臺灣博碩士論文加值系統

口腔癌最主要的型態為鱗狀上皮細胞癌，是全球最常見的癌症之一，且其死亡率仍高居不下，因此希望可以找到好的腫瘤標記物顯示提升口腔癌之檢測及監測達到良好的治療結果。近年來，微型核糖核酸(microRNA,
miRNA)被發現會參與人類癌症的致病機轉，且能穩定存在於生物體液中，確立 miRNAs可作為生物標記物應用於臨床上。為了找出具臨床運用價值的 miRNAs作為診斷或預後的口腔癌標記分子，分析實驗室先前建立的兩組 miRNA微陣列生物晶片數據，選擇了 miR-10b、miR-196b、miR-548b、miR-622b及 miR-638進行研究。為因應早期診斷以及快速篩檢的需求，本研究將發展分泌型 miRNAs的偵測方法，以口腔潤洗液收集病患唾液作為檢體，在 55健康個體、10個白斑病人以及 90個口腔癌病患的臨床檢體偵測前述具潛力的 5個候選 miRNAs。將實驗結果利用 Mann –WhitneyU分析後，發現與健康個體相比， miR-10b、miR-196b、miR-548b、miR-622b及 miR-638的表現量在口腔癌病患的口腔潤洗液檢體中皆有顯著性上升 (p < 0.001, AUC = 0.659 ~ 0.803)。除此之外，也發現 miR-10b、miR-196b及miR-622在白斑病患中會高度表現( p<0.001,AUC=0.840,0.889 and 0.782)。為得到更好偵測鑒別疾病的能力，將 miR-10b、miR-196b、miR-548b、miR-622b及 miR-638做統合模組分析，發現其區分口腔癌變病患中的 AUC值高達 0.910，敏感度及專一性皆高於七成五。綜合以上結果，以非侵入性的口腔潤洗液檢體發展出的 miRNA統合模組 (combined panel)具有高度潛力可應用於早期口腔癌篩檢。

Oral cancer is one of the most common malignance in the world, yet, it is short of useful tumor marker for clinical application. MicroRNAs (miRNAs) which have been reported participating in various cancer pathogenesis are stable and detectable in circulating compartment, further reveal their biomarker potential. Previously, our laboratory has determined specific miRNA profile associated with oral cancer. In this study, we selected 5 candidates to examine their potential of being oral cancer biomarkers in saliva of mouthwash, the non-invasive and easily obtained specimen for oral cancer screening. Total of 155 samples were collected, including 90 from oral cancer patients, 10 from patients with pre-cancer lesions, and 55 from healthy individuals. The RT-qPCR based method was used to determine miRNA levels in mouth wash samples. Results showed that the levels of miR-10b, miR-196b, miR-548b, miR-622 and miR-638 were all remarkably increased in saliva from oral cancer patients that from the healthy subjects, with 3 ~ 16 fold elevations (p < 0.001, AUC = 0.659 ~ 0.803). Furthermore, miR-10, miR-196b and miR-622 were also significantly up-regulated in saliva from the patients with pre-cancer lesions (p < 0.001, AUC = 0.782 ~ 0.889). The combination of all miRNAs obtained outstanding discriminative power for oral cancer (p < 0.0001, AUC = 0.910). After setting cutoff, the predicted diagnostic sensitivity and specificity were 80% and 83%. In conclusion, our study using mouth wash samples suggests a combined panel of miRNA in saliva possess high potential as biomarker for early detection of oral cancer.

指導教授推薦書
口試委員審定書
致謝 iii
摘要 iv
Abstract v
Content vi
Introduction 1
Oral Cancer 1
Biogenesis and mechanism of miRNAs 2
MicroRNAs in cancer 3
MiRNA in body fluids 4
Study aim 7
Materials and Methods 8
Patients and the determination of mouthwash miRNA 8
RNA extraction 8
Quantitative reverse-transcription PCR for miRNA validation 9
Statistical Analyses 9
Result 11
Identification of significant miRNAs by miRNA microarray profiling for discovering potential candidates 11
Establishment of mouthwash miRNAs detection method 11
Detection of miRNAs in mouthwash 13
Candidate miRNA expressions in clinical mouthwash samples 14
Validation of miRNA expressions in clinical mouthwash samples 14
Combination of miRNAs for strengthening discriminative power 15
Discussion 17
Reference 22
Tables 26
Figures 30

Table content
Table 1. The statistical data of ten leading cancers motility in Taiwan. ..................... 27
Table 2. The relative expression levels of miRNAs, and fold change, p-value, AUCs
(area under the ROC curves) with 95% CI, fold change are listed. ............................. 28
Table 3. Sensitivity and specificity with 95% CI of miRNAs. ................................... 29
Table 4. The AUCs (area under the ROC curves), p-value and sensitivity and
specificity with 95% CI for miRNA Panel. ................................................................. 30


Figure content
Figure 1. Validation of miR-10b, miR-148b, miR-196a and miR-196b in 6 oral
cancer cell lines and 5 normal oral keratinocytes by quantitative PCR. ...................... 31
Figure 2. Validation of miR-548b, miR-622 and miR-638, which were selected as
candidates in 3 highly invasive sublines and 3 parental cell lines by quantitative PCR.
...................................................................................................................................... 32
Figure 3. Spike-in real time PCR assay was performed with 15 specimens. .............. 33
Figure 4. (A) Validation of miRNAs by RT-qPCR and (B) optimization of the
method in mouthwash samples from 2 patients with oral cancer and 2 normal
individuals. ................................................................................................................... 34
Figure 5. Relative fold change expression levels of (A) miR-10b, (B) miR-148b, (C)
miR-196a, (D) miR-196b, (E) miR-548b, (F) miR-622 and (G) miR-638 in patients
with oral cancer and normal individuals. The p-values of 6 miRNAs were significant
excluding that of miR-196a. The dot at the center of violin plot represents the mean
expression for each miRNA. ........................................................................................ 35
Figure 6. Relative expression levels and significance of miR-10b in different groups
was shown. ................................................................................................................... 36
Figure 7. Relative expression levels and significance of miR-196b in different groups
was shown. ................................................................................................................... 38
Figure 8. Relative expression levels and significance of miR-548b in different groups
was shown. ................................................................................................................... 40
Figure 9. Relative expression levels and significance of miR-622 in different groups
was shown. ................................................................................................................... 42
Figure 10. Relative expression levels and significance of miR-638 in different groups
was shown. ................................................................................................................... 44
Figure 11. Performance of receiver operating characteristic curves and the area under
curve of the ROC. miRNA Panel derived by logistic regression in distinguishing
patients with oral cancer from healthy subjects. ....................................................... 46
Figure 12. Performance of receiver operating characteristic curves and the area under
curve of the ROC. miRNA Panel derived by logistic regression in distinguishing
patients with disease (oral cancer + pre-cancer lesions) from healthy subjects. ......... 47

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