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.
Competing Interest Statement
The authors have declared no competing interest.
