Conclusion
Differential HERV expression may be applicable to evaluate novel biomarkers for breast cancer. However, more research is needed to reveal their real clinical impact, the biological roles, and regulatory mechanisms in breast carcinogenesis.
Methods
HERVs' expression was evaluated to show the differences between breast cancer and control samples, and their associations with clinicopathological parameters. Gene expression of 12 HERVs, i.e., ERVE-4, ERVW-1, ERVFRD-1, ERVV-1, ERV3-1, ERVH48-1, ERVMER34-1, ERVK-7, ERVK13-1, ERVK11-1, ERVK3-1, and HCP5, was analyzed by qPCR and/or TCGA datasets for breast cancer.
Results
ERV3-1, ERVFRD-1, ERVH48-1, and ERVW-1 provided data to support their tumor suppressor roles in breast cancer. ERV3-1 evinced the best performing diagnostic data based on qPCR, i.e. , auc: 0.819 (p < 0.0001), sensitivity of 72.41%, and specificity of 89.66%. Lower levels of ERV3-1 were noted in advanced stage and higher grades, and significant negative association was found in relation to Ki-67 levels. Oncogenic roles may be inferred for ERVK13-1, ERVV-1, and ERVMER34-1. Data for ERVK-7, ERVE-4, ERVK11-1, and HCP5 remain inconclusive.