Determining the effect of long non-coding RNA maternally expressed gene 3 (lncRNA MEG3) on the transcriptome profile in cervical cancer cell lines

This study investigates the role of the long non-coding RNA Maternally Expressed Gene3 (lncRNA MEG3) gene in cervical cancer, as evidenced by its downregulation in cancerous cell lines. The study demonstrates the effects of the overexpression of lncRNA MEG3 in cervical cancer cell lines, particularly in C33A and CaSki. Through comprehensive analyses, including Next-Generation Sequencing (NGS), alterations in global mRNA expression were analyzed. In C33A cells, 67 genes were upregulated, while 303 genes were downregulated. Similarly, in CaSki cells, 221 genes showed upregulation and 248 genes displayed downregulation. Gene ontology and KEGG pathway analyses were conducted to gain insight into potential mechanisms. Furthermore, the study delves into gene regulatory networks, uncovering intricate interactions among genes. The RNA sequencing data were confirmed for eight genes: PAX3, EGR2, ROR1, NRP1, OAS2, STRA6, CA9, and EDN2 by Real-time PCR. The findings illuminate the complex landscape of gene expression alterations and pathways impacted by the overexpression of lncRNA MEG3. The impact of MEG3 on the overall cervical cancer cells' mRNA profile is reported for the first time. New biomarkers for the prognosis of cervical cancer are also reported in this study. Moreover, identifying specific genes within the regulatory networks provides valuable insights into potential therapeutic targets for managing cervical cancer. • Role of lncRNA MEG3 in Cervical Cancer: The study focuses on the downregulation of lncRNA MEG3 in cervical cancer cell lines and explores the effects of its overexpression, revealing significant changes in gene expression profiles in C33A and CaSki cells. • Gene Expression Changes: Comprehensive analyses, including Next-Generation Sequencing, show substantial alterations in global mRNA expression, with hundreds of genes being upregulated and downregulated in both cell lines, highlighting the complexity of gene regulatory networks involved. • Implications for Prognosis and Treatment: The findings introduce new biomarkers for cervical cancer prognosis and identify potential therapeutic targets based on specific genes within the regulatory networks, contributing valuable insights into managing the disease.