miRNA作为肿瘤标记物在大肠癌及其癌前病变中的发现及验证
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摘要
前言
大肠癌是全球主要的致死性肿瘤之一。早期发现肿瘤对改善肠癌的治疗效果有显著意义。
理想的肿瘤标记物,既要具备高度特异性和敏感性,又要易于测定。MicroRNA (miRNA),是一种18-25nt的非编码RNA,完全符合上述要求。有证据表明,miRNA在肿瘤发生中起着类似于癌基因或抑癌基因的重要作用,并可以被运用到肿瘤的诊断和对治疗的监测中。此外,与mRNA相比,miRNA在体外更稳定,在体内代谢周期更长,因而更适合作为肿瘤标记物。
目前,绝大多数对miRNA表达进行的研究所用的材料不外乎两种组织,即培养细胞或整块的肿瘤组织。培养细胞由于外环境改变而必然导致其表达谱的改变,而整块肿瘤组织则由于组织中包含了多种细胞(如间质细胞、浸润的淋巴细胞和新生血管等)并且无法对不同组织中的各种细胞比例进行控制而使获得的表达谱无法真实代表肿瘤细胞的表达特征。激光捕获显微切割技术(Laser capture microdissection, LCM)成功地解决了分子生物学研究中组织异质性的问题,即可以迅速、准确地选择并捕获组织中的单一种类的靶细胞,甚至于单个细胞。目前,该技术已经被运用到DNA分析和基因表达的研究中。然而该技术尚未在实体肿瘤的miRNA分子标记物的发现中得以运用。
本课题对LCM的组织处理方法进行改良,以提高RNA的质与量,并符合基因芯片检测的要求。将LCM与全基因组miRNA检测相结合,探寻大肠癌多步骤转化演进过程中的miRNA分子标记物。用石蜡标本对上述有表达差异的miRNA在手术切除和肠镜活检组织中进行进一步的验证,旨在明确其在大肠癌早期病变的临床诊断中的应用前景。
第一部分改良显微切割组织处理技术在细胞种类特异性的miRNA基因表达检测中的应用
目的：对显微切割组织处理技术进行改良,并将其运用到细胞种类特异性的miRNA基因表达检测中。
方法：通过改变组织处理方法,分别设计了六种不同的实验步骤。用mirVana miRNA isolation kit试剂盒抽提总RNA, NanoDrop 1000 Spectrophotometer测定总RNA浓度。通过RNA 6000 Pico LabChip kit用2100 Bioanalyzer进行RNA质量监控。对运用最优化的LCM样本处理步骤所获取的101例大肠手术切除冰冻组织上皮细胞(正常组织43例,腺瘤14例和腺癌44例)进行RNA质量的评估,并用配对t检验进行显著性分析。此外,用LCM从18例大肠组织中(正常组织6例,腺瘤6例和腺癌6例)分离出上皮细胞和间质细胞,运用Agilent最新芯片技术对样本进行全基因组miRNA表达分析。用GeneSpring GX10软件进行Quantile数据标准化。运用方差(ANOVA)和聚类分析(Hierarchical clustering)进行miRNA基因表达的差异性分析。
结果：酒精固定2小时能最大程度的提高RNA的质(1.8倍,p=0.0014)与量(1.5倍,p=0.066)。反应RNA质量的RNA完整指数(RNA integrity number, RIN)在显微切割的大肠组织中分别是：正常组织(n=43)为5.2±1.5(均值±SD),腺瘤(n=14)为5.7±1.1(均值±SD),腺癌(n=44)为7.2±1.2(均值±SD)。用Agilent miRNA芯片检测LCM获取的18例(正常组织6例,腺瘤6例和腺癌6例)大肠组织的上皮和间质细胞发现,有51个miRNA在大肠组织上皮和间质细胞之间存在显著的差异性表达(p<=0.001)。此外,有26个miRNA在大肠组织上皮细胞中的特异性表达能把腺瘤从正常组织和腺癌中区分出来。而间质细胞和混合细胞中的miRNA表达则不能区分腺瘤和正常组织。
结论：通过改良激光捕获显微切割(LCM)的组织处理技术,提高了总RNA的质与量,使之符合芯片测试的要求。实验验证LCM结合全基因组miRNA分析技术在探寻细胞特异性miRNA生物标记物过程中的可行性和必要性。
第二部分大肠粘膜上皮转化演进过程中miRNA肿瘤标记物的发现
