微型RNA又稱MicroRNAs (miRNAs)是一群高度保守非編碼的RNA，長度約為18~25個核苷酸所組成，目前已經被證實微型RNA可以透過後轉錄調控的方式，調控基因的表現，因此微型RNA表現也影響細胞的許多功能。最近的一些研究中指出，以微型RNA的表現為基礎的生物標記，會比傳統mRNA的表現或蛋白質的表現為基礎更具有潛力。另外因為微型RNA可以同時扮演抑癌基因的角色，或是致癌基因的角色，所以微型RNA很有機會用於癌症治療。 目前癌症的治療方法主要有三種，分別是放射線治療與化學治療和手術，大約有50%的癌症病患需要接受放射線治療，其中也包含頭頸癌與大腸直腸癌的病患，但是在一些案例中會有部份腫瘤產生對放射治療的抗性，在治療後容易出現復發的情形，導致預後狀況不佳。因此我們希望可以開發一套以偵測微型RNA為基礎，預測癌症病患對放射線治療反應好壞的生物標記，這個研究的結果可以影響癌症病患的存活率，並且改善生活品質。 目前研究微型RNA的表現量的方法，主要是依賴即時定量PCR方法，此種方法其實也早已被大量應用在做DNA及mRNA基因定量的研究之中。藉由壢新醫院提供頭頸癌及大腸直腸癌的病患血液為研究對象，其中包含對放射線治療反應良好的19位病患，以及對放射線治療反應不良的10位共29位病患，先利用高通量即時定量PCR方法來篩選出一群與放射線治療抗性相關的微型RNA，再進一步對這一群微型RNA做驗證，了解這些候選的微型RNA，對於判斷放射線治療反應好壞的靈敏度與特異度和正確率。最後此研究找出了兩組微型RNA的組合(panel)，一組用於治療前病患的診斷，能預測放射線治療反應良好與不良，正確率約為85%，和另一組用於治療後病患的預後，正確率約為80%。期望此研究的成果未來能夠直接應用在臨床做診斷，及預測癌症放射線治療預後，並對癌症病患有實質上的幫助。 ;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.
