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通过计算机辅助评分与分析(CASA)对非小细胞肺癌中p16、c-Myc和mSin3A进行表达分析

Expression Analysis of p16, c-Myc, and mSin3A in Non-small Cell Lung Cancer by Computer Aided Scoring and Analysis (CASA).

作者信息

Salmaninejad Arash, Estiar Mehrdad Asghari, Gill Rajbir K, Shih Joanna H, Hewitt Stephen, Jeon Hyo-Sung, Fukuoka Junya, Shilo Konstantin, Shakoori Abbas, Jen Jin

出版信息

Clin Lab. 2015;61(5-6):549-59. doi: 10.7754/clin.lab.2014.141125.

Abstract

BACKGROUND

Immunohistochemical analysis (IHC) of tissue microarray (TMA) slides enables large sets of tissue samples to be analyzed simultaneously on a single slide. However, manual evaluation of small cores on a TMA slide is time consuming and error prone.

METHODS

We describe a computer aided scoring and analysis (CASA) method to allow facile and reliable scoring of IHC staining using TMA containing 300 non-small cell lung cancer (NSCLC) cases. In the two previous published papers utilizing our TMA slides of lung cancer we examined 18 proteins involved in the chromatin machinery. We developed our study using more proteins of the chromatin complex and several transcription factors that facilitate the chromatin machinery. Then, a total of 78 antibodies were evaluated by CASA to derive a normalized intensity value that correlated with the overall staining status of the targeting protein. The intensity values for TMA cores were then examined for association to clinical variables and predictive significance individually and with other factors. RESULTs: Using our TMA, the intensity of several protein pairs were significantly correlated with an increased risk of death in NSCLC. These included c-Myc with p16, mSin3A with p16 and c-Myc with mSinA. Predictive values of these pairs remained significant when evaluated based on standard IHC scores.

CONCLUSIONS

Our results demonstrate the usefulness of CASA as a valuable tool for systematic assessment of TMA slides to identify potential predictive biomarkers using a large set of primary human tissues.

摘要

背景

组织微阵列(TMA)载玻片的免疫组织化学分析(IHC)能够在一张载玻片上同时分析大量组织样本。然而,手动评估TMA载玻片上的小组织芯既耗时又容易出错。

方法

我们描述了一种计算机辅助评分与分析(CASA)方法,用于对包含300例非小细胞肺癌(NSCLC)病例的TMA进行IHC染色的便捷且可靠的评分。在之前两篇使用我们肺癌TMA载玻片的已发表论文中,我们研究了18种参与染色质机制的蛋白质。我们在研究中纳入了更多染色质复合物蛋白以及几种促进染色质机制的转录因子。然后,通过CASA评估了总共78种抗体,以得出与靶向蛋白的整体染色状态相关的标准化强度值。接着分别以及与其他因素一起检查TMA芯的强度值与临床变量的关联及预测意义。

结果

使用我们的TMA,几对蛋白质的强度与NSCLC患者死亡风险增加显著相关。这些包括c-Myc与p16、mSin3A与p16以及c-Myc与mSinA。基于标准IHC评分评估时,这些蛋白对的预测价值仍然显著。

结论

我们的结果表明,CASA作为一种有价值的工具,可用于系统评估TMA载玻片,以利用大量原发性人体组织识别潜在的预测性生物标志物。

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