目的：从LCM获取的上皮细胞中发现大肠癌各病变阶段的miRNA特异性表达。
方法：运用优化的LCM组织处理方法从225例正常肠上皮、癌前病变和浸润癌手术切除冰冻组织中获取纯净的上皮细胞。用Agilent最新芯片技术对上述225例标本进行全基因组miRNA表达分析,并用荧光实时定量RT-PCR (Taqman)加以验证。用GeneSpring GX10软件进行Quantile数据标准化。用未配对t检验(Benjamini-Hochbergt)和方差分析(ANOVA)对miRNA芯片数据进行显著性差异性分析。用聚类分析(Hierarchical clustering)进行miRNA基因表达差异的分类。用三种不同的芯片预测分析方法(prediction analysis of microarray, genetic algorithm-SVM和one-loop Naive Bayesian)对芯片数据进行预测性分析。
结果：在大肠粘膜上皮转化和演进过程中,共有42个miRNA的表达与大肠癌不同阶段病变显著相关。我们发现miRNA能将肠癌在正常上皮-腺瘤-腺癌的转化和演进过程中分成两个水平分类组：第一水平分类组中20个miRNA可以预测非肿瘤和肿瘤,最高准确性达96.9%；第二水平分类组中14个miRNA可以预测腺瘤和腺癌,最高准确性达99.9%。荧光实时定量RT-PCR和miRNA芯片之间相关性(R)平均为0.980。
结论：miRNA表达与大肠癌肿瘤病理分期有显著的相关性。实验揭示,miRNA可以准确预测肿瘤与非肿瘤及进一步区分腺瘤与腺癌组织。其中部分miRNA在大肠癌的发病机制中可能有一定预示作用。
第三部分大肠癌和癌前病变中miRNA肿瘤标记物的验证
目的：验证大肠癌和癌前病变中的候选miRNA肿瘤标记物。
方法：运用荧光实时定量RT-PCR对14个候选的miRNA肿瘤标记物在185例石蜡标本中进行验证,其中包括124例手术切除组织和61例肠镜活检组织。用小RNA U47进行数据标准化。用未配对t检验对miRNA在大肠癌和癌前病变中的表达进行显著性差异性分析。受试者工作特征曲线(receive operating characteristic curve, ROC)来评估候选miRNA肿瘤标记物在区分大肠癌和癌前病变中的诊断价值。多元相关分析(stepwise logistic regression analysis)评估多个候选miRNA肿瘤标记物协同区分大肠癌和癌前病变的诊断价值。
结果：候选的miRNA肿瘤标记物能鉴别良性肿瘤和恶性肿瘤及高级别上皮内瘤变和早期大肠浸润癌(Dukes'A)。7个miRNA (hsa-miR-125b, hsa-miR-7, hsa-miR-218, hsa-miR-375, hsa-miR-424, hsa-miR-92a, hsa-miR-99a)能在手术切除的石蜡组织中区分良性肿瘤与恶性肿瘤及高级别上皮内瘤变与早期肠癌,其中hsa-miRNA-92a与hsa-miRNA-375组合鉴别诊断高级别上皮内瘤变和早期肠癌的敏感性为95%,特异性为88%。除此之外,这7个miRNA还能在肠镜活检组织中鉴别高级别上皮内瘤变和大肠浸润癌并,结果与术后病理诊断一致。其中hsa-miR-92a具有最高敏感性达93%;hsa-miR-7具有最高特异性达94%。
结论：实验验证7个miRNA肿瘤标记物能鉴别良性肿瘤和恶性肿瘤及高级别上皮内瘤变和早期大肠浸润癌(Dukes'A)。除此之外,这7个miRNA还能在肠镜活检组织中鉴别高级别上皮内瘤变和大肠浸润癌并与术后病理诊断一致。
Introduction
Colorectal adenocarcinoma is a major cause of cancer mortality worldwide. Detecting the cancer at early stages has significant therapeutic values. Therefore, there is an unmet need to identify new class of biomarkers of colorectal early lesions and colorectal adenocarcinoma.
