Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks.

Human metabolism involves thousands of reactions and metabolites. To interpret this complexity, computational modeling becomes an essential experimental tool. One of the most popular techniques to study human metabolism as a whole is genome scale modeling. A key challenge to applying genome scale modeling is identifying critical metabolic reactions across diverse human tissues. Here we introduce a novel algorithm called Cost Optimization Reaction Dependency Assessment (CORDA) to build genome scale models in a tissue-specific manner. CORDA performs more efficiently computationally, shows better agreement to experimental data, and displays better model functionality and capacity when compared to previous algorithms. CORDA also returns reaction associations that can greatly assist in any manual curation to be performed following the automated reconstruction process. Using CORDA, we developed a library of 76 healthy and 20 cancer tissue-specific reconstructions. These reconstructions identified which metabolic pathways are shared across diverse human tissues. Moreover, we identified changes in reactions and pathways that are differentially included and present different capacity profiles in cancer compared to healthy tissues, including up-regulation of folate metabolism, the down-regulation of thiamine metabolism, and tight regulation of oxidative phosphorylation.

In exercise, as well as cancer and ischemia, hypoxia-inducible factor 1 (HIF1) transcriptionally activates hundreds of genes vital for cell homeostasis and angiogenesis. While potentially beneficial in ischemia, upregulation of the HIF1 transcription factor has been linked to inflammation, poor prognosis in many cancers, and decreased susceptibility of tumors to radiotherapy and chemotherapy. Considering HIF1's function, HIF1␣ protein and its hydroxylation cofactors look increasingly attractive as therapeutic targets. Independently, antioxidants have shown promise in lowering the risk of some cancers and improving neurological and cardiac function following ischemia. The mechanism of how different antioxidants and reactive oxygen species influence HIF1␣ expression has drawn interest and intense debate. Here we present an experimentally based computational model of HIF1␣ protein degradation that represents how reactive oxygen species and antioxidants likely affect the HIF1 pathway differentially in cancer and ischemia. We use the model to demonstrate effects on HIF1␣ expression from combined doses of five potential therapeutically targeted compounds (iron, ascorbate, hydrogen peroxide, 2-oxoglutarate, and succinate) influenced by cellular oxidation-reduction and involved in HIF1␣ hydroxylation. Results justify the hypothesis that reactive oxygen species work by two opposite ways on the HIF1 system. We also show how tumor cells and cells under ischemic conditions would differentially respond to reactive oxygen species via changes to HIF1␣ expression over the course of hours to days, dependent on extracellular hydrogen peroxide levels and largely independent of initial intracellular levels, during hypoxia.The transcription factor hypoxia-inducible factor (HIF) plays a critical role in the mammalian response to oxygen (O 2 ) levels. HIF1, the first characterized member of the HIF family, transcriptionally activates hundreds of genes associated with angiogenesis in cancer, exercise, and ischemia, as well as energy metabolism, nutrient transport, cell cycle, and cell migration (85, 98).HIF1␣ and HIF1␤ make up the HIF1 heterodimer. The ␤-subunit is constitutively expressed in cells. Expression of the ␣-subunit may be induced by a number of pathways, and its degradation is highly sensitive to O 2 levels. Called a master switch for hypoxic gene expression (76, 85), intracellular HIF1␣ in normoxia is experimentally undetectable; during hypoxia, it rapidly accumulates in the cell nucleus and triggers gene expression. Molecular players involved in this process have come to light over the past 6 years; research has begun to define roles for prolyl hydroxylases, iron, ascorbate, hydrogen peroxide, 2-oxoglutarate, succinate, and von Hippel-Lindau protein in the HIF1 pathway.Concomitantly, the study of reactive oxygen species (ROS) and the interest in antioxidants as potential dietary supplements for prevention of cancer, cardiac dysfunction, and neurodegeneration has grown rapidly. Ongoing debate surrounds the role of these co...

A single extracellular stimulus can promote diverse behaviors among isogenic cells by differentially regulated signaling networks. We examined Ca2+ signaling in response to VEGF (vascular endothelial growth factor), a growth factor that can stimulate different behaviors in endothelial cells. We found that altering the amount of VEGF signaling in endothelial cells by stimulating them with different VEGF concentrations triggered distinct and mutually exclusive dynamic Ca2+ signaling responses that correlated with different cellular behaviors. These behaviors were cell proliferation involving the transcription factor NFAT (nuclear factor of activated T cells) and cell migration involving MLCK (myosin light chain kinase). Further analysis suggested that this signal decoding was robust to the noisy nature of the signal input. Using probabilistic modeling, we captured both the stochastic and deterministic aspects of Ca2+ signal decoding and accurately predicted cell responses in VEGF gradients, which we used to simulate different amounts of VEGF signaling. Ca2+ signaling patterns associated with proliferation and migration were detected during angiogenesis in developing zebrafish.

Background: Angiogenesis, the growth of capillaries from preexisting blood vessels, has been extensively studied experimentally over the past thirty years. Molecular insights from these studies have lead to therapies for cancer, macular degeneration and ischemia. In parallel, mathematical models of angiogenesis have helped characterize a broader view of capillary network formation and have suggested new directions for experimental pursuit. We developed a computational model that bridges the gap between these two perspectives, and addresses a remaining question in angiogenic sprouting: how do the processes of endothelial cell elongation, migration and proliferation contribute to vessel formation?

Hypoxia-inducible factor-1, HIF1, transcriptionally activates over 200 genes vital for cell homeostasis and angiogenesis. We developed a computational model to gain a detailed quantitative understanding of how HIF1 acts to sense oxygen and respond to hypoxia. The model consists of kinetic equations describing the intracellular variation of 17 compounds, including HIF1, iron, prolyl hydroxylase, oxygen, ascorbate, 2-oxoglutarate, von Hippel Lindau protein and associated complexes. We tested an existing hypothesis of a switch-like change in HIF1 expression in response to a gradual decrease in O2 concentration. Our model predicts that depending on the molecular environment, such as intracellular iron levels, the hypoxic response varies considerably. We show HIF1-activated cellular responses can be divided into two categories: a steep, switch-like response to O2 and a gradual one. Discovery of this dual response prompted comparison of two therapeutic strategies, ascorbate and iron supplementation, and prolyl hydroxylase targeting, to predict under what microenvironments either effectively increases HIF1α hydroxylation. Results provide crucial insight into the effects of iron and prolyl hydroxylase on oxygen sensing. The model advances quantitative molecular level understanding of HIF1 pathways - an endeavor that will help elucidate the diverse responses to hypoxia found in cancer, ischemia and exercise.

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TP53 mutations are associated with the lowest survival rates in acute myeloid leukemia (AML). In addition to mutations, loss of p53 function can arise via aberrant expression of proteins that regulate p53 stability and function. We examined a large AML cohort using proteomics, mutational profiling and network analyses, and showed that (1) p53 stabilization is universal in mutant TP53 samples, it is frequent in samples with wild-type TP53, and in both cases portends an equally dismal prognosis; (2) the p53 negative regulator Mdm2 is frequently overexpressed in samples retaining wild-type TP53 alleles, coupled with absence of p21 expression and dismal prognosis similar to that of cases with p53 stabilization; (3) AML samples display unique patterns of p53 pathway protein expression, which segregate prognostic groups with distinct cure rates; (4) such patterns of protein activation unveil potential AML vulnerabilities that can be therapeutically exploited.