Deep-Sequencing Reveals Specific microRNAs in An Autoregressive Tumor Model
Date Issued
2012
Date
2012
Author(s)
Yu, Chih-Yun
Abstract
MicroRNAs (miRNAs) are a rapidly expanding class of non-coding RNAs, which can be expressed in a cell- and tissue-specific manner. Mature miRNAs are about 18-25 nt, known to work in post-transcriptional regulations. They are active in the processes of development, apoptosis, and differentiation. Strong evidence has also emerged that miRNAs are key molecules involved in cancer initiation, progression, and metastasis. The involvement of miRNAs in all stages of cancer development opens the possibility for miRNA-based diagnosis, prognosis, or even therapeutics. Canine transmissible venereal tumor (CTVT) is a naturally occurring clonally transmissible cancer. The tumor can be transplanted by the direct contact of cancer cells or tumor tissue between individuals. Experimentally transferred CTVT have three distinct phases of growth, described as progressive, stable and regressive phases. The dramatic autoregression phenomenon in CTVT is uncommon to most kind of tumors, and it provides a complete tumor lifecycle to study for. We planned to take CTVT as an extra vision to study miRNA-mediate tumor suppression or oncogenesis. Furthermore, it has been reported that miRNAs in circulating systems are extremely stable, and have the potential to connect with distant cells. In the consideration of all the tumors grow on one dog would regress simultaneously, we believe that there are communications between tumors and host via the circulating system, and it is worth to keep an eye on sera-miRNAs. In this study, we revealed specific miRNAs possibly involved in the autoregression phenomenon in CTVT lifecycle through next generation sequencing (NGS), and confirmed the screening strategy by qRT-PCR upon biological repetitive individuals. For understanding the probable downstream regulatory network of miRNA-drived tumor life cycle, the predicted targets of these miRNAs were then integratively analyzed with the CTVT tissue gene expression data obtained from transcriptome microarray analysis. Together, the investigation of miRNAs in this autoregressive tumor model may provide valuable hints for tumor development and contribute to the therapeutic applications for cancer treatments.
Subjects
miRNA
cancer
CTVT
NGS
biomarker
SDGs
Type
thesis
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