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Gene networks lend insight into cancer virus

Computer modelling of gene interactions has shed new light on how human genes respond to a virus that causes cancer.

The Epstein-Barr Virus causes cell changes linked to cancer.
The Epstein-Barr Virus causes cell changes linked to cancer. Photo credit: CDC/Paul M Feorino

A study of genes has lent insight into the biological pathways behind a virus that causes 200,000 cases of cancer each year around the world.

Researchers used two population data sets involving hundreds of people to examine gene networks, in which some genes affect the function of others.

By using a computer modelling approach to study how genes interact, the team from the Roslin Institute and the University of Edinburgh’s Centre for Cognitive Ageing and Cognitive Epidemiology were able to pinpoint networks involved in key cell changes caused by the Epstein-Barr Virus (EBV), which is linked to cancer.

Researchers have known for some time how genetic differences between people’s genomes can alter the expression – or activity levels – of nearby genes. Many of these changes are linked to increased risk of diseases.

In this latest study, Roslin researchers examined how the expression levels of other, distant, genes can modify the impact of these genetic changes.

The extent of modification of a gene depends on the expression level of a second gene elsewhere in the genome.

These sets of genes were linked to key biological pathways that the virus co-opts to drive tumour growth, providing new insights into how the virus drives cancers.

Population studies

Data for the study was taken from the Lothian Birth Cohort, a set of almost 900 individuals born in and around Edinburgh in 1936, and from almost 350 individuals who took part in the 1000 Genomes Consortium formed by the GEUVADIS collaboration.

Their findings highlight the potential of uncovering novel findings from existing data.

Their study was published in Nature Communications.

Our insights into a virus that causes thousands of cases of cancer is a good example of data science – making use of publicly available data to find useful discoveries and maximising the potential of information that is already out there.

Dr James PrendergastRoslin Institute

** The Roslin Institute receives strategic investment funding from the Biotechnology and Biological Sciences Research Council and it is part of the University of Edinburgh’s Royal (Dick) School of Veterinary Studies. **

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