Identification of genes and pathways associated with pancreatic ductal adenocarcinoma by bioinformatics analyses
نویسندگان
چکیده
This study aimed to explore the underlying genes and pathways associated with pancreatic ductal adenocarcinoma (PDAC) by bioinformatics analyses. Gene expression profile GSE43795 was downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) between six PDAC and five non-neoplastic pancreatic tissue samples were analyzed using the limma package. Gene ontology (GO) and pathway enrichment analyses of DEGs were performed, followed by functional annotation and protein-protein interaction (PPI) network construction. Finally, the sub-network was identified and pathway enrichment analysis was performed on the contained DEGs. A total of 374 downregulated and 559 upregulated DEGs were identified. The downregulated DEGs were enriched in GO terms associated with digestion and transport and pathways related to metabolism, while the upregulated DEGs were enriched in GO terms associated with the cell cycle and mitosis and pathways associated with the occurrence of cancer including the cell cycle pathway. Following functional annotation, the oncogene pituitary tumor-transforming 1 (PTTG1) was upregulated. In the PPI network and sub-network, cell division cycle 20 (CDC20) and BUB1 mitotic checkpoint serine/threonine kinase B (BUB1B) were hub genes with high connectivity degrees. Additionally, DEGs in the sub-network including cyclin B1 (CCNB1) were mainly enriched in the cell cycle and p53 signaling pathways. In conclusion, the cell cycle and p53 signaling pathways may play significant roles in PDAC, and DEGs including CDC20, BUB1B, CCNB1 and PTTG1 may be potential targets for PDAC diagnosis and treatment.
منابع مشابه
Identification of key genes and pathways involved in vitiligo vulgaris by gene network analysis
Background and Aim: Vitiligo vulgaris is an acquired, chronic skin and hair condition characterized clinically by loss of melanin, which, if untreated, is typically progressive and irreversible. The aim of the present study was to identify potential genes involved in the pathogenesis of vitiligo. Methods: One dataset of mRNA expression in patients with vitiligo (GSE65127) were obtained from ...
متن کاملGene Regulation Network Based Analysis Associated with TGF-beta Stimulation in Lung Adenocarcinoma Cells
Background: Transforming growth factor (TGF)-β is over-expressed in a wide variety of cancers such as lung adenocarcinoma. TGF-β plays a major role in cancer progression through regulating cancer cell proliferation and remodeling of the tumor micro-environment. However, it is still a great challenge to explain the phenotypic effects caused by TGF-β stimulation and the effect of TGF-β stimulatio...
متن کاملConstruction of a prognostic prediction system for pancreatic ductal adenocarcinoma to investigate the key prognostic genes
Pancreatic cancer (PC) is associated with high mortality rates and poor prognoses. Pancreatic adenocarcinoma is the most common type of PC, and almost all cases of pancreatic adenocarcinoma are pancreatic ductal adenocarcinoma (PDAC). The aim of the current study was to reveal the genes involved in the prognosis of PDAC. Five datasets, including GSE71729 (145 PDAC samples and 46 normal samples)...
متن کاملTranscriptomic and CRISPR/Cas9 technologies reveal FOXA2 as a tumor suppressor gene in pancreatic cancer.
Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with low survival rates and limited therapeutic options. Thus elucidation of signaling pathways involved in PDAC pathogenesis is essential for identifying novel potential therapeutic gene targets. Here, we used a systems approach to elucidate those pathways by integrating gene and microRNA profiling analyses together with CRISPR/Ca...
متن کاملMetscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data
MOTIVATION Metabolomics is a rapidly evolving field that holds promise to provide insights into genotype-phenotype relationships in cancers, diabetes and other complex diseases. One of the major informatics challenges is providing tools that link metabolite data with other types of high-throughput molecular data (e.g. transcriptomics, proteomics), and incorporate prior knowledge of pathways and...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 11 شماره
صفحات -
تاریخ انتشار 2016