An in vitro model of tumor heterogeneity resolves genetic, epigenetic, and stochastic sources of cell state variability.

Tumor heterogeneity is a primary cause of treatment failure and acquired resistance in cancer patients. Even in cancers driven by a single mutated oncogene, variability in response to targeted therapies is well known. The existence of additional genomic alterations among tumor cells can only partially explain this variability. As such, nongenetic factors are increasingly seen as critical contributors to tumor relapse and acquired resistance in cancer. Here, we show that both genetic and nongenetic factors contribute to targeted drug response variability in an experimental model of tumor heterogeneity. We observe significant variability to epidermal growth factor receptor (EGFR) inhibition among and within multiple versions and clonal sublines of PC9, a commonly used EGFR mutant nonsmall cell lung cancer (NSCLC) cell line. We resolve genetic, epigenetic, and stochastic components of this variability using a theoretical framework in which distinct genetic states give rise to multiple epigenetic "basins of attraction," across which cells can transition driven by stochastic noise. Using mutational impact analysis, single-cell differential gene expression, and correlations among Gene Ontology (GO) terms to connect genomics to transcriptomics, we establish a baseline for genetic differences driving drug response variability among PC9 cell line versions. Applying the same approach to clonal sublines, we conclude that drug response variability in all but one of the sublines is due to epigenetic differences; in the other, it is due to genetic alterations. Finally, using a clonal drug response assay together with stochastic simulations, we attribute subclonal drug response variability within sublines to stochastic cell fate decisions and confirm that one subline likely contains genetic resistance mutations that emerged in the absence of drug treatment.

Unified tumor growth mechanisms from multimodel inference and dataset integration.

Mechanistic models of biological processes can explain observed phenomena and predict responses to a perturbation. A mathematical model is typically constructed using expert knowledge and informal reasoning to generate a mechanistic explanation for a given observation. Although this approach works well for simple systems with abundant data and well-established principles, quantitative biology is often faced with a dearth of both data and knowledge about a process, thus making it challenging to identify and validate all possible mechanistic hypothesis underlying a system behavior. To overcome these limitations, we introduce a Bayesian multimodel inference (Bayes-MMI) methodology, which quantifies how mechanistic hypotheses can explain a given experimental datasets, and concurrently, how each dataset informs a given model hypothesis, thus enabling hypothesis space exploration in the context of available data. We demonstrate this approach to probe standing questions about heterogeneity, lineage plasticity, and cell-cell interactions in tumor growth mechanisms of small cell lung cancer (SCLC). We integrate three datasets that each formulated different explanations for tumor growth mechanisms in SCLC, apply Bayes-MMI and find that the data supports model predictions for tumor evolution promoted by high lineage plasticity, rather than through expanding rare stem-like populations. In addition, the models predict that in the presence of cells associated with the SCLC-N or SCLC-A2 subtypes, the transition from the SCLC-A subtype to the SCLC-Y subtype through an intermediate is decelerated. Together, these predictions provide a testable hypothesis for observed juxtaposed results in SCLC growth and a mechanistic interpretation for tumor treatment resistance.

A biochemical necroptosis model explains cell-type-specific responses to cell death cues.

