Inhalation exposure to Asbestos remains the number 1 cause of pleural Mesothelioma, a lethal cancer of the lining of the chest cavity, diagnosed in approximately 31,000 people annually worldwide
The biology of Mesothelioma is poorly understood for several reasons
- Onset of symptoms may take 30-40 years to develop following acute exposure
- First symptoms (shortness of breath, fluid in the chest cavity) are not disease-specific
- Lack of a clearly defined precursor to malignancy
- Difficulty in distinguishing potential malignancy from non-cancerous pleural inflammation
Modelling Mesothelioma in Genetically Engineered mice (GEMs)
Well-designed state-of-the-art mouse models can yield vital insight into human cancer biology, especially into early and pre-symptomatic stages of cancer development.
The Murphy lab has developed several genetically engineered mouse models (GEMMs) that combine injected exposure to Asbestos with controlled introduction of the same mutations that are found in human Mesothelioma.
Of vital importance, the GEMMs accurately recapitulate the anatomical, cellular and molecular features of human Mesothelioma.
Ongoing Research
- PREDICT-Meso (funded by Cancer Research UK)
- IAMMED-Meso (funded by Cancer Research UK)
- DEBiT-Meso (funded by Asthma + Lung UK)
- REMIT (funded by Cancer Research UK)
PREDICT-Meso
This cross-disciplinary international consortium, led by Prof. Kevin G. Blyth (University of Glasgow), aims to develop tissue, model, & imaging resources to facilitate research, broadly aimed at early detection, accurate diagnosis and better therapeutic interventions for Mesothelioma.
At the core of PREDICT-Meso lies longitudinal collection and DNA/RNA analysis of tissue samples from patients at risk of developing Mesothelioma, with patient-matched follow-up tissue collection from those patients that progress to Mesothelioma development and from those with stable benign pleural disease.
IAMMED-Meso: Integrated Analysis in Mouse and Man for Early Detection of Mesothelioma
This research programme aims to generate diagnostic biomarkers that distinguish benign or non-cancerous pleural disease from neoplastic growth at high risk of progression to Mesothelioma.
The work is focussed on the molecular and cellular features of fluid samples taken from the chest cavity (pleural effusion) of patients at risk of developing Mesothelioma, with cross -species comparison of similar fluid collected from our unique GEM models, enabling filtration of highly conserved recurring features.
The programme also includes artificial-intelligence (AI) assisted morphological analysis of patient and GEMM-derived tissue samples.
DEBiT-Meso: Differential gene Expression in Bystander Transcriptomes for early diagnosis of mesothelioma
Integrated within IAMMED-Meso, this project aims to exploit the immune cell content of pleural effusion to aid with early diagnosis of Mesothelioma.
Overcoming the spatial limitations of biopsy sampling, immune cells survey the entire chest cavity and change their gene expression in response to signals from their environment.
The premise is that malignant mesothelioma cells will emit molecular signals that are distinct from those emitted by non-malignant tissue, resulting in identifiable changes in immune cell gene expression.
REMIT: Reconstructing the Evolution of Mesothelioma for Improved Treatment
Co-led with Prof. Marion MacFarlane, MRC Toxicology Unit, Cambridge, this research programme makes full use of our GEM models to investigate how recurring mutations in mesothelial cells combine over time with asbestos-driven inflammation to drive Mesothelioma development.
The programme aims to define key biological features of early cancer that may present new opportunities for personalised medicine approaches to Mesothelioma treatment.
Reference
- Cancer.net; Cancerresearchuk.org