Keratin-14 Expression in Pneumocytes as a Marker of Lung Regeneration/Repair during Diffuse Alveolar Damage

Ficial, Miriam; Antonaglia, Caterina; Chilosi, Marco; Santagiuliana, Mario; Tahseen, Al-Omoush; Confalonieri, Davide; Zandonà, Lorenzo; Bussani, Rossana; Confalonieri, Marco

doi:10.1164/rccm.201312-2134le

Cited by 14 publications

(14 citation statements)

References 19 publications

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“…While KRT14 + cells have been reported to coexpress AT2 cell markers in DAD [ 18 ], we could not detect any costaining of KRT14 + with differentiation markers. The function of the KRT5 + KRT14 + population therefore remains unclear.…”

Section: Discussioncontrasting

confidence: 86%

“…Details about definitive basal cell subpopulations, however, remain to be elucidated, in particular in the human lung. In this context, basal cell subsets expressing distinct keratin (KRT) isoforms have been described [ 17 ] and recent evidence suggests alterations in KRT abundance and expression in lung disease with features of diffuse alveolar damage [ 18 , 19 ]. Increased KRT5 and KRT14 expression has also been reported in the alveolar regions in idiopathic pulmonary fibrosis (IPF) [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

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Detection and quantification of epithelial progenitor cell populations in human healthy and IPF lungs

et al. 2016

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BackgroundIn the human lung, epithelial progenitor cells in the airways give rise to the differentiated pseudostratified airway epithelium. In mice, emerging evidence confers a progenitor function to cytokeratin 5 (KRT5+) or cytokeratin 14 (KRT14+)-positive basal cells of the airway epithelium. Little is known, however, about the distribution of progenitor subpopulations in the human lung, particularly about aberrant epithelial differentiation in lung disease, such as idiopathic pulmonary fibrosis (IPF).MethodsHere, we used multi-color immunofluorescence analysis to detect and quantify the distribution of airway epithelial progenitor subpopulations in human lungs obtained from healthy donors or IPF patients.ResultsIn lungs from both, healthy donors and IPF patients, we detected KRT5+KRT14-, KRT5-KRT14+ and KRT5+KRT14+ populations in the proximal airways. KRT14+ cells, however, were absent in the distal airways of healthy lungs. In IPF, we detected a dramatic increase in the amount of KRT5+ cells and the emergence of a frequent KRT5+KRT14+ epithelial population, in particular in distal airways and alveolar regions. While the KRT14- progenitor population exhibited signs of proper epithelial differentiation, as evidenced by co-staining with pro-SPC, aquaporin 5, CC10, or MUC5B, the KRT14+ cell population did not co-stain with bronchial/alveolar differentiation markers in IPF.ConclusionsWe provide, for the first time, a quantitative profile of the distribution of epithelial progenitor populations in human lungs. We show compelling evidence for dysregulation and aberrant differentiation of these populations in IPF.

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Section: Discussioncontrasting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Detection and quantification of epithelial progenitor cell populations in human healthy and IPF lungs

et al. 2016

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“…2G–2J), which are markers of AT2 and basal stem cells. Consistently, KRT14 expression, considered as a marker of AT2 regenerative activation after injury [], was upregulated in PSs. The combination of AT2 and mesenchymal cells has been described as an ex vivo lung niche model [].…”

Section: Discussionmentioning

confidence: 81%

Human Lung Spheroids as In Vitro Niches of Lung Progenitor Cells with Distinctive Paracrine and Plasticity Properties

Chimenti

Pagano

Angelini

et al. 2016

Stem Cells Translational Medicine

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Basic and translational research on lung biology has discovered multiple progenitor cell types, specialized or facultative, responsible for turnover, renewal, and repair. Isolation of populations of resident lung progenitor cells (LPCs) has been described by multiple protocols, and some have been successfully applied to healthy human lung tissue. We aimed at understanding how different cell culture conditions may affect, in vitro, the phenotype of LPCs to create an ideal niche‐like microenvironment. The influence of different substrates (i.e., fibronectin, gelatin, laminin) and the impact of a three‐dimensional/two‐dimensional (3D/2D) culture switch on the biology of LPCs isolated as lung spheroids (LSs) from normal adult human lung biopsy specimens were investigated. We applied a spheroid culture system as the selective/inductive step for progenitor cell culture, as described in many biological systems. The data showed a niche‐like proepithelial microenvironment inside the LS, highly sensitive to the 3D culture system and significantly affecting the phenotype of adult LPCs more than culture substrate. LSs favor epithelial phenotypes and LPC maintenance and contain cells more responsive to specific commitment stimuli than 2D monolayer cultures, while secreting a distinctive set of paracrine factors. We have shown for the first time, to our knowledge, how culture as 3D LSs can affect LPC epithelial phenotype and produce strong paracrine signals with a distinctive secretomic profile compared with 2D monolayer conditions. These findings suggest novel approaches to maintain ex vivo LPCs for basic and translational studies. Stem Cells Translational Medicine 2017;6:767–777

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“…More specific, KRT5 is suggested to have the highest diagnostic value for distinguishing between these two cancer types. KRT5 is also reported to be associated to Lung Cancer according to [45][46][47][48][49].…”

Section: Enrichment Analysismentioning

confidence: 99%

Building an Ensemble Feature Selection Approach for Cancer Microarray Datasets Using Different Classifiers

Sayed¹,

Nassef²,

Badr³

et al. 2019

IJIES

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The challenge of processing the Microarray datasets with its high dimensionality opened multiple research directions. Different feature selection techniques have been employed to reduce the dimensionality of such Microarray datasets before being attempted by classification algorithms. This study presents an ensemble feature selection approach based on t-test and Genetic Algorithm with five different classification algorithms as its fitness function: Support Vector Machine, Random Forest, Nearest Centroid, K Nearest Neighbour, and Maximum Likelihood with 5fold cross validation. The proposed approach has been applied on two different datasets for Lung cancer; Microarray Gene Expression and DNA methylation datasets aiming to find the Lung cancer biomarker genes. The experimental results showed that the three genes (DLX5, KRT5, and SELENBP1) resulted from processing both datasets have higher classification accuracy (92.31%) compared to separately processing the Gene Expression and the DNA methylation datasets with accuracies 90.38% and 86.54% respectively. Moreover, the classification accuracy achieved using the three aforementioned genes could not be achieved by other research studies unless by using more genes.

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Keratin-14 Expression in Pneumocytes as a Marker of Lung Regeneration/Repair during Diffuse Alveolar Damage

Cited by 14 publications

References 19 publications

Detection and quantification of epithelial progenitor cell populations in human healthy and IPF lungs

Detection and quantification of epithelial progenitor cell populations in human healthy and IPF lungs

Human Lung Spheroids as In Vitro Niches of Lung Progenitor Cells with Distinctive Paracrine and Plasticity Properties

Building an Ensemble Feature Selection Approach for Cancer Microarray Datasets Using Different Classifiers

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