Identification of molecular signatures of cystic fibrosis disease status with plasma-based functional genomics

Abstract

Although cystic fibrosis (CF) is attributed to dysfunction of a single gene, the relationships between the abnormal gene product and the development of inflammation and progression of lung disease are not fully understood, which limits our ability to predict an individual patient’s clinical course and treatment response. To better understand CF progression, we characterized the molecular signatures of CF disease status with plasma-based functional genomics. Peripheral blood mononuclear cells (PBMCs) from healthy donors were cultured with plasma samples from CF patients ( n = 103) and unrelated, healthy controls ( n = 31). Gene expression levels were measured with an Affymetrix microarray (GeneChip Human Genome U133 Plus 2.0). Peripheral blood samples from a subset of the CF patients ( n = 40) were immunophenotyped by flow cytometry, and the data were compared with historical data for age-matched healthy controls ( n = 351). Plasma samples from another subset of CF patients ( n = 56) and healthy controls ( n = 16) were analyzed by multiplex enzyme-linked immunosorbent assay (ELISA) for numerous cytokines and chemokines. Principal component analysis and hierarchical clustering of induced transcriptional data revealed disease-specific plasma-induced PBMC profiles. Among 1,094 differentially expressed probe sets, 51 genes were associated with pancreatic sufficient status, and 224 genes were associated with infection with Pseudomonas aeruginosa. The flow cytometry and ELISA data confirmed that various immune modulators are relevant contributors to the CF molecular signature. This study provides strong evidence for distinct molecular signatures among CF patients. An understanding of these molecular signatures may lead to unique molecular markers that will enable more personalized prognoses, individualized treatment plans, and rapid monitoring of treatment response.

Transcriptome Profiling and Molecular Therapeutic Advances in Cystic Fibrosis: Recent Insights

“…Although few studies have evaluated blood cells via transcriptomics in CF (Table 1), we have shown using microarray profiling that transcriptional signatures of peripheral blood mononuclear cells (PBMCs) exposed to plasma from patients with CF or from healthy controls (HC) can distinguish CF disease state from non-CF and characterizes its phenotypes. Like others (Table 1), we identified several genes that encode molecules within important biological pathways, especially those of the immune system are dysregulated in CF [17,27]. Others have also shown that transcriptional responses of PBMCs can enhance our understanding of immune dysfunction in CF.…”

“…These include growth hormone receptor ( GHR ), interferon-γ receptor 1 ( IFNGR1 ), interferon-γ receptor 2 ( IFNGR2 ), and insulin receptor ( INSR ) (Table 3). Although these four targets were initially identified with other screening methods to be dysregulated in CF [49], IFNGR1 , and IFNGR2 were among the top genes we identified via transcriptome profiling of CF plasma-induced signatures [27]. Thus, the findings are an indication that advanced high-throughput transcriptome profiling methods hold promise as robust tools for identification of novel molecular targets with therapeutic potential in CF.…”

“…As systemic markers have the potential to reflect the inflammation profile of the CF lung, blood cells have also emerged as targets for transcriptome profiling to delineate host immune factors associated with CF pathophysiology [17,19,26]. Transcriptional profiling has been direct, by assessing gene expression differences in CF blood cells [21,26] or indirect, by assessing transcriptional responses of blood cells exposed to CF-associated external stimuli [17,27], as previously described [37]. Although few studies have evaluated blood cells via transcriptomics in CF (Table 1), we have shown using microarray profiling that transcriptional signatures of peripheral blood mononuclear cells (PBMCs) exposed to plasma from patients with CF or from healthy controls (HC) can distinguish CF disease state from non-CF and characterizes its phenotypes.…”

“…As another example, transcriptional profiling of CF PBMCs exposed to multiple bacterial ligands revealed that dysfunctional autophagy was implicated for heightened inflammatory responses and AMPK-Akt signaling was identified as a potential anti-inflammatory target [19]. We recently identified activated EIF2 signaling pathway as the most significant pathway associated with CF via microarray profiling using a plasma-induced PBMCs model [27]. Follow-up studies are needed to understand the mechanisms involved.…”

“…Human PBMCs stimulated with plasma or serum from patients followed by transcriptome profiling have provided new insights into diseases [81,82]. Recently, we used this model to reveal dysregulated expression of a diverse range of genes encoding molecules crucial for important immune pathways in CF [17,27]. Although this model system is limited by the cellular heterogeneity of PBMCs, it provides a useful resource to quantitatively profile immune cells via transcriptomic approaches.…”