Behnaz Saidy
Unravelling transcriptomic complexity in breast cancer through modulation of DARPP-32 expression and signalling pathways
Saidy, Behnaz; Vasan, Richa; Durant, Rosie; Greener, Megan-Rose; Immanuel, Adelynn; Green, Andrew R.; Rakha, Emad; Ellis, Ian; Ball, Graham; Martin, Stewart G.; Storr, Sarah J.
Authors
Richa Vasan
Rosie Durant
Megan-Rose Greener
Adelynn Immanuel
Dr Andy Green ANDREW.GREEN@NOTTINGHAM.AC.UK
ASSOCIATE PROFESSOR
Professor EMAD RAKHA Emad.Rakha@nottingham.ac.uk
PROFESSOR OF BREAST CANCER PATHOLOGY
Ian Ellis
Graham Ball
Stewart G. Martin
Dr SARAH STORR sarah.storr@nottingham.ac.uk
ASSISTANT PROFESSOR
Abstract
DARPP-32 is a key regulator of protein-phosphatase-1 (PP-1) and protein kinase A (PKA), with its function dependent upon its phosphorylation state. We previously identified DKK1 and GRB7 as genes with linked expression using Artificial Neural Network (ANN) analysis; here, we determine protein expression in a large cohort of early-stage breast cancer patients. Low levels of DARPP-32 Threonine-34 phosphorylation and DKK1 expression were significantly associated with poor patient prognosis, while low levels of GRB7 expression were linked to better survival outcomes. To gain insight into mechanisms underlying these associations, we analysed the transcriptome of T47D breast cancer cells following DARPP-32 knockdown. We identified 202 differentially expressed transcripts and observed that some overlapped with genes implicated in the ANN analysis, including PTK7, TRAF5, and KLK6, amongst others. Furthermore, we found that treatment of DARPP-32 knockdown cells with 17β-estradiol or PKA inhibitor fragment (6–22) amide led to the differential expression of 193 and 181 transcripts respectively. These results underscore the importance of DARPP-32, a central molecular switch, and its downstream targets, DKK1 and GRB7 in breast cancer. The discovery of common genes identified by a combined patient/cell line transcriptomic approach provides insights into the molecular mechanisms underlying differential breast cancer prognosis and highlights potential targets for therapeutic intervention.
Citation
Saidy, B., Vasan, R., Durant, R., Greener, M.-R., Immanuel, A., Green, A. R., Rakha, E., Ellis, I., Ball, G., Martin, S. G., & Storr, S. J. (2023). Unravelling transcriptomic complexity in breast cancer through modulation of DARPP-32 expression and signalling pathways. Scientific Reports, 13(1), Article 21163. https://doi.org/10.1038/s41598-023-48198-y
Journal Article Type | Article |
---|---|
Acceptance Date | Nov 23, 2023 |
Online Publication Date | Nov 30, 2023 |
Publication Date | Nov 30, 2023 |
Deposit Date | Feb 9, 2024 |
Publicly Available Date | Feb 9, 2024 |
Journal | Scientific Reports |
Electronic ISSN | 2045-2322 |
Publisher | Nature Publishing Group |
Peer Reviewed | Peer Reviewed |
Volume | 13 |
Issue | 1 |
Article Number | 21163 |
DOI | https://doi.org/10.1038/s41598-023-48198-y |
Keywords | Breast cancer; Tumour biomarkers |
Public URL | https://nottingham-repository.worktribe.com/output/28133300 |
Publisher URL | https://www.nature.com/articles/s41598-023-48198-y |
Additional Information | Received: 6 June 2023; Accepted: 23 November 2023; First Online: 30 November 2023; : The authors declare no competing interests. |
Files
Unravelling transcriptomic complexity in breast cancer
(1.8 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
Unravelling transcriptomic complexity in breast cancer
(708 Kb)
Image
Unravelling transcriptomic complexity in breast cancer
(13 Kb)
Spreadsheet
Unravelling transcriptomic complexity in breast cancer
(70 Kb)
Spreadsheet
You might also like
The role of the ALKBH5 RNA demethylase in invasive breast cancer
(2024)
Journal Article
Epitranscriptomic mechanisms of androgen signalling and prostate cancer
(2024)
Journal Article
Stromal lymphocytes are associated with upgrade of B3 breast lesions
(2024)
Journal Article
The characteristics and prognostic significance of histone H1 expression in breast cancer
(2024)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search