[Downloaded free from http://www.cancerjournal.net on Thursday, May 21, 2015, IP: 78.83.100.243]
Original Article
Identification of human prolactinoma related genes by DNA microarray ABSTRACT Objective: To identify the genes involved in prolactinoma by bioinformatics methods and provide new potential biomarkers for prolactinoma. Materials and Methods: The gene‑expression profile data, GSE36314, including 4 prolactinoma samples and 3 controls, was downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the limma package in R and were then classified into different functional groups by COG (Clusters of Orthologous Groups) annotation based on BLASTX (Basic Local Alignment Search Tool). Transcriptional factors (TFs) were screened out by employing the Transcription Factor (TRANSFAC) database. An interaction network among DEGs and TFs was constructed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) software. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analysis were then performed for the genes in this network. Results: A total of 52 genes were identified as being significantly different between prolactinomas and normal samples which were classified into 29 COG functional categories. Three TFs, ZIC3 (Zic family member 3), NGFIC (nerve growth factor‑induced protein C) and SP1 (Specificity Protein 1) were screened out, which can regulate part of DEGs. Two down‑regulated genes, FSHB (follicle stimulating hormone β subunit) and LHB (luteinizing hormone β subunit) were involved in GnRH (gonadotropin‑releasing hormone) signaling pathway. Conclusion: Several DEGs between prolactinoma and normal samples were identified in our study and candidate agents such as LHB and FSHB may provide the groundwork for a targeted therapy approach for prolactinomas. KEY WORDS: Differentially expressed gene, function classification, prolactinomas
INTRODUCTION Prolactinoma is a benign tumor (adenoma) of the pituitary gland that produces a hormone called prolactin. It is the most common hormone‑secreting pituitary tumors, representing approximately 40% of all pituitary tumors and the most relevant clinical manifestations of it are usually infertility, gonadal and sexual dysfunction in both sexes.[1,2] Dopamine agonists, such as bromocriptine and cabergoline, are the primary therapy for patients who have prolactinomas.[3] It should be switched to an alternative one or, finally, undergo surgery when patients are resistant to or cannot tolerate a particular dopamine agonist. However, surgical cure rates for patients with invasive macroprolactinomas are poor, and even if resected, large prolactinomas tend to recur postoperatively.[4] With the development of molecular biology theory and technology, targeted therapy or molecularly targeted therapy has been a major focus of cancer research today. It is a type of medication that blocks the growth of cancer cells by interfering with specific targeted molecules needed for 544
carcinogenesis and tumor growth[5] rather than by simply interfering with all rapidly dividing cells. Therefore, one significant advantage that targeted therapies have over most traditional therapies is that they tend to be less toxic to non‑cancerous cells. Molecular profiling is essential for understanding pituitary biology and events leading to tumorigenesis and is important for exploring specific genes related to prolactinoma that can be used as targets for therapy. As mentioned above, a majority of patients with prolactinomas were successfully treated with dopaminergic drugs as the first‑line treatment as prolactinomas express a high level of dopamine (D‑2) receptors. Besides, overexpression of proto‑oncogenes, which include cell cycle‑progression molecules, growth factors or receptors, such as pituitary tumor‑transforming gene (PTTG),[6] high mobility group A2 gene,[7] FGF receptor‑4,[8] have been detected in prolactinomas. Although many studies have focused on the molecular mechanism of prolactinomas, our knowledge of the molecular events involved in prolactinomas is limited. It still needs to explore new genes related to the pathogenesis of prolactinomas.
Lin Zhao, Min Lin, Shousen Wang Department of Neurosurgery, Fuzhou General Hospital of Nanjing Command, PLA, Fuzhou, China Lin Zhao and Min Lin are co-first authors
For correspondence: Dr. Shousen Wang, Department of Neurosurgery, Fuzhou General Hospital of Nanjing Command, 256 Xi’erhuan Road, Fuzhou 350025, China. E‑mail: 954451077@ qq.com
Access this article online Website: www.cancerjournal.net DOI: 10.4103/0973-1482.137962 PMID: *** Quick Response Code:
Journal of Cancer Research and Therapeutics - July-September 2014 - Volume 10 - Issue 3
[Downloaded free from http://www.cancerjournal.net on Thursday, May 21, 2015, IP: 78.83.100.243]
Zhao, et al.: Genes related to human prolactinoma
Microarray technology makes it possible to investigate the expression levels of thousands of genes simultaneously[9] that has been widely used in discovery of cancer biomarkers. In the current study, we analyzed gene expression profiling to identify differentially expressed genes (DEGs) between prolactinoma and normal samples and performed further researches based on these DEGs. Our study derives great insights into the underlying molecular mechanisms of prolactinoma and may provide new strategy for the treatment of prolactinoma.
