ROBUST CROSS-PLATFORM DISEASE PREDICTION USING GENE EXPRESSION MICROARRAYS

Microarray technology has been used to predict patient prognosis and response to treatment, which is starting to have an impact on disease intervention and control, and is a significant measure for public health. However, the process has been hindered by a lack of adequate clinical validation. Since both microarray analyses and clinical trials are time and effort intensive, it is crucial to use accumulated inter-study data to validate information from individual studies. For over a decade, microarray data have been accumulated from different technologies. However, using data from one platform to build a model that robustly predicts the clinical characteristics of a new data from another platform remains a challenge. Current cross-platform gene prediction methods use only genes common to both training and test datasets. There are two main drawbacks to that approach: model reconstruction and loss of information. As a result, the prediction accuracy of those methods is unstable. In this dissertation, a module-based prediction strategy was developed to overcome the aforementioned drawbacks. By the current method, groups of genes sharing similar expression patterns rather than individual genes were used as the basic elements of the model predictor. Such an approach borrows information from genes¡¯ similarity when genes are absent in test data. By overcoming the problems of missing genes and noise across platforms, this method yielded robust predictions independent of information from the test data. The performance of this method was evaluated using publicly available microarray data. K-means clustering was used to group genes sharing similar expression profiles into gene modules and small modules were merged into their nearest neighbors. A univariate or multivariate feature selection procedures was applied and a representative gene from each selected module was identified. A prediction model was then constructed by the representative genes from selected gene modules. As a result, the prediction model is portable to any test study as long as partial genes in each module exist in the test study. The newly developed method showed advantages over the traditional methods in terms of prediction robustness to gene noise and gene mismatch issues in inter-study prediction

Adverse effects of adenovirus-mediated gene transfer of human transforming growth factor beta 1 into rabbit knees

To examine the effect of transforming growth factor (TGF)-β1 on the regulation of cartilage synthesis and other articular pathologies, we used adenovirus-mediated intra-articular gene transfer of TGF-β1 to both naïve and arthritic rabbit knee joints. Increasing doses of adenoviral vector expressing TGF-β1 were injected into normal and antigen-induced arthritis rabbit knee joints through the patellar tendon, with the same doses of an adenoviral vector expressing luciferase injected into the contralateral knees as the control. Intra-articular injection of adenoviral vector expressing TGF-β1 into the rabbit knee resulted in dose-dependent TGF-β1 expression in the synovial fluid. Intra-articular TGF-β1 expression in both naïve and arthritic rabbit knee joints resulted in significant pathological changes in the rabbit knee as well as in adjacent muscle tissue. The observed changes induced by elevated TGF-β1 included inhibition of white blood cell infiltration, stimulation of glycosaminoglycan release and nitric oxide production, and induction of fibrogenesis and muscle edema. In addition, induction of chondrogenesis within the synovial lining was observed. These results suggest that even though TGF-β1 may have anti-inflammatory properties, it is unable to stimulate repair of damaged cartilage, even stimulating cartilage degradation. Gene transfer of TGF-β1 to the synovium is thus not suitable for treating intra-articular pathologies

Increased matrix synthesis following adenoviral transfer of a transforming growth factor beta1 gene into articular chondrocytes

Monolayer cultures of lapine articular chondrocytes were transduced with first-generation adenoviral vectors carrying lacZ or transforming growth factor β1 genes under the transcriptional control of the human cytomegalovirus early promoter. High concentrations of transforming growth factor β1 were produced by chondrocytes following transfer of the transforming growth factor β1 gene but not the lacZ gene. Transduced chondrocytes responded to the elevated endogenous production of transforming growth factor β1 by increasing their synthesis of proteoglycan, collagen, and noncollagenous proteins in a dose-dependent fashion. The increases in collagen synthesis were not accompanied by alterations in the collagen phenotype; type-II collagen remained the predominant collagen. Transforming growth factor β1 could not, however, rescue the collagen phenotype of cells that had undergone phenotypic modulation as a result of serial passaging. These data demonstrate that chondrocytes can be genetically manipulated to produce and respond to the potentially therapeutic cytokine transforming growth factor β1. This technology has a number of experimental and therapeutic applications, including those related to the study and treatment of arthritis and cartilage repair

Distinct genes related to drug response identified in ER positive and ER negative breast cancer cell lines

