Gene expression profiles of acute exacerbations of idiopathic pulmonary fibrosis.

RATIONALE: The molecular mechanisms underlying acute exacerbations of idiopathic pulmonary fibrosis (IPF) are poorly understood. We studied the global gene expression signature of acute exacerbations of IPF. OBJECTIVES: To understand the gene expression patterns of acute exacerbations of IPF. METHODS: RNA was extracted from 23 stable IPF lungs, 8 IPF lungs with acute exacerbation (IPF-AEx), and 15 control lungs and used for hybridization on Agilent gene expression microarrays. Functional analysis of genes was performed with Spotfire and Genomica. Gene validations for MMP1, MMP7, AGER, DEFA1-3, COL1A2, and CCNA2 were performed by real-time quantitative reverse transcription-polymerase chain reaction. Immunohistochemistry and in situ terminal deoxynucleotidyltransferase dUTP nick end-labeling assays were performed on the same tissues used for the microarray. ELISA for alpha-defensins was performed on plasma from control subjects, patients with stable IPF, and patients with IPF-AEx. MEASUREMENTS AND MAIN RESULTS: Gene expression patterns in IPF-AEx and IPF samples were similar for the genes that distinguish IPF from control lungs. Five hundred and seventy-nine genes were differentially expressed (false discovery rate < 5%) between stable IPF and IPF-AEx. Functional analysis of these genes did not indicate any evidence of an infectious or overwhelming inflammatory etiology. CCNA2 and alpha-defensins were among the most up-regulated genes. CCNA2 and alpha-defensin protein levels were also higher and localized to the epithelium of IPF-AEx, where widespread apoptosis was also detected. alpha-Defensin protein levels were increased in the peripheral blood of patients with IPF-AEx. CONCLUSIONS: Our results indicate that IPF-AEx is characterized by enhanced epithelial injury and proliferation, as reflected by increases in CCNA2 and alpha-defensins and apoptosis of epithelium. The concomitant increase in alpha-defensins in the peripheral blood and lungs may suggest their use as biomarkers for this disorder.

A multidisciplinary approach to honest broker services for tissue banks and clinical data: a pragmatic and practical model.

BACKGROUND: Honest broker services are essential for tissue- and data-based research. The honest broker provides a firewall between clinical and research activities. Clinical information is stripped of Health Insurance Portability and Accountability Act-denoted personal health identifiers. Research material may have linkage codes, precluding the identification of patients to researchers. The honest broker provides data derived from clinical and research sources. These data are for research use only, and there are rules in place that prohibit reidentification. Very rarely, the institutional review board (IRB) may allow recontact and develop a recontact plan with the honest broker. Certain databases are structured to serve a clinical and research function and incorporate 'real-time' updating of information. This complex process needs resolution of a variety of issues regarding the precise role of the HB and their interaction with data. There also is an obvious need for software solutions to make the task of deidentification easier. METHODS: The University of Pittsburgh has implemented a novel, IRB-approved mechanism to address honest broker functions to meet the specimen and data needs of researchers. The Tissue Bank stores biologic specimens. The Cancer Registry culls data and annotating information as part of state- and federal-mandated functions and collects data on the clinical progression, treatment, and outcomes of cancer patients. The Cancer Registry also has additional IRB approval to collect data elements only for research purposes. The Clinical Outcomes Group is involved in patient safety and health services research. Radiation Oncology and Medical Oncology provide critical treatment related information. Pathology and Oncology Informatics have designed software tools for querying availability of specimens, extracting data, and deidentifying specimens and annotating data for clinical and translational research. These entities partnered and submitted a joint IRB proposal to create an institutional honest broker facility. The employees of this conglomerate have honest broker agreements with the University of Pittsburgh and the Medical Center. This provides a large group of honest brokers, ensuring availability for projects without any conflict of interest. RESULTS: The honest broker system has been an IRB-approved institutional entity at the University of Pittsburgh since 2003. The honest broker system currently includes 33 certified honest brokers encompassing the multiple partners of this system. The honest broker system has handled >1600 requests over the past 4 years with a 25% increase in volume each year. CONCLUSIONS: The current results indicate that the collaborative honest broker model described herein is robust and provides a highly functional solution to the specimen and data needs for critical clinical and translational research activities.

Gene expression profiles of prostate cancer reveal involvement of multiple molecular pathways in the metastatic process.

BACKGROUND: Prostate cancer is characterized by heterogeneity in the clinical course that often does not correlate with morphologic features of the tumor. Metastasis reflects the most adverse outcome of prostate cancer, and to date there are no reliable morphologic features or serum biomarkers that can reliably predict which patients are at higher risk of developing metastatic disease. Understanding the differences in the biology of metastatic and organ confined primary tumors is essential for developing new prognostic markers and therapeutic targets. METHODS: Using Affymetrix oligonucleotide arrays, we analyzed gene expression profiles of 24 androgen-ablation resistant metastatic samples obtained from 4 patients and a previously published dataset of 64 primary prostate tumor samples. Differential gene expression was analyzed after removing potentially uninformative stromal genes, addressing the differences in cellular content between primary and metastatic tumors. RESULTS: The metastatic samples are highly heterogenous in expression; however, differential expression analysis shows that 415 genes are upregulated and 364 genes are downregulated at least 2 fold in every patient with metastasis. The expression profile of metastatic samples reveals changes in expression of a unique set of genes representing both the androgen ablation related pathways and other metastasis related gene networks such as cell adhesion, bone remodelling and cell cycle. The differentially expressed genes include metabolic enzymes, transcription factors such as Forkhead Box M1 (FoxM1) and cell adhesion molecules such as Osteopontin (SPP1). CONCLUSION: We hypothesize that these genes have a role in the biology of metastatic disease and that they represent potential therapeutic targets for prostate cancer.