3D_CAMP: 3D cancer genome modeling for personalized medicine diagnostics
Our main hypothesis is that 3-dimensional (3D) genome organization influences susceptibility of distinct genomic regions to mutagenesis, and constitutes a critical component in assessment and classification of tumors. On this premise, we will develop a computational framework for accurate estimation of cancer mutation susceptibility in the genome. We subsequently aim to develop a cancer classification tool for use in precision medicine diagnostics. To enable this, a pilot study will aim to improve our 3D genome modeling platform, predict and validate the spatial localization of melanoma and breast cancer mutations, and position ourselves for H2020. The study will consist of two research aims and one administrative aim:
1. Establish a fast, robust and accurate software suite for 3D genome modeling
2. Proof-of-principle - generate 3D models of tumorigenic mutations in skin and breast cancer cells
3. Identify H2020 opportunities and partners; send ERC and Thematic Area Applications.