Signature Center for Computational Diagnostics Translating Experimental Technologies into Clinical Research

poster abstractThe goal of the Center for Computational Diagnostics [http://www.iupui.edu/~compdiag] is to serve as a “reactor” of innovative research for the integration of diverse high throughput technology into clinical trials to allow clinical researchers to obtain a more comprehensive view of the disease states. It has become clear that to better understand diseases we cannot continue to only focus on single genes, proteins or metabolites operating in single linear ordered pathways. Large scale high throughput technologies such as applied in genomics, proteomics and metabolomics allow for a more comprehensive view of the complex interactions occurring within body fluids or tissues at any one time. The Center operates by addressing the three different areas that are required to successfully integrate high throughput methodologies into translational research: 1) High throughput biospecimen banking; 2) Generation of high quality datasets and 3) Workflow development for data storage and analysis. To support high throughput bio-specimen banking we have co-developed caTissue Suite under the national caBIG effort. The key developments of the Center have been: 1. CaTrack, an intelligent barcode-based automatic data capture system 2. protocol-driven Study Calendar 3. xCaCORE, an innovative XML-based data import and export software program 4. Scalable, globally unique specimen identification utilizing an ISO Object Identifiers encoding scheme 5. Barcode generator and label printing We have implemented the Pediatric Biospecimen Repository to be able to develop and test these informatics tools. In addition to functioning as the development and test site for informatics research, the repository also develops research protocols and stores biospecimens for Pediatrics, Ophthalmology and Obstetrics. We also support protocol and data management related to biospecimens for the CTSI and the Fairbanks Institute. We currently have 92 active protocols and data on 119,319 specimens in our production instance of caTissue Suite. This includes specimens from 1200 well-defined healthy control subjects across all age groups including 600 children. To develop the computational and statistical workflows for data storage and analysis, we have generated large well-designed datasets for coronary artery disease (LC-MS/MS, NMR, protein antibody arrays); cancer (osteosarcoma and Wilms tumor; LC-MS/MS, NMR, protein antibody arrays) and ophthalmologic diseases (glaucoma; protein antibody arrays). Our main focus is to develop analytical workflows that translate the large datasets into relevant information for clinical researchers, focusing on the biological interpretation of the results. In this context we developed statistical models for protein quantification for LC-MS/MS and protein antibody arrays. These workflows were implemented in the open source statistical software R and published under the R-based project Bioconductor

The Effect of Molecular Weight on Passage of Proteins Through the Blood-Aqueous Barrier

Purpose: To determine the effect of molecular weight (MW) on the concentration of plasma-derived proteins in aqueous humor and to estimate the plasma-derived and eye-derived fractions for each protein. Methods: Aqueous humor and plasma samples were obtained during cataract surgery on an institutional review board–approved protocol. Protein concentrations were determined by ELISA and quantitative antibody microarrays. A total of 93 proteins were studied, with most proteins analyzed using 27 to 116 aqueous and 6 to 30 plasma samples. Results: Plasma proteins without evidence of intraocular expression by sequence tags were used to fit a logarithmic model relating aqueous-plasma ratio (AH:PL) to MW. The log(AH:PL) appears to be well predicted by the log(MW) (P 80), and 17 proteins had contribution from both plasma and eye tissue (IOF 20–80). Conclusions: Protein concentration of plasma-derived proteins in aqueous is nonlinearly dependent on MW in favor of smaller proteins. Our study demonstrates that for proper interpretation of results, proteomic studies evaluating changes in aqueous humor protein levels should take into account the plasma and eye-derived fractions

Evidence for BCR/ABL1‐positive T‐cell acute lymphoblastic leukemia arising in an early lymphoid progenitor cell

BCR‐ABL1‐positive leukemias have historically been classified as either chronic myelogenous leukemia or Ph+ acute lymphoblastic leukemia. Recent analyses suggest there may be a wider range of subtypes. We report a patient with BCR‐ABL1 fusion positive T‐cell ALL with a previously undescribed cell distribution of the fusion gene. The examination of sorted cells by fluorescence in situ hybridization showed the BCR‐ABL1 fusion in the malignant T cells and a subpopulation of the nonmalignant B cells, but not nonmalignant T cells or myeloid or CD34+ progenitor cells providing evidence that the fusion may have occurred in an early lymphoid progenitor

The RIN: an RNA integrity number for assigning integrity values to RNA measurements

