In the HERCULES EU project, we are studying samples from high-grade serous ovarian cancer tumours. The samples are analysed using mass cytometry, DNA, RNA and ChIP (chromatin immunoprecipitation) sequencing; and computational tools to find optimal biomarkers that would allow the identification of different cell populations from tissue samples. The use of single-cell sequencing for DNA and RNA allows for an unprecedented level of information to be gained from the tumour cell populations. Fresh patient samples and cell lines established from them will be used for examining the cancer cells’ response to anti-cancer drugs.
On this basis, our group will establish computational models and develop computational tools to make predictions predict the most effective drug combinations to kill the cell populations. The key results will be validated using existing high-grade serous ovarian cancer data together with fresh samples, old biobank samples and in vivo models. Based on the results, a prototype of a commercial test for predicting the best drug combinations to individual patients will be developed.