Israel Steinfeld

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

BackgroundSince 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.ResultsGOrilla 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). GOrilla employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the top of a ranked gene list. Building on a complete theoretical characterization of the underlying distribution, called mHG, GOrilla 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.ConclusionGOrilla is an efficient GO analysis tool with unique features that make a useful addition to the existing repertoire of GO enrichment tools. GOrillas unique features and advantages over other threshold free enrichment tools include rigorous statistics, fast running time and an effective graphical representation. GOrilla is publicly available at: http://cbl-gorilla.cs.technion.ac.il

The Fine-Scale and Complex Architecture of Human Copy-Number Variation

Despite considerable excitement over the potential functional significance of copy-number variants (CNVs), we still lack knowledge of the fine-scale architecture of the large majority of CNV regions in the human genome. In this study, we used a high-resolution array-based comparative genomic hybridization (aCGH) platform that targeted known CNV regions of the human genome at approximately 1 kb resolution to interrogate the genomic DNAs of 30 individuals from four HapMap populations. Our results revealed that 1020 of 1153 CNV loci (88%) were actually smaller in size than what is recorded in the Database of Genomic Variants based on previously published studies. A reduction in size of more than 50% was observed for 876 CNV regions (76%). We conclude that the total genomic content of currently known common human CNVs is likely smaller than previously thought. In addition, approximately 8% of the CNV regions observed in multiple individuals exhibited genomic architectural complexity in the form of smaller CNVs within larger ones and CNVs with interindividual variation in breakpoints. Future association studies that aim to capture the potential influences of CNVs on disease phenotypes will need to consider how to best ascertain this previously uncharacterized complexity.

Developmental programming of CpG island methylation profiles in the human genome

CpG island–like sequences are commonly thought to provide the sole signals for designating constitutively unmethylated regions in the genome, thus generating open chromatin domains within a sea of global repression. Using a new database obtained from comprehensive microarray analysis, we show that unmethylated regions (UMRs) seem to be formed during early embryogenesis, not as a result of CpG-ness, but rather through the recognition of specific sequence motifs closely associated with transcription start sites. This same system probably brings about the resetting of pluripotency genes during somatic cell reprogramming. The data also reveal a new class of nonpromoter UMRs that become de novo methylated in a tissue-specific manner during development, and this process may be involved in gene regulation. In short, we show that UMRs are an important aspect of genome structure that have a dynamic role in development.

Chemically modified guide RNAs enhance CRISPR-Cas genome editing in human primary cells.

CRISPR-Cas-mediated genome editing relies on guide RNAs that direct site-specific DNA cleavage facilitated by the Cas endonuclease. Here we report that chemical alterations to synthesized single guide RNAs (sgRNAs) enhance genome editing efficiency in human primary T cells and CD34+ hematopoietic stem and progenitor cells. Co-delivering chemically modified sgRNAs with Cas9 mRNA or protein is an efficient RNA- or ribonucleoprotein (RNP)-based delivery method for the CRISPR-Cas system, without the toxicity associated with DNA delivery. This approach is a simple and effective way to streamline the development of genome editing with the potential to accelerate a wide array of biotechnological and therapeutic applications of the CRISPR-Cas technology.

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

Introduction Few studies have performed expression profiling of both miRNA and mRNA from the same primary breast carcinomas. In this study we present and analyze data derived from expression profiling of 799 miRNAs in 101 primary human breast tumors, along with genome-wide mRNA profiles and extensive clinical information. Methods We investigate the relationship between these molecular components, in terms of their correlation with each other and with clinical characteristics. We use a systems biology approach to examine the correlative relationship between miRNA and mRNAs using statistical enrichment methods. Results We identify statistical significant differential expression of miRNAs between molecular intrinsic subtypes, and between samples with different levels of proliferation. Specifically, we point to miRNAs significantly associated with TP53 and ER status. We also show that several cellular processes, such as proliferation, cell adhesion and immune response, are strongly associated with certain miRNAs. We validate the role of miRNAs in regulating proliferation using high-throughput lysate-microarrays on cell lines and point to potential drivers of this process. Conclusion This study provides a comprehensive dataset as well as methods and system-level results that jointly form a basis for further work on understanding the role of miRNA in primary breast cancer.

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/

Global Methylation Patterns in Idiopathic Pulmonary Fibrosis

Background Idiopathic Pulmonary Fibrosis (IPF) is characterized by profound changes in the lung phenotype including excessive extracellular matrix deposition, myofibroblast foci, alveolar epithelial cell hyperplasia and extensive remodeling. The role of epigenetic changes in determining the lung phenotype in IPF is unknown. In this study we determine whether IPF lungs exhibit an altered global methylation profile. Methodology/Principal Findings Immunoprecipitated methylated DNA from 12 IPF lungs, 10 lung adenocarcinomas and 10 normal histology lungs was hybridized to Agilent human CpG Islands Microarrays and data analysis was performed using BRB-Array Tools and DAVID Bioinformatics Resources software packages. Array results were validated using the EpiTYPER MassARRAY platform for 3 CpG islands. 625 CpG islands were differentially methylated between IPF and control lungs with an estimated False Discovery Rate less than 5%. The genes associated with the differentially methylated CpG islands are involved in regulation of apoptosis, morphogenesis and cellular biosynthetic processes. The expression of three genes (STK17B, STK3 and HIST1H2AH) with hypomethylated promoters was increased in IPF lungs. Comparison of IPF methylation patterns to lung cancer or control samples, revealed that IPF lungs display an intermediate methylation profile, partly similar to lung cancer and partly similar to control with 402 differentially methylated CpG islands overlapping between IPF and cancer. Despite their similarity to cancer, IPF lungs did not exhibit hypomethylation of long interspersed nuclear element 1 (LINE-1) retrotransposon while lung cancer samples did, suggesting that the global hypomethylation observed in cancer was not typical of IPF. Conclusions/Significance Our results provide evidence that epigenetic changes in IPF are widespread and potentially important. The partial similarity to cancer may signify similar pathogenetic mechanisms while the differences constitute IPF or cancer specific changes. Elucidating the role of these specific changes will potentially allow better understanding of the pathogenesis of IPF.

