Analysis and verification of the HMGB1 signaling pathway

Adiponectin Ameliorates Hyperglycemia-Induced Retinal Endothelial Dysfunction, Highlighting Pathways, Regulators, and Networks

Background

The pathophysiology of diabetic retinopathy (DR) is multifaced. A low level of circulating adiponectin (APN) in type 2 diabetes is associated with microvasculature complications, and its role in the evolution of DR is complex.

Aim

This study is designed to explore the potential impact of APN in the pathogenesis of DR, linking the changes in cellular and biological processes with the pathways, networks, and regulators involved in its actions.

Methods

Human microvascular retinal endothelial cells (HMRECs) were exposed to 30mM glucose (HG) and treated with globular adiponectin (30μg/mL) for 24 hours. The cells were evaluated for reactive oxidative stress (ROS) and apoptosis. RT-PCR profile arrays were utilized to evaluate the profile of genes involved in endothelial functions, angiogenesis, extracellular matrix, and adhesion molecules for hyperglycemic HMRECs treated with adiponectin. In addition, the barrier function, leukocyte migration, and angiogenesis were evaluated. The differential expressed genes (DEGs) were outlined, and bioinformatic analysis was applied.

Results

Adiponectin suppresses ROS production and apoptosis in HMRECs under HG conditions. Adiponectin improved migration and barrier functions in hyperglycemic cells. The bioinformatic analysis highlighted that the signaling pathways of integrin, HMGB1, and p38 AMPK, are mainly involved in the actions of APN on HMRECs. APN significantly affects molecular functions, including the adhesion of cells, chemotaxis, migration of WBCs, and angiogenesis. STAT3, NFKB, IKBKB, and mir-8 are the top upstream regulators, which affect the expressions of the genes of the data set, while TNF and TGFB1 are the top regulators.

Conclusion

Adiponectin significantly counteracts hyperglycemia at various cellular and molecular levels, reducing its impact on the pathophysiological progression towards DR in vitro using HMRECs. Adiponectin ameliorates inflammatory response, oxidative stress, and endothelial barrier dysfunction using a causal network of NFBk complex, TNF, and HMGB1 and integrin pathways.

Role of high-mobility group box 1 in cancer

High-mobility group box 1 (HMGB1) is a non-histone nuclear protein in most eukaryocytes. Inside the nucleus, HMGB1 plays an important role in several DNA events such as DNA repair, transcription, telomere maintenance, and genome stability. While outside the nucleus, it fulfils more complicated functions, including promoting cell proliferation, inflammation, angiogenesis, immune tolerance and immune escape, which may play a pro-tumoral role.Meanwhile, HMGB1 acts as an anti-tumoral protein by regulating immune cell recruitment and inducing immunogenic cell death (ICD) during the carcinogenesis process. Therefore, abnormal expression of HMGB1 is associated with oncogenesis, development, and metastasis of cancer, which may play a dual role of pro-tumor and anti-tumor.

Fueling the Fire: Inflammatory Forms of Cell Death and Implications for Cancer Immunotherapy

Unleashing the immune system with immune checkpoint inhibitors (ICI) has significantly improved overall survival for subsets of patients with stage III/IV cancer. However, many tumors are nonresponsive to ICIs, in part due to a lack of tumor-infiltrating lymphocytes (TIL). Converting these immune "cold" tumors to "hot" tumors that are thus more likely to respond to ICIs is a major obstacle for cancer treatment. Triggering inflammatory forms of cell death, such as necroptosis and pyroptosis, may alter the tumor immune microenvironment and the influx of TILs. We present an emerging view that promoting tumor-localized necroptosis and pyroptosis may ultimately enhance responses to ICI. SIGNIFICANCE: Many tumor types respond poorly to ICIs or respond but subsequently acquire resistance. Effective therapies for ICI-nonresponsive tumors are lacking and should be guided by evidence from preclinical studies. Promoting inflammatory cell death mechanisms within the tumor may alter the local immune microenvironment toward an ICI-responsive state.