Necroptosis is a form of regulated cell death associated with degenerative disorders, autoimmune and inflammatory diseases, and cancer. To better understand the biochemical mechanisms regulating necroptosis, we constructed a detailed computational model of tumor necrosis factor-induced necroptosis based on known molecular interactions from the literature. Intracellular protein levels, used as model inputs, were quantified using label-free mass spectrometry, and the model was calibrated using Bayesian parameter inference to experimental protein time course data from a well-established necroptosis-executing cell line. The calibrated model reproduced the dynamics of phosphorylated mixed lineage kinase domain-like protein, an established necroptosis reporter. A subsequent dynamical systems analysis identified four distinct modes of necroptosis signal execution, distinguished by rate constant values and the roles of the RIP1 deubiquitinating enzymes A20 and CYLD. In one case, A20 and CYLD both contribute to RIP1 deubiquitination, in another RIP1 deubiquitination is driven exclusively by CYLD, and in two modes either A20 or CYLD acts as the driver with the other enzyme, counterintuitively, inhibiting necroptosis. We also performed sensitivity analyses of initial protein concentrations and rate constants to identify potential targets for modulating necroptosis sensitivity within each mode. We conclude by associating numerous contrasting and, in some cases, counterintuitive experimental results reported in the literature with one or more of the model-predicted modes of necroptosis execution. In all, we demonstrate that a consensus pathway model of tumor necrosis factor-induced necroptosis can provide insights into unresolved controversies regarding the molecular mechanisms driving necroptosis execution in numerous cell types under different experimental conditions.

Creating a Surgical Biobank: The Hershey Medical Center Experience.

BACKGROUND: Tissue harvesting at the time of surgery offers surgeons and scientists a unique opportunity to discover and better understand disease pathophysiology. Tissue biobanking presents challenges in patient consents, specimen collection, preparation, and storage, but the potential for scientific discovery justifies the effort. Although the number of tissue biobanks is increasing worldwide, information regarding necessary infrastructure, process flow, and management of expected obstacles is lacking. OBJECTIVE: To provide a framework and motivation for clinician scientists intending to start an intestinal tissue biobank under their direction. DATA SOURCES: The Carlino Family Inflammatory Bowel and Colorectal Diseases Biobank is housed at the Milton S. Hershey Medical Center. STUDY SELECTION: Review. INTERVENTION: Implementation of a surgical tissue biobank at a large tertiary care institution. MAIN OUTCOME MEASURES: Assess critical challenges and obstacles over the years as well as keys to the success of the program. RESULTS: Over 2 decades, the institutional biobank grew from an IBD biobank to one which now incorporates thousands of surgical specimens representing numerous colorectal diseases. This was done through a process of refinement focusing on patient recruitment and an efficient consenting and specimen management process. The biobank's success is further insured by institutional, external, and philanthropic support; scientific collaborations; and sharing of biological specimens with other groups of dedicated researchers. LIMITATIONS: This is a single-center experience in collecting surgically resected colorectal specimens. CONCLUSIONS: Surgical specimen biobanks are essential in studying disease cause using genomics, transcriptomics, and proteomic technologies. Therefore, surgeons, clinicians, and scientists should build biobanks at their institutions to promote further scientific discovery and improve specimen diversity.

Thunor: visualization and analysis of high-throughput dose-response datasets.

High-throughput cell proliferation assays to quantify drug-response are becoming increasingly common and powerful with the emergence of improved automation and multi-time point analysis methods. However, pipelines for analysis of these datasets that provide reproducible, efficient, and interactive visualization and interpretation are sorely lacking. To address this need, we introduce Thunor, an open-source software platform to manage, analyze, and visualize large, dose-dependent cell proliferation datasets. Thunor supports both end-point and time-based proliferation assays as input. It provides a simple, user-friendly interface with interactive plots and publication-quality images of cell proliferation time courses, dose-response curves, and derived dose-response metrics, e.g. IC50, including across datasets or grouped by tags. Tags are categorical labels for cell lines and drugs, used for aggregation, visualization and statistical analysis, e.g. cell line mutation or drug class/target pathway. A graphical plate map tool is included to facilitate plate annotation with cell lines, drugs and concentrations upon data upload. Datasets can be shared with other users via point-and-click access control. We demonstrate the utility of Thunor to examine and gain insight from two large drug response datasets: a large, publicly available cell viability database and an in-house, high-throughput proliferation rate dataset. Thunor is available from www.thunor.net.

Unsupervised logic-based mechanism inference for network-driven biological processes.

