Publications

The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly. Uniform processing and comprehensive annotation of these data allow comparison across metazoan phyla, extending beyond earlier within-phylum transcriptome comparisons and revealing ancient, conserved features. Specifically, we discover co-expression modules shared across animals, many of which are enriched in developmental genes. Moreover, we use expression patterns to align the stages in worm and fly development and find a novel pairing between worm embryo and fly pupae, in addition to the embryo-to-embryo and larvae-to-larvae pairings. Furthermore, we find that the extent of non-canonical, non-coding transcription is similar in each organism, per base pair. Finally, we find in all three organisms that the gene-expression levels, both coding and non-coding, can be quantitatively predicted from chromatin features at the promoter using a 'universal model' based on a single set of organism-independent parameters.

While microRNAs (miRNAs) and the KRAS oncogene are known to be dysregulated in various cancers, little is known about the role of miRNAs in the regulation of KRAS in cancer. Here we review a selection of studies published in 2014 that have contributed to our understanding of the molecular mechanisms of KRAS regulation by miRNAs and the clinical relevance of sequence variants that may interfere with functional miRNA-mediated KRAS regulation.

MicroRNAs, a class of small, non-coding RNAs, are now widely known for their importance in many aspects of biology. These small regulatory RNAs have critical functions in diverse biological events, including development and disease. Recent findings show that microRNAs are essential for lifespan determination in the model organisms, Caenorhabditis elegans and Drosophila, suggesting that microRNAs are also involved in the complex process of ageing. Further, short RNA fragments derived from longer parental RNAs, such as transfer RNA cleavage fragments, have now emerged as a novel class of regulatory RNAs that inhibit translation in response to stress. In addition, the RNA editing pathway is likely to act in the double-stranded RNA-mediated silencing machinery to suppress unfavorable RNA interference activity in the ageing process. These multiple, redundant layers in gene regulatory networks may make it possible to both stably and flexibly regulate genetic pathways in ensuring robustness of developmental and ageing processes.

Once considered genetic "oddities", microRNAs (miRNAs) are now recognized as key epigenetic regulators of numerous biological processes, including some with a causal link to the pathogenesis, maintenance, and treatment of cancer. The crux of small RNA-based therapeutics lies in the antagonism of potent cellular targets; the main shortcoming of the field in general, lies in ineffective delivery. Inhibition of oncogenic miRNAs is a relatively nascent therapeutic concept, but as with predecessor RNA-based therapies, success hinges on delivery efficacy. This review will describes the canonical (e.g. pharmacokinetics and clearance, cellular uptake, endosome escape, etc.) and non-canonical (e.g. spatial localization and accessibility of miRNA, technical limitations of miRNA inhibition, off-target impacts, etc.) challenges to the delivery of antisense-based anti-miRNA therapeutics (i.e. antimiRs) for the treatment of cancer. Emphasis will be placed on how the current leading antimiR platforms-ranging from naked chemically modified oligonucleotides to nanoscale delivery vehicles-are affected by and overcome these barriers. The perplexity of antimiR delivery presents both engineering and biological hurdles that must be overcome in order to capitalize on the extensive pharmacological benefits of antagonizing tumor-associated miRNAs.

Radiotherapy is a form of cancer treatment that utilizes the ability of ionizing radiation to induce cell inactivation and cell death, generally via inflicting DNA double-strand breaks. However, different tumors and their normal surrounding tissues are not equally sensitive to radiation, posing a major challenge in the field: to seek out factors that influence radiosensitivity. In this review, we summarize the evidence for microRNA (miRNA) involvement in the radioresponse and discuss their potential as radiosensitizers. MicroRNAs are endogenous small, noncoding RNAs that regulate gene expression posttranscriptionally, influencing many processes including, as highlighted here, cellular sensitivity to radiation. Profiling studies demonstrate that miRNA expression levels change in response to radiation, while certain miRNAs, when overexpressed or knocked down, alter radiosensitivity. Finally, we discuss specific miRNA-target pairs that affect response to radiation and DNA damage as good potential targets for modulating radioresponsitivity.

Although in vivo models are excellent for assessing various facets of whole organism physiology, pathology, and overall response to treatments, evaluating basic cellular functions, and molecular events in mammalian model systems is challenging. It is therefore advantageous to perform these studies in a refined and less costly setting. One approach involves utilizing cells derived from the model under evaluation. The approach to generate such cells varies based on the cell of origin and often the genetics of the cell. Here we describe the steps involved in generating epithelial cells from the lungs of KrasLSL-G12D/+; p53LSL-R172/+ mice (Kasinski and Slack, 2012). These mice develop aggressive lung adenocarcinoma following cre-recombinase dependent removal of a stop cassette in the transgenes and subsequent expression of Kra-G12D and p53R172 . While this protocol may be useful for the generation of epithelial lines from other genetic backgrounds, it should be noted that the Kras; p53 cell line generated here is capable of proliferating in culture without any additional genetic manipulation that is often needed for less aggressive backgrounds.

A select group of microRNAs identified in blood samples can differentiate between Alzheimer's disease, other neurological disorders and age-matched healthy controls with high accuracy.

MOTIVATION: MicroRNAs (miRNAs) play a crucial role in tumorigenesis and development through their effects on target genes. The characterization of miRNA-gene interactions will lead to a better understanding of cancer mechanisms. Many computational methods have been developed to infer miRNA targets with/without expression data. Because expression datasets are in general limited in size, most existing methods concatenate datasets from multiple studies to form one aggregated dataset to increase sample size and power. However, such simple aggregation analysis results in identifying miRNA-gene interactions that are mostly common across datasets, whereas specific interactions may be missed by these methods. Recent releases of The Cancer Genome Atlas data provide paired expression profiling of miRNAs and genes in multiple tumors with sufficiently large sample size. To study both common and cancer-specific interactions, it is desirable to develop a method that can jointly analyze multiple cancers to study miRNA-gene interactions without combining all the data into one single dataset.

RESULTS: We developed a novel statistical method to jointly analyze expression profiles from multiple cancers to identify miRNA-gene interactions that are both common across cancers and specific to certain cancers. The benefit of this joint analysis approach is demonstrated by both simulation studies and real data analysis of The Cancer Genome Atlas datasets. Compared with simple aggregate analysis or single sample analysis, our method can effectively use the shared information among different but related cancers to improve the identification of miRNA-gene interactions. Another useful property of our method is that it can estimate similarity among cancers through their shared miRNA-gene interactions.

AVAILABILITY AND IMPLEMENTATION: The program, MCMG, implemented in R is available at http://bioinformatics.med.yale.edu/group/.