Thyroid carcinomas comprise a broad spectrum of tumors with different clinical behaviors. On the one side, there are occult papillary carcinomas (PTC), slow growing and clinically silent, and on the other side, rapidly growing anaplastic carcinomas (ATC), which are among the most lethal human neoplasms. We have analysed the microRNA (miR) profile of ATC in comparison to the normal thyroid using a microarray (miRNACHIP microarray). By this approach, we found an aberrant miR expression profile that clearly differentiates ATC from normal thyroid tissues and from PTC analysed in previous studies. In particular, a significant decrease in miR-30d, miR-125b, miR-26a and miR-30a-5p was detected in ATC in comparison to normal thyroid tissue. These results were further confirmed by northern blots, quantitative reverse transcription-PCR analyses and in situ hybridization. The overexpression of these four miRs in two human ATC-derived cell lines suggests a critical role of miR-125b and miR-26a downregulation in thyroid carcinogenesis, since a cell growth inhibition was achieved. Conversely, no effect on cell growth was observed after the overexpression of miR-30d and miR-30a-5p in the same cells. In conclusion, these data indicate a miR signature associated with ATC and suggest the miR deregulation as an important event in thyroid cell transformation.

Epithelial ovarian cancer is the most lethal gynecologic malignancy; it is highly aggressive and causes almost 125,000 deaths yearly. Despite advances in detection and cytotoxic therapies, a low percentage of patients with advanced stage disease survive 5 y after the initial diagnosis. The high mortality of this disease is mainly caused by resistance to the available therapies. Here, we profiled microRNA (miR) expression in serous epithelial ovarian carcinomas to assess the possibility of a miR signature associated with chemoresistance. We analyzed tumor samples from 198 patients (86 patients as a training set and 112 patients as a validation set) for human miRs. A signature of 23 miRs associated with chemoresistance was generated by array analysis in the training set. Quantitative RT-PCR in the validation set confirmed that three miRs (miR-484, -642, and -217) were able to predict chemoresistance of these tumors. Additional analysis of miR-484 revealed that the sensitive phenotype is caused by a modulation of tumor vasculature through the regulation of the VEGFB and VEGFR2 pathways. We present compelling evidence that three miRs can classify the response to chemotherapy of ovarian cancer patients in a large multicenter cohort and that one of these three miRs is involved in the control of tumor angiogenesis, indicating an option in the treatment of these patients. Our results suggest, in fact, that blockage of VEGF through the use of an anti-VEGFA antibody may not be sufficient to improve survival in ovarian cancer patients unless VEGFB signaling is also blocked.

Cell cycle progression is controlled by numerous mechanisms ensuring correct cell division. The transition from one cell cycle phase to another occurs in an orderly fashion and is regulated by different cellular proteins. Therefore an alteration of the regulatory mechanisms of the cell cycle results in uncontrolled cell proliferation, which is a distinctive feature of human cancers. Recent evidences suggest that microRNAs (miRs) may also control the levels of multiple cell cycle regulators and therefore control cell proliferation. In fact miRs are a class of small non-coding RNAs, which modulate gene expression. They are involved in numerous physiological cellular processes and most importantly accumulating evidence indicates that many miRs are aberrantly expressed in human cancers. In this report we describe that miR-24 directly targets p27(Kip1) and p16(Ink4a) in primary keratinocyte and in different cancer derived cell lines promoting their proliferation, suggesting that miR-24 is involved in cyclin-dependent kinase inhibitors post-transcriptional regulation and that upregulation of miR-24 may play a role in carcinogenesis.

Autophagy is a conserved evolutionary process that allows cells to maintain macromolecular synthesis and energy homeostasis during starvation and stressful conditions. We prospectively evaluated the relationship between autophagy and prostatic inflammation in a series of transurethral prostatic resection samples. Inflammatory infiltrates were defined according to the standardized classification of chronic prostatitis of the National Institute of Health. The inflammatory score (IS score) was calculated. High IS score was defined as ≥7. Each sample was stained for anti-LC3B and for anti-P62/SQSTM1 and scored. High p62 or LC3B percentage was defined as >25%, whereas low was defined as <25% of cells with dots.We analyzed 94 specimens. Overall, 18/94 (19%) showed no sign of prostatic inflammation, whereas 76/94 (81%) presented inflammatory infiltrates. Inflammation was mild in 61/76 (80%), moderate/severe in 15/76 (20%). Patients with high p62 percentage were 62/94 (66%) while 32 (34%) showed low p62 percentage. Patients with high LC3B percentage were 37/94 (39%) while 57(61%) showed low LC3B percentage. Overall 42/94 (44%) patients presented a high p62 percentage and concomitant a low LC3B percentage. IS score was significantly higher in patients with a with high p62 percentage (median IS 7 (6/8) vs 5 (3/7); p= 0.04) and in patients with a low LC3B percentage (median IS 7 (6/8) vs 5 (3/7); p= 0.004) when compared to patients with a low p62 percentage or a high LC3B percentage respectively. On multivariate analysis, p62 (OR: 10.1, 95%CI: 2.6-38.6; p= 0,001) and LC3B expression (OR: 0.319; 95%CI: 0.112-0.907; p= 0.032) were independent predictors of a high IS.Here we present the first evidence of autophagy deregulation in prostatic inflammation. These results raise many questions about the mechanisms mediating the autophagy dysfunction and the links to prostatic inflammation that need to be addressed.

Background A prostate cancer diagnosis is based on biopsy sampling that is an invasive, expensive procedure, and doesn’t accurately represent multifocal disease. Methods To establish a model using plasma miRs to distinguish Prostate cancer patients from non-cancer controls, we enrolled 600 patients histologically diagnosed as having or not prostate cancer at biopsy. Two hundred ninety patients were eligible for the analysis. Samples were randomly divided into discovery and validation cohorts. Results NGS-miR-expression profiling revealed a miRs signature able to distinguish prostate cancer from non-cancer plasma samples. Of 51 miRs selected in the discovery cohort, we successfully validated 5 miRs (4732-3p, 98-5p, let-7a-5p, 26b-5p, and 21-5p) deregulated in prostate cancer samples compared to controls (p ≤ 0.05). Multivariate and ROC analyses show miR-26b-5p as a strong predictor of PCa, with an AUC of 0.89 (CI = 0.83–0.95;p < 0.001). Combining miRs 26b-5p and 98-5p, we developed a model that has the best predictive power in discriminating prostate cancer from non-cancer (AUC = 0.94; CI: 0,835-0,954). To distinguish between low and high-grade prostate cancer, we found that miR-4732-3p levels were significantly higher; instead, miR-26b-5p and miR-98-5p levels were lower in low-grade compared to the high-grade group (p ≤ 0.05). Combining miR-26b-5p and miR-4732-3p we have the highest diagnostic accuracy for high-grade prostate cancer patients, (AUC = 0.80; CI 0,69-0,873). Conclusions Noninvasive diagnostic tests may reduce the number of unnecessary prostate biopsies. The 2-miRs-diagnostic model (miR-26b-5p and miR-98-5p) and the 2-miRs-grade model (miR-26b-5p and miR-4732-3p) are promising minimally invasive tools in prostate cancer clinical management.