Ideal tumor markers shall have good sensitivity, specificity and can be easy to detect. MicroRNA (miRNA),18-to 25-nucleotides, noncoding RNA molecules, has met the criteria mentioned above. Demonstrated evidences show that miRNAs involve in the regulation of carcinogenesis and function as both tumour suppressors and oncogenes. Furthermore, miRNAs have major potentials as diagnostic and prognostic biomarkers, as they strongly associate with the clinical outcomes. Additionally, miRNAs have advantages over mRNAs as cancer biomarkers, since they are very stable in vitro and long-lived in vivo.
Molecular profiling of clinical tissue specimens is frequently complicated by their cellular heterogeneity. Laser capture microdissection (LCM) has successfully been used to tackle this problem by isolating pure cell populations from tissue sections. However, the quantity and quality of material recovered after LCM is often still limited. Therefore, combination of LCM and whole genome analysis has not been widely applied to discover miRNA biomarkers in solid tumors. So far, the large majority of published miRNA expression studies utilized whole tumor tissues without separating the truly transformed cancerous cells from those other cell types commonly present within a solid tumor. Analysis of such complex tissues could conceal the specific signature of the particular cell type of interest.
In this study, we improved tissue preparation for LCM and combined LCM with genome-wide miRNA analysis to discovery the potential miRNA biomarkers at the multisteps of the colorectal carcinogenesis using frozen surgical specimens. We evaluated the miRNA expression profiles of colorectal adenocarcinoma and the precancerous lesions to study their potential role in the tumor formation and molecular classification in colorectal carcinoma. We then validated the candidate miRNA biomarkers in the colorectal adenocarcinoma and the precancerous lesions using FFPE (formalin-fixed, paraffin-embedded) surgical specimens. We finally explored the clinical utilities of the validated miRNA biomarkers for early cancer detection in FFPE biopsy tissues from colonoscopy.
PartⅠImprovement of tissue preparation for laser capture microdissection: application for cell type-specific miRNA expression profiling
Objective:Improve the tissue preparation for laser capture microdissection in order that this technique can be applied for cell type-specific miRNA expression profiling.
Methods:Six different experiments on tissue preparations were performed. Total RNA was extracted by using mirVana miRNA isolation kit. The concentration was quantified by NanoDrop 1000 Spectrophotometer. The quality control of RNA was performed by a 2100 Bioanalyzer using the RNA 6000 Pico LabChip kit. Using the improved protocol for tissue preparation, laser capture microdissection (LCM) was performed on 101 frozen surgical specimens of colorectal tissues (n=43 normal, n=14 adenomas and n= 44 carcinomas) to assess the RNA quality. Paired t-test was performed for significance analysis. Human miRNA microarrays were used to compare the expression profiles of 18 colorectal tissues (n=6 normal, n=6 adenomas and n=6 carcinomas) between LCM selected pure epithelial cells versus stromal cells. GeneSpring GX10 software was applied for quantile normalization. Unpaired t-test with Benjamini-Hochberg correction and one-way analysis of variance (ANOVA) were used for differential miRNA expression analysis. Hierarchical clustering was performed with Pearson correlation using the differentially expressed miRNAs.
Results:We found that the ethanol fixation of tissue sections for 2 hours had the maximum improvement of RNA quality (1.8 fold, p=0.0014) and quantity (1.5 fold, p=0.066). Overall, the quality (RNA integrity number, RIN) for the microdissected colorectal tissues was 5.2±1.5 (average±SD) for normal (n=43),5.7±1.1 for adenomas (n=14) and 7.2±1.2 for carcinomas (n=44). We then compared miRNA expression profiles of 18 colorectal tissues (6 normal,6 adenomas and 6 carcinomas) between LCM selected pure epithelial cells versus stromal cells using Agilent miRNA microarrays. We identified 51 differentially expressed miRNAs (p<=0.001) between these two cell types. Additionally, we found that 26 miRNAs in the epithelial cells could differentiate adenomas from normal and carcinomas. However, the miRNAs in the stromal and mixed cells could not separate adenomas from normal tissues.
