Alveolar Epithelial Denudation Is a Major Factor in the Pathogenesis of Pleuroparenchymal Fibroelastosis

Loss of cell junctional components and matrix alterations drive cell desquamation and fibrotic changes in Idiopathic Pulmonary Fibrosis

The distal bronchioles in Idiopathic Pulmonary Fibrosis (IPF) exhibit histopathological abnormalities such as bronchiolization, peribronchiolar fibrosis and honeycomb cysts that contribute to the overall architectural remodeling of lung tissue seen in the disease. Here we describe an additional histopathologic finding of epithelial desquamation in patients with IPF, wherein epithelial cells detach from the basement membrane of the distal bronchioles. To understand the mechanism driving this pathology, we performed spatial transcriptomics of the epithelial cells and spatial proteomics of the basement membrane of the distal bronchioles from IPF patients and patients with no prior history of lung disease. Our findings reveal a downregulation of cell junctional components, upregulation of epithelial-mesenchymal transition signatures and dysregulated basement membrane matrix in IPF distal bronchioles, facilitating epithelial desquamation. Further, functional assays identified regulation between Collagen IV in the matrix, and the junctional genes JUP and PLEC , that is crucial for maintaining distal bronchiolar homeostasis. In IPF, this balanced regulation between matrix and cell-junctions is disrupted, leading to loss of epithelial adhesion, peribronchiolar fibrosis and epithelial desquamation. Overall, our study suggests that in IPF the interplay between the loss of cell junctions and a dysregulated matrix results in desquamation of distal bronchiolar epithelium and lung remodeling, exacerbating the disease.

One Sentence Summary

Two-way regulation of cell junctional proteins and matrix proteins drives cellular desquamation and fibrosis in the distal bronchioles of patients with Idiopathic Pulmonary Fibrosis.

Machine-Learning-Based Classification Model to Address Diagnostic Challenges in Transbronchial Lung Biopsy

BACKGROUND

When obtaining specimens from pulmonary nodules in TBLB, distinguishing between benign samples and mis-sampling from a tumor presents a challenge. Our objective is to develop a machine-learning-based classifier for TBLB specimens.

METHODS

Three pathologists assessed six pathological findings, including interface bronchitis/bronchiolitis (IB/B), plasma cell infiltration (PLC), eosinophil infiltration (Eo), lymphoid aggregation (Ly), fibroelastosis (FE), and organizing pneumonia (OP), as potential histologic markers to distinguish between benign and malignant conditions. A total of 251 TBLB cases with defined benign and malignant outcomes based on clinical follow-up were collected and a gradient-boosted decision-tree-based machine learning model (XGBoost) was trained and tested on randomly split training and test sets.

RESULTS

Five pathological changes showed independent, mild-to-moderate associations (AUC ranging from 0.58 to 0.75) with benign conditions, with IB/B being the strongest predictor. On the other hand, FE emerged to be the sole indicator of malignant conditions with a mild association (AUC = 0.66). Our model was trained on 200 cases and tested on 51 cases, achieving an AUC of 0.78 for the binary classification of benign vs. malignant on the test set.

CONCLUSION

The machine-learning model developed has the potential to distinguish between benign and malignant conditions in TBLB samples excluding the presence or absence of tumor cells, thereby improving diagnostic accuracy and reducing the burden of repeated sampling procedures for patients.

Image-based spatial transcriptomics identifies molecular niche dysregulation associated with distal lung remodeling in pulmonary fibrosis

The human lung is structurally complex, with a diversity of specialized epithelial, stromal and immune cells playing specific functional roles in anatomically distinct locations, and large-scale changes in the structure and cellular makeup of this distal lung is a hallmark of pulmonary fibrosis (PF) and other progressive chronic lung diseases. Single-cell transcriptomic studies have revealed numerous disease-emergent/enriched cell types/states in PF lungs, but the spatial contexts wherein these cells contribute to disease pathogenesis has remained uncertain. Using sub-cellular resolution image-based spatial transcriptomics, we analyzed the gene expression of more than 1 million cells from 19 unique lungs. Through complementary cell-based and innovative cell-agnostic analyses, we characterized the localization of PF-emergent cell-types, established the cellular and molecular basis of classical PF histopathologic disease features, and identified a diversity of distinct molecularly-defined spatial niches in control and PF lungs. Using machine-learning and trajectory analysis methods to segment and rank airspaces on a gradient from normal to most severely remodeled, we identified a sequence of compositional and molecular changes that associate with progressive distal lung pathology, beginning with alveolar epithelial dysregulation and culminating with changes in macrophage polarization. Together, these results provide a unique, spatially-resolved characterization of the cellular and molecular programs of PF and control lungs, provide new insights into the heterogeneous pathobiology of PF, and establish analytical approaches which should be broadly applicable to other imaging-based spatial transcriptomic studies.

The Role of Epithelial Damage in the Pulmonary Immune Response

Pulmonary epithelial cells are widely considered to be the first line of defence in the lung and are responsible for coordinating the innate immune response to injury and subsequent repair. Consequently, epithelial cells communicate with multiple cell types including immune cells and fibroblasts to promote acute inflammation and normal wound healing in response to damage. However, aberrant epithelial cell death and damage are hallmarks of pulmonary disease, with necrotic cell death and cellular senescence contributing to disease pathogenesis in numerous respiratory diseases such as idiopathic pulmonary fibrosis (IPF), chronic obstructive pulmonary disease (COPD) and coronavirus disease (COVID)-19. In this review, we summarise the literature that demonstrates that epithelial damage plays a pivotal role in the dysregulation of the immune response leading to tissue destruction and abnormal remodelling in several chronic diseases. Specifically, we highlight the role of epithelial-derived damage-associated molecular patterns (DAMPs) and senescence in shaping the immune response and assess their contribution to inflammatory and fibrotic signalling pathways in the lung.