Computational translation of genomic responses from experimental model systems to humans

The high failure rate of therapeutics showing promise in mouse models to translate to patients is a pressing challenge in biomedical science. Though retrospective studies have examined the fidelity of mouse models to their respective human conditions, approaches for prospective translation of insights from mouse models to patients remain relatively unexplored. Here, we develop a semi-supervised learning approach for inference of disease-associated human differentially expressed genes and pathways from mouse model experiments. We examined 36 transcriptomic case studies where comparable phenotypes were available for mouse and human inflammatory diseases and assessed multiple computational approaches for inferring human biology from mouse datasets. We found that semi-supervised training of a neural network identified significantly more true human biological associations than interpreting mouse experiments directly. Evaluating the experimental design of mouse experiments where our model was most successful revealed principles of experimental design that may improve translational performance. Our study shows that when prospectively evaluating biological associations in mouse studies, semi-supervised learning approaches, combining mouse and human data for biological inference, provide the most accurate assessment of human in vivo disease processes. Finally, we proffer a delineation of four categories of model system-to-human "Translation Problems" defined by the resolution and coverage of the datasets available for molecular insight translation and suggest that the task of translating insights from model systems to human disease contexts may be better accomplished by a combination of translation-minded experimental design and computational approaches.Boehringer Ingelheim PharmaceuticalsInstitute for Collaborative Biotechnologies (Grant W911NF-09-0001

Network analysis of differential Ras isoform mutation effects on intestinal epithelial responses to TNF-α

Tumor necrosis factor alpha (TNF-α) is an inflammatory cytokine that can elicit distinct cellular behaviors under different molecular contexts. Mitogen activated protein kinase (MAPK) pathways, especially the extracellular signal-regulated kinase (Erk) pathway, help to integrate influences from the environmental context, and therefore modulate the phenotypic effect of TNF-α exposure. To test how variations in flux through the Erk pathway modulate TNF-α-elicited phenotypes in a complex physiological environment, we exposed mice with different Ras mutations (K-Ras activation, N-Ras activation, and N-Ras ablation) to TNF-α and observed phenotypic and signaling changes in the intestinal epithelium. Hyperactivation of Mek1, an Erk kinase, was observed in the intestine of mice with K-Ras activation and, surprisingly, in N-Ras null mice. Nevertheless, these similar Mek1 outputs did not give rise to the same phenotype, as N-Ras null intestine was hypersensitive to TNF-α-induced intestinal cell death while K-Ras mutant intestine was not. A systems biology approach applied to sample the network state revealed that the signaling contexts presented by these two Ras isoform mutations were different. Consistent with our experimental data, N-Ras ablation induced a signaling network state that was mathematically predicted to be pro-death, while K-Ras activation did not. Further modeling by constrained Fuzzy Logic (cFL) revealed that N-Ras and K-Ras activate the signaling network with different downstream distributions and dynamics, with N-Ras effects being more transient and diverted more towards PI3K-Akt signaling and K-Ras effects being more sustained and broadly activating many pathways. Our study highlights the necessity to consider both environmental and genomic contexts of signaling pathway activation in dictating phenotypic responses, and demonstrates how modeling can provide insight into complex in vivo biological mechanisms, such as the complex interplay between K-Ras and N-Ras in their downstream effects.National Institute of General Medical Sciences (U.S.) (Grant R01-GM088827)National Cancer Institute (U.S.) (U54-CA112967)United States. Army Research Office (Institute for Collaborative Biotechnologies Grant W911NF-09-D-000

In Vivo Systems Analysis Identifies Spatial and Temporal Aspects of the Modulation of TNF-α-Induced Apoptosis and Proliferation by MAPKs

Cellular responses to external stimuli depend on dynamic features of multipathway network signaling; thus, cell behavior is influenced in a complex manner by the environment and by intrinsic properties. Methods of multivariate systems analysis have provided an understanding of these convoluted effects, but only for relatively simplified examples in vitro. To determine whether such approaches could be successfully used in vivo, we analyzed the signaling network that determines the response of intestinal epithelial cells to tumor necrosis factor–α (TNF-α). We built data-driven, partial least-squares discriminant analysis (PLSDA) models based on signaling, apoptotic, and proliferative responses in the mouse small intestinal epithelium after systemic exposure to TNF-α. The extracellular signal–regulated kinase (ERK) signaling axis was a critical modulator of the temporal variation in apoptosis at different doses of TNF-α and of the spatial variation in proliferation in distinct intestinal regions. Inhibition of MEK, a mitogen-activated protein kinase kinase upstream of ERK, altered the signaling network and changed the temporal and spatial phenotypes consistent with model predictions. Our results demonstrate the dynamic, adaptive nature of in vivo signaling networks and identify natural, tissue-level variation in responses that can be deconvoluted only with quantitative, multivariate computational modeling. This study lays a foundation for the use of systems-based approaches to understand how dysregulation of the cellular network state underlies complex diseases.National Institute of General Medical Sciences (U.S.) (Grant R01-GM088827)National Cancer Institute (U.S.) (Grant U54-CA112967

