Epigenetic Profiling of Menstrual Blood for Precision Cancer Detection and Prevention: EpiPrecise

Programme(s): HORIZON.1.1 - European Research Council (ERC)

Topic(s): ERC-2023-POC - ERC PROOF OF CONCEPT GRANTS

Call for proposal: ERC-2023-POC

Funding Scheme: HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

Grant agreement ID: 101158345

Objective:

Cancer has overtaken cardiovascular disease as the number one cause of mortality in high income countries, cancer incidence is increasing across the globe. Morbidity and mortality from women’s cancers, particularly breast, ovarian, and endometrial cancers, follow or exceed these general trends in cancer incidence.
Tackling this growing cancer burden requires a multifactorial approach including understanding the fundamental drivers of cancer development; improving methods for detecting earlier those forms of cancer with the worst prognosis; predicting a person’s risk of developing cancer; and identifying appropriate targets for preventing cancer. Indeed, one of the biggest obstacles in identifying tailored cancer prevention strategies is a lack of surrogate readout markers reflecting and integrating an individual’s response to the cancer-initiating and cancer-promoting factors that they are exposed to during their lifetime. Our research delivers novel epigenetic tests relating to each of these key areas with an emphasis on women’s cancers and those who are at an increase risk for cancer due to their underlying genetics, such as women with BRCA1 or BRCA2 mutations and women with Lynch Syndrome.
Central to the discovery and development of the epigenetic tests is a cellular deconvolution algorithm that is used to calculate the proportions of cell types within complex, mixed samples such as cervical swabs. In order to broaden the clinical utility of the tests and explore new applications, refinement and expansion of this cellular deconvolution algorithm is now required. The expansion will include cell types in menstrual blood, which is an important and understudied clinical sample type. The EpiPrecise project will deliver this refined and expanded algorithm and apply it to a test case in an area of high unmet clinical need. The refined algorithm will then be applied across the research portfolio and shared.