Integrated miRNA and mRNA profiling of tumor-educated macrophages identifies prognostic subgroups in estrogen receptor-positive breast cancer.

INTRODUCTION: Various studies have identified aberrantly expressed miRNAs in breast cancer and demonstrated an association between distinct miRNAs and malignant progression as well as metastasis. Even though tumor-associated macrophages (TAM) are known mediators of these processes, little is known regarding their miRNA expression upon education by malignant cells in vivo. METHODS: We profiled miRNA and mRNA expression of in vitro tumor-educated macrophages (TEM) by indirectly co-culturing with estrogen-receptor-positive (ER+) MCF-7 breast cancer cells. The prognostic power of the resulting miRNA list was investigated in primary breast cancer datasets and compared to other signatures. Furthermore, miRNA expression levels were correlated to mRNA expression of macrophage markers and the impact on prognosis was assessed. RESULTS: Through the evaluation of the group effects between differentially-expressed miRNAs and their target mRNAs in TEM, the power of detecting regulated miRNAs was greatly increased. The resulting list of 96 miRNAs predicts disease-free survival (DFS) in external datasets of ER+ breast cancer patients and performs well in comparison with other miRNA signatures. Clustering with the predefined miRNA list revealed a significant difference in survival between the two resulting patient groups. Furthermore, an optimized miRNA list, based on correlations with macrophages markers, proved even more capable at identifying patient clusters significantly differing in DFS. CONCLUSIONS: In vitro profiling of TEM and subsequent bioinformatic verification identified miRNAs with a high prognostic power for DFS when transferred into the clinical setting of primary breast cancer. The resulting miRNAs not only verify previously established findings but also lead to new prognostic markers. Furthermore, our data suggest that TAM contribute to the total miRNA expression profile of ER + breast cancers.

Detection of simultaneous group effects in microRNA expression and related target gene sets.

Expression levels of mRNAs are among other factors regulated by microRNAs. A particular microRNA can bind specifically to several target mRNAs and lead to their degradation. Expression levels of both, mRNAs and microRNAs, can be obtained by microarray experiments. In order to increase the power of detecting microRNAs that are differentially expressed between two different groups of samples, we incorporate expression levels of their related target gene sets. Group effects are determined individually for each microRNA, and by enrichment tests and global tests for target gene sets. The resulting lists of p-values from individual and set-wise testing are combined by means of meta analysis. We propose a new approach to connect microRNA-wise and gene set-wise information by means of p-value combination as often used in meta-analysis. In this context, we evaluate the usefulness of different approaches of gene set tests. In a simulation study we reveal that our combination approach is more powerful than microRNA-wise testing alone. Furthermore, we show that combining microRNA-wise results with 'competitive' gene set tests maintains a pre-specified false discovery rate. In contrast, a combination with 'self-contained' gene set tests can harm the false discovery rate, particularly when gene sets are not disjunct.