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More than 26 million people in West Bengal, India, are exposed to arsenic through drinking water, leading to several deleterious endpoints including precancerous and cancerous skin lesions and other non-dermatological health effects. Here, our aim was to identify whether miR21 is associated with such dermatological and non-dermatological health outcomes in chronically exposed humans. A total of 123 subjects from West Bengal were recruited for this study (45 exposed individuals with skin lesions, 38 exposed individuals without skin lesions and 40 unexposed individuals). The miR21 expression patterns in the lymphocytes were studied by quantitative realtime PCR and the effects on downstream targets were validated by Western blotting. Associations between the miR21 expression patterns and non-dermatological health effects were determined from epidemiological survey data. In vitro studies were done with low dose (0.05 ppm) of chronic arsenic exposure to HaCaT cells for 15 passages. Interestingly, within the exposed group, the skin lesion individuals showed almost 4.5 fold up-regulation of miR21 compared to the no skin lesion group. The expression of the downstream targets of miR21 (PTEN and PDCD4) varied inversely, while the expression of pAKT and PI3K varied proportionately with its expression levels. Results of in vitro studies showed similar trends. Again miR21 was 2.03 fold up-regulated in the exposed individuals with respiratory diseases compared to the individuals without the same. This study for the first time shows that miR21 plays an important role in contributing to arsenic induced dermatological and non-dermatological health outcomes in an exposed population. [ABSTRACT FROM AUTHOR]

Background: MicroRNAs (miRNAs) are known to play an important role in cancer development by post-transcriptionally affecting the expression of critical genes. The aims of this study were two-fold: (i) to develop a robust method to isolate miRNAs from small volumes of saliva and (ii) to develop a panel of saliva-based diagnostic biomarkers for the detection of head and neck squamous cell carcinoma (HNSCC). Methods: Five differentially expressed miRNAs were selected from miScript™ miRNA microarray data generated using saliva from five HNSCC patients and five healthy controls. Their differential expression was subsequently confirmed by RT-qPCR using saliva samples from healthy controls ( n = 56) and HNSCC patients ( n = 56). These samples were divided into two different cohorts, i.e., a first confirmatory cohort ( n = 21) and a second independent validation cohort ( n = 35), to narrow down the miRNA diagnostic panel to three miRNAs: miR-9, miR-134 and miR-191. This diagnostic panel was independently validated using HNSCC miRNA expression data from The Cancer Genome Atlas (TCGA), encompassing 334 tumours and 39 adjacent normal tissues. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic capacity of the panel. Results: On average 60 ng/μL miRNA was isolated from 200 μL of saliva. Overall a good correlation was observed between the microarray data and the RT-qPCR data. We found that miR-9 ( P <0.0001), miR-134 ( P <0.0001) and miR-191 ( P <0.001) were differentially expressed between saliva from HNSCC patients and healthy controls, and that these miRNAs provided a good discriminative capacity with area under the curve (AUC) values of 0.85 ( P <0.0001), 0.74 ( P < 0.001) and 0.98 ( P < 0.0001), respectively. In addition, we found that the salivary miRNA data showed a good correlation with the TCGA miRNA data, thereby providing an independent validation. Conclusions: We show that we have developed a reliable method to isolate miRNAs from small volumes of saliva, and that the saliva-derived miRNAs miR-9, miR-134 and miR-191 may serve as novel biomarkers to reliably detect HNSCC. [ABSTRACT FROM AUTHOR]

Abstract: The diversity of breast cancers reflects variations in underlying biology and affects the clinical implications for patients. Gene expression studies have identified five major subtypes– Luminal A, Luminal B, basal-like, ErbB2+ and Normal-Like. We set out to determine the role of DNA methylation in subtypes by performing genome-wide scans of CpG methylation in breast cancer samples with known expression-based subtypes. Unsupervised hierarchical clustering using a set of most varying loci clustered the tumors into a Luminal A majority (82%) cluster, Basal-like/ErbB2+ majority (86%) cluster and a non-specific cluster with samples that were also inconclusive in their expression-based subtype correlations. Contributing methylation loci were both gene associated loci (30%) and non-gene associated (70%), suggesting subtype dependant genome-wide alterations in the methylation landscape. The methylation patterns of significant differentially methylated genes in luminal A tumors are similar to those identified in CD24 + luminal epithelial cells and the patterns in basal-like tumors similar to CD44 + breast progenitor cells. CpG islands in the HOXA cluster and other homeobox (IRX2, DLX2, NKX2-2) genes were significantly more methylated in Luminal A tumors. A significant number of genes (2853, p < 0.05) exhibited expression–methylation correlation, implying possible functional effects of methylation on gene expression. Furthermore, analysis of these tumors by using follow-up survival data identified differential methylation of islands proximal to genes involved in Cell Cycle and Proliferation (Ki-67, UBE2C, KIF2C, HDAC4), angiogenesis (VEGF, BTG1, KLF5), cell fate commitment (SPRY1, OLIG2, LHX2 and LHX5) as having prognostic value independent of subtypes and other clinical factors. [ABSTRACT FROM AUTHOR]