Metabolic state alters economic decision making under risk in humans

Background: Animals' attitudes to risk are profoundly influenced by metabolic state (hunger and baseline energy stores). Specifically, animals often express a preference for risky (more variable) food sources when below a metabolic reference point (hungry), and safe (less variable) food sources when sated. Circulating hormones report the status of energy reserves and acute nutrient intake to widespread targets in the central nervous system that regulate feeding behaviour, including brain regions strongly implicated in risk and reward based decision-making in humans. Despite this, physiological influences per se have not been considered previously to influence economic decisions in humans. We hypothesised that baseline metabolic reserves and alterations in metabolic state would systematically modulate decision-making and financial risk-taking in humans. Methodology/Principal Findings: We used a controlled feeding manipulation and assayed decision-making preferences across different metabolic states following a meal. To elicit risk-preference, we presented a sequence of 200 paired lotteries, subjects' task being to select their preferred option from each pair. We also measured prandial suppression of circulating acyl-ghrelin (a centrally-acting orexigenic hormone signalling acute nutrient intake), and circulating leptin levels (providing an assay of energy reserves). We show both immediate and delayed effects on risky decision-making following a meal, and that these changes correlate with an individual's baseline leptin and changes in acyl-ghrelin levels respectively. Conclusions/Significance: We show that human risk preferences are exquisitely sensitive to current metabolic state, in a direction consistent with ecological models of feeding behaviour but not predicted by normative economic theory. These substantive effects of state changes on economic decisions perhaps reflect shared evolutionarily conserved neurobiological mechanisms. We suggest that this sensitivity in human risk-preference to current metabolic state has significant implications for both real-world economic transactions and for aberrant decision-making in eating disorders and obesity

Characterization of an engineered human purine nucleoside phosphorylase fused to an anti-her2/neu single chain Fv for use in ADEPT

Abstract Background Antibody Directed Enzyme Prodrug Therapy (ADEPT) can be used to generate cytotoxic agents at the tumor site. To date non-human enzymes have mainly been utilized in ADEPT. However, these non-human enzymes are immunogenic limiting the number of times that ADEPT can be administered. To overcome the problem of immunogenicity, a fully human enzyme, capable of converting a non-toxic prodrug to cytotoxic drug was developed and joined to a human tumor specific scFv yielding a fully human targeting agent. Methods A double mutant of human purine nucleoside phosphorylase (hDM) was developed which unlike the human enzyme can cleave adenosine-based prodrugs. For tumor-specific targeting, hDM was fused to the human anti-HER2/neu single chain Fv (scFv), C6 MH3B1. Enzymatic activity of hDM with its natural substrates and prodrugs was determined using spectrophotomeric approaches. A cell proliferation assay was used to assess the cytotoxicity generated following conversion of prodrug to drug as a result of enzymatic activity of hDM. Affinity of the targeting scFv, C6 MH3B1 fused to hDM to Her2/neu was confirmed using affinity chromatography, surface plasmon resonance, and flow-cytometry. Results In vitro hDM-C6 MH3B1 binds specifically to HER2/neu expressing tumor cells and localizes hDM to tumor cells, where the enzymatic activity of hDM-C6 MH3B1, but not the wild type enzyme, results in phosphorolysis of the prodrug, 2-fluoro-2'-deoxyadenosine to the cytotoxic drug 2-fluoroadenine (F-Ade) causing inhibition of tumor cell proliferation. Significantly, the toxic small drug diffuses through the cell membrane of HER2/neu expressing cells as well as cells that lack the expression of HER2/neu, causing a bystander effect. F-Ade is toxic to cells irrespective of their growth rate; therefore, both the slowly dividing tumor cells and the non-dividing neighboring stromal cells that support tumor growth should be killed. Analysis of potential novel MHCII binding peptides resulting from fusion of hDM to C6 MH3B1 and the two mutations in hDM, and of the structure of hDM compared to the wild-type enzyme suggests that hDM-C6 MH3B1 should exhibit minimal immunogenicity in humans. Conclusion hDM-C6 MH3B1 constitutes a novel human based protein that addresses some of the limitations of ADEPT that currently preclude its successful use in the clinic

