Esophageal cancer is the sixth leading cause of death from cancer and one of the least studied cancers worldwide. The global microRNA expression profile of esophageal cancer has not been reported previously. Here, for the first time, we have investigated expressed microRNAs in cryopreserved esophageal cancer tissues using advanced microRNA microarray techniques. Our microarray analyses identified seven microRNAs that could distinguish malignant esophageal cancer lesions from adjacent normal tissues. Some microRNAs could be correlated with the different clinicopathologic classifications. High expression of hsa-miR-103/107 correlated with poor survival by univariate analysis as well as by multivariate analysis. These results indicate that microRNA expression profiles are important diagnostic and prognostic markers of esophageal cancer, which might be analyzed simply using economical approaches such as reverse transcription-PCR.

MicroRNAs (miRNAs) are important gene regulators, which are often deregulated in cancers. In this study, the authors analyzed the microRNAs profiles of 78 matched cancer/noncanerous liver tissues from HCC patients and 10 normal liver tissues and found that 69 miRNAs were differentially expressed between hepatocellular carcinoma (HCC) and corresponding noncancerous liver tissues (N). Then the expressions of 8 differentially expressed miRNAs were validated by real time RT PCR. The set of differentially expressed miRNAs could distinctly classify HCC, N and normal liver tissues (NL). Moreover, some of these differentially expressed miRNAs were related to the clinical factors of HCC patients. Most importantly, Kaplan-Meier estimates and the log-rank test showed that high expression of hsa-miR-125b was correlated with good survival of HCC patients (hazard ratio, 1.787, 95% confidence interval, 1.020-3.133, p 5 0.043). The transfection assay showed that overexpression of miR-125b in HCC cell line could obviously suppress the cell growth and phosporylation of Akt. In conclusion, the authors have demonstrated the diagnostic miRNA profile for HCC, and for the first time, identified the miR-125b with predictive significance for HCC prognosis.

MicroRNAs are important gene regulators that potentially play a profound role in tumorigenesis. Increasing evidence indicates that miR-145 is a tumor suppressor capable of inhibiting breast and colon cancer cell growth both in vitro and in vivo. However, the biological function of miR-145 in non-small cell lung cancer (NSCLC) is largely unknown. In colon cancer cells, c-Myc is a confirmed direct target for miR-145. The aim of this work was to investigate the effect of miR-145 and c-Myc on proliferation of NSCLC cells, using the NSCLC cell lines A549 and H23 as models. We determined the expression level of miR-145 in tumor tissues relative to adjacent non-tumor tissues, and in NSCLC cell lines relative to non-malignant lung cells. Downregulation of miR-145 was seen in tumor tissues and the two NSCLC cell lines by real-time quantitative reverse transcription polymerase chain reaction. MTT and focus formation assays were conducted to measure cell proliferation rates. Cell growth was inhibited and the G1/S transition was blocked by miR-145 in transfection assays of A549 and H23 cells. We further showed that c-Myc was a direct target for miR-145. Introduction of miR-145 dramatically suppressed the c-Myc/eIF4E pathway, which was demonstrated to be crucial for cell proliferation in NSCLC cells. Furthermore, we found that CDK4 was regulated by miR-145 in cell cycle control. Taken together, our study results demonstrate that miR-145 inhibits proliferation of NSCLC cells through c-Myc. Increasing miR-145 expression may provide a novel approach for the treatment of NSCLC.

Smart cities have been a global concern in recent years, involving comprehensive scientific research. To obtain a structural overview and assist researchers in making insights into the characteristics of smart cities research, bibliometric analysis was carried out in this paper. With the application of the bibliometric analysis software VOSviewer and CiteSpace, 4409 smart cities were identified by the core collection of the Web of Science in publications between 1998 and 2019 and used in the analysis of this paper. Concretely, this research visually demonstrates a comprehensive overview of the field relating to smart cities in terms of the production of regular publications, main domain of smart cities researchers, most influential countries (institutions, sources and authors), and interesting research directions in the smart city researches. We also present the research collaboration among countries (regions), organizations and authors based on a series of cooperation analyses. The bibliometric analysis of the existing work provided a valuable and seminal reference for researchers and practitioners in smart cities-related research communities.

Purpose: Recent studies have suggested that microRNA biomarkers could be useful for stratifying lung cancer subtypes, but microRNA signatures varied between different populations. Squamous cell carcinoma (SCC) is one major subtype of lung cancer that urgently needs biomarkers to aid patient management. Here, we undertook the first comprehensive investigation on microRNA in Chinese SCC patients.Experimental Design: MicroRNA expression was measured in cancerous and noncancerous tissue pairs strictly collected from Chinese SCC patients (stages I-III), who had not been treated with chemotherapy or radiotherapy prior to surgery. The molecular targets of proposed microRNA were further examined.Results: We identified a 5-microRNA classifier (hsa-miR-210, hsa-miR-182, hsa-miR-486-5p, hsamiR-30a, and hsa-miR-140-3p) that could distinguish SCC from normal lung tissues. The classifier had an accuracy of 94.1% in a training cohort (34 patients) and 96.2% in a test cohort (26 patients). We also showed that high expression of hsa-miR-31 was associated with poor survival in these 60 SCC patients by Kaplan-Meier analysis (P ¼ 0.007), by univariate Cox analysis (P ¼ 0.011), and by multivariate Cox analysis (P ¼ 0.011). This association was independently validated in a separate cohort of 88 SCC patients (P ¼ 0.008, 0.011, and 0.003 in Kaplan-Meier analysis, univariate Cox analysis, and multivariate Cox analysis, respectively). We then determined that the tumor suppressor DICER1 is a target of hsa-miR-31. Expression of hsa-miR-31 in a human lung cancer cell line repressed DICER1 activity but not PPP2R2A or LATS2.Conclusions: Our results identified a new diagnostic microRNA classifier for SCC among Chinese patients and a new prognostic biomarker, hsa-miR-31. Clin Cancer Res; 17(21); 6802-11. Ó2011 AACR.