Understanding the interplay between metabolism and genetic regulation is considered key to shed light on the mechanisms underlying cancer onset and progression. In thiswork, we reconstruct a number of tumor-specific genome-scale metabolic models and inspect estimated flux profiles via statistical analysis, characterizing the detailed metabolicresponse associated to altered regulation in various tissues. We thus demonstrate that combining complementary computational techniques it is possible to identify polyomicdifferences and commonalities across cancer types
