Deoxyribonucleoside triphosphate pools and thymidine chemosensitization in human T-cell leukemia

Identification of metabolites with anticancer properties by computational metabolomics

Background

Certain endogenous metabolites can influence the rate of cancer cell growth. For example, diacylglycerol, ceramides and sphingosine, NAD⁺ and arginine exert this effect by acting as signaling molecules, while carrying out other important cellular functions. Metabolites can also be involved in the control of cell proliferation by directly regulating gene expression in ways that are signaling pathway-independent, e.g. by direct activation of transcription factors or by inducing epigenetic processes. The fact that metabolites can affect the cancer process on so many levels suggests that the change in concentration of some metabolites that occurs in cancer cells could have an active role in the progress of the disease.

Results

CoMet, a fully automated Computational Metabolomics method to predict changes in metabolite levels in cancer cells compared to normal references has been developed and applied to Jurkat T leukemia cells with the goal of testing the following hypothesis: Up or down regulation in cancer cells of the expression of genes encoding for metabolic enzymes leads to changes in intracellular metabolite concentrations that contribute to disease progression. All nine metabolites predicted to be lowered in Jurkat cells with respect to lymphoblasts that were examined (riboflavin, tryptamine, 3-sulfino-L-alanine, menaquinone, dehydroepiandrosterone, α-hydroxystearic acid, hydroxyacetone, seleno-L-methionine and 5,6-dimethylbenzimidazole), exhibited antiproliferative activity that has not been reported before, while only two (bilirubin and androsterone) of the eleven tested metabolites predicted to be increased or unchanged in Jurkat cells displayed significant antiproliferative activity.

Conclusion

These results: a) demonstrate that CoMet is a valuable method to identify potential compounds for experimental validation, b) indicate that cancer cell metabolism may be regulated to reduce the intracellular concentration of certain antiproliferative metabolites, leading to uninhibited cellular growth and c) suggest that many other endogenous metabolites with important roles in carcinogenesis are awaiting discovery.

Deoxycytidine in human plasma: potential for protecting leukemic cells during chemotherapy

Degradation of DNA produces deoxycytidine. Metabolism of deoxycytidine to dCTP inhibits phosphorylation of cytosine arabinoside (araC), fludarabine (FaraA) and 2-chlorodeoxyadenosine (CdA) by deoxycytidine kinase. This study measured plasma deoxycytidine in healthy adults and two leukemia patients and then determined how clinically relevant deoxycytidine levels would affect drug toxicity in human leukemia and lymphoma cells. Deoxycytidine was well below 0.05 microM in ten healthy persons. In the leukemia patients it was <0.05 and 0.44 microM before chemotherapy, rising to 10.3 and 5.5 microM during treatment. A broad range of clinically relevant deoxycytidine levels were high enough to profoundly decrease araC, FaraA and CdA toxicity in MOLT3, CA46 and HL60 leukemia/lymphoma cells and to change dCTP, DNA synthesis and drug incorporation into DNA in a manner consistent with prior mechanistic studies. Varying deoxycytidine levels could be an important factor influencing leukemia therapy.

Selective potentiation of lometrexol growth inhibition by dipyridamole through cell-specific inhibition of hypoxanthine salvage

The novel antifolate lometrexol (5,10-dideazatetrahydrofolate) inhibits de novo purine biosynthesis, and co-incubation with hypoxanthine abolishes its cytotoxicity. The prevention of hypoxanthine rescue from an antipurine antifolate by the nucleoside transport inhibitor dipyridamole was investigated for the first time in nine human and rodent cell lines from seven different tissues of origin. In A549, HeLa and CHO cells, dipyridamole prevented hypoxanthine rescue and so growth was inhibited by the combination of lometrexol, dipyridamole and hypoxanthine, but in HT29, HCT116, KK47, MDA231, CCRF CEM and L1210 cells dipyridamole had no effect and the combination did not inhibit growth. Dipyridamole inhibited hypoxanthine uptake in A549 but not in CCRF CEM cells. Dipyridamole prevented the hypoxanthine-induced repletion of dGTP pools, depleted by lometrexol, in A549 but not in CCRF CEM cells. Thus, the selective growth-inhibitory effect of the combination of lometrexol, dipyridamole and hypoxanthine is apparently due to the dipyridamole sensitivity (ds) or insensitivity (di) of hypoxanthine transport. Both the human and murine leukaemic cells are of the di phenotype. If this reflects the transport phenotype of normal bone marrow it would suggest that the combination of lometrexol, dipyridamole and hypoxanthine might be selectively toxic to certain tumour types and have reduced toxicity to the bone marrow.