Many tumors including esophagogastric junction adenocarcinomas (EAC) suffer from characteristics responsible for poor prognosis: resistance to therapy, early metastasis and recurrence. All these features may arise from a small fraction of the tumor cells, and so the identification of these cells is of paramount importance.
A patient’s tumor can be highly heterogeneous, containing many different cell types as well as tumor cells. The challenge is to identify the tumor cells that lead, for instance, to therapy resistance from within this high variability.
In order to understand how this variability contributes to treatment resistance it is necessary to characterize the variability within each patient’s tumor before treatment, during treatment, and after treatment.
In the ARREST project we sought to identify tumor subpopulations associated with response to treatment by analyzing tumor material before, during, and after treatment. In this manner it was possible to study the evolution of tumor variability in the context of therapy response.
The variability in the molecular content of the tumor cells was visualized by mass spectrometry imaging (MSI), an unlabeled molecular imaging technique that can be used to identify tumor subpopulations.
The project identified heterogeneity EAC tumors, in the tumor’s proteins and metabolites, and demonstrated how combining MSI datasets from multiple molecular classes led to improved prognostic performance.
It was also demonstrated how specific tumor regions identified by MSI could be isolated and comprehensively characterized by allied omics technologies.