More than 150,000 women die of ovarian cancer every year. Typically, patients with high-grade serous ovarian cancer (HGS-OvCa), which is the most common and lethal subtype of ovarian cancer, respond well to the platinum-based first-line chemotherapy, but the disease becomes increasingly resistant to the treatments, leading to progressive disease and death. In the HERCULES project our goal was to develop methods to firstly gain understanding of mechanisms of drug resistance in HGS-OvCa and secondly identify effective interventions to overcome resistance and kill chemotherapy resistant cancer cells.
HGS-OvCa tumours contain millions of cancer cells that have acquired a numerous and diverse set of changes in their genome, such as mutations and copy number variations. Some genetic aberrations may give a cancer cell the ability to resist chemotherapy. Thus, while a drug kills most cancer cells that do not have resistance to the drug, the remaining small fraction of resistant cells has a growth advantage. Thus, the tumour mass contains more and more resistant cells causing reduced effect of the following chemotherapy cycles. In HERCULES, we used state-of-the-art measurement technologies to obtain information from tumour samples collected at surgery before and after chemotherapy to reveal genetic aberrations that drive chemotherapy resistance. The core of the project was to develop methods to analyse data from tumour samples to find biomarkers that characterise chemotherapy resistant cells.
HERCULES successfully produced new knowledge on chemoresistance mechanisms in HGS-OvCa. Some clinical benefits from the research materialised already during the project period. The core of the project was to develop novel computational methods that enable translating large amounts of molecular level data obtained from tumour samples into knowledge and medical benefits. All the methods developed in HERCULES are open-source and freely available with thorough documentation. Also, the data obtained in HERCULES are available for research purposes. However, as patient data are considered sensitive under EU legislation, the sequencing data are accessible only via the European Phenome Genome (EGA) archive, where a Data Access Committee reviews that the research plan and data security measures comply with the patient consent and EU legislation. As the project was based on a longitudinal patient cohort, the research results from larger numbers of patients as well as clinical benefits will take place later, when more patients have a longer follow-up time.
