PROJECT SUMMARY
Somatic mutations accumulate daily in every cell of the human body. These mutations originate from mutational
processes due to environmental exposures, lifestyle choices, defective cellular machineries, and even normal
cellular activities. Each mutational process imprints a characteristic pattern of mutations on the genome of
somatic cells, termed “mutational signature”. Since somatic mutations are retained in the genomes of cells and
their progenies, the presence of mutational signatures in a somatic genome serves as an “archaeological imprint”
of the activities of the mutational processes that were operative during a person’s lifetime. Recent developments
of computational tools have allowed identifying mutational signatures from the DNA sequences of cancer
samples and quantifying the activities of different mutational processes in individual cancer patients. Analysis of
many thousands of cancer patients across the world has now revealed almost 80 distinct mutational signatures.
Importantly, for each of these patients, we now know the mutational processes that have caused their cancers
and, for many of these patients, we could identify potential strategies to reduce environmental exposures and
prevent their cancers. However, an effective and timely cancer prevention requires knowing the mutational
processes operating in a healthy individual and eliminating or reducing the activities of these processes before
that individual develops cancer. Unfortunately, currently, there are no approaches that allow quantifying
mutational signatures of environmental exposures in a healthy individual and, thus, many opportunities for
personalize cancer prevention are missed. Here, we propose to develop a novel computational approach that
will allow noninvasive monitoring of mutational signatures in easily accessible normal somatic tissues of healthy
individuals. Our approach will perform a direct detection of somatic mutational signatures from low coverage
single-cell DNA sequencing data without relying on prior identification of somatic mutations. The approach will
be optimized and validated using single-cell DNA sequencing data from: (i) in vitro cell lines exposed to
environmental mutagens; (ii) an in vivo mouse model consuming water contaminated with a strong chemical
mutagen; (iii) healthy individuals with established exposures to known environmental mutagens. Overall, this
project will transform our ability to monitor the activities of the mutational processes in normal tissues of healthy
individuals and it will open a plethora of opportunities for personalized cancer prevention through possible
targeted interventions that reduce mutagenic exposures from environment agents and lifestyle choices.