Conclusions:The improvement of the tissue preparation for laser capture microdissection can increase the quality and quantity of RNA, which meet the needs of cell type-specific miRNA expression profiling. Our study demonstrates the feasibility and potential power of discovering cell type-specific miRNA biomarkers in complex tissue using combination of LCM with genome-wide miRNA analysis.
PartⅡDiscovery of miRNA biomarkers in the epithelial cells during the transformation and progression of colorectal cancer
Objective:Discover miRNA biomarkers in LCM-selected epithelial cells covered every stage of colorectal carcinogenesis.
Methods:The optimized LCM protocol was applied to isolate pure epithelial cells from 225 frozen surgical specimens of colorectal normal, precancerous lesion and invasive carcinoma tissues. Genome-wide miRNA analysis was performed to determine the expression profiles in these LCM-selected epithelial cells. GeneSpring GX10 software was used for quantile normalization. Unpaired t-test with Benjamini-Hochberg correction and one-way analysis of variance (ANOVA) were applied for the differential expression analysis. Hierarchical clustering was performed with Pearson correlation using the differentially expressed miRNAs. Three prediction supervised classification algorithms (prediction analysis of microarray, genetic algorithm-SVM and one-loop Naive Bayesian) were employed to analyze the data acquired on the microarrays. Subsequently, quantitative RT-PCR was used to verfy the miRNA expression profiles.
Results:42 miRNA signatures were discovered in the transformation and progression of colorectal cancer. Two classifiers of miRNA signatures were identified for predicting colorectal cancer. A minimal set of 20 miRNAs could distinct non-neoplasm polyps and neoplasm polyps with the highest accuracy of 96.9%, while another minimal set of 14 miRNAs could discriminate benign neoplasm from malignant neoplasm with the highest accuracy of 99.9%. The average quantitative correlation (R) of fold change between Agilent miRNA microarrays and quantitative RT-PCR was 0.980.
Conclusions:The candidate miRNA biomarkers were discovered in the transformation and progression of colorectal cancer. Such biomarkers could accurately discriminate non-neoplasm polyps from neoplasm polyps and benign neoplasm from malignant neoplasm. The predicted outcomes using the miRNA classifiers were well consistent with the pathological diagnosis.
PartⅢValidation of the candidate miRNA biomarkers in discriminating colorectal benign neoplasm from malignant neoplasm
Objective:Validate the candidate miRNA biomarkers in discriminating colorectal benign neoplasm from malignant neoplasm.
Methods:Quantitative RT-PCR was performed on 14 candidate miRNA biomarkers that could discriminate benign neoplasm from malignant neoplasm using 185 FFPE colorectal tissue specimens, including 124 surgical specimens and 61 biopsy sepcimens. Unpaired t-test was performed for significance analysis. Receiver operating characteristic (ROC) curve analysis was performed to determine the specificity and sensitivity of individual miRNA as diagnostic biomarkers. Stepwise logistic regression analysis was performed to determine the specificity and sensitivity of combined miRNAs as diagnostic biomarkers.
Results:The early colorectal carcinomas could be distinguished from benign tumors by the validated miRNA biomarkers. Of the 14 candidate miRNA biomarkers,7 (hsa-miR-125b, hsa-miR-7, hsa-miR-218, hsa-miR-375, hsa-miR-424, hsa-miR-92a, hsa-miR-99a) were validated for distincting benign neoplasm from malignant neoplasm in the FFPE surgical specimens. The combination of hsa-miR-92a and hsa-miR-375 yielded the sensitivity of 95% and spesitivity of 88% in discriminating high-grade intraepithelial neoplasm from Dukes'A carcinoma. Furthermore, these miRNAs have the ability to differentiate the high-grade intraepithelial neoplasm from carcinomas in the biopsy tissues from colonoscopy with sensitivity of 93% by hsa-miR-92a and spesificity of 94% by hsa-miR-7.
Conclusions:The early colorectal carcinoma could be accurately discriminated from benign tumor by 7 validated miRNA biomarkers. Colorectal carcinomas could be distincted from the high-grade intraepithelial neoplasm in the colonoscopy biopsy tissues using these validatd miRNA biomarkers.
