Large-scale integration of microarray data: Investigating the pathologies of cancer and infectious diseases

DNA microarray data provide a high-throughput technique for the genome-wide profiling of genes at the transcript level. With large amounts of microarray data deposited on various types and aspects of malignancies, microarray technology has revolutionized the study of cancer. Such experiments aid in the discovery of novel biomarkers and provide insight into disease diagnosis, prognosis and response to treatment. Nonetheless, microarray data contains non-biological obscuring variations and systemic biases, which can distort the extraction of true aberrations in gene expression. Moreover, the number of samples generated by a single experiment is typically less than is statistically required to support the large number of genes studied. As a result, biomarker gene lists produced from independent datasets show little overlap. Therefore, to understand the pathophysiology of cancers and the influence they exert on the cellular processes they override, methods for combining data from different sources are necessary.Meta-analysis techniques have been utilized to address this issue by conducting an individual statistical analysis on each of the acquired datasets, then incorporating the results to generate a final gene list based on aggregated p-values or ranks. However, much of the publicly accessible cancer microarray datasets are unbalanced or asymmetric and therefore lack data from healthy samples. Consequently, critical and considerable amounts of data are overlooked. An integrative approach that combines data prior to analysis can incorporate asymmetric data. For this reason, a merge approach to the previously validated technique, the significance analysis of microarrays, is proposed. The merged SAM technique reproduced the known-cancer literature with higher coverage than meta-analysis in the five independent cancer tissues considered. The same methodology was extended to a database of approximately 6000 healthy and cancer samples arising from thirteen tissues. The integrative approach has allowed for the identification of key genes common to the invasive paths of multiple cancers and can aid in drug discovery. Moreover, this integrative microarray approach was applied to viral data from HIV-1, hepatitis C and influenza to investigate the effect of these infections on iron-binding proteins. Iron is crucial for proteins involved in metabolism, DNA synthesis and immunity, accentuating such proteins as direct or indirect viral targets.Ph.D., Biomedical Engineering -- Drexel University, 201

Peripheral Immune Cell Gene Expression Predicts Survival of Patients with Non-Small Cell Lung Cancer

Prediction of cancer recurrence in patients with non-small cell lung cancer (NSCLC) currently relies on the assessment of clinical characteristics including age, tumor stage, and smoking history. A better prediction of early stage cancer patients with poorer survival and late stage patients with better survival is needed to design patient-tailored treatment protocols. We analyzed gene expression in RNA from peripheral blood mononuclear cells (PBMC) of NSCLC patients to identify signatures predictive of overall patient survival. We find that PBMC gene expression patterns from NSCLC patients, like patterns from tumors, have information predictive of patient outcomes. We identify and validate a 26 gene prognostic panel that is independent of clinical stage. Many additional prognostic genes are specific to myeloid cells and are more highly expressed in patients with shorter survival. We also observe that significant numbers of prognostic genes change expression levels in PBMC collected after tumor resection. These post-surgery gene expression profiles may provide a means to re-evaluate prognosis over time. These studies further suggest that patient outcomes are not solely determined by tumor gene expression profiles but can also be influenced by the immune response as reflected in peripheral immune cells

Genome-Wide Maps of Circulating miRNA Biomarkers for Ulcerative Colitis

Inflammatory Bowel Disease – comprised of Crohn's Disease and Ulcerative Colitis (UC) - is a complex, multi-factorial inflammatory disorder of the gastrointestinal tract. In this study we have explored the utility of naturally occurring circulating miRNAs as potential blood-based biomarkers for non-invasive prediction of UC incidences. Whole genome maps of circulating miRNAs in micro-vesicles, Peripheral Blood Mononuclear Cells and platelets have been constructed from a cohort of 20 UC patients and 20 normal individuals. Through Significance Analysis of Microarrays, a signature of 31 differentially expressed platelet-derived miRNAs has been identified and biomarker performance estimated through a non-probabilistic binary linear classification using Support Vector Machines. Through this approach, classifier measurements reveal a predictive score of 92.8% accuracy, 96.2% specificity and 89.5% sensitivity in distinguishing UC patients from normal individuals. Additionally, the platelet-derived biomarker signature can be validated at 88% accuracy through qPCR assays, and a majority of the miRNAs in this panel can be demonstrated to sub-stratify into 4 highly correlated intensity based clusters. Analysis of predicted targets of these biomarkers reveal an enrichment of pathways associated with cytoskeleton assembly, transport, membrane permeability and regulation of transcription factors engaged in a variety of regulatory cascades that are consistent with a cell-mediated immune response model of intestinal inflammation. Interestingly, comparison of the miRNA biomarker panel and genetic loci implicated in IBD through genome-wide association studies identifies a physical linkage between hsa-miR-941 and a UC susceptibility loci located on Chr 20. Taken together, analysis of these expression maps outlines a promising catalog of novel platelet-derived miRNA biomarkers of clinical utility and provides insight into the potential biological function of these candidates in disease pathogenesis

The Pediatric Cell Atlas:Defining the Growth Phase of Human Development at Single-Cell Resolution

Single-cell gene expression analyses of mammalian tissues have uncovered profound stage-specific molecular regulatory phenomena that have changed the understanding of unique cell types and signaling pathways critical for lineage determination, morphogenesis, and growth. We discuss here the case for a Pediatric Cell Atlas as part of the Human Cell Atlas consortium to provide single-cell profiles and spatial characterization of gene expression across human tissues and organs. Such data will complement adult and developmentally focused HCA projects to provide a rich cytogenomic framework for understanding not only pediatric health and disease but also environmental and genetic impacts across the human lifespan

Large-scale sequencing identifies multiple genes and rare variants associated with Crohn’s disease susceptibility

peer reviewe

Novel ZBTB24 Mutation Associated with Immunodeficiency, Centromere Instability, and Facial Anomalies Type-2 Syndrome Identified in a Patient with Very Early Onset Inflammatory Bowel Disease

BACKGROUND: Very early onset inflammatory bowel disease, diagnosed in children ≤5 years old, can be the initial presentation of some primary immunodeficiencies.METHODS: In this study, we describe a 17-month-old boy with recurrent infections, growth failure, facial anomalies, and inflammatory bowel disease. Immune evaluation, whole-exome sequencing, karyotyping, and methylation array were performed to evaluate the child's constellation of symptoms and examination findings.RESULTS: Whole-exome sequencing revealed that the child was homozygous for a novel variant in ZBTB24, the gene associated with immunodeficiency, centromere instability, and facial anomalies type-2 syndrome.CONCLUSION: This describes the first case of inflammatory bowel disease associated with immunodeficiency, centromere instability, and facial anomalies type-2 syndrome in a child with a novel disease-causing mutation in ZBTB24 found on whole-exome sequencing

Additional file 2: Figure S2. of H3K4 tri-methylation breadth at transcription start sites impacts the transcriptome of systemic lupus erythematosus

ENCODE data showing histone modifications. Many other histone modifications had patterns complementing to four distinctive H3K4me3 patterns. Sequencing depth from ChIP-seq data of CTCF and 11 histone modifications in CD14+ monocyte was obtained from the ENCODE project