1st International and 10th National Iranian Conference on Bioinformatics
Home Accepted Papers
Identification of Key long noncoding RNAs-related to Pancreatic Cancer Using Network Analysis
Paper ID : 1197-ICB10
Authors:
Sahar Akrami *1, Ali Niazi1, Ahmad Tahmasebi1, Amin Ramezani2, Ali Moghadam1, Abbas Alemzadeh3
1Institute of Biotechnology, Shiraz University, Shiraz, Iran
2Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran Shiraz Institute for Cancer Research, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
3Department of Crop Production and Plant Breeding, School of Agriculture, Shiraz University, Shiraz, Iran
Abstract:
Introduction: Pancreatic ductal adenocarcinoma (PDAC) is one of the most malignant tumors that threaten human health. The molecular mechanisms underlying PDAC still remain unclear. Unreasonable excessive mortality and low survival rates for this disease, mainly result from the delay in diagnosis and treatment. Long non-coding RNAs (lncRNAs), a class of transcripts ≥200 nucleotides, have been proved to regulate various biological processes including apoptosis, invasion, metastasis and angiogenesis through interactions with miRNAs or mRNAs in different cancer types. In this work, we find important lncRNAs involved in PDAC, which are identified by mining The Cancer Genome Atlas (TCGA) PDAC RNA-sequencing differentially expressed data between cancer and normal state and visualization of the network by co-expression method. Method: The RNA-seq expression data of PDAC for cancerous and normal condition retrieved from TCGA database. The lncRNA data was extracted via Biomart tool in Ensemble. To identify the differential expression of lncRNA, the edgeR package was used, with the standard thresholds of |fold change| ≥1 and FDR of ≤0.01. The network of lncRNA-gene was constructed based on the Pearson correlation. Finally, CytoNCA plug-in was used to screen hubs of the network. GO and KEGG pathway analyses were performed, by gProfiler database, to determine the significantly enriched functions and pathways of these lncRNAs in PDAC. Result: We detected 592 mRNAs and 206 lncRNAs that were differentially expressed. After constructing the co-expression network of the lncRNA-mRNA, a total of 5 lncRNAs were found, which includes MIR600HG, C9orf139, LINC01410, IRF1-AS1, and BTG1-DT. GO showed the crucial roles of them in immune system process, immune response, leukocyte activation, cell activation. Also KEGG analysis demonstrated enrichment in natural killer cell mediated cytotoxicity and B cell receptor signaling pathway. Conclusion: Our findings uncovered that these lncRNAs may be used as diagnostic indicators and prognostic factors in PC patients.
Keywords:
Pancreatic Cancer; lncRNA; Network analysis; TCGA data
Status : Paper Accepted (Poster Presentation)