Thesis (D.P.H.)--University of Michigan, 1994.

Thesis (M.S.)--University of Michigan, 1990.

Thesis (D.P.H.)--University of Michigan, 1994.

Thesis (doctoral)--University of Copenhagen.

Thesis (doctoral)--Ludwig Maximilians-Universität zu München, 1979.

Thesis (doctoral)--Lund University, 1994. / Added t.p. with thesis statement inserted.

Thesis (M.S.)--University of Wisconsin--Madison, 1981. / Typescript. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 125-127).

Thesis (doctoral)--Lund University, 1994. / Added t.p. with thesis statement inserted.

The clock-controlled nuclear receptor REV-ERBα has emerged as a critical regulator of multiple pathways involved in metabolism, development and immunity. Recent evidence has highlighted a major role for the clock in epithelial cells regulating lung inflammation, mediated by control of neutrophil chemokine expression. In this thesis, I examined the role of REV-ERBα in pulmonary immunity, using in-vivo gene targeting and nebulised lipopolysaccharide (LPS), a model for gram-negative bacterial infection, ex-vivo cell biology approaches and in vitro cell models. Initial studies of Rev-Erbα knock-out mice revealed an increase in pulmonary neutrophilia and inflammation upon aerosolised LPS challenge. Moreover, by selectively deleting the REV-ERBα DNA binding domain (DBD) in the mouse bronchial epithelium, I observed exaggerated inflammatory responses to LPS and augmented CXCL5 secretion. Interestingly, a dual deletion of REV-ERBα DBD and REV-ERBβ in mouse bronchial epithelium had a more dramatic effect on neutrophil recruitment and chemokine secretion than deletion of just the REV-ERBα DBD; in both basal and bacterial challenged conditions. Ex-vivo analysis revealed bronchial epithelial cells and macrophages both responded to novel REV-ERBα synthetic ligand GSK1362 but displayed divergent inflammatory responses in presence of this compound. Finally, I observed a striking loss of REV-ERBα protein upon pro-inflammatory challenge. Further analysis revealed this degradation was dependent on the 26S proteasome and driven by sumoylation and ubiquitination of REV-ERBα. However, by using novel REV-ERB ligand GSK1362, these post-translational modifications were blocked and the protein protected from degradation. Collectively, my results propose a new model for a central role for REV-ERBα in conferring clock control to lung neutrophilic inflammation. I have also identified a feed-forward circuit activated by inflammatory stimuli, leading to suppression of the endogenous anti-inflammatory REV-ERBα protein. Finally, I have discovered a novel mechanism for small-molecule regulation of REV-ERBα, operating via suppression of endogenous protein ubiquitination process. These observations implicate REV-ERBα as a novel therapeutic target in human inflammatory disease.

The diagnostic evaluation of ever smokers with pulmonary nodules represents a growing clinical challenge due to the implementation of lung cancer screening. The high false-positive rate of screening frequently results in the use of unnecessary invasive procedures in patients who are ultimately diagnosed as benign, clearly highlighting the need for additional diagnostic approaches. We previously derived and validated a bronchial epithelial gene-expression biomarker to detect lung cancer in ever smokers. However, bronchoscopy is not always chosen as a diagnostic modality. Given that bronchial and nasal epithelial gene-expression are similarly altered by cigarette smoke exposure, we sought to determine if cancer-associated gene-expression might also be detectable in the more readily accessible nasal epithelium. Nasal epithelial brushings were prospectively collected from ever smokers undergoing diagnostic evaluation for lung cancer in the AEGIS-1 (n=375) and AEGIS-2 (n=130) clinical trials and gene-expression profiled using microarrays. The computational framework used to discover biomarkers in these data was formalized and implemented in an open-source R-package. We identified 535 genes in the nasal epithelium of AEGIS-1 patients whose expression was associated with lung cancer status. Using matched bronchial gene-expression data from a subset of these patients, we found significantly concordant cancer-associated gene-expression alterations between the two airway sites. A nasal lung cancer classifier derived in the AEGIS-1 cohort that combined clinical factors and nasal gene-expression had significantly higher AUC (0.81) and sensitivity (0.91) than the clinical-factor model alone in independent samples from the AEGIS-2 cohort. These results support that the airway epithelial field of lung cancer-associated injury extends to the nose and demonstrates the potential of using nasal gene-expression as a non-invasive biomarker for lung cancer detection. The framework for deriving this biomarker was generalized and implemented in an open-source R-package. The package provides a computational pipeline to compare biomarker development strategies using microarray data. The results from this pipeline can be used to highlight the optimal model development parameters for a given dataset leading to more robust and accurate models. This package provides the community with a novel and powerful tool to facilitate biomarker discovery in microarray data.