Cancer is often driven by specific combinations of an estimated two to nine gene mutations, known as multi-hit combinations. Identifying these multi-hit combinations of gene mutations that drive cancer is critical for understanding carcinogenesis and designing targeted therapies.
- Speaker
- Date
- Friday 3 Jul 2026, 12:00 - 13:00
- Type
- Seminar
- Room
- ET-14
- Building
- E Building
We formalise this challenge as the Multi-Hit Cancer Driver Set Cover Problem (MHCDSCP), optimising the selection of gene combinations to maximise tumor coverage while strictly minimising normal sample misclassification. While existing approaches rely on exhaustive enumeration and massive parallelisation, we introduce fast heuristics based on constraint programming and mixed integer programming formulations.
Evaluated on real-world cancer genomics data, our framework matches state-of-the-art supercomputing methods using a single commodity CPU in under a minute. We also propose a price-and-branch heuristic which, by solving the root node to optimality, provides the first provably optimal solutions for over half of the benchmark instances, thereby verifying the near-optimality of our fast heuristics.
These findings demonstrate that on real-world problem instances, the MHCDSCP is far less computationally demanding than previously believed, providing an accessible baseline that enables the exploration of previously intractable multi-hit modeling assumptions.
About the speaker
Rick Willemsen is a postdoctoral researcher at Singapore University of Technology and Design. His research focuses on applying mathematical programming techniques to large-scale problems. He obtained his PhD at the Econometric Institute at Erasmus University Rotterdam.
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Lunch will be provided (vegetarian option included).
For more information please contact the Secretariat Econometrics at eb-secr@ese.eur.nl