大肠癌是全球主要的致死性肿瘤之一。早期发现肿瘤对改善肠癌的治疗效果有显著意义。
理想的肿瘤标记物,既要具备高度特异性和敏感性,又要易于测定。MicroRNA (miRNA),是一种18-25nt的非编码RNA,完全符合上述要求。有证据表明,miRNA在肿瘤发生中起着类似于癌基因或抑癌基因的重要作用,并可以被运用到肿瘤的诊断和对治疗的监测中。此外,与mRNA相比,miRNA在体外更稳定,在体内代谢周期更长,因而更适合作为肿瘤标记物。
目前,绝大多数对miRNA表达进行的研究所用的材料不外乎两种组织,即培养细胞或整块的肿瘤组织。培养细胞由于外环境改变而必然导致其表达谱的改变,而整块肿瘤组织则由于组织中包含了多种细胞(如间质细胞、浸润的淋巴细胞和新生血管等)并且无法对不同组织中的各种细胞比例进行控制而使获得的表达谱无法真实代表肿瘤细胞的表达特征。激光捕获显微切割技术(Laser capture microdissection, LCM)成功地解决了分子生物学研究中组织异质性的问题,即可以迅速、准确地选择并捕获组织中的单一种类的靶细胞,甚至于单个细胞。目前,该技术已经被运用到DNA分析和基因表达的研究中。然而该技术尚未在实体肿瘤的miRNA分子标记物的发现中得以运用。
本课题对LCM的组织处理方法进行改良,以提高RNA的质与量,并符合基因芯片检测的要求。将LCM与全基因组miRNA检测相结合,探寻大肠癌多步骤转化演进过程中的miRNA分子标记物。用石蜡标本对上述有表达差异的miRNA在手术切除和肠镜活检组织中进行进一步的验证,旨在明确其在大肠癌早期病变的临床诊断中的应用前景。
第一部分改良显微切割组织处理技术在细胞种类特异性的miRNA基因表达检测中的应用
目的：对显微切割组织处理技术进行改良,并将其运用到细胞种类特异性的miRNA基因表达检测中。
方法：通过改变组织处理方法,分别设计了六种不同的实验步骤。用mirVana miRNA isolation kit试剂盒抽提总RNA, NanoDrop 1000 Spectrophotometer测定总RNA浓度。通过RNA 6000 Pico LabChip kit用2100 Bioanalyzer进行RNA质量监控。对运用最优化的LCM样本处理步骤所获取的101例大肠手术切除冰冻组织上皮细胞(正常组织43例,腺瘤14例和腺癌44例)进行RNA质量的评估,并用配对t检验进行显著性分析。此外,用LCM从18例大肠组织中(正常组织6例,腺瘤6例和腺癌6例)分离出上皮细胞和间质细胞,运用Agilent最新芯片技术对样本进行全基因组miRNA表达分析。用GeneSpring GX10软件进行Quantile数据标准化。运用方差(ANOVA)和聚类分析(Hierarchical clustering)进行miRNA基因表达的差异性分析。
结果：酒精固定2小时能最大程度的提高RNA的质(1.8倍,p=0.0014)与量(1.5倍,p=0.066)。反应RNA质量的RNA完整指数(RNA integrity number, RIN)在显微切割的大肠组织中分别是：正常组织(n=43)为5.2±1.5(均值±SD),腺瘤(n=14)为5.7±1.1(均值±SD),腺癌(n=44)为7.2±1.2(均值±SD)。用Agilent miRNA芯片检测LCM获取的18例(正常组织6例,腺瘤6例和腺癌6例)大肠组织的上皮和间质细胞发现,有51个miRNA在大肠组织上皮和间质细胞之间存在显著的差异性表达(p<=0.001)。此外,有26个miRNA在大肠组织上皮细胞中的特异性表达能把腺瘤从正常组织和腺癌中区分出来。而间质细胞和混合细胞中的miRNA表达则不能区分腺瘤和正常组织。
结论：通过改良激光捕获显微切割(LCM)的组织处理技术,提高了总RNA的质与量,使之符合芯片测试的要求。实验验证LCM结合全基因组miRNA分析技术在探寻细胞特异性miRNA生物标记物过程中的可行性和必要性。
第二部分大肠粘膜上皮转化演进过程中miRNA肿瘤标记物的发现
目的：从LCM获取的上皮细胞中发现大肠癌各病变阶段的miRNA特异性表达。
