Our ERC-PoC funded project was aimed at creating products that improve the ability to select the right treatment for cancer patients based on the unique genetic makeup of their individual tumors. We focused on p53, as it is the most frequently mutated tumor suppressor gene in human cancers, and since specific p53 mutations have been reported to endow resistance to various treatments. We therefore established an experimental system that allows high-throughput screening for the efficacy of a given drug on each of ~10,000 p53 mutants within a single experiment. So far, we have evaluated the effects of different mutants under normal growth conditions, but have not yet succeeded in identifying mutant-specific effects on resistance to relevant treatments. However, our current data already hold important clinical value: distinct p53 mutations that are found in patients endow cells with different oncogenic potential, at least in their effects on cell survival and proliferation. Some mutations, although encoding for amino acid substitutions in functionally important regions of the gene, retain wild-type p53 function and do not significantly change the proliferation rate of the cells, and are thus unlikely to be driving the given tumor. Further calibrations will be required to achieve the project’s goals and map the treatment-specific effects of various mutants.
