The interdisciplinary program project grant, “Tipping points in cancer” has been funded for five years by the National Cancer Institute and awarded to John Lowengrub, Devon Lawson, and Arthur Lander. The grant starts today, and the total costs approved are $10.6 million over 5 years.

A new program project on Tipping Points in Cancer will address fundamental questions about processes
in cancer initiation and progression. The premise of the program is that cancer develops through a series
of stochastic steps, some of which are non-genetic (i.e., not mutational), including steps that are non-cell autonomous (i.e., collective). Three team-oriented research projects will investigate cell states and cell interactions that drive such transitions and explore their impact on cancer prevention and therapy. Each project deals with a cancer that, when modeled using genetically engineered mice, points to the existence of unexplained thresholds in the transition between pre-malignant and malignant states.

One project will leverage an improved mouse model of chronic myeloid leukemia (CML), which suggests
that stochastic, non-genetic transitions are essential in leukemogenesis. The model will be used to investigate the origins of primary therapeutic resistance and the means by which existing therapies may be improved.

A second project will investigate the origins of melanoma, using mouse models to clarify the many cellular states that have been distinguished in this cancer and elucidate relationships between such states and accumulated mutations, arrangements of cells in space, and the microenvironment.

The third project will leverage mouse models of Brca1-driven, triple-negative breast cancer, wherein observations suggest the existence of a distinct pre-malignant state, seeking to identify the signals and cell-cell interactions that create and maintain this state, and elucidate the events that allow rare escape to malignancy.

All three projects combine mathematical modeling, genomics, and computational biology. All three will be served by a shared resource core for analyzing single cell data and providing access to new and emerging technologies and algorithms. An administrative core and an external scientific advisory board will assist with management, integration and evaluation of program activities.