方法：运用优化的LCM组织处理方法从225例正常肠上皮、癌前病变和浸润癌手术切除冰冻组织中获取纯净的上皮细胞。用Agilent最新芯片技术对上述225例标本进行全基因组miRNA表达分析,并用荧光实时定量RT-PCR (Taqman)加以验证。用GeneSpring GX10软件进行Quantile数据标准化。用未配对t检验(Benjamini-Hochbergt)和方差分析(ANOVA)对miRNA芯片数据进行显著性差异性分析。用聚类分析(Hierarchical clustering)进行miRNA基因表达差异的分类。用三种不同的芯片预测分析方法(prediction analysis of microarray, genetic algorithm-SVM和one-loop Naive Bayesian)对芯片数据进行预测性分析。
结果：在大肠粘膜上皮转化和演进过程中,共有42个miRNA的表达与大肠癌不同阶段病变显著相关。我们发现miRNA能将肠癌在正常上皮-腺瘤-腺癌的转化和演进过程中分成两个水平分类组：第一水平分类组中20个miRNA可以预测非肿瘤和肿瘤,最高准确性达96.9%；第二水平分类组中14个miRNA可以预测腺瘤和腺癌,最高准确性达99.9%。荧光实时定量RT-PCR和miRNA芯片之间相关性(R)平均为0.980。
结论：miRNA表达与大肠癌肿瘤病理分期有显著的相关性。实验揭示,miRNA可以准确预测肿瘤与非肿瘤及进一步区分腺瘤与腺癌组织。其中部分miRNA在大肠癌的发病机制中可能有一定预示作用。
第三部分大肠癌和癌前病变中miRNA肿瘤标记物的验证
目的：验证大肠癌和癌前病变中的候选miRNA肿瘤标记物。
方法：运用荧光实时定量RT-PCR对14个候选的miRNA肿瘤标记物在185例石蜡标本中进行验证,其中包括124例手术切除组织和61例肠镜活检组织。用小RNA U47进行数据标准化。用未配对t检验对miRNA在大肠癌和癌前病变中的表达进行显著性差异性分析。受试者工作特征曲线(receive operating characteristic curve, ROC)来评估候选miRNA肿瘤标记物在区分大肠癌和癌前病变中的诊断价值。多元相关分析(stepwise logistic regression analysis)评估多个候选miRNA肿瘤标记物协同区分大肠癌和癌前病变的诊断价值。
结果：候选的miRNA肿瘤标记物能鉴别良性肿瘤和恶性肿瘤及高级别上皮内瘤变和早期大肠浸润癌(Dukes'A)。7个miRNA (hsa-miR-125b, hsa-miR-7, hsa-miR-218, hsa-miR-375, hsa-miR-424, hsa-miR-92a, hsa-miR-99a)能在手术切除的石蜡组织中区分良性肿瘤与恶性肿瘤及高级别上皮内瘤变与早期肠癌,其中hsa-miRNA-92a与hsa-miRNA-375组合鉴别诊断高级别上皮内瘤变和早期肠癌的敏感性为95%,特异性为88%。除此之外,这7个miRNA还能在肠镜活检组织中鉴别高级别上皮内瘤变和大肠浸润癌并,结果与术后病理诊断一致。其中hsa-miR-92a具有最高敏感性达93%;hsa-miR-7具有最高特异性达94%。
结论：实验验证7个miRNA肿瘤标记物能鉴别良性肿瘤和恶性肿瘤及高级别上皮内瘤变和早期大肠浸润癌(Dukes'A)。除此之外,这7个miRNA还能在肠镜活检组织中鉴别高级别上皮内瘤变和大肠浸润癌并与术后病理诊断一致。
Introduction
Colorectal adenocarcinoma is a major cause of cancer mortality worldwide. Detecting the cancer at early stages has significant therapeutic values. Therefore, there is an unmet need to identify new class of biomarkers of colorectal early lesions and colorectal adenocarcinoma.
