Abstract

Abstract DARPP-32 plays a crucial role in regulating both protein-phosphatase-1 (PP-1) and protein kinase A (PKA), its function being reliant on its phosphorylation status. We have previously demonstrated that low DARPP-32 expression is associated with adverse survival of breast cancer patients, particularly those with oestrogen receptor (ER) positive disease; however, there is limited information on how DARPP-32 may alter breast cancer cell behaviour. We have recently published an integrative approach using patient data and cell line transcriptomics to understand the role of DARPP-32 in breast cancer. We analysed the transcriptome of T47D ER positive breast cancer cells following DARPP-32 knockdown, including treatments in combination with 17β-estradiol or PKA inhibitor fragment (6-22) amide. 202 differentially expressed transcripts were identified in DARPP-32 knock down cells and treatment of these cells with 17β-estradiol or PKA inhibitor fragment (6-22) amide led to the differential expression of 193 and 181 transcripts respectively. Differentially expressed transcripts were compared with genes identified as associated with DARPP-32 expression in 1980 breast cancer patients within the METABRIC cohort using an Artificial Neural Network approach (ANN). Several genes overlapped with those identified from cell line transcriptomics, including PTK7, TRAF5, and KLK6. Both DKK1 and GRB7 were identified as genes associated with DARPP-32 expression in patients using ANN, therefore protein expression was determined in a large cohort of early-stage breast cancer patients (n>1000). We demonstrated that DKK1 and GRB7 protein expression was significantly correlated with DARPP-32 Threonine-34 phosphorylation levels within the same samples (all P<0.05). We have now applied an ANN-based integrative data mining approach to identify genes with the largest effect on other genes resulting in an interactome map, which was based on genes identified within the cell line transcriptomics and original ANN. 1878 genes were identified for inclusion within an interactome map in the total patient cohort, whereas 1003 were identified in ER negative disease alone and 2144 in ER positive disease alone. Pathway enrichment analysis identified the ubiquitin proteosome pathway, the insulin pathway-protein kinase B signalling cascade and the RAS pathway. This study underscores the significance of DARPP-32, a central molecular switch, in breast cancer, elucidating its impact on patient prognosis and highlighting potential molecular targets for therapeutic intervention. The integrative approach combining patient data with cell line transcriptomics provides insights into the complex mechanisms underlying breast cancer progression and opens avenues for further research and targeted interventions. Citation Format: Behnaz Saidy, Richa Vasan, Megan-Rose Greener, Rosie Durrant, Adelynn Immanuel, Andrew Green, Emad Rakha, Ian Ellis, Graham Ball, Stewart Martin, Sarah J. Storr. Unveiling the significance of DARPP-32 and its partners, including GRB7 and DKK1, in breast cancer: Integrative insights from patient data and cell line transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB009.

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