WWTR1-AS1 LncRNA as a Novel Potential Diagnostic and Prognostic Biomarker in Breast Cancer
Breast cancer is the most lethal form of cancer in women, and patients face serious health risks. Long non-coding RNAs are involved in a variety of regulatory processes and can influence cancers development at different levels. This study aimed to introduce a central regulatory lncRNA based on diffe...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
University of Mazandaran
2024-02-01
|
| Series: | Journal of Genetic Resources |
| Subjects: | |
| Online Access: | https://sc.journals.umz.ac.ir/article_4942_3995f757769a11ec58f0f292f8ac4e0c.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Breast cancer is the most lethal form of cancer in women, and patients face serious health risks. Long non-coding RNAs are involved in a variety of regulatory processes and can influence cancers development at different levels. This study aimed to introduce a central regulatory lncRNA based on differentially expressed proteins in breast cancer and evaluate its expression level in breast tissues. In this study, proteomic data was obtained from ProteomeXchange and then differentially expressed proteins were detected. The Enrichr database was used to identify the regulatory factors of differentially expressed proteins, and functional enrichment analysis was used to demonstrate key signaling pathways and biological processes. Eventually, a lncRNA with the highest rank in the central hub was chosen, and its expression level was measured by RT-qPCR in 15 breast cancer tissues and their adjacent nontumor tissues. Proteomic analysis recognized 1149 differential expressed proteins in breast cancer with regulatory agents consisting of 76 TFs, 61 kinases, 366 miRNAs, and 162 lncRNAs. A multi-regulatory network with 1811 nodes and 4022 edges was constructed based on differentially expressed proteins and their associated elements. In addition, these regulatory elements were related to three biological functions and 11 pathways. Finally, bioinformatic analysis identified lncRNA WWTR1-AS1 as having the highest node score involved in different mechanisms. Functional experiments confirmed that the expression level of the lncRNA WWTR1-AS1 was significantly increased in breast cancer patients. ROC analysis suggested that this lncRNA can be used as a reliable biomarker. Our data provide evidence that the lncRNA WWTR1-AS1 is an effective factor in the regulation of DEPs, is associated with malignant features in breast cancer, and might be useful as a prognostic marker in Breast cancer. |
|---|---|
| ISSN: | 2423-4257 2588-2589 |