Abstract

Background

Taxol resistance in serous ovarian cancer is responsible for its poor prognosis, yet the underlying mechanism is still poorly understood. Thus, we probed the mechanism of Taxol resistance in serous ovarian cancer with multiple bioinformatic methods to provide novel insights into potential therapies.

Methods

The differentially expressed genes (DEGs) in Taxol-sensitive and Taxol-resistant cell lines and their relationship with the overall survival (OS) and progression-free interval (PFI) of ovarian cancer patients were analyzed using gene expression datasets from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The role of receptor interacting serine/threonine kinase 2 (RIPK2) was validated via identification of its coexpressed genes, functional analysis and generation of a protein-protein interaction (PPI) network. The single sample gene set enrichment analysis (ssGSEA) was used to explore immune infiltration, and genomic alterations of RIPK2 were also analyzed via cBio Cancer Genomics Portal (cBioProtal).

Results

RIPK2 was highly expressed in Taxol resistant ovarian cancer cell lines, and its high expression was also linked with shorter OS and PFI in serous ovarian cancer patients. The PPI network analysis and pathway analysis demonstrated that RIPK2 might participate in the positive regulation of NF-κB transcription factor activity. RIPK2 expression was related to tumor microenvironment alterations, which might participate in the formation of Taxol resistance.

Conclusions

Our studies suggested that high expression of RIPK2 is related to Taxol resistance in serous ovarian cancer, and that RIPK2 induces Taxol resistance through NOD1/RIPK2/NF-κB inflammatory pathway activation and tumor microenvironment changes.

Details

Title
High expression of RIPK2 is associated with Taxol resistance in serous ovarian cancer
Author
Shen, Yuqing; Lin, Hui; Chen, Kelie; Ge, Wanzhong; Xia, Dajing; Wu, Yihua; Lu, Weiguo  VIAFID ORCID Logo 
Pages
1-12
Section
Research
Publication year
2022
Publication date
2022
Publisher
BioMed Central
e-ISSN
17572215
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2666593484
Copyright
© 2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.