Optimized high-throughput microRNA expression profiling provides novel biomarker assessment of clinical prostate and breast cancer biopsies.
Optimized high-throughput microRNA expression profiling provides novel biomarker assessment of clinical prostate and breast cancer biopsies.
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DOI：
10.1186/1476-4598-5-24
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发表时间：
2006-06-19
期刊：
影响因子：
37.3
通讯作者：
Haqq C
中科院分区：
文献类型：
--
作者：
Mattie MD;Benz CC;Bowers J;Sensinger K;Wong L;Scott GK;Fedele V;Ginzinger D;Getts R;Haqq C
最近的研究表明，microRNA（miRNAs）在机制上参与了各种人类恶性肿瘤的发展，这表明它们代表了一类有前途的新的癌症生物标志物。然而，先前报道的用于测量miRNA表达的方法消耗大量的组织，禁止从通常小的临床样品（例如乳腺癌或前列腺癌的切除或芯针活检）进行高通量miRNA分析。在这里，我们描述了一种新的组合的线性扩增和标记的miRNA的高灵敏度的表达微阵列分析只需要皮克量的纯化microRNA。来自两种不同前列腺癌细胞系的微阵列和qRT-PCR测量的miRNA水平的比较显示了两个平台之间的一致性（Pearson相关性R2 = 0.81）;并且使用来自乳腺癌和前列腺癌患者的临床核心和切除活检样品成功地证明了扩增、标记和微阵列平台的扩展。前列腺活检微阵列的无监督聚类分析将晚期和转移性前列腺癌与合并的正常前列腺样本和非恶性前驱病变分开。乳腺癌微阵列的无监督聚类显著区分了ErbB 2阳性/ER阴性、ErbB 2阳性/ER阳性和ErbB 2阴性/ER阳性乳腺癌表型（Fisher精确检验，p = 0.03）;同样，对这些微阵列谱的监督分析鉴定了区分ErbB 2阳性和ErbB 2阴性以及ER阳性和ER阴性乳腺癌的不同miRNA亚群，与其他临床重要参数（患者年龄、肿瘤大小、淋巴结状态和增殖指数）无关。总之，这些研究结果表明，优化的高通量microRNA表达谱提供了新的生物标志物鉴定，从典型的小临床样本，如乳腺癌和前列腺癌活检。
Recent studies indicate that microRNAs (miRNAs) are mechanistically involved in the development of various human malignancies, suggesting that they represent a promising new class of cancer biomarkers. However, previously reported methods for measuring miRNA expression consume large amounts of tissue, prohibiting high-throughput miRNA profiling from typically small clinical samples such as excision or core needle biopsies of breast or prostate cancer. Here we describe a novel combination of linear amplification and labeling of miRNA for highly sensitive expression microarray profiling requiring only picogram quantities of purified microRNA. Comparison of microarray and qRT-PCR measured miRNA levels from two different prostate cancer cell lines showed concordance between the two platforms (Pearson correlation R2 = 0.81); and extension of the amplification, labeling and microarray platform was successfully demonstrated using clinical core and excision biopsy samples from breast and prostate cancer patients. Unsupervised clustering analysis of the prostate biopsy microarrays separated advanced and metastatic prostate cancers from pooled normal prostatic samples and from a non-malignant precursor lesion. Unsupervised clustering of the breast cancer microarrays significantly distinguished ErbB2-positive/ER-negative, ErbB2-positive/ER-positive, and ErbB2-negative/ER-positive breast cancer phenotypes (Fisher exact test, p = 0.03); as well, supervised analysis of these microarray profiles identified distinct miRNA subsets distinguishing ErbB2-positive from ErbB2-negative and ER-positive from ER-negative breast cancers, independent of other clinically important parameters (patient age; tumor size, node status and proliferation index). In sum, these findings demonstrate that optimized high-throughput microRNA expression profiling offers novel biomarker identification from typically small clinical samples such as breast and prostate cancer biopsies.
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