A New Paradigm of RNA-Signal Quantitation and Contextual Visualization for On-Slide Tissue Analysis

An objective digital pathology solution to quantify the ribonucleic acid (RNA) signal in tissue samples could enable analysis of gene expression changes in individual cancer and dysregulated normal cells (immune cells, etc.). Here, we present a new method that leverages the punctate RNA In-situ hybridization (ISH) signal to quantify gene expression, while maintaining tissue context and enabling single cell analysis and workflow. This digital pathology solution detects and quantifies the punctate dot signals generated by one- and two-color RNA ISH technology in formaldehyde fixed-paraffin embedded (FFPE) tissue. The digital pathology solution was implemented to determine the characteristics of individual spots including size, intensity, blurriness and roundness all of which were used to determine individual spot feature characteristics. Significantly, we determined that spots maintain similar characteristics irrespective of the RNA biomarker and/or tissue used. The verification on 31 microscope images shows agreement of R² = 0.99 and a concordance correlation coefficient (CCC) = 0.99 for the total spot counts identified by the observer (115,154) and the algorithm (112,809). We have leveraged the unique detection features of the RNA ISH technology to develop a new method to quantify RNA signal while maintaining tissue context. It is anticipated that this method will enable analysis of gene expression changes in heterogeneous cancer and normal cells and tissues with single cell resolution.