A comparison between the effects of over-expression of miRNA-16 and miRNA-34a on cell cycle progression of mesothelioma cell lines and on their cisplatin sensitivity

The prognosis of patients affected by malignant pleural mesothelioma (MPM) is presently poor and no therapeutic strategies have improved their survival yet. Introduction of miRNA mimics to restore their reduced or absent functionality in cancer cells is considered an important opportunity and a combination of miR's might be even more effective. In the present study, miR-16 and miR-34a were transfected, singularly and in combination, in MPM cell lines H2052 and H28, and their effects on cell proliferation and sensitivity to cisplatin are reported. Interestingly, the overexpression of both miRs, alone or combined, slows down the cell cycle progression, modulates the p53 and HMGB1 expression and increases the sensitivity of cells to cisplatin, producing a marked impairment of cell proliferation and strengthening the apoptotic effect of the drug. However, the co-overexpression of the two miRs results more effective only in the regulation of the cell cycle, but does not enhance the sensitivity of MPM cells to cisplatin. Consequently, although the potential of miR-16 and miR-34a is confirmed, we must conclude that their combination does not improve the response of MPM to chemotherapy.

An Integrative Analysis of Time-varying Regulatory Networks From High-dimensional Data

Directed networks have been widely used to describe many biological processes and functions. Understanding the structure of biological networks, especially regulatory networks, could help discover the mechanisms underlying important biological processes and pathogenesis of diseases. Most network inference methods assume the network structure is time-invariant or stationary. However, in some processes, the network structure is non-stationary or time-varying. The stationary network inference methods might not be able to directly used to reconstruct time-varying networks. Some non-stationary network learning methods have been proposed to infer the networks, but, the inferred networks are not regulatory networks which require activation and inhibition information. This work proposes an integrative approach, which combines the changepoint estimation, weighted network learning and searching, and model checking technique, to reconstruct time varying regulatory networks from high-dimensional time series data. We illustrate this approach to study the structure changes of Drosophila's regulatory networks in its life cycle.

High-mobility group box 1 protein (HMGB1) gene polymorphisms and cancer susceptibility: A comprehensive meta-analysis

AIM

The role of HMGB1 polymorphisms in cancer predisposition remains unclear. This meta-analysis was performed assess four HMGB1 polymorphisms (rs1045411, rs2249825, rs1360485 and rs1412125) in cancer risk.

METHODS

We searched published studies till January 2018 from EMBASE, PubMed, Google scholar, and Cochrane library. Thereafter, the statistical software "R" was used to calculate Pooled Odds Ratios (OR), and 95% confidence intervals (CI) for assessment of association between different HMGB1 polymorphisms and cancer risk.

RESULT

In this meta-analysis we used eight studies totaling 7017 subjects. HMGB1 rs1045411 polymorphism in recessive model (OR 1.4159, 95% CI 0.9197-2.1798, P = 0.1142) and homozygous model (OR 1.4157, 95% CI 0.8711-2.3006, P = 0.1606) emerged as a risk factor for cancer development. Dominant model in rs2249825 polymorphism (OR: 0.8954) and rs1412125 polymorphism (OR: 0.9029) emerged as protective factors. Statistical significance was not achieved for any genetic model. Begg's test and Egger's test for all analysis suggested no publication bias.

CONCLUSION

This is the first meta-analysis exploring the association of four HMGB1 polymorphisms with cancer. Although polymorphism rs1045411 emerged as a risk candidate, additional studies are suggested to confirm these findings.

On the importance of modelling the internal spatial dynamics of biological cells

Spatial effects such as cell shape have very often been considered negligible in models of cellular pathways, and many existing simulation infrastructures do not take such effects into consideration. Recent experimental results are reversing this judgement by showing that very small spatial variations can make a big difference in the fate of a cell. This is particularly the case when considering eukaryotic cells, which have a complex physical structure and many subtle control mechanisms, but bacteria are also interesting for the huge variation in shape both between species and in different phases of their lifecycle. In this work we perform simulations that measure the effect of three common bacterial shapes on the behaviour of model cellular pathways. To perform these experiments we develop ReDi-Cell, a highly scalable GPGPU cell simulation infrastructure for the modelling of cellular pathways in spatially detailed environments. ReDi-Cell is validated against known-good simulations, prior to its use in new work. We then use ReDi-Cell to conduct novel experiments that demonstrate the effect that three common bacterial shapes (Cocci, Bacilli and Spirilli) have on the behaviour of model cellular pathways. Pathway wavefront shape, pathway concentration gradients, and chemical species distribution are measured in the three different shapes. We also quantify the impact of internal cellular clutter on the same pathways. Through this work we show that variations in the shape or configuration of these common cell shapes alter model cell behaviour.

