The Maley laboratory is exploring fundamental concepts in neoplastic progression, the processes by which normal tissue becomes cancerous, for the purposes of developing better methods for cancer prevention and therapy. They are applying evolutionary biology, ecology, computational biology and genetics to the understanding of these problems.
The reason cancer is such a vicious disease, and so hard to cure, is that the cells in a neoplasm (an abnormal growth) evolve by natural selection. There are three necessary and sufficient conditions for natural selection, all of which are met in a neoplasm:
- There must be variation in the population. Neoplasms are mosaics of different mutant cells.
- That variation must be heritable. The variation in a neoplasm is due to mutations and methylation of the DNA in the cells. The variation is thus passed down to both daughter cells when a neoplastic cell divides.
- The variation must affect reproduction or survival. Most of the hallmarks of cancer are examples of mutations that give a reproductive or survival advantage to the mutant cell. This includes uncontrolled proliferation, suppression of apoptosis (programmed cell death), stimulation of new growth of blood vessels to feed the neoplasm, evasion of the immune system, and invasion of other organs.
A consequence of this evolution within a neoplasm is that a treatment will tend to kill the susceptible cells but leave the resistant ones to flourish. A few months later, the cancer will reappear and will be resistant to the previous treatment. Thus, evolution lies at the heart of both neoplastic progression and our difficulties in treating cancer.
The Maley laboratory is applying evolutionary and ecological theory to neoplastic progression and cancer therapy in order to modulate the evolution of neoplastic cells and thereby prevent cancer and its relapse. They take three, mutually reinforcing approaches to these problems: computational simulations to explore hypotheses, data mining of (application of evolutionary theory to) genetic data from neoplasms, and evolutionary experiments in tissue culture.
- Measuring genetic diversity in neoplasms and testing if it predicts both progression and therapeutic resistance.
- Applying phylogenetic methods to measure the parameters of evolution in neoplasms.
- Studying the selective effects of therapy and differentiation in acute myeloid leukemia.
- Peto's paradox: why large, long-lived animals like whales do not get proportionally more cancer than humans.
- Harnessing clonal evolution to prevent cancer.
- Computational modeling of the mechanisms of clonal expansion.
- Computational modeling of neoplastic progression.