Abstract
BACKGROUND: Studies on tumor-secreted microRNAs point to a functional role of these in cellular communication and reprogramming of the tumor microenvironment. Uptake of tumor-secreted microRNAs by neighboring cells may result in the silencing of mRNA targets and, in turn, modulation of the transcriptome. Studying miRNAs externalized from tumors could improve cancer patient diagnosis and disease monitoring and help to pinpoint which miRNA-gene interactions are central for tumor properties such as invasiveness and metastasis. METHODS: Using a bioinformatics approach, we analyzed the profiles of secreted tumor and normal interstitial fluid (IF) microRNAs, from women with breast cancer (BC). We carried out differential abundance analysis (DAA), to obtain miRNAs, which were enriched or depleted in IFs, from patients with different clinical traits. Subsequently, miRNA family enrichment analysis was performed to assess whether any families were over-represented in the specific sets. We identified dysregulated genes in tumor tissues from the same cohort of patients and constructed weighted gene co-expression networks, to extract sets of co-expressed genes and co-abundant miRNAs. Lastly, we integrated miRNAs and mRNAs to obtain interaction networks and supported our findings using prediction tools and cancer gene databases. RESULTS: Network analysis showed co-expressed genes and miRNA regulators, associated with tumor lymphocyte infiltration. All of the genes were involved in immune system processes, and many had previously been associated with cancer immunity. A subset of these, BTLA, CXCL13, IL7R, LAMP3, and LTB, was linked to the presence of tertiary lymphoid structures and high endothelial venules within tumors. Co-abundant tumor interstitial fluid miRNAs within this network, including miR-146a and miR-494, were annotated as negative regulators of immune-stimulatory responses. One co-expression network encompassed differences between BC subtypes. Genes differentially co-expressed between luminal B and triple-negative breast cancer (TNBC) were connected with sphingolipid metabolism and predicted to be co-regulated by miR-23a. Co-expressed genes and TIF miRNAs associated with tumor grade were BTRC, CHST1, miR-10a/b, miR-107, miR-301a, and miR-454. CONCLUSION: Integration of IF miRNAs and mRNAs unveiled networks associated with patient clinicopathological traits, and underlined molecular mechanisms, specific to BC sub-groups. Our results highlight the benefits of an integrative approach to biomarker discovery, placing secreted miRNAs within a biological context.