Histological Image Processing Features Induce a Quantitative Characterization of Chronic Tumor Hypoxia

Hypoxia in tumors signifies resistance to therapy. Despite a wealth of tumor histology data, including anti-pimonidazole staining, no current methods use these data to induce a quantitative characterization of chronic tumor hypoxia in time and space. We use image-processing algorithms to develop a set of candidate image features that can formulate just such a quantitative description of xenographed colorectal chronic tumor hypoxia. Two features in particular give low-variance measures of chronic hypoxia near a vessel: intensity sampling that extends radially away from approximated blood vessel centroids, and multithresholding to segment tumor tissue into normal, hypoxic, and necrotic regions. From these features we derive a spatiotemporal logical expression whose truth value depends on its predicate clauses that are grounded in this histological evidence. As an alternative to the spatiotemporal logical formulation, we also propose a way to formulate a linear regression function that uses all of the image features to learn what chronic hypoxia looks like, and then gives a quantitative similarity score once it is trained on a set of histology images.

Computational Modeling, Formal Analysis, and Tools for Systems Biology

As the amount of biological data in the public domain grows, so does the range of modeling and analysis techniques employed in systems biology. In recent years, a number of theoretical computer science developments have enabled modeling methodology to keep pace. The growing interest in systems biology in executable models and their analysis has necessitated the borrowing of terms and methods from computer science, such as formal analysis, model checking, static analysis, and runtime verification. Here, we discuss the most important and exciting computational methods and tools currently available to systems biologists. We believe that a deeper understanding of the concepts and theory highlighted in this review will produce better software practice, improved investigation of complex biological processes, and even new ideas and better feedback into computer science.

Circulating HMGB1 and RAGE as Clinical Biomarkers in Malignant and Autoimmune Diseases

High molecular group box 1 (HMGB1) is a highly conserved member of the HMG-box-family; abundantly expressed in almost all human cells and released in apoptosis; necrosis or by activated immune cells. Once in the extracellular space, HMGB1 can act as a danger associated molecular pattern (DAMP), thus stimulating or inhibiting certain functions of the immune system; depending on the “combinatorial cocktail” of the surrounding milieu. HMGB1 exerts its various functions through binding to a multitude of membrane-bound receptors such as TLR-2; -4 and -9; IL-1 and RAGE (receptor for advanced glycation end products); partly complex-bound with intracellular fragments like nucleosomes. Soluble RAGE in the extracellular space, however, acts as a decoy receptor by binding to HMGB1 and inhibiting its effects. This review aims to outline today’s knowledge of structure, intra- and extracellular functions including mechanisms of release and finally the clinical relevance of HMGB1 and RAGE as clinical biomarkers in therapy monitoring, prediction and prognosis of malignant and autoimmune disease.

Emerging roles for HMGB1 protein in immunity, inflammation, and cancer

High-mobility group box 1 (HMGB1) protein is a member of the highly conserved non-histone DNA binding protein family. First identified in 1973, as one of a group of chromatin-associated proteins with high acidic and basic amino acid content, it was so named for its characteristic rapid mobility in polyacrylamide gel electrophoresis. HMGB1 was later discovered to have another function. It is released from a variety of cells into the extracellular milieu to act on specific cell-surface receptors. In this latter role, HMGB1 is a proinflammatory cytokine that may contribute to many inflammatory diseases, including sepsis. Therefore, HMGB1 regulates intracellular cascades influencing immune cell functions, including chemotaxis and immune modulation. The bioactivity of the HMGB1 is determined by specific posttranslational modifications that regulate its role in inflammation and immunity. During tumor development, HMGB1 has been reported to play paradoxical roles in promoting both cell survival and death by regulating multiple signaling pathways. In this review, we focus on the role of HMGB1 in physiological and pathological responses, as well as the mechanisms by which it contributes to immunity, inflammation, and cancer progression.

A novel procedure for statistical inference and verification of gene regulatory subnetwork

Background

The reconstruction of gene regulatory network from time course microarray data can help us comprehensively understand the biological system and discover the pathogenesis of cancer and other diseases. But how to correctly and efficiently decifer the gene regulatory network from high-throughput gene expression data is a big challenge due to the relatively small amount of observations and curse of dimensionality. Computational biologists have developed many statistical inference and machine learning algorithms to analyze the microarray data. In the previous studies, the correctness of an inferred regulatory network is manually checked through comparing with public database or an existing model.

Results

In this work, we present a novel procedure to automatically infer and verify gene regulatory networks from time series expression data. The dynamic Bayesian network, a statistical inference algorithm, is at first implemented to infer an optimal network from time series microarray data of S. cerevisiae, then, a weighted symbolic model checker is applied to automatically verify or falsify the inferred network through checking some desired temporal logic formulas abstracted from experiments or public database.

