Supplementary Material for: Human endogenous retroviruses (HERVs) in breast cancer: altered expression pattern implicates divergent roles in carcinogenesis

Introduction
Breast cancer is the most common cancer and the leading cause of cancer death in women. Recent research indicates that human endogenous retroviruses (HERVs) may be linked to carcinogenesis, but the data remain controversial.
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, ERVK7, 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.
Conclusion
Differential HERVs 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.

引言
乳腺癌是女性最常见的恶性肿瘤，亦是女性癌症相关死亡的首要原因。现有研究提示人类内源性逆转录病毒（human endogenous retroviruses, HERVs）可能与肿瘤发生存在关联，但相关数据仍存在争议。
方法
本研究通过检测HERVs的表达水平，以对比乳腺癌样本与对照样本的表达差异，并分析其与临床病理参数的关联。本研究采用实时定量聚合酶链反应（quantitative real-time polymerase chain reaction, qPCR）及/或乳腺癌癌症基因组图谱（The Cancer Genome Atlas, TCGA）数据集，对12种HERVs的基因表达水平进行分析，这12种HERVs分别为ERVE-4、ERVW-1、ERVFRD-1、ERVV-1、ERV3-1、ERVH48-1、ERVMER34-1、ERVK7、ERVK13-1、ERVK11-1、ERVK3-1及HCP5。
结果
ERV3-1、ERVFRD-1、ERVH48-1及ERVW-1的表达数据支持其在乳腺癌中发挥肿瘤抑制因子的作用。其中，基于qPCR检测结果，ERV3-1展现出最优的诊断效能：受试者工作特征曲线下面积（Area Under the Curve, AUC）为0.819（p<0.0001），灵敏度达72.41%，特异度达89.66%。ERV3-1的表达水平在晚期及高分级乳腺癌样本中更低，且与Ki-67表达水平呈显著负相关。ERVK13-1、ERVV-1及ERVMER34-1则可能发挥致癌作用。而ERVK7、ERVE-4、ERVK11-1及HCP5的相关研究数据仍未得出明确结论。
结论
HERVs的差异表达可用于筛选乳腺癌新型生物标志物。然而，仍需开展更多研究以明确其在乳腺癌发生过程中的真实临床价值、生物学功能及调控机制。