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Breast cancer (BC) is one of the leading causes of death in women worldwide. A major challenge in BC is chemoresistance, which is often modulated by epigenetic regulators such as long non-coding RNAs (lncRNAs). Because these regulator lncRNAs may play diverse roles, determining their specific pathways and/or functions is crucial to identify possible biomarkers and/or therapeutic targets for BC. In this study, we used gene expression microarrays in order to identify lncRNAs related to the BC biology. We found, among six differentially expressed (DE) lncRNAs, that the expression of lnc-ERP44-3:6 was consistently down-regulated in all breast tumor tissues compared to normal adjacent tissues of BC patients from northeastern Mexico. Since the role of lnc-ERP44-3:6 remains unknown in BC, we induced its transient overexpression in three different BC cell lines (i.e., MCF10A, MCF-7, and HCC1395) by transfection in order to elucidate its potential downstream effects. Remarkably, our results showed a significant increase in cell death and chemosensitivity to cisplatin at 48 h post-transfection (p < 0.01). In addition, we observed that GAPDH and FAS were up-regulated following the overexpression of lnc-ERP44-3:6. As GAPDH and FAS promote apoptosis in cancer, our findings suggest that the lnc-ERP44-3:6 overexpression induces cell death possibly via up-regulation of one or both genes in BC cell lines. To the best of our knowledge, this is the first study evaluating the overexpression of lnc-ERP44-3:6 and providing insights about its role in BC cells, which suggests that this lncRNA may be an interesting candidate as a potential therapeutic target for BC in our population. However, further studies would be needed to clarify the mechanisms by which an overexpression of lnc-ERP44-3:6 causes both cell death and chemosensitivity to cisplatin. [ABSTRACT FROM AUTHOR]

There is a growing interest in unraveling gene expression mechanisms leading to viral host invasion and infection progression. Current findings reveal that long non-coding RNAs (lncRNAs) are implicated in the regulation of the immune system by influencing gene expression through a wide range of mechanisms. By mining whole-transcriptome shotgun sequencing (RNA-seq) data using machine learning approaches, we detected two lncRNAs (ENSG00000254680 and ENSG00000273149) that are downregulated in a wide range of viral infections and different cell types, including blood monocluclear cells, umbilical vein endothelial cells, and dermal fibroblasts. The efficiency of these two lncRNAs was positively validated in different viral phenotypic scenarios. These two lncRNAs showed a strong downregulation in virus-infected patients when compared to healthy control transcriptomes, indicating that these biomarkers are promising targets for infection diagnosis. To the best of our knowledge, this is the very first study using host lncRNAs biomarkers for the diagnosis of human viral infections.