Conclusions

Our studies show that the marriage of statistical inference algorithm with model checking technique provides a more efficient way to automatically infer and verify the gene regulatory network from time series expression data than previous studies.

HMGB1 bound to cisplatin-DNA adducts undergoes extensive acetylation and phosphorylation in vivo

Cisplatin, one of the most effective anticancer drugs, is a DNA-damaging agent that induces cell death primarily by apoptosis. For many years, HMGB1 has been known to be a recognition protein for cisplatin-DNA lesions. Here, an application of a biomolecular probe based on a peptide-oligonucleotide conjugate is presented as a novel method for investigating this recognition process in vivo. Proteins known to be involved in the recognition of cisplatin-damaged DNA were pulled down and identified, including members of the HMGB family and a number of other proteins. Interestingly, at least 4 subforms of HMGB1 bind to cisplatin-DNA adducts. These proteins were further identified as post-translationally acetylated or phosphorylated forms of HMGB1. These results provide a rich pool of protein candidates whose roles in the mechanism of action of platinum drugs should be explored. These newly discovered molecular components of the DNA damage signalling cascade could serve as novel links between the initial cell responses to DNA damage and the downstream apoptotic or DNA repair pathways.

Association of Upregulated HMGB1 and c-IAP2 Proteins With Hepatocellular Carcinoma Development and Progression

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most important health problems in China.

OBJECTIVES

This study analyzed expression of high-mobility group protein B1 (HMGB1) and inhibitor of apoptosis protein-2 (c-IAP2) proteins in HCC compared to paired para-tumor tissue samples to assess the association with HCC pathogenesis and progression.

MATERIALS AND METHODS

Sixty-eight HCC and para-tumor tissue samples were collected for Western blot, qRT-PCR and immunohistochemical analyses of HMGB1 and c-IAP2.

RESULTS

HMGB1 and c-IAP2 proteins were highly expressed in HCC tissue samples [85.3% (58/68) and 82.4% (56/68), respectively] compared to para-tumor tissue samples [32.3% and 27.9%, respectively]. Furthermore, expression of HMGB1 was significantly associated with enhanced c-IAP2 expression in HCC tissue samples (r = 0.878, P < 0.01). Expression of HMGB1 was associated with tumor multiplicity and size, alpha-fetoprotein (AFP) level and advanced TNM stage, while expression of c-IAP2 was associated with tumor size, AFP level and advanced TNM stage.

CONCLUSIONS

Expression of HMGB1 and c-IAP2 proteins was associated with HCC development and progression, and the expression of HMGB1 and c-IAP2 proteins in HCC were significantly associated with each other. Additionally, these proteins may show promise as biomarkers to predict HCC progression.

Computational analysis of the roles of ER-Golgi network in the cell cycle

BACKGROUND

ER-Golgi network plays an important role in the processing, sorting and transport of proteins, and it's also a site for many signaling pathways that regulate the cell cycle. Accumulating evidence suggests that, the stressed ER and malfunction of Golgi apparatus are associated with the pathogenesis of cancer and Alzheimer's disease (AD). Our previous work discovered and verified that altering the expression levels of target SNARE and GEF could modulate the size of Golgi apparatus. Moreover, Golgi's structure and size undergo dramatic changes during the development of several diseases. It is of importance to investigate the roles of ER-Golgi network in the cell cycle progression and some diseases.

RESULTS

In this work, we first develop a computational model to study the ER stress-induced and Golgi-related apoptosis-survival signaling pathways. Then, we propose and apply both asynchronous and synchronous model checking methods, which extend our previous verification technique, to automatically and formally analyze the ER-Golgi-regulated signaling pathways in the cell cycle progression through verifying some computation tree temporal logic formulas.

CONCLUSIONS

The proposed asynchronous and synchronous verification technique has advantages for large network analysis and verification over traditional simulation methods. Using the model checking method, we verified several Alzheimer's disease and cancer-related properties, and also identified important proteins (NFκB, ATF4, ASK1 and TRAF2) in the ER-Golgi network, which might be responsible for the pathogenesis of cancer and AD. Our studies indicate that targeting the ER stress-induced and Golgi-related pathways might serve as potent therapeutic targets for the treatment of cancer and Alzheimer's disease.

