Clinically driven semi-supervised class discovery in gene expression data

Abstract Motivation: Unsupervised class discovery in gene expression data relies on the statistical signals in the data to exclusively drive the results. It is often the case, however, that one is interested in constraining the search space to respect certain biological prior knowledge while still allowing a flexible search within these boundaries. Results: We develop an approach to semi-supervised class discovery. One component of our approach uses clinical sample information to constrain the search space and guide the class discovery process to yield biologically relevant partitions. A second component consists of using known biological annotation of genes to drive the search, seeking partitions that manifest strong differential expression in specific sets of genes. We develop efficient algorithmics for these tasks, implementing both approaches and combinations thereof. We show that our method is robust enough to detect known clinical parameters in accordance with expected clinical values. We also use our method to elucidate cardiovascular disease (CVD) putative risk factors. Availability: MonoClaD (Monotone Class Discovery). See http://bioinfo.cs.technion.ac.il/people/zohar/MonoClad/ Supplementary information: Supplementary data is available at http://bioinfo.cs.technion.ac.il/people/zohar/MonoClad/software.html Contact: [email protected]

Novel Rank-Based Statistical Methods Reveal MicroRNAs with Differential Expression in Multiple Cancer Types

BACKGROUND:MicroRNAs (miRNAs) regulate target genes at the post-transcriptional level and play important roles in cancer pathogenesis and development. Variation amongst individuals is a significant confounding factor in miRNA (or other) expression studies. The true character of biologically or clinically meaningful differential expression can be obscured by inter-patient variation. In this study we aim to identify miRNAs with consistent differential expression in multiple tumor types using a novel data analysis approach. METHODS:Using microarrays we profiled the expression of more than 700 miRNAs in 28 matched tumor/normal samples from 8 different tumor types (breast, colon, liver, lung, lymphoma, ovary, prostate and testis). This set is unique in putting emphasis on minimizing tissue type and patient related variability using normal and tumor samples from the same patient. We develop scores for comparing miRNA expression in the above matched sample data based on a rigorous characterization of the distribution of order statistics over a discrete state set, including exact p-values. Specifically, we compute a Rank Consistency Score (RCoS) for every miRNA measured in our data. Our methods are also applicable in various other contexts. We compare our methods, as applied to matched samples, to paired t-test and to the Wilcoxon Signed Rank test. RESULTS:We identify consistent (across the cancer types measured) differentially expressed miRNAs. 41 miRNAs are under-expressed in cancer compared to normal, at FDR (False Discovery Rate) of 0.05 and 17 are over-expressed at the same FDR level. Differentially expressed miRNAs include known oncomiRs (e.g miR-96) as well as miRNAs that were not previously universally associated with cancer. Specific examples include miR-133b and miR-486-5p, which are consistently down regulated and mir-629* which is consistently up regulated in cancer, in the context of our cohort. Data is available in GEO. Software is available at: http://bioinfo.cs.technion.ac.il/people/zohar/RCoS

A Novel Translocation Breakpoint within the BPTF Gene Is Associated with a Pre-Malignant Phenotype

Partial gain of chromosome arm 17q is an abundant aberrancy in various cancer types such as lung and prostate cancer with a prominent occurrence and prognostic significance in neuroblastoma – one of the most common embryonic tumors. The specific genetic element/s in 17q responsible for the cancer-promoting effect of these aberrancies is yet to be defined although many genes located in 17q have been proposed to play a role in malignancy. We report here the characterization of a naturally-occurring, non-reciprocal translocation der(X)t(X;17) in human lung embryonal-derived cells following continuous culturing. This aberrancy was strongly correlated with an increased proliferative capacity and with an acquired ability to form colonies in vitro. The breakpoint region was mapped by fluorescence in situ hybridization (FISH) to the 17q24.3 locus. Further characterization by a custom-made comparative genome hybridization array (CGH) localized the breakpoint within the Bromodomain PHD finger Transcription Factor gene (BPTF), a gene involved in transcriptional regulation and chromatin remodeling. Interestingly, this translocation led to elevation in the mRNA levels of the endogenous BPTF. Knock-down of BPTF restricted proliferation suggesting a role for BPTF in promoting cellular growth. Furthermore, the BPTF chromosomal region was found to be amplified in various human tumors, especially in neuroblastomas and lung cancers in which 55% and 27% of the samples showed gain of 17q24.3, respectively. Additionally, 42% percent of the cancer cell lines comprising the NCI-60 had an abnormal BPTF locus copy number. We suggest that deregulation of BPTF resulting from the translocation may confer the cells with the observed cancer-promoting phenotype and that our cellular model can serve to establish causality between 17q aberrations and carcinogenesis

GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists

<p>Abstract</p> <p>Background</p> <p>Since the inception of the GO annotation project, a variety of tools have been developed that support exploring and searching the GO database. In particular, a variety of tools that perform GO enrichment analysis are currently available. Most of these tools require as input a target set of genes and a background set and seek enrichment in the target set compared to the background set. A few tools also exist that support analyzing ranked lists. The latter typically rely on simulations or on union-bound correction for assigning statistical significance to the results.</p> <p>Results</p> <p><it>GOrilla </it>is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets. This is particularly useful in many typical cases where genomic data may be naturally represented as a ranked list of genes (e.g. by level of expression or of differential expression). <it>GOrilla </it>employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the <it>top </it>of a ranked gene list. Building on a complete theoretical characterization of the underlying distribution, called mHG, <it>GOrilla </it>computes an exact p-value for the observed enrichment, taking threshold multiple testing into account without the need for simulations. This enables rigorous statistical analysis of thousand of genes and thousands of GO terms in order of seconds. The output of the enrichment analysis is visualized as a hierarchical structure, providing a clear view of the relations between enriched GO terms.</p> <p>Conclusion</p> <p><it>GOrilla </it>is an efficient GO analysis tool with unique features that make a useful addition to the existing repertoire of GO enrichment tools. <it>GOrilla</it>'s unique features and advantages over other threshold free enrichment tools include rigorous statistics, fast running time and an effective graphical representation. <it>GOrilla </it>is publicly available at: <url>http://cbl-gorilla.cs.technion.ac.il</url></p

miRNA-mRNA Integrated Analysis Reveals Roles for miRNAs in Primary Breast Tumors

Peer reviewe

NMR hyperpolarization techniques of gases

Nuclear spin polarization can be significantly increased through the process of hyperpolarization, leading to an increase in the sensitivity of nuclear magnetic resonance (NMR) experiments by 4–8 orders of magnitude. Hyperpolarized gases, unlike liquids and solids, can often be readily separated and purified from the compounds used to mediate the hyperpolarization processes. These pure hyperpolarized gases enabled many novel MRI applications including the visualization of void spaces, imaging of lung function, and remote detection. Additionally, hyperpolarized gases can be dissolved in liquids and can be used as sensitive molecular probes and reporters. This Minireview covers the fundamentals of the preparation of hyperpolarized gases and focuses on selected applications of interest to biomedicine and materials science

Silencing of a large microRNA cluster on human chromosome 14q32 in melanoma: biological effects of mir-376a and mir-376c on insulin growth factor 1 receptor

<p>Abstract</p> <p>Background</p> <p>Metastatic melanoma is a devastating disease with limited therapeutic options. MicroRNAs (miRNAs) are small non coding RNA molecules with important roles in post-transcriptional gene expression regulation, whose aberrant expression has been implicated in cancer.</p> <p>Results</p> <p>We show that the expression of miRNAs from a large cluster on human chromosome 14q32 is significantly down-regulated in melanoma cell lines, benign nevi and melanoma samples relative to normal melanocytes. This miRNA cluster resides within a parentally imprinted chromosomal region known to be important in development and differentiation. In some melanoma cell lines, a chromosomal deletion or loss-of-heterozygosity was observed in the cis-acting regulatory region of this cluster. In several cell lines we were able to re-express two maternally-induced genes and several miRNAs from the cluster with a combination of de-methylating agents and histone de-acetylase inhibitors, suggesting that epigenetic modifications take part in their silencing. Stable over-expression of mir-376a and mir-376c, two miRNAs from this cluster that could be re-expressed following epigenetic manipulation, led to modest growth retardation and to a significant decrease in migration in-vitro. Bioinformatic analysis predicted that both miRNAs could potentially target the 3'UTR of IGF1R. Indeed, stable expression of mir-376a and mir-376c in melanoma cells led to a decrease in IGF1R mRNA and protein, and a luciferase reporter assay indicated that the 3'UTR of IGF1R is a target of both mir-376a and mir-376c.</p> <p>Conclusions</p> <p>Our work is the first to show that the large miRNA cluster on chromosome 14q32 is silenced in melanoma. Our results suggest that down-regulation of mir-376a and mir-376c may contribute to IGF1R over-expression and to aberrant negative regulation of this signaling pathway in melanoma, thus promoting tumorigenesis and metastasis.</p