Institute for Systems Biology

About: Institute for Systems Biology is a nonprofit organization based out in Seattle, Washington, United States. It is known for research contribution in the topics: Population & Proteomics. The organization has 1277 authors who have published 2777 publications receiving 353165 citations.

Urinary MicroRNA Profiling Predicts the Development of Microalbuminuria in Patients with Type 1 Diabetes

Abstract: Microalbuminuria provides the earliest clinical marker of diabetic nephropathy among patients with Type 1 diabetes, yet it lacks sensitivity and specificity for early histological manifestations of disease. In recent years microRNAs have emerged as potential mediators in the pathogenesis of diabetes complications, suggesting a possible role in the diagnosis of early stage disease. We used quantiative polymerase chain reaction (qPCR) to evaluate the expression profile of 723 unique microRNAs in the normoalbuminuric urine of patients who did not develop nephropathy (n = 10) relative to patients who subsequently developed microalbuminuria (n = 17). Eighteen microRNAs were strongly associated with the subsequent development of microalbuminuria, while 15 microRNAs exhibited gender-related differences in expression. The predicted targets of these microRNAs map to biological pathways known to be involved in the pathogenesis and progression of diabetic renal disease. A microRNA signature (miR-105-3p, miR-1972, miR-28-3p, miR-30b-3p, miR-363-3p, miR-424-5p, miR-486-5p, miR-495, miR-548o-3p and for women miR-192-5p, miR-720) achieved high internal validity (cross-validated misclassification rate of 11.1%) for the future development of microalbuminuria in this dataset. Weighting microRNA measurements by their number of kidney-relevant targets improved the prognostic performance of the miRNA signature (cross-validated misclassification rate of 7.4%). Future studies are needed to corroborate these early observations in larger cohorts.

Quantitative Proteomics Analysis Integrated with Microarray Data Reveals That Extracellular Matrix Proteins, Catenins, and P53 Binding Protein 1 Are Important for Chemotherapy Response in Ovarian Cancers

Abstract: Chemotherapy with carboplatin and paclitaxel is the standard treatment for ovarian cancer patients. Although most patients initially respond to this treatment, few are cured. Resistance to chemotherapy is the major cause of treatment failure. We applied a quantitative proteomic approach based on ICAT/MS/MS technology to analyze tissues harvested at primary debulking surgery before the initiation of combination chemotherapy in order to identify potential naive or intrinsic chemotherapy response proteins in ovarian cancers. We identified 44 proteins that are overexpressed, and 34 proteins that are underexpressed in the chemosensitive tissue compared to the chemoresistant tissue. The overexpressed proteins identified in the chemoresistant tissue include 10 proteins (25.6%) belonging to the extracellular matrix (ECM), including decorin, versican, basigin (CD147), fibulin-1, extracellular matrix protein 1, biglycan, fibronectin 1, dermatopontin, alpha-cardiac actin (smooth muscle actin), and an EGF-containing fibulin-like extracellular matrix protein 1. Interesting proteins identified as overexpressed in the chemosensitive tissue include gamma-catenin (junction plakoglobin) and delta-catenin, tumor suppressor p53-binding protein 1 (53BP1), insulin-like growth factor-binding protein 2 (IGFBP2), proliferating cell nuclear antigen (PCNA), annexin A11, and 53 kDa selenium binding protein 1. Integrative analysis with expression profiling data of eight chemoresistant tissues and 13 chemosensitive tissues revealed that 16 proteins showed consistent changes at both the protein and the RNA levels. These include P53 binding protein 1, catenin delta 1 and plakoglobin, EGF-containing fibulin-like extracellular matrix protein 1 and voltage-dependent anion-selective channel protein 1. Our results suggest that chemotherapy response may be determined by multiple and complex system properties involving extracellular-matrix, cell adhesion and junction proteins.

A call for benchmarking transposable element annotation methods

Abstract: DNA derived from transposable elements (TEs) constitutes large parts of the genomes of complex eukaryotes, with major impacts not only on genomic research but also on how organisms evolve and function. Although a variety of methods and tools have been developed to detect and annotate TEs, there are as yet no standard benchmarks—that is, no standard way to measure or compare their accuracy. This lack of accuracy assessment calls into question conclusions from a wide range of research that depends explicitly or implicitly on TE annotation. In the absence of standard benchmarks, toolmakers are impeded in improving their tools, annotators cannot properly assess which tools might best suit their needs, and downstream researchers cannot judge how accuracy limitations might impact their studies. We therefore propose that the TE research community create and adopt standard TE annotation benchmarks, and we call for other researchers to join the authors in making this long-overdue effort a success.