HMGB1 promotes a p38MAPK associated non-infectious inflammatory response pathway in human fetal membranes

Objective

Spontaneous preterm birth (PTB) and preterm prelabor rupture of membranes (pPROM) are major pregnancy complications often associated with a fetal inflammatory response. Biomolecular markers of this fetal inflammatory response to both infectious and non-infectious risk factors and their contribution to PTB and pPROM mechanism are still unclear. This study examined fetal membrane production, activation and mechanistic properties of high mobility group box 1 (HMGB1) as a contributor of the non-infectious fetal inflammatory response.

Materials and Methods

HMGB1 transcripts and active HMGB1 were profiled in fetal membranes and amniotic fluids collected from PTB and normal term birth. In vitro, normal term not in labor fetal membranes were exposed to lipopolysaccharide (LPS) and water soluble cigarette smoke extract (CSE). HMGB1-transcripts and its protein concentrations were documented by RT-PCR and ELISA. Recombinant HMGB1 treated membranes and media were subjected to RT-PCR for HMGB1 receptors, mitogen activated protein kinase pathway analysis, cytokine levels, and Western blot for p38MAPK.

Results

HMGB1 expression and its active forms were higher in PTB and pPROM than normal term membranes and amniotic fluid samples. Both LPS and CSE enhanced HMGB1 expression and release in vitro. Fetal membrane exposure to HMGB1 resulted in increased expression of TLR2 and 4 and dose-dependent activation of p38MAPK-mediated inflammation.

Conclusions

HMGB1 increase by fetal membrane cells in response to either oxidative stress or infection can provide a positive feedback loop generating non-infectious inflammatory activation. Activation of p38MAPK by HMGB1 promotes development of the senescence phenotype and senescence associated sterile inflammation. HMGB1 activity is an important regulator of the fetal inflammatory response regardless of infection.

Marine sponge derived natural products between 2001 and 2010: trends and opportunities for discovery of bioactives

Marine sponges belonging to the phylum Porifera (Metazoa), evolutionarily the oldest animals are the single best source of marine natural products. The present review presents a comprehensive overview of the source, taxonomy, country of origin or geographical position, chemical class, and biological activity of sponge-derived new natural products discovered between 2001 and 2010. The data has been analyzed with a view to gaining an outlook on the future trends and opportunities in the search for new compounds and their sources from marine sponges.

Systems biology of cancer: a challenging expedition for clinical and quantitative biologists

A systems-biology approach to complex disease (such as cancer) is now complementing traditional experience-based approaches, which have typically been invasive and expensive. The rapid progress in biomedical knowledge is enabling the targeting of disease with therapies that are precise, proactive, preventive, and personalized. In this paper, we summarize and classify models of systems biology and model checking tools, which have been used to great success in computational biology and related fields. We demonstrate how these models and tools have been used to study some of the twelve biochemical pathways implicated in but not unique to pancreatic cancer, and conclude that the resulting mechanistic models will need to be further enhanced by various abstraction techniques to interpret phenomenological models of cancer progression.

HMGB1 enhances embryonic neural stem cell proliferation by activating the MAPK signaling pathway

Neural stem cells (NSCs) are involved in neural tube formation. As the high-mobility group box 1 (HMGB1) protein is involved in neurulation and is present at elevated levels in neural tube defects (NTDs) induced by hyperthermia, we have now investigated the effects of HMGB1 on proliferation, differentiation, and MAPK signaling pathways of NSCs in vitro. We constructed a lentivirus vector with HMGB1 siRNA and used it to infect NSCs. Down-regulation of HMGB1 expression was confirmed. Proliferation of NSCs was determined by MTS and nestin/BrdU double-labeling. Differentiation of NSCs was assessed using β-tubulinIII and GFAP. Knockdown of HMGB1 significantly suppressed NSC proliferation but hardly affected differentiation, which was regulated by decreased expression of MAPK signaling pathways. Thus, HMGB1 has beneficial effects on neurulation and may serve as a new target for the prevention of NTDs.

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and posttranslational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation).

Analysis of intercellular signal transduction in the tumor microenvironment

Background

Recent cancer studies revealed, the interaction between pancreatic cancer cells and pancreatic stellate cells is of importance in the cancer progression. The activation of stellate cells is mediated by some growth factors and cytokines secreted by the cancer cells. In turn, the activated stellate cells will synthesize and secrete multiple growth factors to continuously stimulate the growth of surrounding cancer cells through paracrine pathways. The mechanism behind the evolution of stellate cells from quiescent state to a cancer-associated phenotype is still not well understood.