Modern analytical techniques enable researchers to collect data about cellular states, before and after perturbations. These states can be characterized using analytical techniques, but the inference of regulatory interactions that explain and predict changes in these states remains a challenge. Here we present a generalizable, unsupervised approach to generate parameter-free, logic-based models of cellular processes, described by multiple discrete states. Our algorithm employs a Hamming-distance based approach to formulate, test, and identify optimized logic rules that link two states. Our approach comprises two steps. First, a model with no prior knowledge except for the mapping between initial and attractor states is built. We then employ biological constraints to improve model fidelity. Our algorithm automatically recovers the relevant dynamics for the explored models and recapitulates key aspects of the biochemical species concentration dynamics in the original model. We present the advantages and limitations of our work and discuss how our approach could be used to infer logic-based mechanisms of signaling, gene-regulatory, or other input-output processes describable by the Boolean formalism.

Clinical and Genetic Factors Impact Time to Surgical Recurrence After Ileocolectomy for Crohn's Disease.

OBJECTIVE: The aim of this study was to evaluate factors associated with time to surgical recurrence after Crohn's ileocolectomy. SUMMARY BACKGROUND DATA: The most common surgery performed for Crohn's disease is ileocolectomy. Identifying patients at high risk for surgical recurrence may assist with medical and surgical decision-making. METHODS: Data were obtained from 409 patients with Crohn's disease (CD) who had undergone ≥1 ileocolectomies at Penn State Hershey Medical Center. Six single-nucleotide polymorphisms (SNPs) associated with CD were evaluated in these patients: rs2076756, rs2066844, and rs2066845 in NOD2, rs4958847 and rs13361189 in IRGM, and rs2241880 in ATG16L1. Genotype and clinical factors were analyzed to determine associations with time to recurrent ileocolectomy. A subgroup analysis was performed on 241 patients naïve to biologics before initial ileocolectomy to assess the effect of biologic therapy on time to recurrent surgery. RESULTS: There were 286 patients who underwent a single ileocolectomy, whereas 123 required multiple ileocolectomies. Ileocolonic involvement [hazard ratio (HR) 1.90, 95% confidence interval (CI) 1.21-3.00, P = 0.006] and rs2066844 in NOD2 (HR 1.8, 95% CI 1.17-2.77, P = 0.007) were associated with decreased time to surgical recurrence by multivariate analysis. In patients naïve to preoperative biologics, the initiation of postoperative biologics was associated with a 40% decreased incidence of surgical recurrence (HR 0.60, CI 0.39-0.93, P = 0.02) over time. CONCLUSIONS: Ileocolonic distribution of disease and the rs2066844 SNP in NOD2 are associated with shorter time to recurrent ileocolectomy. The initiation of postoperative biologics in naïve patients was associated with a reduced incidence of recurrence over time.

COLQ and ARHGAP15 are Associated with Diverticular Disease and are Expressed in the Colon.

BACKGROUND: Diverticular disease is a common but poorly understood disease of the gastrointestinal tract. Recent studies have identified several single nucleotide polymorphisms (SNPs) that are associated with diverticular disease. MATERIALS AND METHODS: The genotypes of three SNPs (rs4662344 in ARHGAP15, rs7609897 in COLQ, and rs67153654 in FAM155A) were identified by Taqman assay in 204 patients with diverticular disease. Clinical characteristics were obtained from the medical record to study association with genotype. To evaluate gene expression in colon tissue, qPCR was performed on 24 patients with diverticulitis, and COLQ was localized using immunohistochemistry. RESULTS: The ARHGAP15 and COLQ SNPs were significantly associated with both diverticular disease and specifically diverticulitis, while the FAM155A was not associated with either. No association was found with clinical disease characteristics. Heterozygous genotypes at the ARHGAP15 SNP was associated with lower ARHGAP15 expression in colon tissues. COLQ protein localized to the myenteric plexus in the colon. CONCLUSIONS: This study confirmed association of the ARHGAP15 and COLQ SNPs with diverticular disease in our patients but could not confirm FAM155A SNP association. Neither of these SNPs appeared to associate with more severe disease, but genotype at the ARHGAP15 SNP did impact expression of ARHGAP15 in the colon. Additionally, this study is the first to localize COLQ in the colon. Its presence in the myenteric nervous system suggests COLQ SNP variants may contribute to diverticular disease by altering motility.

