Back to Search Start Over

Construction of a paclitaxel-related competitive endogenous RNA network and identification of a potential regulatory axis in pancreatic cancer

Authors :
Si Yuan Lu
Jie Hua
Jiang Liu
Miao Yan Wei
Chen Liang
Qing Cai Meng
Bo Zhang
Xian Jun Yu
Wei Wang
Jin Xu
Source :
Translational Oncology, Vol 20, Iss , Pp 101419- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

Background: Increasing numbers of studies have elucidated the role of competitive endogenous RNA (ceRNA) networks in carcinogenesis. However, the potential role of the paclitaxel-related ceRNA network in the innate mechanism and prognosis of pancreatic cancer has not been identified. Methods: Comprehensive bioinformatics analyses were performed to identify drug-related miRNAs (DRmiRNAs), drug-related mRNAs (DRmRNAs) and drug-related lncRNAs (DRlncRNAs) and construct a ceRNA network. The ssGSEA and CIBERSORT algorithms were utilized for immune cell infiltration analysis. Additionally, we validated our paclitaxel-related ceRNA regulatory axis at the gene expression level; functional experiments were conducted to explore the biological functions of the key genes. Results: A total of 182 mRNAs, 13 miRNAs, and 53 lncRNAs were confirmed in the paclitaxel-related ceRNA network. In total, 6 mRNAs, 4 miRNAs, and 6 lncRNAs were identified to establish a risk signature and exhibited optimal prognostic effects. The mRNA signature can predict the abundance of immune cell infiltration and the sensitivity of different chemotherapeutic drugs and may also have a guiding effect in immune checkpoint therapy. A potential PART1/hsa-mir-21/SCRN1 axis was confirmed according to the ceRNA theory and was verified by qPCR. The results indicated that PART1 knockdown markedly increased hsa-mir-21 expression but inhibited SCRN1 expression, weakening the proliferation and migration abilities. Conclusions: We hypothesized that the paclitaxel-related ceRNA network strongly influences the innate mechanism, prognosis, and immune infiltration of pancreatic cancer. Our risk signatures can accurately predict survival outcomes and provide a clinical basis.

Details

Language :
English
ISSN :
19365233
Volume :
20
Issue :
101419-
Database :
Directory of Open Access Journals
Journal :
Translational Oncology
Publication Type :
Academic Journal
Accession number :
edsdoj.b414d66f03714b06902daa1dde3aeaf7
Document Type :
article
Full Text :
https://doi.org/10.1016/j.tranon.2022.101419