Genomics of Signaling Crosstalk of Estrogen Receptor α in Breast Cancer Cells

BACKGROUND: The estrogen receptor alpha (ERalpha) is a ligand-regulated transcription factor. However, a wide variety of other extracellular signals can activate ERalpha in the absence of estrogen. The impact of these alternate modes of activation on gene expression profiles has not been characterized. METHODOLOGY/PRINCIPAL FINDINGS: We show that estrogen, growth factors and cAMP elicit surprisingly distinct ERalpha-dependent transcriptional responses in human MCF7 breast cancer cells. In response to growth factors and cAMP, ERalpha primarily activates and represses genes, respectively. The combined treatments with the anti-estrogen tamoxifen and cAMP or growth factors regulate yet other sets of genes. In many cases, tamoxifen is perverted to an agonist, potentially mimicking what is happening in certain tamoxifen-resistant breast tumors and emphasizing the importance of the cellular signaling environment. Using a computational analysis, we predicted that a Hox protein might be involved in mediating such combinatorial effects, and then confirmed it experimentally. Although both tamoxifen and cAMP block the proliferation of MCF7 cells, their combined application stimulates it, and this can be blocked with a dominant-negative Hox mutant. CONCLUSIONS/SIGNIFICANCE: The activating signal dictates both target gene selection and regulation by ERalpha, and this has consequences on global gene expression patterns that may be relevant to understanding the progression of ERalpha-dependent carcinomas

Angiogenesis inhibitors in the treatment of prostate cancer

Prostate cancer remains a significant public health problem, with limited therapeutic options in the setting of castrate-resistant metastatic disease. Angiogenesis inhibition is a relatively novel antineoplastic approach, which targets the reliance of tumor growth on the formation of new blood vessels. This strategy has been used successfully in other solid tumor types, with the FDA approval of anti-angiogenic agents in breast, lung, colon, brain, and kidney cancer. The application of anti-angiogenic therapy to prostate cancer is reviewed in this article, with attention to efficacy and toxicity results from several classes of anti-angiogenic agents. Ultimately, the fate of anti-angiogenic agents in prostate cancer rests on the eagerly anticipated results of several key phase III studies

Intracellular Trafficking Considerations in the Development of Natural Ligand-Drug Molecular Conjugates for Cancer

Overexpressed receptors, characteristic of many cancers, have been targeted by various researchers to achieve a more specific treatment for cancer. A common approach is to use the natural ligand for the overexpressed receptor as a cancer-targeting agent which can deliver a chemically or genetically conjugated toxic molecule. However, it has been found that the therapeutic efficacy of such ligand-drug molecular conjugates can be limited, since they naturally follow the intracellular trafficking pathways of the endogenous ligands. Therefore, a thorough understanding of the intracellular trafficking properties of these ligands can lead to novel design criteria for engineering ligands to be more effective drug carriers. This review presents a few commonly used ligand/receptor systems where intracellular trafficking considerations can potentially improve the therapeutic efficacy of the ligand-drug molecular conjugates

A Bioinformatics Filtering Strategy for Identifying Radiation Response Biomarker Candidates

The number of biomarker candidates is often much larger than the number of clinical patient data points available, which motivates the use of a rational candidate variable filtering methodology. The goal of this paper is to apply such a bioinformatics filtering process to isolate a modest number (<10) of key interacting genes and their associated single nucleotide polymorphisms involved in radiation response, and to ultimately serve as a basis for using clinical datasets to identify new biomarkers. In step 1, we surveyed the literature on genetic and protein correlates to radiation response, in vivo or in vitro, across cellular, animal, and human studies. In step 2, we analyzed two publicly available microarray datasets and identified genes in which mRNA expression changed in response to radiation. Combining results from Step 1 and Step 2, we identified 20 genes that were common to all three sources. As a final step, a curated database of protein interactions was used to generate the most statistically reliable protein interaction network among any subset of the 20 genes resulting from Steps 1 and 2, resulting in identification of a small, tightly interacting network with 7 out of 20 input genes. We further ranked the genes in terms of likely importance, based on their location within the network using a graph-based scoring function. The resulting core interacting network provides an attractive set of genes likely to be important to radiation response