Transcriptomic analysis of ileal tissue from Crohn's disease patients identifies extracellular matrix genes that distinguish individuals by age at diagnosis.

Crohn's disease (CD) is a debilitating gastrointestinal (GI) disorder that can impact the entirety of the GI tract. While substantial progress has been made in the medical management of CD, it remains incurable, frequently relapses, and is a significant financial and medical burden. The pathophysiology of CD is not well understood, but it is thought to arise in genetically susceptible individuals upon an environmental insult. Further elucidation of the disease etiology promises to expose additional therapeutic avenues, with the hope of reducing the burden of CD. One approach to understanding disease pathophysiology is to identify clinically relevant molecular disease subsets by using transcriptomics. In this report, we use hierarchical clustering of the ileal transcriptomes of 34 patients and identify two CD subsets. Clinically, these clusters differed in the age of the patients at CD diagnosis, suggesting that age of onset affects disease pathophysiology. The clusters were segregated by three major gene ontology categories: developmental processes, ion homeostasis, and the immune response. Of the genes constituting the immune system category, expression of extracellular matrix-associated genes, COL4A1, S100A9, ADAMTS2, SERPINE1, and FCN1, exhibits the strongest correlation with an individual's age at CD diagnosis. Together these findings demonstrate that transcriptional profiling is a powerful approach to subclassify CD patients.

Novel Therapies for Relapsed or Refractory Diffuse Large B-Cell Lymphoma.

The most common type of non-Hodgkin lymphoma in adults is diffuse large B-cell (DLBCL). There is a historical unmet need for more effective therapies in the 2nd and 3rd line setting. Emerging immunochemotherapies have shown activity in small studies of heavily pre-treated patients with prolonged remissions achieved in some patients. Anti-CD19 CAR (chimeric antigen receptor) T cells are potentially curative in the 3rd line and beyond setting and are under investigation in earlier lines of therapy. Antibody-drug conjugates (ADC's) such as polatuzumab vedotin targeting the pan-B-cell marker CD79b has proven effectiveness in multiply-relapsed DLBCL patients. Tafasitamab (MOR208) is an anti-CD19 monoclonal antibody producing prolonged remissions when combined with Lenalidomide (LEN) in patients who were not candidates for salvage chemotherapy or autologous stem cell transplant. Selinexor, an oral, small-molecule selective inhibitor of XPO1-mediated nuclear export (SINE), demonstrated prolonged activity against heavily-pretreated DLBCL without cumulative toxicity and is being investigated as part of an oral, chemotherapy-free regimen for relapsed aggressive lymphoma. This article reviews current strategies and novel therapies for relapsed/refractory DLBCL.

Identification of a rare LAMB4 variant associated with familial diverticulitis through exome sequencing.

Diverticulitis is a chronic disease of the colon in which diverticuli, or outpouching through the colonic wall, become inflamed. Although recent observations suggest that genetic factors may play a significant role in diverticulitis, few genes have yet been implicated in disease pathogenesis and familial cases are uncommon. Here, we report results of whole exome sequencing performed on members from a single multi-generational family with early onset diverticulitis in order to identify a genetic component of the disease. We identified a rare single nucleotide variant in the laminin ß 4 gene (LAMB4) that segregated with disease in a dominant pattern and causes a damaging missense substitution (D435N). Targeted sequencing of LAMB4 in 148 non-familial and unrelated sporadic diverticulitis patients identified two additional rare variants in the gene. Immunohistochemistry indicated that LAMB4 localizes to the myenteric plexus of colonic tissue and patients harboring LAMB4 variants exhibited reduced LAMB4 protein levels relative to controls. Laminins are constituents of the extracellular matrix and play a major role in regulating the development and function of the enteric nervous system. Reduced LAMB4 levels may therefore alter innervation and morphology of the enteric nervous system, which may contribute to colonic dysmotility associated with diverticulitis.

