Our lab focuses on computational biology and cancer research. We analyze large genomics and other -omics datasets of various cancer types using statistical and machine learning approaches. We alo develop new methods to ask unique questions on the data. We occasionally perform functional experiments in close collaborations with experimental labs to validate our most promising findings. Research in the lab falls under three broad themes.

Drivers & passengers of the cancer genome

Cancer is a genetic disease caused by somatic mutations in the genome. Single nucleotide variants (SNVs) and other classes of mutations accumulate in the genome over time and through exposures to DNA-damaging agents. Most mutations have little consequence and are often called passengers, while a small minority of mutations called drivers affect critical genes in cells and cause aberrant activity of oncogenic and tumor suppresive pathways in cells.

Recent research in the lab has focused on both drivers and passengers in large whole-genome sequencing datasets.

For driver mutations, we recently performed a systematic analysis of potential non-coding drivers in gene-regulatory regions and three-dimensional interaction hubs of the cancer genome using cancer whole-genome sequencing data. We found dozens of potential novel driver mutations and performed functional experiments with CRISPR genome editing and transcriptome-wide profiling to validate one non-coding region controlling the tumor suppressor gene CCNB1IP1. We developed the computational tool ActiveDriverWGS to enable such discovery.


Candidate cancer driver mutations in distal regulatory elements and long-range chromatin interaction networks.
Helen Zhu*, Liis Uusküla-Reimand*, Keren Isaev*, .. , Jüri Reimand.
Molecular Cell 77 (6) 1307-1321. e10 (2020)

For passenger mutations, we recently focused on localized mutational processes acting on thousands of gene-regulatory and chromatin architectural elements of the cancer genome. We characterized the potential functional and genetic determinants of mutational processes at binding sites of the CTCF chromatin architectural factor, gene promoter elements and cancer-specific open-chromatin regions. For example, promoters of highly expressed genes and CTCF binding sites epigenetically conserved across many human tissues display the greatest extent of somatic mutagenesis. We also found that certain driver mutations in cancer genomes significantly increase the apparent activity of these mutational processes.


Functional and genetic determinants of mutation rate variability in regulatory elements of cancer genomes.
Christian A Lee*, Diala Abd-Rabbo*, Jüri Reimand.
Genome Biology 22 (1), 133 (2021)

Multi-omics data integration

Biomarker & target discovery