BACKGROUND: The integrity of RNA molecules is of paramount importance for experiments that try to reflect the snapshot of gene expression at the moment of RNA extraction. Until recently, there has been no reliable standard for estimating the integrity of RNA samples and the ratio of 28S:18S ribosomal RNA, the common measure for this purpose, has been shown to be inconsistent. The advent of microcapillary electrophoretic RNA separation provides the basis for an automated high-throughput approach, in order to estimate the integrity of RNA samples in an unambiguous way. METHODS: A method is introduced that automatically selects features from signal measurements and constructs regression models based on a Bayesian learning technique. Feature spaces of different dimensionality are compared in the Bayesian framework, which allows selecting a final feature combination corresponding to models with high posterior probability. RESULTS: This approach is applied to a large collection of electrophoretic RNA measurements recorded with an Agilent 2100 bioanalyzer to extract an algorithm that describes RNA integrity. The resulting algorithm is a user-independent, automated and reliable procedure for standardization of RNA quality control that allows the calculation of an RNA integrity number (RIN). CONCLUSION: Our results show the importance of taking characteristics of several regions of the recorded electropherogram into account in order to get a robust and reliable prediction of RNA integrity, especially if compared to traditional methods

Riociguat treatment in patients with chronic thromboembolic pulmonary hypertension: Final safety data from the EXPERT registry

Objective: The soluble guanylate cyclase stimulator riociguat is approved for the treatment of adult patients with pulmonary arterial hypertension (PAH) and inoperable or persistent/recurrent chronic thromboembolic pulmonary hypertension (CTEPH) following Phase

Discovering biomarkers for myocardial infarction from SELDI-TOF spectra

Höner zu Siederdissen C, Ragg S, Rahmann S. Discovering biomarkers for myocardial infarction from SELDI-TOF spectra. In: Advances in Data Analysis. Proceedings of the 30th Annual Conference of the Gesellschaft für Klassifikation e.V. Studies in Classification, Data Analysis, and Knowledge Organization. Springer; 2007: 569-576

Statistical protein quantification and significance analysis in label-free LC-MS experiments with complex designs

Background Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) is widely used for quantitative proteomic investigations. The typical output of such studies is a list of identified and quantified peptides. The biological and clinical interest is, however, usually focused on quantitative conclusions at the protein level. Furthermore, many investigations ask complex biological questions by studying multiple interrelated experimental conditions. Therefore, there is a need in the field for generic statistical models to quantify protein levels even in complex study designs. Results We propose a general statistical modeling approach for protein quantification in arbitrary complex experimental designs, such as time course studies, or those involving multiple experimental factors. The approach summarizes the quantitative experimental information from all the features and all the conditions that pertain to a protein. It enables both protein significance analysis between conditions, and protein quantification in individual samples or conditions. We implement the approach in an open-source R-based software package MSstats suitable for researchers with a limited statistics and programming background. Conclusions We demonstrate, using as examples two experimental investigations with complex designs, that a simultaneous statistical modeling of all the relevant features and conditions yields a higher sensitivity of protein significance analysis and a higher accuracy of protein quantification as compared to commonly employed alternatives. The software is available at http://www.stat.purdue.edu/~ovitek/Software.html.ISSN:1471-210

Molybdenum trioxide nanoparticles with intrinsic sulfite oxidase activity

Sulfite oxidase is a mitochondria-located molybdenum-containing enzyme catalyzing the oxidation of sulfite to sulfate in the amino acid and lipid metabolism. Therefore, it plays a major role in detoxification processes, where defects in the enzyme cause a severe infant disease leading to early death with no efficient or cost-effective therapy in sight. Here we report that molybdenum trioxide (MoO3) nanoparticles display an intrinsic biomimetic sulfite oxidase activity under physiological conditions, and, functionalized with a customized bifunctional ligand containing dopamine as anchor group and triphenylphosphonium ion as targeting agent, they selectively target the mitochondria while being highly dispersible in aqueous solutions. Chemically induced sulfite oxidase knockdown cells treated with MoO3 nanoparticles recovered their sulfite oxidase activity in vitro, which makes MoO3 nanoparticles a potential therapeutic for sulfite oxidase deficiency and opens new avenues for cost-effective therapies for gene-induced deficiencies

Molybdenum Trioxide Nanoparticles with Intrinsic Sulfite Oxidase Activity

Sulfite oxidase is a mitochondria-located molybdenum-containing enzyme catalyzing the oxidation of sulfite to sulfate in the amino acid and lipid metabolism. Therefore, it plays a major role in detoxification processes, where defects in the enzyme cause a severe infant disease leading to early death with no efficient or cost-effective therapy in sight. Here we report that molybdenum trioxide (MoO₃) nanoparticles display an intrinsic biomimetic sulfite oxidase activity under physiological conditions, and, functionalized with a customized bifunctional ligand containing dopamine as anchor group and triphenylphosphonium ion as targeting agent, they selectively target the mitochondria while being highly dispersible in aqueous solutions. Chemically induced sulfite oxidase knockdown cells treated with MoO₃ nanoparticles recovered their sulfite oxidase activity <i>in vitro</i>, which makes MoO₃ nanoparticles a potential therapeutic for sulfite oxidase deficiency and opens new avenues for cost-effective therapies for gene-induced deficiencies