An unbiased metric of antiproliferative drug effect in vitro.

In vitro cell proliferation assays are widely used in pharmacology, molecular biology, and drug discovery. Using theoretical modeling and experimentation, we show that current metrics of antiproliferative small molecule effect suffer from time-dependent bias, leading to inaccurate assessments of parameters such as drug potency and efficacy. We propose the drug-induced proliferation (DIP) rate, the slope of the line on a plot of cell population doublings versus time, as an alternative, time-independent metric.

Multifocal Versus Conventional Unifocal Diverticulitis: A Comparison of Clinical and Transcriptomic Characteristics.

BACKGROUND: The management of diverticulitis is compromised by difficulty in identifying patients who require surgery for recurrent or persistent disease. Here, we introduce the concept of multifocal diverticulitis (MFD), characterized by multiple episodes of diverticulitis occurring at different locations within the colon. AIMS: To compare clinical characteristics, success of surgical management, and colonic transcriptomes of MFD patients to patients with conventional unifocal diverticulitis (UFD). METHODS: This retrospective study included 404 patients with CT-confirmed diverticulitis episodes. Patients with diverticulitis seen in at least two different colonic locations were classified as the MFD group and compared to the UFD group based on number of episodes, sites of disease, family history, surgeries performed, and postoperative recurrence. RNA-seq was conducted on full-thickness colonic tissues of ten MFD and 11 UFD patients. RESULTS: Twenty-eight patients (6.9%) with MFD were identified. MFD patients had more diverticulitis episodes and were more likely to have positive family history, have right-sided disease, require surgery, and have recurrence after surgery. All MFD patients treated with segmental resection had recurrence, while recurrence was less common in patients undergoing more extensive surgery (P < 0.001). Using RNA-seq, we identified 69 genes that were differentially expressed between MFD and UFD patients. Significantly down-regulated genes were associated with immune response pathways. CONCLUSIONS: MFD appears to be a more severe subset of diverticulitis with a possible genetic component. Transcriptomic data suggest that MFD may be associated with alteration of the immune response.

A Nonquiescent "Idling" Population State in Drug-Treated, BRAF-Mutated Melanoma.

Targeted therapy is an effective standard of care in BRAF-mutated malignant melanoma. However, the duration of tumor remission varies unpredictably among patients, and relapse is almost inevitable. Here, we examine the responses of several BRAF-mutated melanoma cell lines (including isogenic subclones) to BRAF inhibitors. We observe complex response dynamics across cell lines, with short-term responses (<100 h) varying from cell line to cell line. In the long term, however, we observe equilibration of all drug-treated populations into a nonquiescent state characterized by a balanced rate of death and division, which we term the "idling" state, and to our knowledge, this state has not been previously reported. Using mathematical modeling, we propose that the observed population-level dynamics are the result of cells transitioning between basins of attraction within a drug-modified phenotypic landscape. Each basin is associated with a drug-induced proliferation rate, a recently introduced metric of an antiproliferative drug effect. The idling population state represents a new dynamic equilibrium in which cells are distributed across the landscape such that the population achieves zero net growth. By fitting our model to experimental drug-response data, we infer the phenotypic landscapes of all considered melanoma cell lines and provide a unifying view of how BRAF-mutated melanomas respond to BRAF inhibition. We hypothesize that the residual disease observed in patients after targeted therapy is composed of a significant number of idling cells. Thus, defining molecular determinants of the phenotypic landscape that idling populations occupy may lead to "targeted landscaping" therapies based on rational modification of the landscape to favor basins with greater drug susceptibility.

