| Summary: | 碩士 === 國立中央大學 === 系統生物與生物資訊研究所 === 104 === MicroRNAs (miRNAs) are a large family of high conserved non-coding RNAs. The length of miRNAs are about 18 ~ 25 nuleotides. miRNAs can regulate gene expression through post-transcriptional regulation and thus miRNAs can affect a lot of cell functions. Recent study reported that miRNA profiles displayed more potential as biomakers than mRNA profile. Moreover, miRNAs can act as oncomirs or tumor suppressors, it can be applied in therapeutic application such as cancer.
For the cancer treatment, radiotherapy, surgery and chemotherapy are the three primary modalities. Approximately 50% cancer patients will receive the radiation treatment including head and neck cancer and colorectal cancer. However, in some case, the cancer will recurrent with radioresistance and cause poor outcome. We try to develop the miRNAs cohort profiles as prognostic biomarkers for cancer patients. The results of this project could impact the survival rate for cancer patients and improve the quality of life.
The detection method for miRNA expression usually rely on quantitative RT-PCR. This method has been applied in many research of DNA or mRNA expression. we utilized the blood samples from head and neck cancer and colorectal cancer patients which provide from landseed hospital. There are twenty-nine cancer patient’s plasma samples, including nineteen patients who resulted in the good response to radiation therapy, and ten patients who resulted in the poor response in radiation therapy samples. We characterized a group of miRNAs which be involved in radioresistant by using RT-qPCR. Moreover, We used those candidate miRNAs to test the sensitivity, specificity and accuracy. The results discovered two sets of miRNAs. One is the diagnosis set , which can predict the good response or poor response before radiation therapy perform and the other is prognosis set which can predict the good response or poor response after radiation therapy, The accuracy of this diagnosis set is about 87% and the accuracy of prognosis set is about 75%. We hope the result from this study can be apply to clinical diagnosis and prognosis, and give some benefit to cancer patients in the future.
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