Dataset Information

BAL Cell Gene Expression Is Indicative of Outcome and Airway Basal Cell Involvement in Idiopathic Pulmonary Fibrosis.

ABSTRACT:

Rationale

Idiopathic pulmonary fibrosis (IPF) is a fatal disease with a variable and unpredictable course.

Objectives

To determine whether BAL cell gene expression is predictive of survival in IPF.

Methods

This retrospective study analyzed the BAL transcriptome of three independent IPF cohorts: Freiburg (Germany), Siena (Italy), and Leuven (Belgium) including 212 patients. BAL cells from 20 healthy volunteers, 26 patients with sarcoidosis stage III and IV, and 29 patients with chronic obstructive pulmonary disease were used as control subjects. Survival analysis was performed by Cox models and component-wise boosting. Presence of airway basal cells was tested by immunohistochemistry and flow cytometry.

Measurements and main results

A total of 1,582 genes were predictive of mortality in the IPF derivation cohort in univariate analyses adjusted for age and sex at false discovery rate less than 0.05. A nine-gene signature, derived from the discovery cohort (Freiburg), performed well in both replication cohorts, Siena (P < 0.0032) and Leuven (P = 0.0033). nCounter expression analysis confirmed the array results (P < 0.0001). The genes associated with mortality in BAL cells were significantly enriched for genes expressed in airway basal cells. Further analyses by gene expression, flow cytometry, and immunohistochemistry showed an increase in airway basal cells in BAL and tissues of IPF compared with control subjects, but not in chronic obstructive pulmonary disease or sarcoidosis.

Conclusions

Our results identify and validate a BAL signature that predicts mortality in IPF and improves the accuracy of outcome prediction based on clinical parameters. The BAL signature associated with mortality unmasks a potential role for airway basal cells in IPF.

SUBMITTER: Prasse A

PROVIDER: S-EPMC6396865 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundGiven the plethora of pathophysiologic mechanisms described in idiopathic pulmonary fibrosis (IPF), we hypothesize that the mechanisms driving fibrosis in IPF may be different from one patient to another.Research questionDo IPF endotypes exist and are they associated with outcome?Study design and methodsUsing a publicly available gene expression dataset retrieved from BAL samples of patients with IPF and control participants (GSE70867), we clustered IPF samples based on a dimension reduction algorithm specifically designed for -omics data, called DDR Tree. After clustering, gene set enrichment analysis was performed for functional annotation, associations with clinical variables and prognosis were investigated, and differences in transcriptional regulation were determined using motif enrichment analysis. The findings were validated in three independent publicly available gene expression datasets retrieved from IPF blood samples.ResultsOne hundred seventy-six IPF samples from three centers were clustered in six IPF clusters, with distinct functional enrichment. Although clinical characteristics did not differ between the clusters, one cluster conferred worse sex-age-physiology score-corrected survival, whereas another showed a numeric trend toward worse survival (P = .08). The first was enriched for increased epithelial and innate and adaptive immunity signatures, whereas the other showed important telomere and mitochondrial dysfunction, loss of proteostasis, and increased myofibroblast signatures. The existence of these two endotypes, including the impact on survival of the immune endotype, was validated in three independent validation cohorts. Finally, we identified transcription factors regulating the expression of endotype-specific survival-associated genes.InterpretationGene expression-based endotyping in IPF is feasible and can inform clinical evolution. As endotype-specific pathways and survival-associated transcription factors are identified, endotyping may open up the possibility of endotype-tailored therapy.