부산대학교 도서관

As a cancer develops, its cells accrue new mutations, resulting in a heterogeneous, complex genomic profile. We make use of this heterogeneity to derive simple, analytic estimates of parameters driving carcinogenesis and reconstruct the timeline of selective events following initiation of an individual cancer, where two longitudinal samples are available for sequencing. Using stochastic computer simulations of cancer growth, we show that we can accurately estimate mutation rate, time before and after a driver event occurred, and growth rates of both initiated cancer cells and subsequently appearing subclones. We demonstrate that in order to obtain accurate estimates of mutation rate and timing of events, observed mutation counts should be corrected to account for clonal mutations that occurred after the founding of the tumor, as well as sequencing coverage. Chronic lymphocytic leukemia (CLL), which often does not require treatment for years after diagnosis, presents an optimal system to study the untreated, natural evolution of cancer cell populations. When we apply our methodology to reconstruct the individual evolutionary histories of CLL patients, we find that the parental leukemic clone typically appears within the first fifteen years of life. Author summary: By the time a patient's cancer is diagnosed, it has been growing undetected for years, or even decades. A cancer's initiation, development, and progression are driven by a sequence of driver mutations, genetic alterations that confer a fitness advantage to the cells containing them. As a cancer expands, it also accumulates many neutral mutations that don't confer a growth advantage. As a result, tumors are highly heterogeneous, made up of different genetically distinct populations, or subclones, of cancer cells. Most cancers will require immediate treatment upon diagnosis, making study of their natural progression over time difficult. However, the blood cancer chronic lymphocytic leukemia (CLL) often does not require immediate treatment and is closely monitored for years, which makes it ideal for studying cancer evolution before treatment radically alters the cancer's dynamics. We make use of the complex tumor heterogeneity to reconstruct the timing of key driver events in the tumor's development, showing that the initial leukemic clone often appears early in life. Additionally, we estimate mutation rate, subclone growth rates, and fitness advantage provided by driver mutations. [ABSTRACT FROM AUTHOR]