Integrative transcriptomic and competing endogenous RNA network analysis reveal two circular RNAs associated with cervical precancerous lesion progression

Description

These data encompass circular RNA (circRNA) annotation, the identification of differentially expressed circRNAs (DEcircRNAs), and circRNA–miRNA interaction analyses derived from three publicly available RNA-sequencing datasets comprising normal cervical (NC) tissues, high-grade squamous intraepithelial lesions (HSIL), and cervical cancer (CC) samples. Publicly available RNA sequencing datasets, including GSE206224, GSE173112, GSE147009, and GSE63514, were retrieved from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/).

Steps to reproduce

This study employed an integrated transcriptomic and computational workflow to identify circRNAs associated with CC progression. Differential expression analyses were performed to identify candidate circRNAs exhibiting progressive dysregulation across cervical lesions using transcriptomic datasets obtained from public databases. Subsequently, circRNA-miRNA-mRNA regulatory networks were constructed, followed by functional and pathway enrichment analyses to elucidate their potential biological functions.

Institutions

• Khon Kaen University

  Khon Kaen, Khon Kaen

Categories

Funders

• Khon Kaen University

  Khon Kaen, Khon Kaen

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