The gut microbiota is essential for human health and plays an important role in the pathogenesis of several diseases. Short-chain fatty acids (SCFA), such as acetate, butyrate and propionate, are end-products of microbial fermentation of macronutrients that distribute systemically via the blood. The aim of this study was to investigate the transcriptional response of immature and LPS-matured human monocyte-derived DC to SCFA. Our data revealed distinct effects exerted by each individual SCFA on gene expression in human monocyte-derived DC, especially in the mature ones. Acetate only exerted negligible effects, while both butyrate and propionate strongly modulated gene expression in both immature and mature human monocyte-derived DC. An Ingenuity pathway analysis based on the differentially expressed genes suggested that propionate and butyrate modulate leukocyte trafficking, as SCFA strongly reduced the release of several pro-inflammatory chemokines including CCL3, CCL4, CCL5, CXCL9, CXCL10 and CXCL11. Additionally, butyrate and propionate inhibited the expression of lipopolysaccharide (LPS)-induced cytokines such as IL-6 and IL-12p40 showing a strong anti-inflammatory effect. This work illustrates that bacterial metabolites far from the site of their production can differentially modulate the inflammatory response and generally provides new insights into host-microbiome interactions.

Prostate cancer (PCa) is the most frequent male malignancy and the second most common cause of cancer-related death in Western countries. Current clinical and pathological methods are limited in the prediction of postoperative outcome. It is becoming increasingly evident that small non-coding RNA (ncRNA) species are associated with the development and progression of this malignancy. To assess the diversity and abundance of small ncRNAs in PCa, we analyzed the composition of the entire small transcriptome by Illumina/Solexa deep sequencing. We further analyzed the microRNA (miRNA) expression signatures of 102 fresh-frozen patient samples during PCa progression by miRNA microarrays. Both platforms were cross-validated by quantitative reverse transcriptase–PCR. Besides the altered expression of several miRNAs, our deep sequencing analyses revealed strong differential expression of small nucleolar RNAs (snoRNAs) and transfer RNAs (tRNAs). From microarray analysis, we derived a miRNA diagnostic classifier that accurately distinguishes normal from cancer samples. Furthermore, we were able to construct a PCa prognostic predictor that independently forecasts postoperative outcome. Importantly, the majority of miRNAs included in the predictor also exhibit high sequence counts and concordant differential expression in Illumina PCa samples, supported by quantitative reverse transcriptase–PCR. Our findings provide miRNA expression signatures that may serve as an accurate tool for the diagnosis and prognosis of PCa.

Cutaneous T-cell lymphomas (CTCLs) are the most frequent primary skin lymphomas. Nevertheless, diagnosis of early disease has proven difficult because of a clinical and histologic resemblance to benign inflammatory skin diseases. To address whether microRNA (miRNA) profiling can discriminate CTCL from benign inflammation, we studied miRNA expression levels in 198 patients with CTCL, peripheral T-cell lymphoma (PTL), and benign skin diseases (psoriasis and dermatitis). Using microarrays, we show that the most induced (miR-326, miR-663b, and miR-711) and repressed (miR-203 and miR-205) miRNAs distinguish CTCL from benign skin diseases with > 90% accuracy in a training set of 90 samples and a test set of 58 blinded samples. These miRNAs also distinguish malignant and benign lesions in an independent set of 50 patients with PTL and skin inflammation and in experimental human xenograft mouse models of psoriasis and CTCL. Quantitative (q)RT-PCR analysis of 103 patients with CTCL and benign skin disorders validates differential expression of 4 of the 5 miRNAs and confirms previous reports on miR-155 in CTCL. A qRT-PCR–based classifier consisting of miR-155, miR-203, and miR-205 distinguishes CTCL from benign disorders with high specificity and sensitivity, and with a classification accuracy of 95%, indicating that miRNAs have a high diagnostic potential in CTCL.