Flux balance analysis predicts essential genes in clear cell renal cell carcinoma metabolism

摘要: Flux balance analysis is the only modelling approach that capable of producing genome-wide predictions gene essentiality may aid to unveil metabolic liabilities in cancer. Nevertheless, a systemic validation by flux currently missing. Here, we critically evaluated accuracy two cancer types, clear cell renal carcinoma (ccRCC) and prostate adenocarcinoma, comparison with large-scale experiments vitro. We found ccRCC, but not could predict essential genes beyond random expectation. Five identified genes, AGPAT6, GALT, GCLC, GSS, RRM2B, were predicted be dispensable normal metabolism. Hence, targeting these selectively prevent ccRCC growth. Based on our analysis, discuss benefits limitations for metabolism, its use exposing whose emergent network enforces outstanding anabolic requirements cellular proliferation.