Ideal tumor markers shall have good sensitivity, specificity and can be easy to detect. MicroRNA (miRNA),18-to 25-nucleotides, noncoding RNA molecules, has met the criteria mentioned above. Demonstrated evidences show that miRNAs involve in the regulation of carcinogenesis and function as both tumour suppressors and oncogenes. Furthermore, miRNAs have major potentials as diagnostic and prognostic biomarkers, as they strongly associate with the clinical outcomes. Additionally, miRNAs have advantages over mRNAs as cancer biomarkers, since they are very stable in vitro and long-lived in vivo.
Molecular profiling of clinical tissue specimens is frequently complicated by their cellular heterogeneity. Laser capture microdissection (LCM) has successfully been used to tackle this problem by isolating pure cell populations from tissue sections. However, the quantity and quality of material recovered after LCM is often still limited. Therefore, combination of LCM and whole genome analysis has not been widely applied to discover miRNA biomarkers in solid tumors. So far, the large majority of published miRNA expression studies utilized whole tumor tissues without separating the truly transformed cancerous cells from those other cell types commonly present within a solid tumor. Analysis of such complex tissues could conceal the specific signature of the particular cell type of interest.
In this study, we improved tissue preparation for LCM and combined LCM with genome-wide miRNA analysis to discovery the potential miRNA biomarkers at the multisteps of the colorectal carcinogenesis using frozen surgical specimens. We evaluated the miRNA expression profiles of colorectal adenocarcinoma and the precancerous lesions to study their potential role in the tumor formation and molecular classification in colorectal carcinoma. We then validated the candidate miRNA biomarkers in the colorectal adenocarcinoma and the precancerous lesions using FFPE (formalin-fixed, paraffin-embedded) surgical specimens. We finally explored the clinical utilities of the validated miRNA biomarkers for early cancer detection in FFPE biopsy tissues from colonoscopy.
PartⅠImprovement of tissue preparation for laser capture microdissection: application for cell type-specific miRNA expression profiling
Objective:Improve the tissue preparation for laser capture microdissection in order that this technique can be applied for cell type-specific miRNA expression profiling.
Methods:Six different experiments on tissue preparations were performed. Total RNA was extracted by using mirVana miRNA isolation kit. The concentration was quantified by NanoDrop 1000 Spectrophotometer. The quality control of RNA was performed by a 2100 Bioanalyzer using the RNA 6000 Pico LabChip kit. Using the improved protocol for tissue preparation, laser capture microdissection (LCM) was performed on 101 frozen surgical specimens of colorectal tissues (n=43 normal, n=14 adenomas and n= 44 carcinomas) to assess the RNA quality. Paired t-test was performed for significance analysis. Human miRNA microarrays were used to compare the expression profiles of 18 colorectal tissues (n=6 normal, n=6 adenomas and n=6 carcinomas) between LCM selected pure epithelial cells versus stromal cells. GeneSpring GX10 software was applied for quantile normalization. Unpaired t-test with Benjamini-Hochberg correction and one-way analysis of variance (ANOVA) were used for differential miRNA expression analysis. Hierarchical clustering was performed with Pearson correlation using the differentially expressed miRNAs.
Results:We found that the ethanol fixation of tissue sections for 2 hours had the maximum improvement of RNA quality (1.8 fold, p=0.0014) and quantity (1.5 fold, p=0.066). Overall, the quality (RNA integrity number, RIN) for the microdissected colorectal tissues was 5.2±1.5 (average±SD) for normal (n=43),5.7±1.1 for adenomas (n=14) and 7.2±1.2 for carcinomas (n=44). We then compared miRNA expression profiles of 18 colorectal tissues (6 normal,6 adenomas and 6 carcinomas) between LCM selected pure epithelial cells versus stromal cells using Agilent miRNA microarrays. We identified 51 differentially expressed miRNAs (p<=0.001) between these two cell types. Additionally, we found that 26 miRNAs in the epithelial cells could differentiate adenomas from normal and carcinomas. However, the miRNAs in the stromal and mixed cells could not separate adenomas from normal tissues.