EGF Decreases the Abundance of MicroRNAs That Restrain Oncogenic Transcription Factors

Some cancers showed decreased abundance of a subset of EGF-regulated microRNAs, which allows the production of oncogenic transcription factors. A Loss of Restraint Growth factors, such as epidermal growth factor (EGF), bind to receptors to stimulate cell proliferation, a process critical during development and in wound healing. Dysregulation of the signaling pathways initiated by the EGF receptor (EGFR) has been implicated in cancer. Noting that aberrant expression of microRNAs, small noncoding RNAs that inhibit the expression of target genes, is common in human malignancies, Avraham et al. explored the role of microRNAs in regulating EGFR signaling. They found that EGF elicited a rapid—and transient—decrease in the abundance of a group of 23 microRNAs, thereby enabling the induction of potentially oncogenic transcription factor targets. Moreover, the abundance of this group of microRNAs was decreased in breast cancers and brain cancers with molecular lesions consistent with increased EGFR signaling. The authors conclude that, under basal conditions, this group of microRNAs restrains potentially oncogenic signaling pathways downstream of the EGFR. Their decreased abundance in cancer thus enables the dysregulated activity of oncogenic transcription factors and signaling pathways transiently activated by EGF signaling, thereby promoting the aberrant cellular behaviors associated with cancer. Epidermal growth factor (EGF) stimulates cells by launching gene expression programs that are frequently deregulated in cancer. MicroRNAs, which attenuate gene expression by binding complementary regions in messenger RNAs, are broadly implicated in cancer. Using genome-wide approaches, we showed that EGF stimulation initiates a coordinated transcriptional program of microRNAs and transcription factors. The earliest event involved a decrease in the abundance of a subset of 23 microRNAs. This step permitted rapid induction of oncogenic transcription factors, such as c-FOS, encoded by immediate early genes. In line with roles as suppressors of EGF receptor (EGFR) signaling, we report that the abundance of this early subset of microRNAs is decreased in breast and in brain tumors driven by the EGFR or the closely related HER2. These findings identify specific microRNAs as attenuators of growth factor signaling and oncogenesis.

Deregulation of cancer-related miRNAs is a common event in both benign and malignant human breast tumors

MicroRNAs (miRNAs) are endogenous non-coding RNAs, which play an essential role in the regulation of gene expression during carcinogenesis. The role of miRNAs in breast cancer has been thoroughly investigated, and although many miRNAs are identified as cancer related, little is known about their involvement in benign tumors. In this study, we investigated miRNA expression profiles in the two most common types of human benign tumors (fibroadenoma/fibroadenomatosis) and in malignant breast tumors and explored their role as oncomirs and tumor suppressor miRNAs. Here, we identified 33 miRNAs with similar deregulated expression in both benign and malignant tumors compared with the expression levels of those in normal tissue, including breast cancer-related miRNAs such as let-7, miR-21 and miR-155. Additionally, messenger RNA (mRNA) expression profiles were obtained for some of the same samples. Using integrated mRNA/miRNA expression analysis, we observed that overexpression of certain miRNAs co-occurred with a significant downregulation of their candidate target mRNAs in both benign and malignant tumors. In support of these findings, in vitro functional screening of the downregulated miRNAs in non-malignant and breast cancer cell lines identified several possible tumor suppressor miRNAs, including miR-193b, miR-193a-3p, miR-126, miR-134, miR-132, miR-486-5p, miR-886-3p, miR-195 and miR-497, showing reduced growth when re-expressed in cancer cells. The finding of deregulated expression of oncomirs and tumor suppressor miRNAs in benign breast tumors is intriguing, indicating that they may play a role in proliferation. A role of cancer-related miRNAs in the early phases of carcinogenesis and malignant transformation can, therefore, not be ruled out.

Association of N-Glycosylation with Breast Carcinoma and Systemic Features Using High-Resolution Quantitative UPLC

An improved separation of the human serum N-glycome using hydrophilic interaction chromatography technology with UPLC is described, where more than 140 N-glycans were assigned. Using this technique, serum samples from 107 healthy controls and 62 newly diagnosed breast cancer patients were profiled. The most statistically significant alterations were observed in cancer patients compared with healthy controls: an increase in sialylation, branching, and outer-arm fucosylation and a decrease in high-mannosylated and biantennary core-fucosylated glycans. In the controls and cases combined systemic features were analyzed; serum estradiol was associated with increase in digalactosylated glycans, and higher mammographic density was associated with increase in biantennary digalactosylated glycans and with decrease in trisialylated and in outer-arm fucosylated glycans. Furthermore, particular glycans were altered in some features of the breast carcinomas; bisected biantennary nonfucosylated glycans were decreased in patients with progesterone receptor positive tumors, and core-fucosylated biantennary bisected monogalactosylated glycans were decreased in patients with the TP53 mutation. Systemic features show more significant associations with the serum N-glycome than do the features of the breast carcinomas. In conclusion, the UPLC-based glycan analysis technique described here reveals highly significant differences between healthy women and breast cancer patients. Significant associations with breast carcinoma and systemic features are described.