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Updated: May 10, 2026
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Analysis of Combinatorial miRNA Treatments to Regulate Cell Cycle and Angiogenesis
Published on: March 30, 2019
Bioinformatics analyses combined microarray identify the desregulated microRNAs in lung cancer
1Departments of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
European Review for Medical and Pharmacological Sciences
|June 18, 2013
Summary
MicroRNAs (miRNAs) are key in cancer. This study identified 17 differentially expressed miRNAs, including hsa-miR-339-5p, which may serve as lung cancer biomarkers.
Area of Science:
- Molecular Biology
- Genomics
- Cancer Research
Background:
- MicroRNAs (miRNAs) are crucial regulators of cellular processes like growth, differentiation, apoptosis, and carcinogenesis.
- Aberrant miRNA expression is observed in blood cells of cancer patients, indicating their potential role in disease pathology.
Purpose of the Study:
- To identify differentially expressed miRNAs (DE-miRNAs) capable of distinguishing lung cancer from non-cancerous lung tissues.
- To uncover molecular signatures associated with differences in tumor histology.
Main Methods:
- Utilized miRNA expression profiles from the Gene Expression Omnibus (GEO) database (GSE17681).
- Employed three statistical methods to identify DE-miRNAs between lung cancer and healthy control tissues.
- Retrieved and analyzed target genes of DE-miRNAs using KEGG pathway analysis and constructed a protein-protein interaction (PPI) network with STRING and Cytoscape.
Main Results:
- Identified a total of 17 DE-miRNAs, with hsa-miR-339-5p showing particular significance.
- Pathway analysis indicated that target genes of RASSF1 and KRAS are involved in lung cancer progression as oncogenes or tumor suppressors.
- A protein-protein interaction module was formed by target genes of RASSF1 and ERBB4, and response to hypoxia was a significantly enriched biological process.
Conclusions:
- hsa-miR-339-5p plays a significant role in lung cancer regulation.
- This miRNA holds potential as a biomarker for predicting lung cancer progression.
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