Results

To systematically investigate the interaction between cancer cells and stellate cells, we constructed a multicellular discrete value model, which is composed of several intracellular and intercellular signaling pathways that are frequently mutated in the pancreatic cancer, to study the cell cycle progression and angiogenesis. We, then, introduced and applied a formal verification technique, Symbolic Model Checking, to automatically analyze the cells' proliferation, angiogenesis and apoptosis in the proposed signal transduction model of tumor microenvironment.

Conclusions

Our studies predicted some important temporal logic properties and dynamic behaviors in the pancreatic cancer cells and stellate cells. The verification technique identified several signaling components, including the RAS, RAGE, AKT, IKK, DVL, RB and PTEN, whose mutation or loss of function can promote cell growth and inhibit apoptosis, some of which have been confirmed by existing experiments. Our formal studies demonstrated that, the bidirectional interaction between cancer cells and stellate cells could significantly increase cell proliferation, inhibit apoptosis, induce tumor angiogenesis, and promote cancer metastasis.

In silico modeling: methods and applications to trauma and sepsis

OBJECTIVES

To familiarize clinicians with advances in computational disease modeling applied to trauma and sepsis.

DATA SOURCES

PubMed search and review of relevant medical literature.

SUMMARY

Definitions, key methods, and applications of computational modeling to trauma and sepsis are reviewed.

CONCLUSIONS

Computational modeling of inflammation and organ dysfunction at the cellular, organ, whole-organism, and population levels has suggested a positive feedback cycle of inflammation → damage → inflammation that manifests via organ-specific inflammatory switching networks. This structure may manifest as multicompartment "tipping points" that drive multiple organ dysfunction. This process may be amenable to rational inflammation reprogramming.

Efficient stochastic simulation of chemical kinetics networks using a weighted ensemble of trajectories

We apply the "weighted ensemble" (WE) simulation strategy, previously employed in the context of molecular dynamics simulations, to a series of systems-biology models that range in complexity from a one-dimensional system to a system with 354 species and 3680 reactions. WE is relatively easy to implement, does not require extensive hand-tuning of parameters, does not depend on the details of the simulation algorithm, and can facilitate the simulation of extremely rare events. For the coupled stochastic reaction systems we study, WE is able to produce accurate and efficient approximations of the joint probability distribution for all chemical species for all time t. WE is also able to efficiently extract mean first passage times for the systems, via the construction of a steady-state condition with feedback. In all cases studied here, WE results agree with independent "brute-force" calculations, but significantly enhance the precision with which rare or slow processes can be characterized. Speedups over "brute-force" in sampling rare events via the Gillespie direct Stochastic Simulation Algorithm range from ~10(12) to ~10(18) for characterizing rare states in a distribution, and ~10(2) to ~10(4) for finding mean first passage times.

Circulating nucleosomes and immunogenic cell death markers HMGB1, sRAGE and DNAse in patients with advanced pancreatic cancer undergoing chemotherapy

Serum biomarkers are urgently needed for patient stratification and efficient treatment monitoring in pancreatic cancer (PC). Within a prospective diagnostic observation study, blood samples were obtained from 78 patients with advanced PC before and weekly during the course of palliative chemotherapy. Circulating nucleosomes and immunogenic cell death markers, high-mobility group box 1 (HMGB1), soluble receptors of advanced glycation end products (sRAGE) and DNAse activity, were measured by enzyme-linked immunosorbent assay and correlated with results of radiological staging after 2 months of treatment, with time to progression (TTP) and overall survival (OS). Median TTP and OS of PC patients were 3.9 and 7.7 months, respectively. Pretherapeutic baseline biomarker levels did not correlate with objective response; however, nucleosome levels on day (d) 28 were higher (p = 0.048) and sRAGE levels at time of staging (d56) were lower in progressive patients (p = 0.046). Concerning estimation of prognosis, high nucleosome levels (d7, d14, d21 and d56), low sRAGE levels (d56) and DNAse activity courses (d0-d7) correlated with TTP, whereas high nucleosomes (d7, d14 and d56), high HMGB1 (d21 and d56) and DNAse (d0-d7) were associated with OS. After adjustment to Karnofsky performance score, nucleosomes and HMGB1 (both d56) and DNAse (d0-d7) remained independent prognostic factors. Thus, courses of circulating nucleosomes and immunogenic cell death markers HMGB1 and sRAGE show prognostic relevance in PC patients undergoing chemotherapy.

