人類胰臟腺管腺癌之MicroRNA-基因調控網路之計算生物預測

Abstract

胰臟癌是台灣第八大以及美國第四大癌症死因。胰臟腺管腺癌 (PDAC)的高致死率來自於缺乏有效的標靶療法。具有抑制標靶基因功能的MicroRNA (miRNA)是一個當前作為診斷胰臟癌的biomarker以及可能的標靶療法。miRNA-基因調控網路 (MTI) 能夠描繪出不同功能的miRNAs與胰臟腫瘤組織之分子生物路徑的關係性。我們整合TCGA的胰臟腺管腺癌病人的RNA-seq/miRNA-seq資料以及GEO的Microarray資料篩選出顯著差異表現的基因與miRNAs。使用MTI預測工具得到潛在的MTI配對，並得到Functional Annotation Analysis結果。我們使用miRTarBase找到所有該資料庫紀錄已被實驗驗證的PDAC MTIs以及所有MTIs與TCGA/GEO結果資料的交集。我們也進行文獻調查並找到更多已被實驗驗證的PDAC中的MTIs。最後我們找到一些能經實驗驗證的PDAC MTIs。

Pancreatic cancer is the 8th deadly cancer in Taiwan and the 4th deadly cancer in USA. The high fatality of pancreatic ductal adenocarcinoma (PDAC) is due to the lack in effective target therapy. MicroRNA (miRNAs), which has function of inhibition to their target genes, are a current biomarker for pancreatic cancer diagnosis and a possible target therapy. The miRNA-target interaction (MTI) network can depict the relationship between different functional miRNAs and the molecular biological pathways of pancreatic cancer. We integrated the RNA-seq/miRNA-seq data of TCGA and the GEO microarray datasets to select significantly differentially expressed genes and miRNAs. We used miRNA-target prediction tools to gain potential MTI pairs, and gained the result of functional annotation analysis. We used the recorded data of miRTarBase to find the all currently recorded experimentally validated PDAC MTIs and the intersection of previously validated MTIs. We also did literature survey to find more previously validated MTIs in PDAC. Eventually we found some MTIs able to be further validated in pancreatic tissue.