Breast cancer patients have different responses to chemotherapeutic treatments. Genes associated with drug response can provide insight to understand the mechanisms of drug resistance, identify promising therapeutic opportunities, and facilitate personalized treatment. Estrogen receptor (ER) positive and ER negative breast cancer have distinct clinical behavior and molecular properties. However, to date, few studies have rigorously assessed drug response genes in them. In this study, our goal was to systematically identify genes associated with multidrug response in ER positive and ER negative breast cancer cell lines. We tested 27 human breast cell lines for response to seven chemotherapeutic agents (cyclophosphamide, docetaxel, doxorubicin, epirubicin, fluorouracil, gemcitabine, and paclitaxel). We integrated publicly available gene expression profiles of these cell lines with their in vitro drug response patterns, then applied meta-analysis to identify genes related to multidrug response in ER positive and ER negative cells separately. One hundred eighty-eight genes were identified as related to multidrug response in ER positive and 32 genes in ER negative breast cell lines. Of these, only three genes (DBI, TOP2A, and PMVK) were common to both cell types. TOP2A was positively associated with drug response, and DBI was negatively associated with drug response. Interestingly, PMVK was positively associated with drug response in ER positive cells and negatively in ER negative cells. Functional analysis showed that while cell cycle affects drug response in both ER positive and negative cells, most biological processes that are involved in drug response are distinct. A number of signaling pathways that are uniquely enriched in ER positive cells have complex cross talk with ER signaling, while in ER negative cells, enriched pathways are related to metabolic functions. Taken together, our analysis indicates that distinct mechanisms are involved in multidrug response in ER positive and ER negative breast cells. © 2012 Shen et al

Hormonal intervention for the treatment of veterans with COVID-19 requiring hospitalization (HITCH): a multicenter, phase 2 randomized controlled trial of best supportive care vs best supportive care plus degarelix: study protocol for a randomized controlled trial

Background Therapeutic targeting of host-cell factors required for SARS-CoV-2 entry is an alternative strategy to ameliorate COVID-19 severity. SARS-CoV-2 entry into lung epithelium requires the TMPRSS2 cell surface protease. Pre-clinical and correlative data in humans suggest that anti-androgenic therapies can reduce the expression of TMPRSS2 on lung epithelium. Accordingly, we hypothesize that therapeutic targeting of androgen receptor signaling via degarelix, a luteinizing hormone-releasing hormone (LHRH) antagonist, will suppress COVID-19 infection and ameliorate symptom severity. Methods This is a randomized phase 2, placebo-controlled, double-blind clinical trial in 198 patients to compare efficacy of degarelix plus best supportive care versus placebo plus best supportive care on improving the clinical outcomes of male Veterans who have been hospitalized due to COVID-19. Enrolled patients must have documented infection with SARS-CoV-2 based on a positive reverse transcriptase polymerase chain reaction result performed on a nasopharyngeal swab and have a severity of illness of level 3–5 (hospitalized but not requiring invasive mechanical ventilation). Patients stratified by age, history of hypertension, and severity are centrally randomized 2:1 (degarelix: placebo). The composite primary endpoint is mortality, ongoing need for hospitalization, or requirement for mechanical ventilation at 15 after randomization. Important secondary endpoints include time to clinical improvement, inpatient mortality, length of hospitalization, duration of mechanical ventilation, time to achieve a normal temperature, and the maximum severity of COVID-19 illness. Exploratory analyses aim to assess the association of cytokines, viral load, and various comorbidities with outcome. In addition, TMPRSS2 expression in target tissue and development of anti-viral antibodies will also be investigated. Discussion In this trial, we repurpose the FDA approved LHRH antagonist degarelix, commonly used for prostate cancer, to suppress TMPRSS2, a host cell surface protease required for SARS-CoV-2 cell entry. The objective is to determine if temporary androgen suppression with a single dose of degarelix improves the clinical outcomes of patients hospitalized due to COVID-19. Trial registration ClinicalTrials.gov NCT04397718. Registered on May 21, 202

Ind. Eng. Chem. Res.

A short-range Sutherland potential is mapped with the two-Yukawa potential and incorporated into the first-order mean spherical approximation (FMSA) theory to deal with the short-range dispersion interactions of ion-ion, ion-solvent, and solvent-solvent. An equation of state (EOS) based on primitive MSA and FMSA is constructed to describe the single- and multiple-salt solutions. With the universal and transferable ionic parameters derived from mean ionic activity coefficients and solution densities of single-salt solutions for five cations (Li+, Na+, K+, Ca2+, Mg2+) and five anions (Cl-, Br-, I-, NO3-, SO42- ), the proposed EOS predicts the correct osmotic coefficients as well as water activities for 19 monovalent and bivalent two-salt solutions. Without any additional mixing parameter, the predicted osmotic coefficients for aqueous two-salt solutions are in good agreement with experimental data.A short-range Sutherland potential is mapped with the two-Yukawa potential and incorporated into the first-order mean spherical approximation (FMSA) theory to deal with the short-range dispersion interactions of ion-ion, ion-solvent, and solvent-solvent. An equation of state (EOS) based on primitive MSA and FMSA is constructed to describe the single- and multiple-salt solutions. With the universal and transferable ionic parameters derived from mean ionic activity coefficients and solution densities of single-salt solutions for five cations (Li+, Na+, K+, Ca2+, Mg2+) and five anions (Cl-, Br-, I-, NO3-, SO42- ), the proposed EOS predicts the correct osmotic coefficients as well as water activities for 19 monovalent and bivalent two-salt solutions. Without any additional mixing parameter, the predicted osmotic coefficients for aqueous two-salt solutions are in good agreement with experimental data