Applying human lung tissue models to develop a personalised treatment for critically ill

Acute respiratory distress syndrome (ARDS) is a major cause of mortality in the critically ill patients with no effective pharmacological treatment.

Recently, two distinct endotypes of ARDS were identified and validated in four large randomized controlled trials: a hyper-inflammatory and a hypo-inflammatory endotype.

These endotypes have strikingly different clinical characteristics, biomarker profiles, clinical outcomes, and treatment responses. While these data are highly promising, the biology of these endotypes is not understood.

Mesenchymal Stem Cells (MSCs) hold significant therapeutic promise for ARDS and are rapidly progressing to clinical trials across the world. However, concern for the use of stem cells, specifically the risk of tumor formation, remains unresolved.

Accumulating evidence suggests that MSCs exert their therapeutic benefit through the release of extracellular vesicles (EVs).

MSC EVs are being actively developed as a cell free therapy for ARDS, but for the effective clinical translation it is important to establish EV therapeutic potential for both biological endotypes of patients.

In this project, I am going to use cutting edge technology and employ the most physiological human lung tissue models to date to study the biology of ARDS endotypes and to test therapeutic potential of MSC EVs.

The main objectives are: i) To reveal how endotype–specific environments alter human lung tissue and how these changes are affected by EV treatment at a single cell level, using single cell RNA-Seq transcriptomic profiling of precision-cut human lung tissue slices, ii) to study how endotype-specific environments (with or without EV treatment) alter functional properties of the alveolar epithelial-endothelial barrier using lung-on-a-chip microfluidic model, iii) to study how endotype-specific environments (with or without EVs) alter metabolism of the primary human pulmonary cells involved in ARDS pathophysiology using Seahorse Metabolic Analyser.