Abstract
Triple-negative breast cancer (TNBC) presents a major challenge in the clinic due to its lack of reliable prognostic markers and targeted therapies. Accumulating evidence strongly supports the notion that microRNAs (miRNAs) are involved in tumorigenesis and could serve as biomarkers for diagnostic purposes. To identify miRNAs that functionally suppress metastasis of TNBC, we employed a concerted approach with selecting miRNAs that display differential expression profiles from bioinformatic analyses of breast cancer patient databases and validating top candidates with functional assays using breast cancer cell lines and mouse models. We have found that miR-148a exhibits properties as a tumor suppressor as its expression is inversely correlated with the ability of both human and mouse breast cancer cells to colonize the lung in mouse xenograft tumor models. Mechanistically, miR-148a appears to suppress the extravasation process of cancer cells, likely by targeting two genes WNT1 and NRP1 in a cell non-autonomous manner. Importantly, lower expression of miR-148a is detected in higher-grade tumor samples and correlated with increased likelihood to develop metastases and poor prognosis in subsets of breast cancer patients, particularly those with TNBC. Thus, miR-148a is functionally defined as a suppressor of breast cancer metastasis and may serve as a prognostic biomarker for this disease.
Highlights
Breast cancer is the most commonly diagnosed and the second most fatal cancer in women
We show that miR-148a is downregulated in breast cancer cell lines with high metastatic potential
Using statistical www.impactjournals.com/oncotarget analysis of multiple databases of breast cancer patients, we found that low expression of miR-148a is associated with diagnosis of high-grade primary tumors and poor prognosis of breast cancer patients, for patients with Basal and Luminal B subtypes
Summary
Breast cancer is the most commonly diagnosed and the second most fatal cancer in women. The current clinical treatment plan for breast cancer varies depending on characteristics of the primary tumor divided into four major molecular subtypes (LumA, LumB, Triple-negative/ basal-like, and HER2 type) and two less common subtypes (Normal-like and Claudin-low) [1,2,3]. The triple-negative subtype of breast cancer, which often includes the Claudinlow subtype [4], lacks expression of estrogen receptor (ER), progesterone receptor (PR), and HER2, presents a difficult therapeutic challenge as this subtype is characterized by its aggressive nature and lack of targeted therapies [5, 6]. Identification of biomarkers to predict metastatic likelihood of the primary tumor can potentially be very useful to guide treatment for breast cancer
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