Tracking Internal Cancer Cell Signalling

1) Brief description of the context of the research including potential impact

This project aims to develop a novel methodology for better understanding and treating cancer by improving the modelling mechanisms of c-Met, a receptor tyrosine kinase belonging to the MET family. c-Met is expressed on the surface of numerous cells, and it is understood that the binding to its ligand Hepatocyte growth factor (HGF) initiates intracellular signalling that mediates embryogenesis and wound healing in normal cells. However, in the case of cancer cells, this binding promotes tumour development and progression, and has been found to play a major role in metastasis, i.e., cancer spreading from a primary tumour to other parts of the body. This activation is believed to affect many properties of the cell such as cell adhesion, migration, and invasion.

Thus, c-Met and its signalling pathways are clinically important targets for the development of novel therapeutic drugs and the quantification of their efficacy. It was previously believed that c-Met acted from the cell boundaries, however recent studies have shown that c-Met can enter the cells by endocytosis for cell signalling and that its movement determines the type and intensity of signalling that it will trigger. Currently, cell behaviour and the effects on tumour cell migration and invasion remain poorly understood. Hence there is a need to analyse the localisation of this receptor and its signalling pathways to better understand the mechanisms in promoting tumour growth and development. Moreover, given the role that c-Met plays in cancer development, it has recently emerged as an important target for cancer therapy with drugs being developed. This project will make use of human breast cell lines and tissue samples along with confocal microscopy and image processing to model c-Met's intracellular movement. This will be achieved by obtaining both the distribution and quantification of endosomal co-localisation of C-Met and signalling at different time points, beginning with cell lines (2D), and subsequently extending to 3D and tissue samples. Furthermore, the project will aim to study the influence of therapeutic drugs on the intra-cellular signalling.

2) Aims and Objectives

- Quantification of the distribution of time-dependent endosomal co-localization of c-Met and signalling from immunofluorescence images of human breast cell lines and tissue samples, confocal microscopy for 3D tissue imaging, and advanced image processing.
- Improvement of data accuracy and reliability by extending the image analysis from 2D (cell lines) to 3D and tissue samples and employing machine learning for automatic classification.
- Development of an algorithm that can automatically analyse the signalling pathways of c-Met within the cells, requiring accurate detection of the cell nuclei and boundaries from the confocal microscopy images. Utilising both 2D and 3D imaging to calculate time-dependent relative c-Met propagation from the cell membrane towards the nucleus.

3) Novelty of Research Methodology

The binding of c-Met (receptor) to HGF (ligand) has been shown to play a major role in tumour development and metastasis. However, the mechanisms in which this occurs remains poorly understood. This project aims to develop a novel methodology that models the mechanisms of c-Met in promoting cancer spread, improving current understanding to quantify the efficacy of novel drugs for cancer treatment.

4) Alignment to EPSRC's strategies and research areas

"Transforming early prediction and diagnosis" - this project aims to develop a novel methodology that can predict and model patients' response to cancer treatment.

"Discovering and accelerating the development of new interventions" - better understanding of c-Met's signalling pathways and further modelling will help to predict the response to therapeutic drugs.

5) Any companies or collaborators involved

Prof Stephanie Kermorgant