GPU-powered model analysis with PySB/cupSODA.

SUMMARY: A major barrier to the practical utilization of large, complex models of biochemical systems is the lack of open-source computational tools to evaluate model behaviors over high-dimensional parameter spaces. This is due to the high computational expense of performing thousands to millions of model simulations required for statistical analysis. To address this need, we have implemented a user-friendly interface between cupSODA, a GPU-powered kinetic simulator, and PySB, a Python-based modeling and simulation framework. For three example models of varying size, we show that for large numbers of simulations PySB/cupSODA achieves order-of-magnitude speedups relative to a CPU-based ordinary differential equation integrator. AVAILABILITY AND IMPLEMENTATION: The PySB/cupSODA interface has been integrated into the PySB modeling framework (version 1.4.0), which can be installed from the Python Package Index (PyPI) using a Python package manager such as pip. cupSODA source code and precompiled binaries (Linux, Mac OS/X, Windows) are available at github.com/aresio/cupSODA (requires an Nvidia GPU; developer.nvidia.com/cuda-gpus). Additional information about PySB is available at pysb.org. CONTACT: paolo.cazzaniga@unibg.it or c.lopez@vanderbilt.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Activated Oncogenic Pathway Modifies Iron Network in Breast Epithelial Cells: A Dynamic Modeling Perspective.

Dysregulation of iron metabolism in cancer is well documented and it has been suggested that there is interdependence between excess iron and increased cancer incidence and progression. In an effort to better understand the linkages between iron metabolism and breast cancer, a predictive mathematical model of an expanded iron homeostasis pathway was constructed that includes species involved in iron utilization, oxidative stress response and oncogenic pathways. The model leads to three predictions. The first is that overexpression of iron regulatory protein 2 (IRP2) recapitulates many aspects of the alterations in free iron and iron-related proteins in cancer cells without affecting the oxidative stress response or the oncogenic pathways included in the model. This prediction was validated by experimentation. The second prediction is that iron-related proteins are dramatically affected by mitochondrial ferritin overexpression. This prediction was validated by results in the pertinent literature not used for model construction. The third prediction is that oncogenic Ras pathways contribute to altered iron homeostasis in cancer cells. This prediction was validated by a combination of simulation experiments of Ras overexpression and catalase knockout in conjunction with the literature. The model successfully captures key aspects of iron metabolism in breast cancer cells and provides a framework upon which more detailed models can be built.

RNA-seq implicates deregulation of the immune system in the pathogenesis of diverticulitis.

Individuals with diverticula or outpouchings of the colonic mucosa and submucosa through the colonic wall have diverticulosis, which is usually asymptomatic. In 10-25% of individuals, the diverticula become inflamed, resulting in diverticulitis. Very little is known about the pathophysiology or gene regulatory pathways involved in the development of diverticulitis. To identify these pathways, we deep sequenced RNAs isolated from full-thickness sections of sigmoid colon from diverticulitis patients and control individuals. Specifically for diverticulitis cases, we analyzed tissue adjacent to areas affected by chronic disease. Since the tissue was collected during elective sigmoid resection, the disease was in a quiescent state. A comparison of differentially expressed genes found that gene ontology (GO) pathways associated with the immune response were upregulated in diverticulitis patients compared with nondiverticulosis controls. Next, weighted gene coexpression network analysis was performed to identify the interaction among coexpressed genes. This analysis revealed RASAL3, SASH3, PTPRC, and INPP5D as hub genes within the brown module eigengene, which highly correlated (r = 0.67, P = 0.0004) with diverticulitis. Additionally, we identified elevated expression of downstream interacting genes. In summary, transcripts associated with the immune response were upregulated in adjacent tissue from the sigmoid colons of chronic, recurrent diverticulitis patients. Further elucidating the genetic or epigenetic mechanisms associated with these alterations can help identify those at risk for chronic disease and may assist in clinical decision management.NEW & NOTEWORTHY By using an unbiased approach to analyze transcripts expressed in unaffected colonic tissues adjacent to those affected by chronic diverticulitis, our study implicates that a defect in the immune response may be involved in the development of the disease. This finding expands on the current data that suggest the pathophysiology of diverticulitis is mediated by dietary, age, and obesity-related factors. Further characterizing the immunologic differences in diverticulitis may better inform clinical decision-making.

