Charting the molecular landscape of tumors

What are the characteristics and vulnerabilities of cancer cells? 

Recurrent copy number aberration of a single gene is a classical sign of its involvement in tumor development. In many cases tumors become dependent on such driver genes and targeting these genes has proven to be a fruitful strategy in combatting cancer. Similarly, recurrent patterns of copy number aberration involving multiple genes also provide valuable clues regarding ways in which genes collaborate during oncogenesis. For example, genes that are simultaneously inactivated can point to redundant pathways that both need to be inactivated during tumor development. As with single genes, frequent recurrence of such patterns is strong evidence that these patterns were selected for during tumor development and most likely represent dependencies that can be exploited in treatment strategies. Reliably identifying recurrently aberrated (groups of) genes is therefore an essential step in charting the cancer landscape. As a first step, reliable estimates of copy number profiles are required. To this end we have developed an approach to capitalize on the growing amount of (capture-based) DNA sequencing data to accurately estimate copy number profiles of tumors. For the subsequent steps required to chart the landscape, we have developed algorithms to identify recurrently aberrated single genes and co-occurrently aberrated gene pairs from copy number data. 


  • Recurrent aberrations (e.g. mutations, copy number alterations)
  • Interactions between them (e.g. co-occurrence, mutual exclusivity)
  • Gene prioritization


  • PropSeg
  • CIS
  • Co-occur
  • Mutascape
  • Gene prioritizer