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Abstract:
Cancer cells, like microbes, live in complex metabolic environments.
Recent evidence suggests that microbial behavior across metabolic
environments is well described by simple empirical growth relationships,
or growth laws. Do such empirical growth relationships also exist in
cancer cells? To test this question, we develop a high-throughput
approach to extract quantitative measurements of cancer cell behaviors
in systematically altered metabolic environments. Using this approach,
we examine relationships between growth and three frequently studied
cancer phenotypes: drug-treatment survival, cell migration, and lactate
overflow. Drug-treatment survival follows simple linear growth
relationships, which differ quantitatively between chemotherapeutics and
EGFR inhibition. Cell migration follows a weak grow-and-go growth
relationship, with substantial deviation in some environments. Finally,
lactate overflow is mostly decoupled from growth rate and is instead
determined by the cells' ability to maintain high sugar uptake rates.
Altogether, this work provides a quantitative approach for formulating
empirical growth laws of cancer.
