Evidence map›Paper›PMID 38616694›Full record

ArticleTuberculosis and respiratory diseases2024

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

Leila Alimardanian, Bahram Mohammad Soltani, Shiva Irani, Mojgan Sheikhpour

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Article in Tuberculosis and respiratory diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.9field-weighted citation impact, top 28% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 3 institutions in 1 country.

Leila AlimardanianDepartment of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Bahram Mohammad SoltaniDepartment of Molecular Genetics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran.
Shiva IraniDepartment of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Mojgan SheikhpourDepartment of Mycobacteriology and Pulmonary Research, Pasteur Institute of Iran, Tehran, Iran.
Islamic Azad University, Science and Research Branch · IRPasteur Institute of Iran · IRTarbiat Modares University · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung 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.

methodsUsing 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.

resultsAccording 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.

conclusionReducing 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.

Indexed as

BioinformaticsExpression ProfilesLung CancerMicroRNAsTuberculosis

Identifiers

PMID38616694
PMCPMC11222103
OpenAlexW4394816129

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.