Radiogenomic Analysis of Prediction HER2 status in Breast Cancer by Linking Ultrasound Radiomic Feature Modules with Biological Functions

Abstract Background Human epidermal growth factor receptor 2 (HER2) overexpressed associated with poor prognosis in breast cancer (BRCA) and HER2 has been defined as a therapeutic target for BRCA treatment. We aimed to exploring the molecular biological information in ultrasound radiomic features (URFs) of HER2-positive BRCA using radiogenomic analysis. Moreover, a radiomics model was developed to predict the status of HER2 in BRCA. Methods This retrospective study included 394 patients who were diagnosed with BRCA. URFs were extracted from a radiomics analysis set using PyRadiomics. The correlations between differential URFs and HER2-related genes were calculated using Pearson correlation analysis. Functional enrichment of the identified URFs-correlated HER2 positive-specific genes was performed. Lastly, the radiomics model was developed based on the URF-modules mined from auxiliary differential URFs to assess the HER2 status of BRCA. Results Eight differential URFs (P < 0.05) were identified among the 86 URFs extracted by Pyradiomics. Twenty-five genes that were found to be the most closely associated with URFs. Then, the relevant biological functions of each differential URF were obtained through functional enrichment analysis. Among them, Zone Entropy is related to immune cell activity, which regulate the generation of calcification in BRCA. The radiomics model based on the Logistic classifier and URF-modules showed good discriminative ability (AUC = 0.80, 95% CI). Conclusion We searched for the URFs of HER2-positive BRCA, and explore the underlying genes and biological functions of these URFs. Furthermore, the radiomics model based on the Logistic classifier and URF-modules accurately predicted the HER2 status in BRCA.