Comparative Analysis of Gene Expression Analysis Methods for RNA in Situ Hybridization Images

IF 3.4 3区 医学 Q1 PATHOLOGY
Valeria Ariotta , Eros Azzalini , Vincenzo Canzonieri , Sampsa Hautaniemi , Serena Bonin
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引用次数: 0

Abstract

Gene expression analysis is pivotal in cancer research and clinical practice. Although traditional methods lack spatial context, RNA in situ hybridization (RNA-ISH) is a powerful technique that retains spatial tissue information. Here, RNAscope score, RT–droplet digital PCR, and automated QuantISH and QuPath were used for quantifying RNA-ISH expression values from formalin-fixed, paraffin-embedded samples. The methods were compared using high-grade serous ovarian carcinoma samples, focusing on CCNE1, WFDC2, and PPIB genes. The findings demonstrate good concordance between automated methods and RNAscope, with RT–droplet digital PCR showing less concordance. Additionally, QuantISH exhibits robust performance, even for low-expressed genes like CCNE1, showcasing its modular design and enhancing accessibility as a viable alternative for gene expression analysis.

RNA 原位杂交图像基因表达分析方法的比较分析。
基因表达分析在癌症研究和临床实践中举足轻重。传统方法缺乏空间背景,而 RNA 原位杂交(RNA-ISH)是一种保留组织空间信息的强大技术。本文采用了 RNAscope 评分、RT-液滴数字 PCR(RT-ddPCR)、自动定量ISH 和 QuPath 来量化福尔马林固定石蜡包埋样本的 RNA-ISH 表达值。研究人员利用高级别浆液性卵巢癌样本对这些方法进行了比较,重点研究了 CCNE1、WFDC2 和 PPIB 基因。研究结果表明,自动方法与 RNAscope 的一致性很好,而 RT-ddPCR 的一致性较差。此外,QuantISH 表现出强大的性能,即使是 CCNE1 这样的低表达基因也不例外,这展示了它的模块化设计,提高了作为基因表达分析可行替代方法的可及性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.10
自引率
2.40%
发文量
143
审稿时长
43 days
期刊介绍: The Journal of Molecular Diagnostics, the official publication of the Association for Molecular Pathology (AMP), co-owned by the American Society for Investigative Pathology (ASIP), seeks to publish high quality original papers on scientific advances in the translation and validation of molecular discoveries in medicine into the clinical diagnostic setting, and the description and application of technological advances in the field of molecular diagnostic medicine. The editors welcome for review articles that contain: novel discoveries or clinicopathologic correlations including studies in oncology, infectious diseases, inherited diseases, predisposition to disease, clinical informatics, or the description of polymorphisms linked to disease states or normal variations; the application of diagnostic methodologies in clinical trials; or the development of new or improved molecular methods which may be applied to diagnosis or monitoring of disease or disease predisposition.
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