GO and Pathway analysis of DEGs FuncAssociate is a web application that discovers properties enriched in lists of genes or proteins.[17] The DEGs in the interaction network were inputted into the FuncAssociate web for Gene Ontology GO function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis with FDR
Original Article
Identification of human prolactinoma related genes by DNA microarray ABSTRACT Objective: To identify the genes involved in prolactinoma by bioinformatics methods and provide new potential biomarkers for prolactinoma. Materials and Methods: The gene‑expression profile data, GSE36314, including 4 prolactinoma samples and 3 controls, was downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using the limma package in R and were then classified into different functional groups by COG (Clusters of Orthologous Groups) annotation based on BLASTX (Basic Local Alignment Search Tool). Transcriptional factors (TFs) were screened out by employing the Transcription Factor (TRANSFAC) database. An interaction network among DEGs and TFs was constructed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) software. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analysis were then performed for the genes in this network. Results: A total of 52 genes were identified as being significantly different between prolactinomas and normal samples which were classified into 29 COG functional categories. Three TFs, ZIC3 (Zic family member 3), NGFIC (nerve growth factor‑induced protein C) and SP1 (Specificity Protein 1) were screened out, which can regulate part of DEGs. Two down‑regulated genes, FSHB (follicle stimulating hormone β subunit) and LHB (luteinizing hormone β subunit) were involved in GnRH (gonadotropin‑releasing hormone) signaling pathway. Conclusion: Several DEGs between prolactinoma and normal samples were identified in our study and candidate agents such as LHB and FSHB may provide the groundwork for a targeted therapy approach for prolactinomas. KEY WORDS: Differentially expressed gene, function classification, prolactinomas
INTRODUCTION Prolactinoma is a benign tumor (adenoma) of the pituitary gland that produces a hormone called prolactin. It is the most common hormone‑secreting pituitary tumors, representing approximately 40% of all pituitary tumors and the most relevant clinical manifestations of it are usually infertility, gonadal and sexual dysfunction in both sexes.[1,2] Dopamine agonists, such as bromocriptine and cabergoline, are the primary therapy for patients who have prolactinomas.[3] It should be switched to an alternative one or, finally, undergo surgery when patients are resistant to or cannot tolerate a particular dopamine agonist. However, surgical cure rates for patients with invasive macroprolactinomas are poor, and even if resected, large prolactinomas tend to recur postoperatively.[4] With the development of molecular biology theory and technology, targeted therapy or molecularly targeted therapy has been a major focus of cancer research today. It is a type of medication that blocks the growth of cancer cells by interfering with specific targeted molecules needed for 544
carcinogenesis and tumor growth[5] rather than by simply interfering with all rapidly dividing cells. Therefore, one significant advantage that targeted therapies have over most traditional therapies is that they tend to be less toxic to non‑cancerous cells. Molecular profiling is essential for understanding pituitary biology and events leading to tumorigenesis and is important for exploring specific genes related to prolactinoma that can be used as targets for therapy. As mentioned above, a majority of patients with prolactinomas were successfully treated with dopaminergic drugs as the first‑line treatment as prolactinomas express a high level of dopamine (D‑2) receptors. Besides, overexpression of proto‑oncogenes, which include cell cycle‑progression molecules, growth factors or receptors, such as pituitary tumor‑transforming gene (PTTG),[6] high mobility group A2 gene,[7] FGF receptor‑4,[8] have been detected in prolactinomas. Although many studies have focused on the molecular mechanism of prolactinomas, our knowledge of the molecular events involved in prolactinomas is limited. It still needs to explore new genes related to the pathogenesis of prolactinomas.
Lin Zhao, Min Lin, Shousen Wang Department of Neurosurgery, Fuzhou General Hospital of Nanjing Command, PLA, Fuzhou, China Lin Zhao and Min Lin are co-first authors
For correspondence: Dr. Shousen Wang, Department of Neurosurgery, Fuzhou General Hospital of Nanjing Command, 256 Xi’erhuan Road, Fuzhou 350025, China. E‑mail: 954451077@ qq.com
Access this article online Website: www.cancerjournal.net DOI: 10.4103/0973-1482.137962 PMID: *** Quick Response Code:
Journal of Cancer Research and Therapeutics - July-September 2014 - Volume 10 - Issue 3
[Downloaded free from http://www.cancerjournal.net on Thursday, May 21, 2015, IP: 78.83.100.243]
Zhao, et al.: Genes related to human prolactinoma
Microarray technology makes it possible to investigate the expression levels of thousands of genes simultaneously[9] that has been widely used in discovery of cancer biomarkers. In the current study, we analyzed gene expression profiling to identify differentially expressed genes (DEGs) between prolactinoma and normal samples and performed further researches based on these DEGs. Our study derives great insights into the underlying molecular mechanisms of prolactinoma and may provide new strategy for the treatment of prolactinoma.
GO and Pathway analysis of DEGs FuncAssociate is a web application that discovers properties enriched in lists of genes or proteins.[17] The DEGs in the interaction network were inputted into the FuncAssociate web for Gene Ontology GO function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis with FDR
