Ongoing Projects

Towards virtual cell state maps: multiscale image-omics to uncover the spatial heterogeneity in ILD.

Spatial heterogeneity in disease patterns is a key hallmark of interstitial lung diseases (ILDs). High-dimensional image analysis (image-omics) of routinely performed computed tomography (CT) scans (radiomics) offers quantitative insights into organ-scale pathophysiology, creating digital disease fingerprints. In this project, we aim to integrate spatially resolved imaging profiles with matched molecular data to decipher the cellular programs underlying the spatial heterogeneity in ILDs and how they are reflected in imaging phenotypes. Our ultimate aim is to develop radiomic signatures for non-invasive assessment of cell state profiles and pathway activations on the tissue level.

Decoding the molecular drivers of lung fibrosis development and progression

Homeostatic maintenance, regeneration and repair of the lung requires precise spatiotemporal controlling and orchestrating the activities of functionally linked multilineage circuits of regenerative cell states. It is currently unknown how the dysregulation of regenerative cell states is linked to pulmonary fibrosis. 

In this project, we employ single-cell multiomics and spatial profiling in fibrosing ILD patients and experimental disease models to uncover the cell-intrinsic (epigenomic) and -extrinsic (niche/microenvironmental) factors driving dysregulation of regenerative cell states and fibrosis progression, particularly focusing on immunoregulatory mechanisms.

Developing multiomic prediction models for fibrosis progression    

In this project, we combine image-omics (radiomics) and molecular profiling to decipher the cellular and tissue phenotypes that determine ILD outcomes and to develop non-invasive multiomic imaging/fluid-based biomarkers capable of predicting progressive fibrosis development and course of progression across various ILD subtypes. This will pave the way for patient specific early and targeted interventions and, thus, precision medicine.