Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/8279
Title: Noncoding RNA’s competing endogenous gene pair as motif in serous ovarian cancer
Authors: Cheng, Lixin 
Zheng, Xubin 
Zhang, Ning 
Gao, Jing 
Prof. LEUNG Kwong Sak 
Wong, Man-Hon 
Yang, Shu 
Liu, Yakun 
Dong, Ming 
Bai, Huimin 
Kang, Lin 
Li, Haili 
Issue Date: 2022
Source: bioRxiv, 2022.
Journal: bioRxiv 
Abstract: Understanding the regulatory mechanisms in serous ovarian carcinoma (SOC) is critical for its diagnosis and targeted therapy. However, some critical motifs in the competing endogenous RNA (ceRNA) network in SOC were still undiscovered. We profiled a whole transcriptome of eight human SOCs and eight controls and constructed a ceRNA network including mRNAs, lncRNAs, and circRNAs. We hypothesized the noncoding RNA’s competing endogenous gene pairs (ceGPs) relationship for the mRNA–ncRNA–mRNA motifs in the ceRNA network. Then, we proposed the denoised individualized pair analysis of gene expression (deiPAGE) to identify mRNA–ncRNA–mRNA motifs from integrated multi-cohorts. 18 cricRNA’s ceGPs (cceGPs) were identified and fused as an indicator (SOC index) for SOC discrimination, which carried a high predictive capacity in independent cohorts. The index was negatively correlated with the CD8+/CD4+ ratio in tumour-infiltration, reflecting the migration and growth of tumour cells in ovarian cancer progression.
Type: Peer Reviewed Journal Article
URI: http://hdl.handle.net/20.500.11861/8279
ISSN: 2692-8205
DOI: https://doi.org/10.1101/2022.04.04.486923
Appears in Collections:Applied Data Science - Publication

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