MCCA (Multiparametric cell-by-cell analyses)

Results from multiple analyses from a single case can be viewed in HistoTracker. A slide from a case can be stained and restained several times, allowing different types of analyses, from single cell analyses to whole slide analyses.

Background 

This project aims to establish a framework to quantify and study features such as protein expression from multiple proteins, methylation status, chromatin organisation and DNA content in the same cells. The tissue in which the cells are located is also characterised and segmented according to tissue type. The idea of studying different properties in the same sample simultaneously is not new, but the approach involves a range of technical difficulties including immunohistochemical staining and restaining of the same section multiple times and alignment of the resulting stained cells. The novelty of the project lies in the ability to overcome the technical challenges and to utilise the results. This project brings together the different prognostic markers that we have developed over the years and improves our insight into how they work and how they can be utilized even better. 

HistoTracker

A tool called HistoTracker has been developed to register and present the aligned cell-by-cell information for a visual interpretation both in the routine HE-section and in the section and staining used to obtain the result (e.g. immunohistochemically stained part). HistoTracker can, for example, be used to visualise the simultaneous loss of PTEN and the presence of aneuploidy in cells in the invasive front of tumours from prostate cancer patients with Gleason score 8. Similar patterns can be identified automatically and can be linked to a patient outcome to provide candidates for new prognostic markers. 

Focus on prostate cancer

Prostate cancer is known to harbour significant intra-tumour heterogeneity and will be used to develop the framework. We aim to characterise the tumours in a way that captures the heterogeneity appropriately based on feature levels of cells in a spatial context. Prostate cancer is also the cancer type in which we have developed the first prototype of most of our prognostic markers. The extension to a multi-parameter framework is natural choice for further development.