Quantifying Argonaute 2 (Ago2) expression to stratify breast cancer

量化 Argonaute 2 (Ago2) 表达以对乳腺癌进行分层

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Background

Argonaute-2 (Ago2) is an essential component of microRNA biogenesis implicated in tumourigenesis. However Ago2 expression and localisation in breast cancer remains undetermined. The

Conclusions

Quantification of Ago2 improves the stratification of breast cancer and suggests a differential role for Ago2 in breast cancer subtypes, based on levels and cellular localisation. Further investigation of the mechanisms affecting Ago2 dysregulation will reveal insights into the molecular differences underpinning breast cancer subtypes.

Methods

Ago2 protein was stained in breast cancer cell lines and tissue microarrays (TMAs), with intensity and localization assessed. Staining intensity was correlated with clinicopathological details. Using independent databases, Ago2 mRNA expression and gene alterations in breast cancer were investigated.

Results

In the breast cancer TMAs, 4 distinct staining intensities were observed (Negative, Weak, Moderate, Strong), with 64.2% of samples stained weak or negatively for Ago2 protein. An association was found between strong Ago2 staining and, the Her2 positive or basal subtypes, and between Ago2 intensity and receptor status (Estrogen or Progesterone). In tumours Ago2 mRNA expression correlated with reduced relapse free survival. Conversely, Ago2 mRNA was expressed significantly lower in SK-BR-3 (HER2 positive) and BT-20 (Basal/Triple negative) cell lines. Interestingly, high levels of Ago2 gene amplification (10-27%) were observed in breast cancer across multiple patient datasets. Importantly, knowledge of Ago2 expression improves predictions of breast cancer subtype by 20%, ER status by 15.7% and PR status by 17.5%. Conclusions: Quantification of Ago2 improves the stratification of breast cancer and suggests a differential role for Ago2 in breast cancer subtypes, based on levels and cellular localisation. Further investigation of the mechanisms affecting Ago2 dysregulation will reveal insights into the molecular differences underpinning breast cancer subtypes.

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