Rationale: Current understanding of the molecular regulation of lung development is limited and derives mostly from animal studies. Objectives: To define global patterns of gene expression during human lung development. Methods: Genome-wide expression profiling was used to measure the developing lung transcriptome in RNA samples derived from 38 normal human lung tissues at 53 to 154 days post conception. Principal component analysis was used to characterize global expression variation and to identify genes and bioontologic attributes contributing to these variations. Individual gene expression patterns were verified by quantitative reverse transcriptase–polymerase chain reaction analysis. Measurements and Main Results: Gene expression analysis identified attributes not previously associated with lung development, such as chemokine-immunologic processes. Lung characteristics attributes (e.g., surfactant function) were observed at an earlier-than-anticipated age. We defined a 3,223 gene developing lung characteristic subtranscriptome capable of describing a majority of the process. In gene expression space, the samples formed a time-contiguous trajectory with transition points correlating with histological stages and suggesting the existence of novel molecular substages. Induction of surfactant gene expression characterized a pseudoglandular “molecular phase” transition. Individual gene expression patterns were independently validated. We predicted the age of independent human lung transcriptome profiles with a median absolute error of 5 days, supporting the validity of the data and modeling approach. Conclusions: This study extends our knowledge of key gene expression patterns and bioontologic attributes underlying early human lung developmental processes. The data also suggest the existence of molecular phases of lung development.

Chronic obstructive pulmonary disease (COPD) is an inflammatory lung disorder with complex pathological features and largely unknown etiology. The identification of biomarkers for this disease could aid the development of methods to facilitate earlier diagnosis, the classification of disease subtypes, and provide a means to define therapeutic response. To identify gene expression biomarkers, we completed expression profiling of RNA derived from the lung tissue of 56 subjects with varying degrees of airflow obstruction using the Affymetrix U133 Plus 2.0 array. We applied multiple, independent analytical methods to define biomarkers for either discrete or quantitative disease phenotypes. Analysis of differential expression between cases (n = 15) and controls (n = 18) identified a set of 65 discrete biomarkers. Correlation of gene expression with quantitative measures of airflow obstruction (FEV1%predicted or FEV1/FVC) identified a set of 220 biomarkers. Biomarker genes were enriched in functions related to DNA binding and regulation of transcription. We used this group of biomarkers to predict disease in an unrelated data set, generated from patients with severe emphysema, with 97% accuracy. Our data contribute to the understanding of gene expression changes occurring in the lung tissue of patients with obstructive lung disease and provide additional insight into potential mechanisms involved in the disease process. Furthermore, we present the first gene expression biomarker for COPD validated in an independent data set.

Peroxisome proliferator‐activated receptor (PPAR)‐γ is a member of the nuclear hormone receptor superfamily that can promote cellular differentiation and organ development. PPARγ expression has been reported in a number of pulmonary cell types, including inflammatory, mesenchymal, and epithelial cells. We find that PPARγ is prominently expressed in the airway epithelium in the mouse lung. In an effort to define the physiological role of PPARγ within the lung, we have ablated PPARγ using a novel line of mice capable of specifically targeting the airway epithelium. Airway epithelial cell PPARγ‐targeted mice display enlarged airspaces resulting from insufficient postnatal lung maturation. The increase in airspace size is accompanied by alterations in lung physiology, including increased lung volumes and decreased tissue resistance. Genome‐wide expression profiling reveals a reduction in structural extracellular matrix (ECM) gene expression in conditionally targeted mice, suggesting a disruption in epithelial‐mesenchymal interactions necessary for the establishment of normal lung structure. Expression profiling of airway epithelial cells isolated from conditionally targeted mice indicates PPARγ regulates genes encoding known PPARγ targets, additional lipid metabolism enzymes, and markers of cellular differentiation. These data reveal airway epithelial cell PPARγ is necessary for normal lung structure and function.—Simon, D. M., Arikan, M. C., Srisuma, S., Bhattacharya, S., Tsai, L. W., Ingenito, E. P., Gonzalez, F., Shapiro, S. D., and Mariani, T. J. Epithelial cell PPARγ contributes to normal lung maturation. FASEB J. 20, E710–E720 (2006)

Rationale: Bronchopulmonary dysplasia (BPD) is a major complication of premature birth. Risk factors for BPD are complex and include prenatal infection and O2 toxicity. BPD pathology is equally complex and characterized by inflammation and dysmorphic airspaces and vasculature. Due to the limited availability of clinical samples, an understanding of the molecular pathogenesis of this disease and its causal mechanisms and associated biomarkers is limited. Objectives: Apply genome-wide expression profiling to define pathways affected in BPD lungs. Methods: Lung tissue was obtained at autopsy from 11 BPD cases and 17 age-matched control subjects without BPD. RNA isolated from these tissue samples was interrogated using microarrays. Standard gene selection and pathway analysis methods were applied to the data set. Abnormal expression patterns were validated by quantitative reverse transcriptase–polymerase chain reaction and immunohistochemistry. Measurements and Main Results: We identified 159 genes differentially expressed in BPD tissues. Pathway analysis indicated previously appreciated (e.g., DNA damage regulation of cell cycle) as well as novel (e.g., B-cell development) biological functions were affected. Three of the five most highly induced genes were mast cell (MC)-specific markers. We confirmed an increased accumulation of connective tissue MCTC (chymase expressing) mast cells in BPD tissues. Increased expression of MCTC markers was also demonstrated in an animal model of BPD-like pathology. Conclusions: We present a unique genome-wide expression data set from human BPD lung tissue. Our data provide information on gene expression patterns associated with BPD and facilitated the discovery that MCTC accumulation is a prominent feature of this disease. These observations have significant clinical and mechanistic implications.