RNA sequencing data from neutrophils of patients with cystic fibrosis reveals potential for developing biomarkers for pulmonary exacerbations

Jiang, Kaiyu; Poppenberg, Kerry E.; Wong, Lai-Ping; Chen, Yanmin; Borowitz, Drucy; Goetz, Danielle; Sheehan, Daniel W.; Frederick, Carla; Tutino, Vincent M.; Jarvis, James N.

doi:10.1016/j.jcf.2018.05.014

Cited by 19 publications

(12 citation statements)

References 68 publications

(84 reference statements)

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“…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.…”

Section: Transcriptome Profiling In Cystic Fibrosismentioning

confidence: 99%

“…Further, a recent study utilizing transcriptome profiling by RNA-Sequencing of blood neutrophils identified 83 gene isoforms that demonstrated significant (False discovery rate-adjusted p < 0.05) changes in expression levels following treatment for exacerbations in CF [26]. Although functional enrichment was not performed, the results are indicative that alternative splicing events may be relevant to CF disease progression.…”

Section: Transcriptome Profiling In Cystic Fibrosismentioning

confidence: 99%

“…This approach has already led to the discovery and characterization of several dysregulated disease-specific isoforms in recent times [71,73,74]. Although the literature is still sparse with regard to genome-wide implications of aberrant alternative splicing in CF progression, a recent study utilizing transcriptome profiling by RNA-Sequencing identified 83 transcript isoforms in blood neutrophils that distinguished CF following treatment for exacerbation [26]. Thus, identifying the CF-specific isoforms of key genes may be useful for discovering novel diagnostic and therapeutic targets.…”

Section: Emerging Targets For Transcriptome Profilingmentioning

confidence: 99%

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

Zhang

McColley

Levy

2019

Genes

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In cystic fibrosis (CF), mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene disrupt the capacity of the encoded protein to function as a channel to transport chloride ions and water across cell membranes. The consequences are deleterious, system-wide, and immensely variable, even among patients with the same CFTR genotype. This underscores the need to characterize the mechanisms contributing to CF pathophysiology. Gene replacement and gene editing therapies have been pursued intensively and are expected to provide a one-time treatment for CF. However, gene replacement therapy is limited by the lack of efficient vectors to deliver functional copies of CFTR to cells without immunological complications, while gene editing technologies such as CRISPR/Cas9 are still in their infancy, mainly useful in somatic cells and limited by off-target insertions. Small molecule treatments targeted at potentiating or correcting CFTR have shown clinical benefits, but they are limited to a few CFTR mutations and insufficient to overcome challenges related to clinical heterogeneity. Transcriptome profiling approaches have emerged as robust tools capable of characterizing phenotypic variability and revealing novel molecular targets with therapeutic potential for CF. We summarize current insights gained through transcriptome profiling approaches in CF studies and recent advances in molecular therapeutics.

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Section: Transcriptome Profiling In Cystic Fibrosismentioning

confidence: 99%

Section: Transcriptome Profiling In Cystic Fibrosismentioning

confidence: 99%

Section: Emerging Targets For Transcriptome Profilingmentioning

confidence: 99%

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

Zhang

McColley

Levy

2019

Genes

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“…With a fold change ≥ 2 and FDR < 0.05 as the screening criteria [28], a total of 172 differentially expressed genes were screened in the four-week-old males (Figure 1a). Among them, there were 68 upregulated genes and 104 downregulated genes in the fast-growth group (M4F) when compared with the slow-growth group (M4S) (Supplementary Files S1, S2).…”

Section: Resultsmentioning

confidence: 99%

Transcriptome Analysis of Differentially Expressed Genes Related to the Growth and Development of the Jinghai Yellow Chicken

Chen

Shen

et al. 2019

Genes

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The growth traits are important traits in chickens. Compared to white feather broiler breeds, Chinese local broiler breeds have a slow growth rate. The main genes affecting the growth traits of local chickens in China are still unclear and need to be further explored. This experiment used fast-growth and slow-growth groups of the Jinghai Yellow chicken as the research objects. Three males and three females with similar body weights were selected from the two groups at four weeks old and eight weeks old, respectively, with a total of 24 individuals selected. After slaughter, their chest muscles were taken for transcriptome sequencing. In the differentially expressed genes screening, all of the genes obtained were screened by fold change ≥ 2 and false discovery rate (FDR) < 0.05. For four-week-old chickens, a total of 172 differentially expressed genes were screened in males, where there were 68 upregulated genes and 104 downregulated genes in the fast-growth group when compared with the slow-growth group. A total of 31 differentially expressed genes were screened in females, where there were 11 upregulated genes and 20 downregulated genes in the fast-growth group when compared with the slow-growth group. For eight-week-old chickens, a total of 37 differentially expressed genes were screened in males. The fast-growth group had 28 upregulated genes and 9 downregulated genes when compared with the slow-growth group. A total of 44 differentially expressed genes were screened in females. The fast-growth group had 13 upregulated genes and 31 downregulated genes when compared with the slow-growth group. Through gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, many genes were found to be related to cell proliferation and differentiation, muscle growth, and cell division such as SNCG, MCL1, ARNTL, PLPPR4, VAMP1, etc. Real-time PCR results were consistent with the RNA-Seq data and validated the findings. The results of this study will help to understand the regulation mechanism of the growth and development of Jinghai Yellow chicken and provide a theoretical basis for improving the growth rate of Chinese local chicken breeds.

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“…Likewise, ML models integrating biomarker and clinical data are being trained to predict clinical outcomes and drug response. These technologies are already driving innovations in CF research, ranging from the identification of a novel cell type (the ionocyte) that likely contributes to the pathogenesis of lung disease in CF (12, 13) to the discovery of biomarkers of CF pulmonary exacerbations based on RNA-seq of neutrophils (14).…”

mentioning

confidence: 99%

RNA Sequencing: A Potentiator of Discovery-based Research

Alexander

Reyfman

2019

Am J Respir Cell Mol Biol

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RNA sequencing data from neutrophils of patients with cystic fibrosis reveals potential for developing biomarkers for pulmonary exacerbations

Abstract: Our findings demonstrate the potential of machine learning approaches for classifying disease states and thus developing sensitive biomarkers that can be used to monitor pulmonary disease activity in CF.

Cited by 19 publications

References 68 publications

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

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

Transcriptome Analysis of Differentially Expressed Genes Related to the Growth and Development of the Jinghai Yellow Chicken

RNA Sequencing: A Potentiator of Discovery-based Research

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