Computational analysis identifies invasion-associated genes in pituitary adenomas

Cao,Changjun; Wang,Wei; Ma,Chao; Jiang,Pucha

doi:10.3892/mmr.2015.3564

Computational analysis identifies invasion-associated genes in pituitary adenomas

Authors:
- Changjun Cao
- Wei Wang
- Chao Ma
- Pucha Jiang
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Affiliations: Department of Neurosurgery, Zhongnan Hospital of Wuhan University, Wuhan, Hubei 430071, P.R. China
Published online on: March 27, 2015 https://doi.org/10.3892/mmr.2015.3564
Pages: 1977-1982

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Abstract

Pituitary adenomas are considered to be benign tumours. However, they can infiltrate surrounding tissues, which may cause a failure of complete removal during surgical resection. Thus far, no molecular biomarkers have been identified, which are able to reliably predict the behaviour of this type of tumour. In the present study, a list of differentially expressed genes in invasive pituitary adenomas was obtained using a computational bioinformatics analysis on the DNA microarray expression profiles. The gene expression datasets of a total of 16 samples were retrieved from the National Center for Biotechnology Information Gene Expression Omnibus database. The gene set enrichment analysis was later conducted on the significantly (FDR<0.05) differentially expressed genes. A total of 194 genes were identified as differentially expressed. The pathway impact analysis revealed that cell adhesion molecules may be vital in the progression of pituitary adenoma invasion. A total of six genes, claudin 7, contactin associated protein‑like 2, integrin α6, junctional adhesion molecule 3, protein tyrosine phosphatase, receptor type C and cadherin‑associated protein α1 were identified as molecular biomarkers for pituitary adenoma invasion. The present study identified six novel molecular biomarkers, which may be used for diagnostic or therapeutic purposes. However, further experimental investigations are required to validate the present findings.

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