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

Abstract

Gene expression analysis is pivotal in cancer research and clinical practice. While traditional methods lack spatial context, RNA in situ hybridization (RNA-ISH) is a powerful technique that retains spatial tissue information. Here, we investigated RNAscope score, RT-droplet digital PCR (RT-ddPCR), and automated QuantISH and QuPath in quantifying RNA-ISH expression values from formalin-fixed paraffin-embedded samples. We compared the methods using high-grade serous ovarian carcinoma samples, focusing on CCNE1, WFDC2, and PPIB genes. Our findings demonstrate good concordance between automated methods and RNAscope, with RT-ddPCR showing less concordance. We conclude that 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.