Proteomic analysis of apoptotic and oncotic pancreatic acinar AR42J cells treated with caerulein

This study aims to determine the differentially expressed proteins in the pancreatic acinar cells undergoing apoptosis and oncosis stimulated with caerulein to explore different cell death process of the acinar cell. AR42J cells were treated with caerulein to induce cell model of acute pancreatitis. Cells that were undergoing apoptosis and oncosis were separated by flow cytometry. Then differentially expressed proteins in the two groups of separated cells were detected by shotgun liquid chromatography-tandem mass spectrometry. The results showed that 11 proteins were detected in both apoptosis group and oncosis group, 17 proteins were detected only in apoptosis group and 29 proteins were detected only in oncosis group. KEGG analysis showed that proteins detected only in apoptosis group were significantly enriched in 10 pathways, including ECM-receptor interaction, cell adhesion molecules, and proteins detected only in oncosis group were significantly enriched in three pathways, including endocytosis, base excision repair, and RNA degradation. These proteins we detected are helpful for us to understand the process of cell death in acute pancreatitis and may be useful for changing the death mode of pancreatic acinar cells, thus attenuating the severity of pancreatitis.

HMGB1: A Promising Therapeutic Target for Prostate Cancer

High mobility group box 1 (HMGB1) was originally discovered as a chromatin-binding protein several decades ago. It is now increasingly evident that HMGB1 plays a major role in several disease conditions such as atherosclerosis, diabetes, arthritis, sepsis, and cancer. It is intriguing how deregulation of HMGB1 can result in a myriad of disease conditions. Interestingly, HMGB1 is involved in cell proliferation, angiogenesis, and metastasis during cancer progression. Furthermore, HMGB1 has been demonstrated to exert intracellular and extracellular functions, activating key oncogenic signaling pathways. This paper focuses on the role of HMGB1 in prostate cancer development and highlights the potential of HMGB1 to serve as a key target for prostate cancer treatment.

HMGB1 protein does not mediate the inflammatory response in spontaneous spinal cord regeneration: a hint for CNS regeneration

Uncontrolled, excessive inflammation contributes to the secondary tissue damage of traumatic spinal cord, and HMGB1 is highlighted for initiation of a vicious self-propagating inflammatory circle by release from necrotic cells or immune cells. Several regenerative-competent vertebrates have evolved to circumvent the second damages during the spontaneous spinal cord regeneration with an unknown HMGB1 regulatory mechanism. By genomic surveys, we have revealed that two paralogs of HMGB1 are broadly retained from fish in the phylogeny. However, their spatial-temporal expression and effects, as shown in lowest amniote gecko, were tightly controlled in order that limited inflammation was produced in spontaneous regeneration. Two paralogs from gecko HMGB1 (gHMGB1) yielded distinct injury and infectious responses, with gHMGB1b significantly up-regulated in the injured cord. The intracellular gHMGB1b induced less release of inflammatory cytokines than gHMGB1a in macrophages, and the effects could be shifted by exchanging one amino acid in the inflammatory domain. Both intracellular proteins were able to mediate neuronal programmed apoptosis, which has been indicated to produce negligible inflammatory responses. In vivo studies demonstrated that the extracellular proteins could not trigger a cascade of the inflammatory cytokines in the injured spinal cord. Signal transduction analysis found that gHMGB1 proteins could not bind with cell surface receptors TLR2 and TLR4 to activate inflammatory signaling pathway. However, they were able to interact with the receptor for advanced glycation end products to potentiate oligodendrocyte migration by activation of both NFκB and Rac1/Cdc42 signaling. Our results reveal that HMGB1 does not mediate the inflammatory response in spontaneous spinal cord regeneration, but it promotes CNS regeneration.

Improved statistical model checking methods for pathway analysis

Statistical model checking techniques have been shown to be effective for approximate model checking on large stochastic systems, where explicit representation of the state space is impractical. Importantly, these techniques ensure the validity of results with statistical guarantees on errors. There is an increasing interest in these classes of algorithms in computational systems biology since analysis using traditional model checking techniques does not scale well. In this context, we present two improvements to existing statistical model checking algorithms. Firstly, we construct an algorithm which removes the need of the user to define the indifference region, a critical parameter in previous sequential hypothesis testing algorithms. Secondly, we extend the algorithm to account for the case when there may be a limit on the computational resources that can be spent on verifying a property; i.e, if the original algorithm is not able to make a decision even after consuming the available amount of resources, we resort to a p-value based approach to make a decision. We demonstrate the improvements achieved by our algorithms in comparison to current algorithms first with a straightforward yet representative example, followed by a real biological model on cell fate of gustatory neurons with microRNAs.