BioNetGen 2.2: advances in rule-based modeling.

: BioNetGen is an open-source software package for rule-based modeling of complex biochemical systems. Version 2.2 of the software introduces numerous new features for both model specification and simulation. Here, we report on these additions, discussing how they facilitate the construction, simulation and analysis of larger and more complex models than previously possible. AVAILABILITY AND IMPLEMENTATION: Stable BioNetGen releases (Linux, Mac OS/X and Windows), with documentation, are available at http://bionetgen.org Source code is available at http://github.com/RuleWorld/bionetgen CONTACT: bionetgen.help@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online.

Diverticulitis and Crohn's disease have distinct but overlapping tumor necrosis superfamily 15 haplotypes.

BACKGROUND: Diverticulitis (DD) and Crohn's disease (CD) have overlapping features including bowel structuring, inflammation, and infection. Tumor necrosis superfamily 15 (TNFSF15) is an immunoregulatory, anti-angiogenic gene. CD has been previously associated with a haplotype of five TNFSF15 single-nucleotide polymorphism alleles: rs3810936 (G allele), rs6478108 (A), rs6478109 (G), rs7848647 (G), and rs7869487 (A). We aimed to determine the TNFSF15 risk haplotype for DD versus controls with a subgroup analysis of youthful DD patients (aged ≤55 y) versus older controls (aged ≥55 y). METHODS: A total of 148 diverticulitis patients (90 aged ≤55 y) and 200 controls (87 aged ≥55 y) were genotyped using our custom-designed Illumina Veracode microarray chip. Genotypes from rs3810936, rs6478108, rs6478109, rs7848647, rs7869487 and two additional TNFSF15 single nucleotide polymorphisms, rs3810936 and rs11554257, were analyzed. PHASE version 2.1, R with HaploStats and the Broad Institute's Haploview program were used for statistics and imputed haplotype frequency. Permutation corrected for multiple comparisons. RESULTS: The CD GAGGA haplotype was significantly associated with diverticulitis (P = 0.03) in the all DD versus all controls comparison. A second haplotype, rs6478108 (A), rs6478109 (G), rs7869487 (A), and rs4263839 (G), was also associated with DD in this cohort (P = 0.025). A third haplotype rs6478108 (A), rs6478109 (G), rs7848647 (G) and rs7869487 (A), rs4263839 (G) was demonstrated in the DD < 55 versus controls >55 comparison (P = 0.045). CONCLUSIONS: Distinct but overlapping TNFSF15 haplotypes were demonstrated in diverticulitis patients versus healthy controls when compared with the known Crohn's risk haplotype suggesting similar but distinct genetic predispositions. This study strengthens the role for a genetic predisposition to diverticulitis that involves the TNFSF15 gene.

Modeling for (physical) biologists: an introduction to the rule-based approach.

Models that capture the chemical kinetics of cellular regulatory networks can be specified in terms of rules for biomolecular interactions. A rule defines a generalized reaction, meaning a reaction that permits multiple reactants, each capable of participating in a characteristic transformation and each possessing certain, specified properties, which may be local, such as the state of a particular site or domain of a protein. In other words, a rule defines a transformation and the properties that reactants must possess to participate in the transformation. A rule also provides a rate law. A rule-based approach to modeling enables consideration of mechanistic details at the level of functional sites of biomolecules and provides a facile and visual means for constructing computational models, which can be analyzed to study how system-level behaviors emerge from component interactions.