Human papillomaviruses (HPV) are associated with nearly all cervical cancers, 20% to 30% of head and neck cancers (HNC), and other cancers. Because HNCs also arise in HPV-negative patients, this type of cancer provides unique opportunities to define similarities and differences of HPV-positive versus HPVnegative cancers arising in the same tissue.

Using highly sensitive microarray-based procedures, we identified eight microRNAs (miRNAs) showing robust differential expression between 31 laser-capture-microdissected nasopharyngeal carcinomas (NPCs) and 10 normal healthy nasopharyngeal epithelial samples. In particular, miRNA mir-29c was expressed at one-fifth the levels in tumors as in normal epithelium. In NPC tumors, the lower mir-29c levels correlated with higher levels of multiple mRNAs whose 3 UTRs can bind mir-29c at target sequences conserved across many vertebrates. In cultured cells, introduction of mir-29c down-regulated these genes at the level of mRNA and inhibited expression of luciferase encoded by vectors having the 3 UTRs of these genes. Moreover, for each of several genes tested, mutating the mir-29c target sites in the 3 UTR abrogated mir-29c-induced inhibition of luciferase expression. Most of the mir-29c-targeted genes identified encode extracellular matrix proteins, including multiple collagens and laminin ␥1, that are associated with tumor cell invasiveness and metastatic potential, prominent characteristics of NPC. Thus, we identify eight miRNAs differentially expressed in NPC and demonstrate the involvement of one in regulating genes involved in metastasis.microarray ͉ collagen ͉ metastasis ͉ miRNA M icroRNAs (miRNAs) are short (Ϸ22 nucleotides) noncoding RNAs involved in posttranscriptional silencing of target genes. In animals, miRNAs control expression of target genes by inhibiting translation, by degrading target mRNAs, or both, through binding to their 3Ј UTRs with varying degrees of sequence complementarity (1). miRNAs have been found to regulate genes involved in diverse biological functions, including development, differentiation, proliferation, and stress response (2). Recently, a growing number of miRNAs have been implicated in cancers, including mir-15 and mir-16 in B cell chronic lymphocytic leukemias (3, 4); mir-143 and mir-145 in colorectal cancer (5); mir- 17-5p, mir-21, mir-125b, mir-145, and mir-155 in breast cancer (6, 7); mir-19, mir-146, mir-181b, mir-221, mir-222, and mir-346 in thyroid cancer (8-10); and mir-21 in glioblastoma (11). A significant number of miRNAs also have been mapped to cancer-associated genomic regions (12). Expression of miRNA let-7 has been correlated with prognosis in lung cancer (13) and found to regulate Ras in the same tumor (14). Very recently, mir-10b has been shown to contribute to metastasis in breast cancer (15). Although many miRNAs have been implicated in regulating cancers, very few of their target genes, and hence their downstream mode of action, have been identified.We developed a sensitive microarray-based assay to profile miRNA expression and used it to analyze human miRNAs in laser-microdissected tumor and normal cells from biopsies of a highly invasive cancer, nasopharyngeal carcinoma (NPC), and site-matched normal tissues. Eight miRNAs were differentially expressed. One of them, mir-29c, down-regulated in NPC, was shown to target multiple mRNAs encoding extracellular ma...

A prespecified set of genes may be enriched, to varying degrees, for genes that have altered expression levels relative to two or more states of a cell. Knowing the enrichment of gene sets defined by functional categories, such as gene ontology (GO) annotations, is valuable for analyzing the biological signals in microarray expression data. A common approach to measuring enrichment is by crossclassifying genes according to membership in a functional category and membership on a selected list of significantly altered genes. A small Fisher's exact test p-value, for example, in this 2 × 2 table is indicative of enrichment. Other category analysis methods retain the quantitative gene-level scores and measure significance by referring a category-level statistic to a permutation distribution associated with the original differential expression problem. We describe a class of random-set scoring methods that measure distinct components of the enrichment signal. The class includes Fisher's test based on selected genes and also tests that average gene-level evidence across the category. Averaging and selection methods are compared empirically using Affymetrix data on expression in nasopharyngeal cancer tissue, and theoretically using a location model of differential expression. We find that each method has a domain of superiority in the state space of enrichment problems, and that both methods have benefits in practice. Our analysis also addresses two problems related to multiple-category inference, namely, that equally enriched categories are not detected with equal probability if they are of different sizes,

