BackgroundMicroRNAs (miRNAs) can act as oncogenes or tumor suppressors by controlling cell proliferation, differentiation, metastasis and apoptosis, and miRNA dysregulation is involved in the development of pancreatic cancer (PC). Our previous study demonstrated that Gabra3 plays critical roles in cancer progression. However, whether Gabra3 is regulated by miRNAs in PC remains unknown.MethodsThe expression levels of miR-92b-3p and Gabra3 were measured by quantitative PCR (qPCR), immunoblotting, in situ hybridization (ISH) and immunohistochemistry (IHC). The proliferation rate of PC cells was detected by MTS assay. Wound-healing and transwell assays were used to examine the invasive abilities of PC cells. Dual-luciferase reporter assays were used to determine how miR-92b-3p regulates Gabra3. Xenograft mouse models were used to assess the role of miR-92b-3p in PC tumor formation in vivo.ResultsHere, we provide evidence that miR-92b-3p acted as a tumor suppressor in PC by regulating Gabra3 expression. MiR-92b-3p expression levels were lower in PC tissues than corresponding noncancerous pancreatic (CNP) tissues and were associated with a poor prognosis in PC patients. MiR-92b-3p overexpression suppressed the proliferation and invasion of PC cells in both in vivo and in vitro models. Conversely, miR-92b-3p knockdown induced an aggressive phenotype in PC cells. Mechanistically, miR-92b-3p overexpression suppressed Gabra3 expression, which then led to the inactivation of important oncogenic pathways, including the AKT/mTOR and JNK pathways.ConclusionOur results suggest that miR-92b-3p acted as a tumor suppressor by targeting Gabra3-associated oncogenic pathways; these results provide novel insight into future treatments for PC patients.Electronic supplementary materialThe online version of this article (10.1186/s12943-017-0723-7) contains supplementary material, which is available to authorized users.

Common lung diseases are first diagnosed via chest X-rays. Here, we show that a fully automated deep-learning pipeline for chest-X-ray-image standardization, lesion visualization and disease diagnosis can identify viral pneumonia caused by Coronavirus disease 2019 (COVID-19), assess its severity, and discriminate it from other types of pneumonia. The deep-learning system was developed by using a heterogeneous multicentre dataset of 145,202 images, and tested retrospectively and prospectively with thousands of additional images across four patient cohorts and multiple countries. The system generalized across settings, discriminating between viral pneumonia, other types of pneumonia and absence of disease with areas under the receiver operating characteristic curve (AUCs) of 0.88–0.99, between severe and non-severe COVID-19 with an AUC of 0.87, and between severe or non-severe COVID-19 pneumonia and other viral and non-viral pneumonia with AUCs of 0.82–0.98. In an independent set of 440 chest X-rays, the system performed comparably to senior radiologists, and improved the performance of junior radiologists. Automated deep-learning systems for the assessment of pneumonia could facilitate early intervention and provide clinical-decision support.

Exosome‐derived miRNAs are regarded as biomarkers for the diagnosis and prognosis of many human cancers. However, its function in clear cell renal cell carcinoma (ccRCC) remains unclear. In this study, differentially expressed miRNAs from urinal exosomes were identified using next‐generation sequencing (NGS) and verified using urine samples of ccRCC patients and healthy donors. Then, the exosomes were analysed in early‐stage ccRCC patients, healthy individuals and patients suffering from other urinary system cancers. Thereafter, the target gene of the miRNA was detected. Its biological function was investigated in vitro and in vivo. The results showed that miR‐30c‐5p could be amplified in a stable manner. Its expression pattern was significantly different only between ccRCC patients and healthy control individuals, but not compared with that of other urinary system cancers, which indicated its specificity for ccRCC. Additionally, the overexpression of miR‐30c‐5p inhibited ccRCC progression in vitro and in vivo. Heat‐shock protein 5 (HSPA5) was found to be a direct target gene of miR‐30c‐5p. The depletion of HSPA5 caused by miR‐30c‐5p inhibition reversed the promoting effect of ccRCC growth. In conclusion, urinary exosomal miR‐30c‐5p acts as a potential diagnostic biomarker of early‐stage ccRCC and may be able to modulate the expression of HSPA5, which is correlated with the progression of ccRCC.