Dysregulated LncRNAs Act as Competitive Endogenous RNAs and Are Associated With Cervical Cancer Development in UYGHUR Women

Abstract

Cervical cancer is one of the most malignant tumors in women, particularly those in rural and remote areas. Its underlying molecular mechanisms, including the functions of non-coding RNA (ncRNAs), require more extensive investigation. In this study, high throughput transcriptome sequencing (RNA-seq) was used to identify differentially expressed lncRNAs and mRNAs in normal, cervical intraepithelial neoplasia and cervical cancer tissues from Uyghur women in western China. Dysregulated lncRNAs were found to extensively participate in cervical cancer development, including viral carcinogenesis, cell cycle and cytokine-cytokine receptor signaling. Two miRNA-host lncRNAs, LINC00925 and MIR155HG, showed elevated expression in cervical cancer samples, but prolonged the survival time of cervical cancer patients. The 2 mature miRNAs of the above 2 lncRNAs, miR-9 and miR-155, also showed similar features in cervical cancer. In addition, we identified 545 lncRNAs with potential functions in regulating these 2 miRNAs as competing endogenous RNAs (ceRNAs). In summary, our study demonstrated the dysregulated lncRNAs/miRNAs, particularly LINC00925/miR-9 and MIR155HG/miR-155, regulate the development of cervical cancer by forming a interaction network with mRNAs, highlighting the importance of elucidating the underlying mechanisms of ncRNAs in cervical cancer development.

Exploration of the Immune-Related Long Noncoding RNA Prognostic Signature and Inflammatory Microenvironment for Cervical Cancer

“…LINC00925, also known as MIR9-3HG, has shown that it is strongly linked to the occurrence and development of cervical cancer in current studies ( Wu et al, 2018 ; Gast et al, 2019 ). Chen’s study suggests that as an miRNA-host lncRNA, LINC00925 exhibited high expression in cervical cancer patients, prolonging their survival time ( Chen et al, 2021 ); the aforementioned research results are consistent with ours, but the detailed mechanism of MIR9-3HG in CC development is not known. Studies have shown that removing MIR9-3HG inhibits the proliferation of cells and promotes apoptosis in CC ( Li et al, 2021 ).…”

A novel prognostic biomarker CD3G that correlates with the tumor microenvironment in cervical cancer

“…Moreover, this dataset additionally includes samples spanning three stages of cervical intraepithelial neoplasia (14 CIN1, 22 CIN2 and 40 CIN3) ( 19 ); and the array data of GSE7410 which includes five normal tissues and nine early-stage cervical tumors (Agilent) ( 20 ). Second, we obtained three sets of high-throughput RNA sequencing data: GSE87410 which includes paired samples (tumor and the adjacent normal tissue) from six CESC patients ( 21 ); GSE192804 which includes paired samples from 14 CESC patients; and GSE149763 which includes normal tissues and tumors with three biological replicates ( 22 ). We used kallisto ( 23 ) to calculate the expression level of each gene for GSE192804 because it provides the raw sequencing data.…”

Construction of ceRNA network and key gene screening in cervical squamous intraepithelial lesions

“…Based on the relevant requirements, GSE149763 was selected to construct differential expression profiles of lncRNAs and mRNA between cervical squamous intraepithelial lesions and normal groups. [13] GSE105409 dataset was used to verify the predicted miRNAs. [14] GSE149763 used high-throughput sequencing as the detection method and included three patients with cervicitis, three with CIN III, and three with cervical cancer.…”

“…The GSE149763 dataset uses the online analysis tool GEO2R to analyze the stability of the data, download the original data, and use the limma package in R software to analyze the difference data. [15] The expressed lncRNAs were screened to obtain differentially expressed lncRNAs (DELs) and their sequences, [13] the miRNAs associated with DELs were predicted using lncRNA sequences and the miRcode database (http://www.mircode.org). [16] This data include many non-coding genes, which can provide “whole transcriptome” human miRNA target prediction with reliable data information.…”

“…Differentially expressed miRNAs (DEMs) were obtained using the miRDB (http://mirdb.org), Targetscan database (https:// www.targetscan.org/vert_80/), and mirtarbase database (http:// mirtarbase. cuhk.edu.cn/~miRTarBase/miRTarBase_2022/php/ index.php) for correlated mRNA prediction, [16] and the predicted results were co-expressed with the differentially expressed mRNAs screened in the GSE149763 dataset, [13] and the intersection mRNA was screened out.…”