Abstract
Cystic fibrosis (CF), caused by mutations to CFTR, leads to severe and progressive lung disease. The most common mutant, ΔF508-CFTR, undergoes proteasomal degradation, extinguishing its anion channel function. Numerous in vitro interventions have been identified to partially rescue ΔF508-CFTR function yet remain poorly understood. Improved understanding of both the altered state of CF cells and the mechanisms of existing rescue strategies could reveal novel therapeutic strategies. Toward this aim, we measured transcriptional profiles of established temperature, genetic, and chemical interventions that rescue ΔF508-CFTR and also re-analyzed public datasets characterizing transcription in human CF vs. non-CF samples from airway and whole blood. Meta-analysis yielded a core disease signature and two core rescue signatures. To interpret these through the lens of prior knowledge, we compiled a “CFTR Gene Set Library” from literature. The core disease signature revealed remarkably strong connections to genes with established effects on CFTR trafficking and function and suggested novel roles of EGR1 and SGK1 in the disease state. Our data also revealed an unexpected mechanistic link between several genetic rescue interventions and the unfolded protein response. Finally, we found that C18, an analog of the CFTR corrector compound Lumacaftor, induces almost no transcriptional perturbation despite its rescue activity.
Highlights
Italicized gene names refer to DNA or RNA, whereas non‐italicized names refer to proteins BP Biological process CF Cystic fibrosis CFBE CF bronchial epithelia CFG CFTR functional genomics Chip-X Enrichment Analysis (ChEA) Chip-X enrichment analysis differentially expressed genes (DEGs) Differentially expressed genes Enrichment scores (ES) Enrichment score FC Fold change FDA Food and Drug Administration FEV1 Forced expiratory volume at one second GO Gene ontology Gene Set Enrichment Analysis (GSEA) Gene set enrichment analysis Hallmark pathways54 (HLMRK) Hallmark gene set library heat shock proteins (HSPs) Heat shock protein Kinase Enrichment Analysis (KEA) Kinase enrichment analysis Kyoto Encyclopedia of Genes and Genomes (KEGG) Kyoto encyclopedia of genes and genomes
Italicized gene names refer to DNA or RNA, whereas non‐italicized names refer to proteins BP Biological process CF Cystic fibrosis CFBE CF bronchial epithelia CFG CFTR functional genomics ChEA Chip-X enrichment analysis DEG Differentially expressed genes ES Enrichment score FC Fold change FDA Food and Drug Administration FEV1 Forced expiratory volume at one second GO Gene ontology GSEA Gene set enrichment analysis HLMRK Hallmark gene set library HSP Heat shock protein KEA Kinase enrichment analysis KEGG Kyoto encyclopedia of genes and genomes
It is caused by mutations to the cystic fibrosis transmembrane conductance regulator (CFTR) gene, which encodes an anion channel expressed in epithelia and other cell types
Summary
Italicized gene names refer to DNA or RNA, whereas non‐italicized names refer to proteins BP Biological process CF Cystic fibrosis CFBE CF bronchial epithelia CFG CFTR functional genomics ChEA Chip-X enrichment analysis DEG Differentially expressed genes ES Enrichment score FC Fold change FDA Food and Drug Administration FEV1 Forced expiratory volume at one second GO Gene ontology GSEA Gene set enrichment analysis HLMRK Hallmark gene set library HSP Heat shock protein KEA Kinase enrichment analysis KEGG Kyoto encyclopedia of genes and genomes. There are many established rescue interventions believed to act through such indirect means (e.g., low-temperature treatment[1]; overexpression of miR-1384; or miR-165; or knockdown of AHA16, SIN3A4, SYVN17, or NEDD87). These interventions have limited efficacy or are poorly understood. We studied four categories of experiments: one that compared CF vs non-CF expression in relevant human tissues, and three types of in vitro rescue strategies: (1) low-temperature rescue; (2) RNAi-based rescue (namely, siRNA-mediated knockdown of SYVN1, NEDD8, or SIN3A, or overexpression of miR-138); and (3) chemical rescue via C18. Using this and other resources, we developed an original bioinformatic workflow to analyze and interpret these signatures
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