Dietary restriction of methionine (Met) and cysteine (Cys) delays the aging process and aging-related diseases, improves glucose and fat metabolism and reduces oxidative stress in numerous laboratory animal models. Little is known regarding the effects of sulfur amino acid restriction in humans. Thus, our objectives were to determine the impact of feeding diets restricted in Met alone (MetR) or in both Met and Cys (total sulfur amino acids, SAAR) to healthy adults on relevant biomarkers of cardiometabolic disease risk. A controlled feeding study. We included 20 healthy adults (11 females/9 males) assigned to MetR or SAAR diet groups consisting of three 4-wk feeding periods: Control period; low level restriction period (70% MetR or 50% SAAR); and high level restriction period (90% MetR or 65% SAAR) separated by 3-4-wk washout periods. No adverse effects were associated with either diet and level of restriction and compliance was high in all subjects. SAAR was associated with significant reductions in body weight and plasma levels of total cholesterol, LDL, uric acid, leptin, and insulin, BUN, and IGF-1, and increases in body temperature and plasma FGF-21 after 4 weeks (P<0.05). Fewer changes occurred with MetR including significant reductions in BUN, uric acid and 8-isoprostane and an increase in FGF-21 after 4 weeks (P<0.05). In the 65% SAAR group, plasma Met and Cys levels were significantly reduced by 15% and 13% respectively (P<0.05). These results suggest that many of the short-term beneficial effects of SAAR observed in animal models are translatable to humans and support further clinical development of this intervention.

Introduction: Se-methylselenocysteine (MSC), a naturally occurring selenium compound, is a promising chemopreventive agent against in vivo and in vitro models of carcinogen-induced mouse and rat mammary tumorigenesis. We have demonstrated previously that MSC induces apoptosis after a cell growth arrest in S phase in a mouse mammary epithelial tumor cell model (TM6 cells) in vitro. The present study was designed to examine the involvement of the phosphatidylinositol 3-kinase (PI3-K) pathway in TM6 tumor model in vitro after treatment with MSC. Methods: Synchronized TM6 cells treated with MSC and collected at different time points were examined for PI3-K activity and Akt phosphorylation along with phosphorylations of Raf, MAP kinase/ERK kinase (MEK), extracellular signal-related kinase (ERK) and p38 mitogen-activated protein kinase (MAPK). The growth inhibition was determined with a [³H]thymidine incorporation assay. Immunoblotting and a kinase assay were used to examine the molecules of the survival pathway. Results: PI3-K activity was inhibited by MSC followed by dephosphorylation of Akt. The phosphorylation of p38 MAPK was also downregulated after these cells were treated with MSC. In parallel experiments MSC inhibited the Raf–MEK–ERK signaling pathway. Conclusion: These studies suggest that MSC blocks multiple signaling pathways in mouse mammary tumor cells. MSC inhibits cell growth by inhibiting the activity of PI3-K and its downstream effector molecules in mouse mammary tumor cells in vitro.

Pancreatic cancer is one of the most fatal malignancies and the seventh leading cause of cancer-related deaths related to late diagnosis, poor survival rates, and high incidence of metastasis. Unfortunately, pancreatic cancer is predicted to become the third leading cause of cancer deaths in the future. Therefore, diagnosis at the early stages of pancreatic cancer for initial diagnosis or postoperative recurrence is a great challenge, as well as predicting prognosis precisely in the context of biomarker discovery. From the personalized medicine perspective, the lack of molecular biomarkers for patient selection confines tailored therapy options, including selecting drugs and their doses or even diet. Currently, there is no standardized pancreatic cancer screening strategy using molecular biomarkers, but CA19-9 is the most well known marker for the detection of pancreatic cancer. In contrast, recent innovations in high-throughput techniques have enabled the discovery of specific biomarkers of cancers using genomics, transcriptomics, proteomics, metabolomics, glycomics, and metagenomics. Panels combining CA19-9 with other novel biomarkers from different “omics” levels might represent an ideal strategy for the early detection of pancreatic cancer. The systems biology approach may shed a light on biomarker identification of pancreatic cancer by integrating multi-omics approaches. In this review, we provide background information on the current state of pancreatic cancer biomarkers from multi-omics stages. Furthermore, we conclude this review on how multi-omics data may reveal new biomarkers to be used for personalized medicine in the future.