[Spotlight seminar] Investigating the regulatory impact of rare non-coding somatic mutations in cancer
May 20, 2025 @ 15:15 – 16:15 CEST
Spotlight seminar series proudly presents Lude Franke, Professor of functional genomics, University Medical Centre Groningen, The Netherlands
Abstract
Both germline and somatic variation play an important role in cancer. In the past years a lot of progress has been made in the identification of germline variants that confer cancer risk, and a large number of somatic driver mutations have now been found. Here, we set out to study the role of non-coding somatic mutations in cancer and studied whole-genome sequence data of 25,000 cancer patients where we employed sequence-based models to identify hundreds of non-coding regions that are enriched for activating or repressing mutations. We subsequently studied how these non-coding somatic mutations cause disease and observed these mutations are related to known somatic driver genes ad germline risk variants through when employing gene regulatory networks. I will discuss how such gene regulatory networks can be reconstructed using trans-eQTL data in 43,000 invidiuals.
Biography
Lude Franke develops and applies computational methods to understand the downstream molecular consequences of genetic risk factors. We studied the effect of somatic copy number alterations on gene expression levels (Fehrmann et al, Nature Genetics 2015) and studied the effect of genetic single-nucleotide polymorphism on methylation (Bonder et al, Nature Genetics 2017) and gene expression (i.e. expression quantitative trait loci), both in blood using bulk data (Zhernakova et al, Nature Genetics 2017 and Vosa et al, Nature Genetics 2021) and single-cell data (Van der Wijst, Nature Genetics 2018). Recently, we did this in brain (De Klein, Nature Genetics 2023). We lead the eQTLGen and single-cell eQTL consortia (see eQTLGen.org), where we use federated meta-analyses approaches to generate comprehensive maps how genetic variation is exerting cell-type and context-specific effects on gene expression, with the aim to help identify and validate drug targets.
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