Broad Anti-Cancer Activity Produced by Targeted Nutrients Deprivation (TND) of Multiple Non-Essential Amino Acids.

It has been known for close to 100 years that the metabolism of cancer cells is altered and different than that of healthy cells in the body. On that basis, we have developed an entirely novel approach to managing cancer, termed Targeted Nutrients Deprivation (TND). TND employs a formulated diet depleted of multiple non-essential amino acids (NEAAs) that are required by tumor cells but not by normal cells. Cancer cells specifically require those NEAAs due to their heightened and rewired metabolism. We demonstrated that our first proprietary formulated TND diet-FTN203-significantly reduced the growth of multiple human tumor xenografts in mouse. In combination with chemotherapy and immunotherapy, FTN203 further enhanced therapeutic efficacy. Reliance on FTN203 as the sole nutrition source was shown to be safe without causing detrimental body-weight loss or internal organ damage. Our findings indicate that TND is a novel and safe approach to managing cancer.Supplemental data for this article is available online at https://doi.org/10.1080/01635581.2021.2013904 .

Divergent patterns of selection on metabolite levels and gene expression.

BACKGROUND: Natural selection can act on multiple genes in the same pathway, leading to polygenic adaptation. For example, adaptive changes were found to down-regulate six genes involved in ergosterol biosynthesis-an essential pathway targeted by many antifungal drugs-in some strains of the yeast Saccharomyces cerevisiae. However, the impact of this polygenic adaptation on metabolite levels was unknown. Here, we performed targeted mass spectrometry to measure the levels of eight metabolites in this pathway in 74 yeast strains from a genetic cross. RESULTS: Through quantitative trait locus (QTL) mapping we identified 19 loci affecting ergosterol pathway metabolite levels, many of which overlap loci that also impact gene expression within the pathway. We then used the recently developed v-test, which identified selection acting upon three metabolite levels within the pathway, none of which were predictable from the gene expression adaptation. CONCLUSIONS: These data showed that effects of selection on metabolite levels were complex and not predictable from gene expression data. This suggests that a deeper understanding of metabolism is necessary before we can understand the impacts of even relatively straightforward gene expression adaptations on metabolic pathways.

Investigating metabolite-protein interactions: an overview of available techniques.

Metabolites comprise the molar majority of chemical substances in living cells, and metabolite-protein interactions are expected to be quite common. Many interactions have already been identified and have been shown to be involved in the regulation of different types of cellular processes including signaling events, enzyme activities, protein localizations and interactions. Recent technological advances have greatly facilitated the detection of metabolite-protein interactions at high sensitivity and some of these have been applied on a large scale. In this manuscript, we review the available in vitro, in silico and in vivo technologies for mapping small-molecule-protein interactions. Although some of these were developed for drug-protein interactions they can be applied for mapping metabolite-protein interactions. Information gained from the use of these approaches can be applied to the manipulation of cellular processes and therapeutic applications.