Tuberc Respir Dis.  2024 Jul;87(3):398-408. 10.4046/trd.2023.0172.

Bioinformatics Study and Experimental Evaluation of miR-182, and miR-34 Expression Profiles in Tuberculosis and Lung Cancer

• Alimardanian L
• Soltani BM
• Irani S
• Sheikhpour M

• KMID: 2556838
• DOI: http://doi.org/10.4046/trd.2023.0172

Abstract

Background
Lung cancer is one of the most dangerous cancers and tuberculosis is one of the deadliest infectious diseases in the world. Many studies have confirmed the connection between lung cancer and tuberculosis, and also the microRNAs (miRNAs) that play a major role in the development of these two diseases. This study aims to use different databases to find effective miRNAs and their role in different genes in lung and tuberculosis diseases. It also aims to determine the role of miR-34a and miR-182 in lung cancer and tuberculosis.
Methods
Using the Gene Expression Omnibus (GEO) database, the influential miRNA databases were studied in the two diseases. Finally, considering bioinformatics results and literature studies, two miR-34a and miR-182 were selected. The role of these miRNAs and their target genes was carefully evaluated using bioinformatics. The expression of miRNAs in the plasma of patients with lung cancer and tuberculosis and healthy individuals was investigated.
Results
According to the GEO database, miR-34a and miR-182 are miRNAs that affect tuberculosis and lung cancer. By checking the miRBase, miRcode, DIANA, miRDB, galaxy, Kyoto Encyclopedia of Genes and Genomes databases, the role of these miRNAs on genes and different molecular pathways and their effect on these miRNAs were mentioned. The results of the present study showed that the expression of miR-34a and miR-182 was lower than that of healthy people. The p-value for miR-182 was <0.0001 and for miR-34a was 0.3380.
Conclusion
Reducing the expression pattern of these miRNAs indicates their role in lung cancer and tuberculosis occurrence. Therefore, these miRNAs can be used as a biomarker for prognosis, diagnosis, and treatment methods.

Keyword

Lung Cancer; Tuberculosis; MicroRNAs; Expression Profiles; Bioinformatics