Venkatasubramanian, G and Kelkar, DA and Mandal, S and Jolly, MK and Kulkarni, M (2022) Analysis of Yes-Associated Protein-1 (YAP1) Target Gene Signature to Predict Progressive Breast Cancer. In: Journal of Clinical Medicine, 11 (7).
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Abstract
Breast cancers are treated according to the ER/PR or HER2 expression and show better survival outcomes with targeted therapy. Triple-negative breast cancers (TNBCs) with a lack of expression of ER/PR and HER2 are treated with systemic therapy with unpredictable responses and outcomes. It is essential to investigate novel markers to identify targeted therapies for TNBC. One such marker is YAP1, a transcription co-activator protein that shows association with poor prognosis of breast cancer. YAP1 transcriptionally regulates the expression of genes that drive the oncogenic phenotypes. Here, we assess a potential YAP target gene signature to predict a progressive subset of breast tumors from METABRIC and TCGA datasets. YAP1 target genes were shortlisted based on expression correlation and concordance with YAP1 expression and significant association with survival outcomes of patients. Hierarchical clustering was performed for the shortlisted genes. The utility of the clustered genes was assessed by survival analysis to identify a recurring subset. Expression of the shortlisted target genes showed significant association with survival outcomes of HER2-positive and TNBC subset in both datasets. The shortlisted genes were verified using an independent dataset. Further validation using IHC can prove the utility of this potential prognostic signature to identify a recurrent subset of HER2-positive and TNBC subtypes. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
| Item Type: | Journal Article |
|---|---|
| Publication: | Journal of Clinical Medicine |
| Publisher: | MDPI |
| Additional Information: | The copyright for this article belongs to author |
| Department/Centre: | Division of Interdisciplinary Sciences > Centre for Biosystems Science and Engineering |
| Date Deposited: | 17 May 2022 06:48 |
| Last Modified: | 17 May 2022 06:48 |
| URI: | https://eprints.iisc.ac.in/id/eprint/71764 |
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