Conclusions:The improvement of the tissue preparation for laser capture microdissection can increase the quality and quantity of RNA, which meet the needs of cell type-specific miRNA expression profiling. Our study demonstrates the feasibility and potential power of discovering cell type-specific miRNA biomarkers in complex tissue using combination of LCM with genome-wide miRNA analysis.
PartⅡDiscovery of miRNA biomarkers in the epithelial cells during the transformation and progression of colorectal cancer
Objective:Discover miRNA biomarkers in LCM-selected epithelial cells covered every stage of colorectal carcinogenesis.
Methods:The optimized LCM protocol was applied to isolate pure epithelial cells from 225 frozen surgical specimens of colorectal normal, precancerous lesion and invasive carcinoma tissues. Genome-wide miRNA analysis was performed to determine the expression profiles in these LCM-selected epithelial cells. GeneSpring GX10 software was used for quantile normalization. Unpaired t-test with Benjamini-Hochberg correction and one-way analysis of variance (ANOVA) were applied for the differential expression analysis. Hierarchical clustering was performed with Pearson correlation using the differentially expressed miRNAs. Three prediction supervised classification algorithms (prediction analysis of microarray, genetic algorithm-SVM and one-loop Naive Bayesian) were employed to analyze the data acquired on the microarrays. Subsequently, quantitative RT-PCR was used to verfy the miRNA expression profiles.
Results:42 miRNA signatures were discovered in the transformation and progression of colorectal cancer. Two classifiers of miRNA signatures were identified for predicting colorectal cancer. A minimal set of 20 miRNAs could distinct non-neoplasm polyps and neoplasm polyps with the highest accuracy of 96.9%, while another minimal set of 14 miRNAs could discriminate benign neoplasm from malignant neoplasm with the highest accuracy of 99.9%. The average quantitative correlation (R) of fold change between Agilent miRNA microarrays and quantitative RT-PCR was 0.980.
Conclusions:The candidate miRNA biomarkers were discovered in the transformation and progression of colorectal cancer. Such biomarkers could accurately discriminate non-neoplasm polyps from neoplasm polyps and benign neoplasm from malignant neoplasm. The predicted outcomes using the miRNA classifiers were well consistent with the pathological diagnosis.
PartⅢValidation of the candidate miRNA biomarkers in discriminating colorectal benign neoplasm from malignant neoplasm
Objective:Validate the candidate miRNA biomarkers in discriminating colorectal benign neoplasm from malignant neoplasm.
Methods:Quantitative RT-PCR was performed on 14 candidate miRNA biomarkers that could discriminate benign neoplasm from malignant neoplasm using 185 FFPE colorectal tissue specimens, including 124 surgical specimens and 61 biopsy sepcimens. Unpaired t-test was performed for significance analysis. Receiver operating characteristic (ROC) curve analysis was performed to determine the specificity and sensitivity of individual miRNA as diagnostic biomarkers. Stepwise logistic regression analysis was performed to determine the specificity and sensitivity of combined miRNAs as diagnostic biomarkers.
Results:The early colorectal carcinomas could be distinguished from benign tumors by the validated miRNA biomarkers. Of the 14 candidate miRNA biomarkers,7 (hsa-miR-125b, hsa-miR-7, hsa-miR-218, hsa-miR-375, hsa-miR-424, hsa-miR-92a, hsa-miR-99a) were validated for distincting benign neoplasm from malignant neoplasm in the FFPE surgical specimens. The combination of hsa-miR-92a and hsa-miR-375 yielded the sensitivity of 95% and spesitivity of 88% in discriminating high-grade intraepithelial neoplasm from Dukes'A carcinoma. Furthermore, these miRNAs have the ability to differentiate the high-grade intraepithelial neoplasm from carcinomas in the biopsy tissues from colonoscopy with sensitivity of 93% by hsa-miR-92a and spesificity of 94% by hsa-miR-7.
Conclusions:The early colorectal carcinoma could be accurately discriminated from benign tumor by 7 validated miRNA biomarkers. Colorectal carcinomas could be distincted from the high-grade intraepithelial neoplasm in the colonoscopy biopsy tissues using these validatd miRNA biomarkers.
引文
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