High Specificity MicroRNA Microarray Analysis without PCR for Cancer Screening and Research

 描述(申请人提供)：最近的研究，如那些关于胰腺癌的研究表明，microRNA(MiRNA)是几种类型癌症的有效生物标志物，其中超过100种被鉴定为癌基因、肿瘤抑制因子和癌症干细胞和转移的调节器。在临床症状出现之前，miRNA图谱有可能在高特异性的癌症早期诊断中具有很高的有效性。目前的miRNA测序技术，定量逆转录聚合酶链式反应(qRT-PCR)，难以多重，而且成本太高，无法用于筛选。这项拟议的研究将开发一种利用微阵列进行定量miRNA分析的技术，这种微阵列的成本要低得多，而且易于多重。然而，微阵列面临着以下挑战：(A)由于非特异性结合引起的统计数据不佳，miRNA的小尺寸使得推断不可靠；(B)来自同一前miRNA家族的序列中一到几个核苷酸(NT)的变异很难区分；(C)用于制造cDNA的小miRNA的RT-PCR并不简单，以及(D)PCR通过夸大相对浓度较大的miRNA序列的扩增来扭曲分布。建议的R21研究的目标是开发一种微阵列方法，通过测量对非特异性结合是“盲目的”的探针-靶结合，在没有PCR的情况下分析miRNA序列。该信号将定量区分完全结合(PM)、单核苷酸不匹配(1 MM)和大小不均一。这项概念验证研究将重点放在合成和血液来源的相同序列的miRNA上。萨拉夫的实验室开发了一种方法，只需扫描一束激光，就可以电化学“读取”整体式电极上的微阵列斑点。扫描双电层静电仪(SEED)可以检测到不到1个阿托摩尔(阿摩尔)的固定探针-靶结合，并区分PM和1 MM；非特异性结合产生最小的信号。种子的0.1a摩尔响应性将利用另一项创新来提高结合效率，以实现至少0.05 nM的检测极限(LOD)，需要0.2 ng miRNA。这项研究将分为三个具体目标：1)种子性能将使用合成miRNA进行量化，2)合成miRNA混合物将被定量分析，3)胰腺癌患者和健康对照的血清样本将使用SEED进行分析。种子是一种潜在的变革性技术，它将利用快速增长的miRNA生物标志物知识库，以及一种成熟的电化学转导方法，无需在最小背景下使用标记即可检测特定结合。该技术的范例是，它在硬件检测水平而不是在实验设计水平上解决微阵列中的背景问题。如果成功，该团队将通过使用针对特定癌症的生物样品的R33来验证该方法，以启动向筛查技术和假设驱动的R01研究的转化。

 DESCRIPTION (provided by applicant): Recent studies, such as those on pancreatic cancer, indicate that microRNA (miRNA) are effective biomarkers for several types of cancer, with over 100 of them identified that act as oncogenes, tumor suppressors, and modulators of cancer stem cells and metastasis. MiRNA profiles have the potential to be highly effective in the early diagnosis of cancer at high specificity before clinical signs emerge. Current technology for miRNA sequencing, quantitative reverse transcribe-polymerase chain reaction (qRT-PCR), is difficult to multiplex and too expensive to be used for screening. The proposed research will develop a technology for quantitative miRNA profiling using microarrays that are considerably less expensive and easy to multiplex. Microarrays, however, have challenges: (a) the small size of miRNA makes the inference unreliable due to poor statistics caused by nonspecific binding; (b) the one to few nucleotide (nt) variation in the sequence from the same family of pre-miRNA is difficult to discern, (c) RT-PCR of small miRNAs used to make cDNA is not straightforward, and (d) PCR skews the distribution by exaggerating the amplification of miRNA sequences that are larger in relative concentration. The goal of the proposed R21 research is to develop a microarray method for profiling a miRNA sequence without PCR by measuring probe-target binding that is "blind" to nonspecific binding. The signal will quantitatively distinguish between perfect binding (PM), single nucleotide mismatch (1MM), and size heterogeneity. This proof-of-concept study will focus on synthetic and blood derived miRNA of the same sequence. A method, developed in Saraf's lab, can electrochemically "read" microarray spots on a monolith electrode by simply scanning a laser. Scanning Electrometer for Electrical Double-layer (SEED) can detect less than 1 atto-moles (amoles) of immobilized probe-target binding and differentiate between PM and 1MM; and nonspecific binding produces minimal signal. The 0.1aMole responsivity of SEED will be leveraged using an additional innovation to enhance binding efficiency to achieve a limit of detection (LOD) of at least 0.05 nM, requiring 0.2 ng miRNA. The study will be organized into three specific aims: 1) SEED performance will be quantified using synthetic miRNA, 2) mixtures of synthetic miRNA will be quantitatively analyzed, and 3) serum samples from pancreatic cancer patients and healthy controls will be analyzed using SEED. SEED is a potentially transformative technology that will leverage the rapidly growing knowledge base of miRNA biomarkers and a proven electrochemical transduction method for detecting specific binding without using labels at minimal background. The paradigm of the technology is that it addresses the background issue in microarrays at the hardware detection level rather than at the design-of-experiment level. If successful, the team will validate the method via an R33 using biospecimens for specific cancers to initiate translation to a screening technology and hypothesis-driven R01 research.