Multi-Scale In Vivo Systems Analysis Reveals the Influence of Immune Cells on TNF-α-Induced Apoptosis in the Intestinal Epithelium

Intestinal epithelial cells exist within a complex environment that affects how they interpret and respond to stimuli. We have applied a multi-scale in vivo systems approach to understand how intestinal immune cells communicate with epithelial cells to regulate responses to inflammatory signals. Multivariate modeling analysis of a large dataset composed of phospho-signals, cytokines, and immune cell populations within the intestine revealed an intimate relationship between immune cells and the epithelial response to TNF-α. Ablation of lymphocytes in the intestine prompted a decrease in the expression of MCP-1, which in turn increased the steady state number of intestinal plasmacytoid dendritic cells (pDCs). This change in the immune compartment affected the intestinal cytokine milieu and subsequent epithelial cell signaling network, with cells becoming hypersensitive to TNF-α-induced apoptosis in a way that could be predicted by mathematical modeling. In summary, we have uncovered a novel cellular network that regulates the response of intestinal epithelial cells to inflammatory stimuli in an in vivo setting

Microfluidic Chemotaxis Platform for Differentiating the Roles of Soluble and Bound Amyloid-β on Microglial Accumulation

Progressive microglial accumulation at amyloid-β (Aβ) plaques is a well-established signature of the pathology of Alzheimer's disease, but how and why microglia accumulate in the vicinity of Aβ plaques is unknown. To understand the distinct roles of Aβ on microglial accumulation, we quantified microglial responses to week-long lasting gradients of soluble Aβ and patterns of surface-bound Aβ in microfluidic chemotaxis platforms. We found that human microglia chemotaxis in gradients of soluble Aβ42 was most effective at two distinct concentrations of 23 pg.mL−1 and 23 ng.mL−1 Aβ42 in monomers and oligomers. We uncovered that while the chemotaxis at higher Aβ concentrations was exclusively due to Aβ gradients, chemotaxis at lower concentrations was enhanced by Aβ-induced microglial production of MCP-1. Microglial migration was inhibited by surface-bound Aβ42 in oligomers and fibrils above 45 pg.mm−2. Better understanding of microglial migration can provide insights into the pathophysiology of senile plaques in AD

Dominant Role of Oncogene Dosage and Absence of Tumor Suppressor Activity in Nras-Driven Hematopoietic Transformation

Biochemical properties of Ras oncoproteins and their transforming ability strongly support a dominant mechanism of action in tumorigenesis. However, genetic studies unexpectedly suggested that wild-type (WT) Ras exerts tumor suppressor activity. Expressing oncogenic Nras[superscript G12D] in the hematopoietic compartment of mice induces an aggressive myeloproliferative neoplasm that is exacerbated in homozygous mutant animals. Here, we show that increased Nras[superscript G12D] gene dosage, but not inactivation of WT Nras, underlies the aggressive in vivo behavior of Nras[superscript G12D over G12D] hematopoietic cells. Modulating Nras[superscript G12D] dosage had discrete effects on myeloid progenitor growth, signal transduction, and sensitivity to MAP-ERK kinase (MEK) inhibition. Furthermore, enforced WT N-Ras expression neither suppressed the growth of Nras-mutant cells nor inhibited myeloid transformation by exogenous Nras[superscript G12D]. Importantly, NRAS expression increased in human cancer cell lines with NRAS mutations. These data have therapeutic implications and support reconsidering the proposed tumor suppressor activity of WT Ras in other cancers.Pfizer Inc. (PD0325901)National Institutes of Health (U.S.) (Grant R37CA72614)National Institutes of Health (U.S.) (Grant P01CA40046)National Institutes of Health (U.S.) (Grant K08CA134649)Leukemia & Lymphoma Society of America (Specialized Center of Research Award LLS 7019-04))American Lebanese Syrian Associated Charitie

Analyses of clinicopathological, molecular, and prognostic associations of KRAS codon 61 and codon 146 mutations in colorectal cancer: cohort study and literature review

