Multi-omic analysis of cervical cancer and related endpoints
Description: Cervical cancer is common among women (more than 311 000 deaths worldwide every year). However, underlying genetic factors and molecular changes are not entirely understood, hindering development of novel treatments and genetic risk predictors. The aim of the project is to increase the knowledge on the biology of cervical cancer to develop a personalised approach and augment the screening and vaccination strategies for early detection and prevention of the disease. We will do this by combining clinical phenotypes and novel granular subphenotypes (such as cellular phenotypes derived from histology images with computer vision) with cutting edge computational approaches. We will then translate this to genetic risk prediction tools. These analyses give new knowledge on the genetic background, while also highlighting novel ways for more personalised patient counselling to decrease the risk of cervical cancer and associated comorbidities.
Funder: Eesti Teadusagentuur
Amount: €369,100
Funding type: grant
Funder scheme: Personal research funding: Start-up grant (PSG)
Start date: 2022-01-01
End date: 2026-12-31
Investigator: Triin Laisk
Institution: University of Tartu, Faculty of Science and Technology, Institute of Genomics
Funded outputs count: 15
Funder award ID: PSG776
OpenAlex ID: G4402704620