BACKGROUND: Pancreatic cancer is a devastating disease; its lethality is related to rapid growth and tendency to invade adjacent organs and metastasize at an early stage. OBJECTIVE: The aim of this study was to identify miRNAs and their gene targets involved in the invasive phenotype in pancreatic cancer to better understand the biological behaviour and the rapid progression of this disease. METHODS: miRNA profiling was performed in isogenic matched high invasive and low-invasive subclones derived from the MiaPaCa-2 cell line and validated in a panel of pancreatic cancer cell lines, tumour, and normal pancreas. Online miRNA target prediction algorithms and gene expression arrays were used to predict the target genes of the differentially expressed miRNAs. miRNAs and potential target genes were subjected to overexpression and knockdown approaches and downstream functional assays to determine their pathological role in pancreatic cancer. RESULTS: Differential expression analysis revealed 10 significantly dysregulated miRNAs associated with invasive capacity (Student's t-tests; P value <0.05; fold change = ±2). The expression of top upregulated miR-135b and downregulated let-7c miRNAs correlated with the invasive abilities of eight pancreatic cancer cell lines and displayed differential expression in pancreatic cancer and adjacent normal tissue specimens. Ectopic overexpression of let-7c decreased proliferation, invasion, and colony formation. Integrated analysis of miRNA-mRNA using in silico algorithms and experimental validation databases identified four putative gene targets of let-7c. One of these targets, SOX13, was found to be upregulated in PDAC tumour compared with normal tissue in TCGA and an independent data set by qPCR and immunohistochemistry. RNAi knockdown of SOX13 reduced the invasion and colony formation ability of pancreatic cancer cells. CONCLUSION: The identification of key miRNA-mRNA gene interactions and networks provide potential diagnostic and therapeutic strategies for better treatment options for pancreatic cancer patients.
BACKGROUND: Pancreatic cancer is a devastating disease; its lethality is related to rapid growth and tendency to invade adjacent organs and metastasize at an early stage. OBJECTIVE: The aim of this study was to identify miRNAs and their gene targets involved in the invasive phenotype in pancreatic cancer to better understand the biological behaviour and the rapid progression of this disease. METHODS: miRNA profiling was performed in isogenic matched high invasive and low-invasive subclones derived from the MiaPaCa-2 cell line and validated in a panel of pancreatic cancer cell lines, tumour, and normal pancreas. Online miRNA target prediction algorithms and gene expression arrays were used to predict the target genes of the differentially expressed miRNAs. miRNAs and potential target genes were subjected to overexpression and knockdown approaches and downstream functional assays to determine their pathological role in pancreatic cancer. RESULTS: Differential expression analysis revealed 10 significantly dysregulated miRNAs associated with invasive capacity (Student's t-tests; P value <0.05; fold change = ±2). The expression of top upregulated miR-135b and downregulated let-7c miRNAs correlated with the invasive abilities of eight pancreatic cancer cell lines and displayed differential expression in pancreatic cancer and adjacent normal tissue specimens. Ectopic overexpression of let-7c decreased proliferation, invasion, and colony formation. Integrated analysis of miRNA-mRNA using in silico algorithms and experimental validation databases identified four putative gene targets of let-7c. One of these targets, SOX13, was found to be upregulated in PDAC tumour compared with normal tissue in TCGA and an independent data set by qPCR and immunohistochemistry. RNAi knockdown of SOX13 reduced the invasion and colony formation ability of pancreatic cancer cells. CONCLUSION: The identification of key miRNA-mRNA gene interactions and networks provide potential diagnostic and therapeutic strategies for better treatment options for pancreatic cancer patients.
Authors: Gang Zhao; Bo Wang; Yang Liu; Jun-Gang Zhang; Shi-Chang Deng; Qi Qin; Kui Tian; Xiang Li; Shuai Zhu; Yi Niu; Qiong Gong; Chun-You Wang Journal: Mol Cancer Ther Date: 2013-09-06 Impact factor: 6.261
Authors: H Kasimiotis; M A Myers; A Argentaro; S Mertin; S Fida; T Ferraro; J Olsson; M J Rowley; V R Harley Journal: Diabetes Date: 2000-04 Impact factor: 9.461
Authors: A E Pasquinelli; B J Reinhart; F Slack; M Q Martindale; M I Kuroda; B Maller; D C Hayward; E E Ball; B Degnan; P Müller; J Spring; A Srinivasan; M Fishman; J Finnerty; J Corbo; M Levine; P Leahy; E Davidson; G Ruvkun Journal: Nature Date: 2000-11-02 Impact factor: 49.962
Authors: Nagalakshmi Nadiminty; Ramakumar Tummala; Wei Lou; Yezi Zhu; Xu-Bao Shi; June X Zou; Hongwu Chen; Jin Zhang; Xinbin Chen; Jun Luo; Ralph W deVere White; Hsing-Jien Kung; Christopher P Evans; Allen C Gao Journal: PLoS One Date: 2012-03-30 Impact factor: 3.240
Authors: Catherine Demos; Janie Johnson; Aitor Andueza; Christian Park; Yerin Kim; Nicolas Villa-Roel; Dong-Won Kang; Sandeep Kumar; Hanjoong Jo Journal: Front Cardiovasc Med Date: 2022-09-30