Background: KRAS mutations in codons 12 and 13 are established predictive biomarkers for anti-EGFR therapy in colorectal cancer. Previous studies suggest that KRAS codon 61 and 146 mutations may also predict resistance to anti-EGFR therapy in colorectal cancer. However, clinicopathological, molecular, and prognostic features of colorectal carcinoma with KRAS codon 61 or 146 mutation remain unclear. Methods: We utilized a molecular pathological epidemiology database of 1267 colon and rectal cancers in the Nurse’s Health Study and the Health Professionals Follow-up Study. We examined KRAS mutations in codons 12, 13, 61 and 146 (assessed by pyrosequencing), in relation to clinicopathological features, and tumor molecular markers, including BRAF and PIK3CA mutations, CpG island methylator phenotype (CIMP), LINE-1 methylation, and microsatellite instability (MSI). Survival analyses were performed in 1067 BRAF-wild-type cancers to avoid confounding by BRAF mutation. Cox proportional hazards models were used to compute mortality hazard ratio, adjusting for potential confounders, including disease stage, PIK3CA mutation, CIMP, LINE-1 hypomethylation, and MSI. Results: KRAS codon 61 mutations were detected in 19 cases (1.5%), and codon 146 mutations in 40 cases (3.2%). Overall KRAS mutation prevalence in colorectal cancers was 40% (=505/1267). Of interest, compared to KRAS-wild-type, overall, KRAS-mutated cancers more frequently exhibited cecal location (24% vs. 12% in KRAS-wild-type; P < 0.0001), CIMP-low (49% vs. 32% in KRAS-wild-type; P < 0.0001), and PIK3CA mutations (24% vs. 11% in KRAS-wild-type; P < 0.0001). These trends were evident irrespective of mutated codon, though statistical power was limited for codon 61 mutants. Neither KRAS codon 61 nor codon 146 mutation was significantly associated with clinical outcome or prognosis in univariate or multivariate analysis [colorectal cancer-specific mortality hazard ratio (HR) = 0.81, 95% confidence interval (CI) = 0.29-2.26 for codon 61 mutation; colorectal cancer-specific mortality HR = 0.86, 95% CI = 0.42-1.78 for codon 146 mutation]. Conclusions: Tumors with KRAS mutations in codons 61 and 146 account for an appreciable proportion (approximately 5%) of colorectal cancers, and their clinicopathological and molecular features appear generally similar to KRAS codon 12 or 13 mutated cancers. To further assess clinical utility of KRAS codon 61 and 146 testing, large-scale trials are warranted

Molecular network analysis of phosphotyrosine and lipid metabolism in hepatic PTP1b deletion mice

Metabolic syndrome describes a set of obesity-related disorders that increase diabetes, cardiovascular, and mortality risk. Studies of liver-specific protein-tyrosine phosphatase 1b (PTP1b) deletion mice (L-PTP1b[superscript −/−]) suggest that hepatic PTP1b inhibition would mitigate metabolic-syndrome through amelioration of hepatic insulin resistance, endoplasmic-reticulum stress, and whole-body lipid metabolism. However, the altered molecular-network states underlying these phenotypes are poorly understood. We used mass spectrometry to quantify protein-phosphotyrosine network changes in L-PTP1b[superscript −/−] mouse livers relative to control mice on normal and high-fat diets. We applied a phosphosite-set-enrichment analysis to identify known and novel pathways exhibiting PTP1b- and diet-dependent phosphotyrosine regulation. Detection of a PTP1b-dependent, but functionally uncharacterized, set of phosphosites on lipid-metabolic proteins motivated global lipidomic analyses that revealed altered polyunsaturated-fatty-acid (PUFA) and triglyceride metabolism in L-PTP1b[superscript −/−] mice. To connect phosphosites and lipid measurements in a unified model, we developed a multivariate-regression framework, which accounts for measurement noise and systematically missing proteomics data. This analysis resulted in quantitative models that predict roles for phosphoproteins involved in oxidation–reduction in altered PUFA and triglyceride metabolism.Pfizer Inc. (grant)National Institutes of Health (U.S.) (grant 5R24DK090963)National Institutes of Health (U.S.) (grant U54-CA112967)National Institutes of Health (U.S.) (grant CA49152 R37)National Institutes of Health (U.S.) (grant R01-DK080756)National Mouse Metabolic Phenotyping Center at UMASS (Grant (U24-DK093000))National Science Foundation (U.S.) (Graduate Research Fellowship

K-Ras4A splice variant is widely expressed in cancer and uses a hybrid membrane-targeting motif

The KRAS oncogene is mutated more frequently in human cancer than any other. The KRAS transcript is alternatively spliced to give rise to two products, K-Ras4A and K-Ras4B, both of which are oncogenic when KRAS is mutated. We detected significant amounts of each transcript in human tumor cells and colorectal carcinomas. We found that K-Ras4A is targeted to the plasma membrane by dual targeting motifs distinct from those of K-Ras4B. Because interfering with membrane association of Ras proteins remains one of the most attractive approaches to anti-Ras therapy, efforts in this direction will have to disrupt both the K-Ras4A and the K-Ras4B membrane-targeting pathways