Biomedical subjects

Wai-Nang P Lee

Publications and source records attributed to Wai-Nang P Lee.

3 recordsLinked to original sources

PubMed2006

Pentose phosphate cycle oxidative and nonoxidative balance: A new vulnerable target for overcoming drug resistance in cancer.

The metabolic network of cancer cells confers adaptive mechanisms against many chemotherapeutic agents, but also presents critical constraints that make the cells vulnerable to perturbation of the network due to drug therapy. To identify these fragilities, combination therapies based on targeting the nucleic acid synthesis metabolic network at multiple points were tested. Results showed that cancer cells overcome single hit strategies through different metabolic network adaptations, demonstrating the robustness of cancer cell metabolism. Analysis of these adaptations also identified the maintenance of pentose phosphate cycle oxidative and nonoxidative balance to be critical for cancer cell survival and vulnerable to chemotherapeutic intervention. The vulnerability of cancer cells to the imbalance on pentose phosphate cycle was demonstrated by phenotypic phase plane analysis.

Animals↗

PubMed2005

K-ras codon-specific mutations produce distinctive metabolic phenotypes in NIH3T3 mice [corrected] fibroblasts.

Among K-ras mutations, codon 12 mutations have been identified as those conferring a more aggressive phenotype. This aggressiveness is primarily associated with slow proliferation but greatly increased resistance to apoptosis. Using transfected NIH3T3 fibroblasts with a mutated K-ras minigene either at codon 12 (K12) or at codon 13 (K13), and taking advantage of [1,2-13C2]glucose tracer labeling, we show that codon 12 mutant K-ras (K12)-transformed cells exhibit greatly increased glycolysis with only a slight increase in activity along pathways that produce nucleic acid and lipid synthesis precursors in the oxidative branch of the pentose phosphate pathway and via pyruvate dehydrogenase flux. K13 mutants display a modest increase in anaerobic glycolysis associated with a large increase in oxidative pentose phosphate pathway activity and pyruvate dehydrogenase flux. The distinctive differences in metabolic profiles of K12 and K13 codon mutated cells indicate that a strong correlation exists between the flow of glucose carbons towards either increased anaerobic glycolysis, and resistance to apoptosis (K12), or increased macromolecule synthesis, rapid proliferation, and increased sensitivity to apoptosis.

Anaerobiosis↗

PubMed2005

Nutrient-gene interaction: tracer-based metabolomics.

Understanding nutrient-gene interaction requires tools for both the study of nutrigenomics and the characterization of phenotype. Metabolomics or metabolite profiling is a powerful tool for characterizing metabolic phenotype, and tracer-based metabolomics is a subset of metabolomics that focuses on metabolite distribution and flux determination using tracers. In this review, the characterizations of metabolic phenotype by metabolite profiling and by metabolic flux measurements are compared. The rationale and methodologies of tracer-based metabolomics are explained. Tracer-based metabolomics provides a relational database of metabolites linked by the relationship of shared metabolic pathways, common substrates, and cofactors. Such a collection of flux measurements provides precise and accurate information on the operation of the cellular metabolic network and its response to genetic and nutrient environment changes. Nutrient-gene interaction can be studied using the concept of constraint-based modeling, which states that the observed metabolic phenotype is a consequence of constraints from genetic factors and the nutrient environment. Thus, genetic inheritance (genomic constraints) confers a wide range of possible phenotypes whereas selection by metabolic (structural and pathway relationship) and environmental (physical environment and nutrient availability) constraints determines the final observed phenotype. The study of the contribution from nutrient and genetic factors to the survival advantage of cancer cells using flux measurements is a critical first step in our understanding of the relationship between nutrient intake and cancer risk.

Diet↗