Integrative Assessment of RNA-seq and IHC: Linking Tumor Biomarkers and Microenvironment

This study aimed to assess the correlation between RNA sequencing (RNA-seq) and immunohistochemistry (IHC) in detecting key cancer biomarkers across solid tumors, and then, to establish RNA-seq thresholds that accurately reflect clinical IHC classifications. Expression levels of nine biomarkers—ESR1, PGR, AR, MKI67, ERBB2, CD274, CDX2, KRT7, and KRT20—were analyzed in 365 formalin-fixed, paraffin-embedded samples from breast, lung, gastrointestinal, and other solid carcinomas. Correlations between RNA-seq data and IHC scores were determined using Spearman’s correlation coefficients, with RNA-seq cut-offs established to distinguish positive from negative IHC scores. The results revealed strong correlations for most biomarkers, with coefficients ranging from 0.53 to 0.89. RNA-seq thresholds were confirmed across internal and external cohorts, demonstrating high diagnostic accuracy (up to 98%) and precision in identifying biomarker expression levels. The analysis also highlighted the influence of tumor microenvironment and purity, particularly in the moderate correlation 0.63 observed for PD-L1. Our study demonstrates that RNA-seq can serve as a robust complementary tool to IHC, offering objective and high-throughput biomarker assessment. The RNA-seq thresholds established provide a reliable method for determining biomarker positivity, supporting the integration of RNA-seq in clinical diagnostics to enhance precision, especially where tumor purity and microenvironment factors are significant. FFPE tissue blocks from 365 patient samples formed the internal cohort (Supplementary Table 1). For 313 patients, FFPE blocks from the clinical program were provided initially and used for RNA-seq. For 52 patients, tissue samples were originally provided as fresh frozen tissue (FF) specimens (were purchased from Cureline Tissue Bank (Brisbane, CA)), which were used for RNA-seq directly. *************************************************************** Raw files for human/patient samples were not submitted to GEO due to concerns about submitting personally identifiable sequence data for open access. ***************************************************************