 deficiency, breast cancer progression, serine metabolism, DNA methylation, histone methylation, DNMT1, DNMT3A, G9a, c-Myc, TEAD1, FOS, metabolic remodeling, epigenetics, amino acid transporters, phosphoserine phosphatase
- MeSH terms
- DNA (Cytosine-5-)-Methyltransferase 1, YAP-Signaling Proteins, AMP-Activated Protein Kinase Kinases, TEA Domain Transcription Factors, Breast Neoplasms, DNA-Binding Proteins, Female, Histocompatibility Antigens, Humans, Nuclear Proteins, Phosphoproteins, Histone-Lysine N-Methyltransferase, Serine, Transcription Factors, Proto-Oncogene Proteins c-myc, Protein Serine-Threonine Kinases, Disease Progression, DNA Methylation, Adaptor Proteins, Signal Transducing
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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.
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