Illuminating the origin and consequences of genomic structural variation in cancer

Structural variants (SVs) are a pervasive trait of cancer genomes but their origin, evolution, and clinical impact remain poorly understood.

In this project, I aim at unraveling the mechanisms of origin, pathogenic effects, and clinical consequences of cancer-associated SVs with the overarching goal of developing new tools and knowledge for precision cancer medicine.

In Aim 1, we build on my strong track-record in method development to develop innovative assays to detect SVs and measure their effects on gene expression in single cells, as well as advanced computational tools to model the impact of SVs on the 3D genome.

In Aim 2, we leverage our new tools to pioneer studies of how SVs form and evolve under various types of stress and genetic conditions, and then in Aim 3 we generate the first-ever atlas of single-cell 3D cancer genome in silico reconstructions to study how SVs rewire the 3D genome and in turn disrupt gene expression.

Finally, in Aim 4, we bring our methods and knowledge closer to the clinic by assessing the predictive value of SVs for improved prognostication in luminal breast cancer patients, and by performing proof-of-principle applications of our methods to detect SVs in circulating tumor DNA and improve breast cancer molecular subtyping.

This project has the potential to generate unique insights into the biology and pathological consequences of SVs in cancer, and to ultimately pave the way to routine SV profiling in precision cancer medicine.