Xiaowei Wang

MicroRNAs play important roles in animal development, cell differentiation, and metabolism and have been implicated in human cancer. The let-7 microRNA controls the timing of cell cycle exit and terminal differentiation in Caenorhabditis elegans and is poorly expressed or deleted in human lung tumors. Here, we show that let-7 is highly expressed in normal lung tissue, and that inhibiting let-7 function leads to increased cell division in A549 lung cancer cells. Overexpression of let-7 in cancer cell lines alters cell cycle progression and reduces cell division, providing evidence that let-7 functions as a tumor suppressor in lung cells. let-7 was previously shown to regulate the expression of the RAS lung cancer oncogenes, and our work now shows that multiple genes involved in cell cycle and cell division functions are also directly or indirectly repressed by let-7. This work reveals the let-7 microRNA to be a master regulator of cell proliferation pathways.

PrimerBank (http://pga.mgh.harvard.edu/primerbank/) is a public resource for the retrieval of human and mouse primer pairs for gene expression analysis by PCR and Quantitative PCR (QPCR). A total of 306,800 primers covering most known human and mouse genes can be accessed from the PrimerBank database, together with information on these primers such as T(m), location on the transcript and amplicon size. For each gene, at least one primer pair has been designed and in many cases alternative primer pairs exist. Primers have been designed to work under the same PCR conditions, thus facilitating high-throughput QPCR. There are several ways to search for primers for the gene(s) of interest, such as by: GenBank accession number, NCBI protein accession number, NCBI gene ID, PrimerBank ID, NCBI gene symbol or gene description (keyword). In all, 26,855 primer pairs covering most known mouse genes have been experimentally validated by QPCR, agarose gel analysis, sequencing and BLAST, and all validation data can be freely accessed from the PrimerBank web site.

Here, we present LNCipedia (http://www.lncipedia.org), a novel database for human long non-coding RNA (lncRNA) transcripts and genes. LncRNAs constitute a large and diverse class of non-coding RNA genes. Although several lncRNAs have been functionally annotated, the majority remains to be characterized. Different high-throughput methods to identify new lncRNAs (including RNA sequencing and annotation of chromatin-state maps) have been applied in various studies resulting in multiple unrelated lncRNA data sets. LNCipedia offers 21 488 annotated human lncRNA transcripts obtained from different sources. In addition to basic transcript information and gene structure, several statistics are determined for each entry in the database, such as secondary structure information, protein coding potential and microRNA binding sites. Our analyses suggest that, much like microRNAs, many lncRNAs have a significant secondary structure, in-line with their presumed association with proteins or protein complexes. Available literature on specific lncRNAs is linked, and users or authors can submit articles through a web interface. Protein coding potential is assessed by two different prediction algorithms: Coding Potential Calculator and HMMER. In addition, a novel strategy has been integrated for detecting potentially coding lncRNAs by automatically re-analysing the large body of publicly available mass spectrometry data in the PRIDE database. LNCipedia is publicly available and allows users to query and download lncRNA sequences and structures based on different search criteria. The database may serve as a resource to initiate small- and large-scale lncRNA studies. As an example, the LNCipedia content was used to develop a custom microarray for expression profiling of all available lncRNAs.

BACKGROUND: Recent studies have demonstrated that long non-coding RNAs (lncRNAs) were present in the blood of cancer patients and have shown great potential as powerful and non-invasive tumor markers. However, little is known about the value of lncRNAs in the diagnosis of esophageal squamous cell carcinoma (ESCC). We hypothesized that ESCC-related lncRNAs might be released into the circulation during tumor initiation and could be utilized to detect and monitor ESCC. METHODS: Ten lncRNAs (HOTAIR, AFAP1-AS1, POU3F3, HNF1A-AS1, 91H, PlncRNA1, SPRY4-IT1, ENST00000435885.1, XLOC_013104 and ENST00000547963.1) which previously found to be differently expressed in esophageal cancer were selected as candidate targets for subsequent circulating lncRNA assay. A four-stage exploratory study was conducted to test the hypothesis: (1) optimization of detected method to accurately and reproducibly measure ESCC-related lncRNAs in plasma and serum; (2) evaluation of the stability of circulating lncRNAs in human plasma or serum; (3) exploration the origin of ESCC-related lncRNAs in vitro and in vivo; (4) evaluation the diagnostic power of circulating lncRNAs for ESCC. RESULTS: ESCC-related lncRNAs were detectable and stable in plasma of cancer patients, and derived largely from ESCC tumor cells. Furthermore, plasma levels of POU3F3, HNF1A-AS1 and SPRY4-IT1 were significantly higher in ESCC patients compared with normal controls. By receiver operating characteristic curve (ROC) analysis, among the three lncRNAs investigated, plasma POU3F3 provided the highest diagnostic performance for detection of ESCC (the area under the ROC curve (AUC), 0.842; p < 0.001; sensitivity, 72.8%; specificity, 89.4%). Moreover, use of POU3F3 and SCCA in combination could provide a more effective diagnosis performance (AUC, 0.926, p < 0.001, sensitivity, 85.7%; specificity, 81.4%). Most importantly, this combination was effective to detect ESCC at an early stage (80.8%). CONCLUSIONS: Plasma POU3F3 could serve as a potential biomarker for diagnosis of ESCC, and the combination of POU3F3 and SCCA was more efficient for ESCC detection, in particular for early tumor screening.

BACKGROUND: Extracellular communication within the tumor microenvironment plays a critical role in tumor progression. Although exosomes can package into long non-coding RNAs (lncRNAs) to mediate extracellular communication, the role of exosomal lncRNA PTENP1 in bladder cancer (BC) remains unclear. METHOD: We detected PTENP1 expression between patients with BC and healthy controls; the expression occurred in tissues and exosomes from plasma. We assessed the diagnostic accuracy by the receiver operating characteristic curve (ROC) and the area under curve (AUC). Cell phenotypes and animal experiments were performed to determine the effect of exosomal PTENP1. RESULTS: PTENP1 was significantly reduced in BC tissues and in exosomes from plasma of patients with BC (P < 0.05). We found that PTENP1 was mainly wrapped by exosomes. Exosomal PTENP1 could distinguish patients with BC from healthy controls (AUC = 0.743; 95% confidence interval (CI) = 0.645-0.840). Normal cells secreted exosomal PTENP1 and transmitted it to BC cells, thus inhibiting the biological malignant behavior of BC cells by increasing cell apoptosis and reducing the ability to invade and migrate (P < 0.05). Exosomal PTENP1 could suppress tumor growth in vivo. Furthermore, exosomal PTENP1 mediated the expression of PTEN by competitively binding to microRNA-17. CONCLUSION: Exosomal PTENP1 is a promising novel biomarker that can be used for the clinical detection of BC. Exosomes derived from normal cells transfer PTENP1 to BC cells, which reduce the progression of BC both in vitro and in vivo and suggest that exosomal PTENP1 participates in normal-cell-to-bladder-cell communication during the carcinogenesis of BC.