档案组织能揭示现代研究问题的答案吗?60年来收集的神经母细胞瘤肿瘤的计算机辅助组织学评估。

Albert Chetcuti, Nicole Mackie, Siamak Tafavogh, Nicole Graf, Tony Henwood, Amanda Charlton, Daniel Catchpoole
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引用次数: 5

摘要

尽管神经母细胞瘤是儿童最常见的颅外实体癌,但它仍然是一种罕见的疾病。因此,无法获得用于研究的组织限制了研究的统计能力。病理档案是罕见组织的可能来源,如果证明这些组织随着时间的推移保持一致,可能对罕见疾病类型的研究有用。我们应用免疫组织化学来研究长期储存是否会引起神经母细胞瘤诊断所用抗原的变化。我们构建并定量评估了一个组织微阵列,其中包含1950年至2007年之间的神经母细胞瘤档案材料。共纳入了119个神经母细胞瘤组织核心,时间跨度为60年。通过组织微阵列(TMA)筛选了14种抗体。其中包括7个阳性神经母细胞瘤诊断标志物(NB84、Chromogranin A、NSE、Ki-67、INI1、Neurofilament Protein、Synaptophysin), 2个预计阴性(S100A、CD99), 5个研究抗体(IL-7、IL-7R、JAK1、JAK3、STAT5)。使用Aperio ImageScope软件以及新的模式识别和定量算法评估这些抗体的染色情况。该分析表明,标记信号强度不会随着时间的推移而降低,并且60年的储存对抗原性几乎没有影响。该神经母细胞瘤TMA的构建和评估证明了利用档案样本进行研究的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Can Archival Tissue Reveal Answers to Modern Research Questions?: Computer-Aided Histological Assessment of Neuroblastoma Tumours Collected over 60 Years.

Can Archival Tissue Reveal Answers to Modern Research Questions?: Computer-Aided Histological Assessment of Neuroblastoma Tumours Collected over 60 Years.

Can Archival Tissue Reveal Answers to Modern Research Questions?: Computer-Aided Histological Assessment of Neuroblastoma Tumours Collected over 60 Years.

Can Archival Tissue Reveal Answers to Modern Research Questions?: Computer-Aided Histological Assessment of Neuroblastoma Tumours Collected over 60 Years.

Despite neuroblastoma being the most common extracranial solid cancer in childhood, it is still a rare disease. Consequently, the unavailability of tissue for research limits the statistical power of studies. Pathology archives are possible sources of rare tissue, which, if proven to remain consistent over time, could prove useful to research of rare disease types. We applied immunohistochemistry to investigate whether long term storage caused any changes to antigens used diagnostically for neuroblastoma. We constructed and quantitatively assessed a tissue microarray containing neuroblastoma archival material dating between 1950 and 2007. A total of 119 neuroblastoma tissue cores were included spanning 6 decades. Fourteen antibodies were screened across the tissue microarray (TMA). These included seven positive neuroblastoma diagnosis markers (NB84, Chromogranin A, NSE, Ki-67, INI1, Neurofilament Protein, Synaptophysin), two anticipated to be negative (S100A, CD99), and five research antibodies (IL-7, IL-7R, JAK1, JAK3, STAT5). The staining of these antibodies was evaluated using Aperio ImageScope software along with novel pattern recognition and quantification algorithms. This analysis demonstrated that marker signal intensity did not decrease over time and that storage for 60 years had little effect on antigenicity. The construction and assessment of this neuroblastoma TMA has demonstrated the feasibility of using archival samples for research.

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来源期刊
自引率
0.00%
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0
审稿时长
11 weeks
期刊介绍: High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: Microarrays, DNA Sequencing, RNA Sequencing, Protein Identification and Quantification, Cell-based Approaches, Omics Technologies, Imaging, Bioinformatics, Computational Biology/Chemistry, Statistics, Integrative Omics, Drug Discovery and Development, Microfluidics, Lab-on-a-chip, Data Mining, Databases, Multiplex Assays.
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