Ciliated (FOXJ1 + ) Cells Display Reduced Ferritin Light Chain in the Airways of Idiopathic Pulmonary Fibrosis Patients.
Sofia C WijkPavan PrabhalaAnna LöfdahlAnnika NybomStefan LangHans BrunnströmLeif BjermerGunilla Westergren-ThorssonMattias MagnussonPublished in: Cells (2022)
Cell-based therapies hold great promise in re-establishing organ function for many diseases, including untreatable lung diseases such as idiopathic pulmonary fibrosis (IPF). However, many hurdles still remain, in part due to our lack of knowledge about the disease-driving mechanisms that may affect the cellular niche and thereby possibly hinder the function of any transplanted cells by imposing the disease phenotype onto the newly generated progeny. Recent findings have demonstrated increased ciliation of lung cells from IPF patients, but how this affects ciliated cell function and the airway milieu is not well-known. Here, we performed single-cell RNA sequencing on primary ciliated (FOXJ1 + ) cells isolated from IPF patients and from healthy control donors. The sequencing identified multiple biological processes, such as cilium morphogenesis and cell signaling, that were significantly changed between IPF and healthy ciliated cells. Ferritin light chain (FTL) was downregulated in IPF, which suggests that iron metabolism may be affected in the IPF ciliated cells. The RNA expression was confirmed at the protein level with histological localization in lung tissue, prompting future functional assays to reveal the potential role of FTL. Taken together, our data demonstrate the importance of careful analyses in pure cell populations to better understand the IPF disease mechanism.
Keyphrases
- idiopathic pulmonary fibrosis
- single cell
- induced apoptosis
- end stage renal disease
- cell cycle arrest
- ejection fraction
- interstitial lung disease
- newly diagnosed
- chronic kidney disease
- prognostic factors
- poor prognosis
- stem cells
- cell therapy
- healthcare
- bone marrow
- gene expression
- systemic sclerosis
- cell proliferation
- small molecule
- electronic health record
- machine learning
- binding protein
- big data