Alterations in metabolic pathways are known to characterize cancer. In order to suppress cancer growth, however, multiple proteins involved in these pathways have to be targeted simultaneously. We have developed a screening method to assess the best drug combination for cancer treatment based on targeting several factors implicated in tumor specific metabolism. Following a review of the literature, we identified those enzymes known to be deregulated in cancer and established a list of sixty-two drugs targeting them. These molecules are used routinely in clinical settings for diseases other than cancer. We screened a first library in vitro against four cell lines and then evaluated the most promising binary combinations in vivo against three murine syngeneic cancer models, (LL/2, Lewis lung carcinoma; B16-F10, melanoma; and MBT-2, bladder cancer). The optimum result was obtained using a combination of α-lipoic acid and hydroxycitrate (METABLOC(TM)). In this study, a third agent was added by in vivo evaluation of a large number of combinations. The addition of octreotide strongly reduced tumor development (T/C% value of 30.2 to 34.5%; P < 0.001) in the same models and prolonged animal survival (P < 0.001) as compared to cisplatin. These results were confirmed in a different laboratory setting using a human xenograft model (NCI-H69, small cell lung cancer). None of these three molecules are known to target DNA. The effectiveness of this combination in several animal models, as well as the low toxicity of these inexpensive drugs, emphasizes the necessity of rapidly setting up a clinical trial.
Screening of well-established drugs targeting cancer metabolism: reproducibility of the efficacy of a highly effective drug combination in mice