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Identification of potential therapeutic targets for lung cancer by bioinformatics analysis.

ABSTRACT: The aim of the present study was to identify potential therapeutic targets for lung cancer and explore underlying molecular mechanisms of its development and progression. The gene expression profile datasets no. GSE3268 and GSE19804, which included five and 60 pairs of tumor and normal lung tissue specimens, respectively, were downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) between lung cancer and normal tissues were identified, and gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis of the DEGs was performed. Furthermore, protein?protein interaction (PPI) networks and a transcription factor (TF) regulatory network were constructed and key target genes were screened. A total of 466 DEGs were identified, and the PPI network indicated that IL?6 and MMP9 had key roles in lung cancer. A PPI module containing 34 nodes and 547 edges was obtained, including PTTG1. The TF regulatory network indicated that TFs of FOSB and LMO2 had a key role. Furthermore, MMP9 was indicated to be the target of FOSB, while PTTG1 was the target of LMO2. In conclusion, the bioinformatics analysis of the present study indicated that IL?6, MMP9 and PTTG1 may have key roles in the progression and development of lung cancer and may potentially be used as biomarkers or specific therapeutic targets for lung cancer.

SUBMITTER: Wang LQ

PROVIDER: S-EPMC4768991 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Identification of potential therapeutic targets for lung cancer by bioinformatics analysis.

Wang Li-Quan LQ Zhao Lan-Hua LH Qiao Yi-Ze YZ

Molecular medicine reports 20151231 3

The aim of the present study was to identify potential therapeutic targets for lung cancer and explore underlying molecular mechanisms of its development and progression. The gene expression profile datasets no. GSE3268 and GSE19804, which included five and 60 pairs of tumor and normal lung tissue specimens, respectively, were downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) between lung cancer and normal tissues were identified, and gene ontology and Kyoto Encyclop ...[more]

PMID: 26739332

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Identification of potential therapeutic targets for lung cancer by bioinformatics analysis.

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Identification of potential therapeutic targets for lung cancer by bioinformatics analysis.

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