To identify the molecular mechanisms by which EBVassociated epithelial cancers are maintained, we measured the expression of essentially all human genes and all latent EBV genes in a collection of 31 laser-captured, microdissected nasopharyngeal carcinoma (NPC) tissue samples and 10 normal nasopharyngeal tissues. Global gene expression profiles clearly distinguished tumors from normal healthy epithelium. Expression levels of six viral genes (EBNA1, EBNA2, EBNA3A, EBNA3B, LMP1, and LMP2A) were correlated among themselves and strongly inversely correlated with the expression of a large subset of host genes. Among the human genes whose inhibition was most strongly correlated with increased EBV gene expression were multiple MHC class I HLA genes involved in regulating immune response via antigen presentation. The association between EBV gene expression and inhibition of MHC class I HLA expression implies that antigen display is either directly inhibited by EBV, facilitating immune evasion by tumor cells, and/or that tumor cells with inhibited presentation are selected for their ability to sustain higher levels of EBV to take maximum advantage of EBV oncogenemediated tumor-promoting actions. Our data clearly reflect such tumor promotion, showing that deregulation of key proteins involved in apoptosis (BCL2-related protein A1 and Fas apoptotic inhibitory molecule), cell cycle checkpoints (AKIP, SCYL1, and NIN), and metastasis (matrix metalloproteinase 1) is closely correlated with the levels of EBV gene expression in NPC. (Cancer Res 2006; 66(16): 7999-8006)

The salamander has the remarkable ability to regenerate its limb after amputation. Cells at the site of amputation form a blastema and then proliferate and differentiate to regrow the limb. To better understand this process, we performed deep RNA sequencing of the blastema over a time course in the axolotl, a species whose genome has not been sequenced. Using a novel comparative approach to analyzing RNA-seq data, we characterized the transcriptional dynamics of the regenerating axolotl limb with respect to the human gene set. This approach involved de novo assembly of axolotl transcripts, RNA-seq transcript quantification without a reference genome, and transformation of abundances from axolotl contigs to human genes. We found a prominent burst in oncogene expression during the first day and blastemal/limb bud genes peaking at 7 to 14 days. In addition, we found that limb patterning genes, SALL genes, and genes involved in angiogenesis, wound healing, defense/immunity, and bone development are enriched during blastema formation and development. Finally, we identified a category of genes with no prior literature support for limb regeneration that are candidates for further evaluation based on their expression pattern during the regenerative process.

Epstein-Barr Virus (EBV) encodes multiple microRNAs (miRNAs) from two primary transcripts, BHRF1 and the BARTs. The expression of BHRF1 miRNAs is dependent on the type of viral latency, whereas the BART miRNAs are expressed in cells during all forms of latency. It is not known how these miRNAs are otherwise regulated, though. We have used quantitative, stem-loop, real-time PCR to measure the expression of EBV’s miRNAs and found them to differ nearly 50- and 25-fold among all tested cell lines and among EBV-positive Burkitt’s lymphomas, respectively. In addition, the expression of individual BART miRNAs within a cell can differ by 50-fold or more despite the fact these miRNAs are likely transcribed together as a single primary transcript. These measurements are illuminating: they indicate that few of EBV’s miRNAs are expressed at levels comparable to those of cellular miRNAs in most cell lines and therefore likely function interdependently.

Human embryonic stem (ES) cells exhibit a shorter G(1) cell cycle phase than most somatic cells. Here, we examine the role of an abundant, human ES cell-enriched microRNA, miR-92b, in cell cycle distribution. Inhibition of miR-92b in human ES cells results in a greater number of cells in the G(1) phase and a lower number in the S phase. Conversely, overexpression of miR-92b in differentiated cells results in a decreased number of cells in G1 phase and an increased number in S-phase. p57, a gene whose product inhibits G(1) to S-phase progression, is one of the predicted targets of miR-92b. Inhibition of miR-92b in human ES cells increases p57 protein levels, and miR-92b overexpression in differentiated cells decreases p57 protein levels. Furthermore, miR-92b inhibits a luciferase reporter construct that includes part of the 3' untranslated region of the p57 gene containing the predicted target of the miR-92b seed sequence. Thus, we show that the miRNA miR-92b directly downregulates protein levels of the G(1)/S checkpoint gene p57. STEM CELLS 2009;27:1524-1528.

Microarrays of virus-specific oligonucleotides may provide a method of screening samples for the presence or absence of a large variety of viruses simultaneously. Influenza viruses are ideal for evaluating such microarrays because of their genetic and host diversity, and the availability of an extensive sequence database. A collection of 476 influenza virus-specific oligonucleotides was spotted onto glass slides as probes. Viral RNAs were reverse transcribed and amplified by PCR, and the products were labeled with cyanine dyes. The presence of viruses and their identities were determined by hybridization. The fluorescence intensities of oligonucleotide spots were highly reproducible within each slide and satisfactorily proportional between experiments. However, the intensities of probe spots completely complementary to target sequences varied from background to saturation. The variations did not correlate with base composition, nucleotide sequence, or internal secondary structures. Therefore, thresholds for determining whether hybridization to a spot should be judged as positive were assigned individually. Considering only positive spots from probes predicted to be monospecific for influenza virus species, subtype, host source, or gene segment, this method made correct identifications at the species, hemagglutinin subtype, and gene segment levels. Monospecific neuraminidase (NA) subtype probes were insufficiently diverse to allow confident NA subtype assignment. Incorporating positive spots from polyspecific probes into the identification scheme gave similar results. Overall, the results demonstrate the potential of microarray-based oligonucleotide hybridization for multiple virus detection.