Metastasis represents a major clinical challenge that is driven by an as of yet poorly understood switch in cell state. Without acquiring additional genetic alterations, a cancer cell can switch from an immotile cell growing in a cluster to a motile, selfcontained cancer cell that can home at a secondary site and re-start proliferation. There is growing evidence that individual tumors are composed of multiple clonal subsets resulting in various levels of non-genetic intratumor heterogeneity that determines their metastatic ability.
In pancreatic cancer (PDAC) distinct metabolic dependencies and subtypes associated with glycolysis, lipogenesis and redox pathways have been described, and metabolic PDAC heterogeneity and longitudinal plasticity play an important role in therapy response. We hypothesize that the different tumor cell populations found in PDAC patients have a distinct impact on the metastatic progress and therapy outcome. As part of PhenoTImE, our goal is to identify the tumor cell sub-population(s) that confer resistance to therapy and determine metabolic treatment-strategies that can target these clones to achieve more efficient treatment.

We recently developed a multiplexed small molecule screening platform that allows interrogating small molecules in vivo in an efficient high-throughput manner for their effect on cancer metastasis. This approach integrates molecular cell barcoding, in vitro compound pretreatment, and in vivo selection to allow multiplexed compound screening in mice. In preliminary experiments we have successfully applied this platform and identified and validated the selective OXPHOS inhibitor atovaquone as an inhibitor of metastatic ability in pancreatic ductal adenocarcinoma (PDAC) without affecting overall cell survival or proliferation.

We will in detail investigate the effect of mitochondria-directed therapies on pancreatic cancer cells with distinct metastatic abilities and identify those compounds that specifically target metastatic PDAC cells using our barcoding technology. Metabolic, functional, and clone-tracing analyses will be performed to characterize metastatic heterogeneity, clonal evolution and subclone-specific responses to the most-specific mitochondria-targeting compounds and to identify the tumor cell sub-population(s) that confer resistance to therapy. Overall, our results will have immediate impact on the design for clinical trials and personalized companion metabolic treatment options.

Contact

Prof. Dr. rer. Nat. Barbara M. Grüner

West German Cancer Center
Department of Medical Oncology
University Hospital Essen

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