Screening for genes and subnetworks associated with pancreatic cancer based on the gene expression profile

نویسندگان

  • JIN LONG
  • ZHE LIU
  • XINGDA WU
  • YUANHONG XU
  • CHUNLIN GE
چکیده

The present study aimed to screen for potential genes and subnetworks associated with pancreatic cancer (PC) using the gene expression profile. The expression profile GSE 16515 was downloaded from the Gene Expression Omnibus database, which included 36 PC tissue samples and 16 normal samples. Limma package in R language was used to screen differentially expressed genes (DEGs), which were grouped as up‑ and downregulated genes. Then, PFSNet was applied to perform subnetwork analysis for all the DEGs. Moreover, Gene Ontology (GO) and REACTOME pathway enrichment analysis of up‑ and downregulated genes was performed, followed by protein‑protein interaction (PPI) network construction using Search Tool for the Retrieval of Interacting Genes Search Tool for the Retrieval of Interacting Genes. In total, 1,989 DEGs including 1,461 up‑ and 528 downregulated genes were screened out. Subnetworks including pancreatic cancer in PC tissue samples and intercellular adhesion in normal samples were identified, respectively. A total of 8 significant REACTOME pathways for upregulated DEGs, such as hemostasis and cell cycle, mitotic were identified. Moreover, 4 significant REACTOME pathways for downregulated DEGs, including regulation of β‑cell development and transmembrane transport of small molecules were screened out. Additionally, DEGs with high connectivity degrees, such as CCNA2 (cyclin A2) and PBK (PDZ binding kinase), of the module in the protein‑protein interaction network were mainly enriched with cell‑division cycle. CCNA2 and PBK of the module and their relative pathway cell‑division cycle, and two subnetworks (pancreatic cancer and intercellular adhesion subnetworks) may be pivotal for further understanding of the molecular mechanism of PC.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Exploring Gene Signatures in Different Molecular Subtypes of Gastric Cancer (MSS/ TP53+, MSS/TP53-): A Network-based and Machine Learning Approach

Gastric cancer (GC) is one of the leading causes of cancer mortality, worldwide. Molecular understanding of GC’s different subtypes is still dismal and it is necessary to develop new subtype-specific diagnostic and therapeutic approaches. Therefore developing comprehensive research in this area is demanding to have a deeper insight into molecular processes, underlying these subtypes. In this st...

متن کامل

Identification of Prognostic Genes in Her2-enriched Breast Cancer by Gene Co-Expression Net-work Analysis

Introduction: HER2-enriched subtype of breast cancer has a worse prognosis than luminal subtypes. Recently, the discovery of targeted therapies in other groups of breast cancer has increased patient survival. The aim of this study was to identify genes that affect the overall survival of this group of patients based on a systems biology approach. Methods: Gene expression data and clinical infor...

متن کامل

The effect of 8 weeks of HIIT training and supplementation of black grape seed extract on Wnt and Β-catenin gene expression in pancreatic tissue in male rats with type 2 diabetes

Objective:The aim of the present study was to investigate the effect of 8 weeks of HIIT training and supplementation of black grape seed extract on Wnt and Β-catenin gene expression in pancreatic tissue in male rats with type 2 diabetes. Methods:In this experimental study, 40 male Wistar rats, with average weight of 250 ± 20 gr, after induction of diabetes by STZ, were randomly divided into 5 ...

متن کامل

Evaluation of gene expression level of GPRC6A, E.cadherin and ZEB1 in prostate cancer in comparison to benign tissues

Background: Prostate cancer is currently the third malignant disease in Iran and fifth common cancer worldwide. The aim of this study was to determine the expression of GPRC6A, E.cadherin, and ZEB1 genes in prostate cancer in comparison with benign tumor. Since early detection of cancer plays an important role in treatment, this study aims to identify the role of GPRC6A, E.cadherin and ZEB1 gen...

متن کامل

Classification and Biomarker Genes Selection for Cancer Gene Expression Data Using Random Forest

Background & objective: Microarray and next generation sequencing (NGS) data are the important sources to find helpful molecular patterns. Also, the great number of gene expression data increases the challenge of how to identify the biomarkers associated with cancer. The random forest (RF) is used to effectively analyze the problems of large-p and smal...

متن کامل

ذخیره 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 13  شماره 

صفحات  -

تاریخ انتشار 2016