Characterizing cytotoxic therapy induced shifts in the cost-to-benefit ratio of high ploidy

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SUMMARY Traditional phase I dose-finding strategies monitor drug response only for two weeks, based on the assumption that it will suffice to observe how therapy affects doubling time of a homogeneous population over 2-4 generations. But with the paradigm shift that most cancers are heterogeneous comes an urgent need to consider that therapy-induced shifts in population composition manifest over longer time frames. We previously coined the “tip-over hypothesis of DNA damage therapy sensitivity”, proposing that cytotoxic therapy is effective if it pushes a cell’s somatic copy number alteration (SCNA) load above a tipping point. Variable proximity of co-existing tumor cells to this tipping point imply that dose-response relations need not be monotonic. Cytotoxic therapy can drive one cell into apoptosis, while skyrocketing another cell into malignant proliferation. As the developers of widely used computational and mathematical methods, with established research programs in tumor metabolism, and with a broad record of modeling dynamic processes and integrating various omics- and imaging platforms, our team brings complementary expertise to develop a personalized cytotoxic therapy strategy that confines therapy-induced selection of resistant clones. We will test the potential of tumor cell DNA content and dNTP substrate availability to predict a tumor’s vulnerability to increasing SCNA rate. Hereby, the aforementioned tipping point is accounted for not by elevated SCNA load alone, but by an inability of the tissue micro-environment (TME) to provide the necessary resources. Experiments are proposed in stomach and brain tumors—two cancer types whose TME can “afford” vastly different amounts of DNA. Our preliminary studies show that energetic costs of DNA content levels required for >75% SCNA load do not, in the absence of cytotoxic therapy, justify the masking benefits they bring. In particular, we showed that limiting dNTP concentrations amplify divergence in S-phase duration between high- and low-ploidy cells. Our hypothesis is that cytotoxic therapy causes a net-increase in fitness of tumors that exceed the SCNA tipping point. This hypothesis is founded on two unexpected recent findings: (i) integrated single-cell RNA- and DNA-sequencing analyses of stomach cancer cells suggests that the risk of cell death immediately after an SCNA event, rather than just SCNA rate, impacts clonal diversity. Aim 1 will integrate single cell sequencing with imaging and mathematical modeling of heterogeneous populations that evolve through chromosome missegregations, to examine observed SCNA landscapes and missegregation tolerances, and to predict effective cytotoxic therapy doses. (ii) Even minimal changes in DNA content among co-existing clones within the same Glioblastoma can result in significantly longer S-phases. Aim 2 will evaluate Oxygen, Phosphate and Glucose as rate-limiting substrates of dNTP synthesis of co-evolving subpopulations in stomach and brain tissue environments. This is the first study to investigate if and how clinical decisions can benefit from integrating a tumor environment’s energetic provision with the energetic demands of cancer cells’ genomic makeup.