همایش ملی بیوانفورماتیک ایران

صفحه اصلی / 4th international edition and 13th Iranian Conference on Bioinformatics

Reconstruction and analysis of lncRNA-miRNA-mRNA ceRNA network to explore the potential biomarkers for colorectal cancer

نویسندگان :

Sara Nafei Milani¹ Negar Sadat Soleimani Zakeri² Habib MotieGhader³

1- Department of Biology, Tabriz Branch, Islamic Azad University, Tabriz, Iran 2- Department of Software Engineering, Engineering and Architecture Faculty, Istanbul Nişantaşi University, Istanbul, Turkey 3- Department of Biology, Tabriz Branch, Islamic Azad University, Tabriz, Iran

کلمات کلیدی :

Colorectal cancer،Biomarker،miRNA،ceRNA،Bioinformatics

چکیده :

Background Colorectal cancer (CRC) is ranked among the most prevalent and most life-threating cancers worldwide. Despite progress in treatment methods, CRC is still responsible for a significant percentage of cancer deaths, as it is often diagnosed at advanced stages. Early detection and identifying novel therapeutic targets are crucial for outcomes, a goal that bioinformatics is making increasingly achievable. Through molecular-level analysis of disease mechanisms and structure, bioinformatics enables researchers to uncover critical biomarkers and regulatory pathways, leading to earlier diagnosis and development of targeted and personalized therapies. In colorectal cancer, miRNAs have a significant contribution to the genesis, cellular differentiation, and disease progression. The current study proposes four miRNAs as biomarkers through the analysis of the lncRNA-miRNA-mRNA tripartite network for the diagnosis and treatment of colorectal cancer. Furthermore, the biological functions of obtained biomarkers in colorectal cancer were analyzed. Methods Using colorectal cancer-filtered data from the dbDEMC database, cancer-specific differentially expressed miRNAs (DEmiRNAs) were identified. The interactions between lncRNAs and mRNAs were identified using lncACTdb and miRTarBase databases, respectively. Using the interactions between the specified molecules, a ceRNA network was constructed by integrating lncRNA-miRNA and miRNA-mRNA networks which was visualized using Cytoscape. Then Protein-Protein Interaction (PPI) network was constructed based on the identified target genes using the STRING database and analyzed further using the MCODE algorithm to extract gene modules. Finally, functional enrichment for the identified lncRNAs, miRNAs, and their target genes was conducted using the GeneCodis platform to reveal their biological roles, cellular components, and molecular function, and involved pathways. Results Two bipartite networks linking lncRNAs to miRNAs and miRNAs to mRNAs were constructed and subsequently were integrated to create a ceRNA network comprising lncRNAs, miRNAs, and mRNAs. This integration enables us to determine the key biomarkers associated with the CRC. The obtained networks highlighted potential regulatory interactions involved in the pathogenesis and facilitated the identification of candidate biomarkers for further studies. Conclusions Through the assembly of a tripartite lncRNA–miRNA–mRNA ceRNA network, we were able to discover four miRNAs that are potential biomarkers for the studied disease. Out of this, three miRNAs were shown to be up-regulated and one was down-regulated in a disease context thus, making them to be involved in regulatory roles.