Multiple promoters and targeted microRNAs direct the expressions of HMGB3 gene transcripts in dairy cattle

HMGB3 (high-mobility group box 3) is an X-linked member of a family of sequence-independent chromatin-binding proteins and functions as a universal sentinel for nucleic acid-mediated innate immune responses. The splice variant expression, promoter characterization and targeted microRNAs of the bovine HMGB3 gene were investigated to explore its expression pattern and possible regulatory mechanism. The results revealed that the expression of HMGB3 transcript variants 1 and 2 (HMGB3-TV1 and HMGB3-TV2) mRNA in the mastitis-infected mammary gland tissues was up-regulated by 8.46- and 5.31-fold respectively compared with that in healthy tissues (P < 0.05). HMGB3-TV1 was highly expressed in the mammary gland tissues, whereas HMGB3-TV2 was expressed primarily in liver. Functional analyses indicated that HMGB3 transcription is regulated by three distinct promoters - promoters 1, 2 and 3 (P1, P2 and P3) - resulting in two alternative transcripts with the same 3'-untranslated region. Promoter luciferase activity analysis suggested that the core sequences of P1 and P2 were mapped in the region of g.1535 to ~g.2076 and g.2074 to ~g.2491 respectively. The g.5880C>T SNP in P3 affected its base promoter activity, and different genotypes were associated with the bovine somatic count score. The expression of targets bovine miR-17-5p, miR-20b and miR-93 of the HMGB3 gene was down-regulated 1.56-, 1.72- and 2.94-fold respectively in mammary gland tissues as compared with that in healthy tissues (P < 0.05). The findings suggest that HMGB3 expression is under complex transcriptional and post-transcriptional control by alternate promoter usage, alternative splicing mechanism and microRNAs in dairy cattle.

High-mobility group box 1 activates caspase-1 and promotes hepatocellular carcinoma invasiveness and metastases

Hypoxia is often found in solid tumors and is associated with tumor progression and poor clinical outcomes. The exact mechanisms related to hypoxia-induced invasion and metastasis remain unclear. We elucidated the mechanism by which the nuclear-damage-associated molecular pattern molecule, high-mobility group box 1 (HMGB1), released under hypoxic stress, can induce an inflammatory response to promote invasion and metastasis in hepatocellular carcinoma (HCC) cells. Caspase-1 activation was found to occur in hypoxic HCC cells in a process that was dependent on the extracellular release of HMGB1 and subsequent activation of both Toll-like receptor 4 (TLR4)- and receptor for advanced glycation endproducts (RAGE)-signaling pathways. Downstream from hypoxia-induced caspase-1 activation, cleavage and release of proinflammatory cytokines interleukin (IL)-1β and -18 occurred. We further demonstrate that overexpression of HMGB1 or treatment with recombinant HMGB1 enhanced the invasiveness of HCC cells, whereas stable knockdown of HMGB1 remarkably reduced HCC invasion. Moreover, in a murine model of HCC pulmonary metastasis, stable knockdown of HMGB1 suppressed HCC invasion and metastasis.

CONCLUSION

These results suggest that in hypoxic HCC cells, HMGB1 activates TLR4- and RAGE-signaling pathways to induce caspase-1 activation with the subsequent production of multiple inflammatory mediators, which, in turn, promote cancer invasion and metastasis.

Using proteomic approach to identify tumor-associated proteins as biomarkers in human esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers in China. The lower survival rate of ESCC is attributed to late diagnosis and poor therapeutic efficacy; therefore, the identification of tumor-associated proteins as biomarkers for early diagnosis, and the discovery of novel targets for therapeutic intervention, seems very important for increasing the survival rate of ESCC. To identify tumor-associated proteins as biomarkers in ESCC, we have analyzed ESCC tissues and adjacent normal tissues by two-dimensional electrophoresis (2DE) and matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) analysis. The results showed that a total of 104 protein spots with different expression levels were found on 2DE, and 47 proteins were eventually identified by MALDI-TOF MS. Among these identified proteins, 33 proteins including keratin 17 (KRT17), biliverdin reductase B (BLVRB), proteasome activator subunit 1 (PSME1), manganese superoxide dismutase (MnSOD), high-mobility group box-1(HMGB1), heat shock protein 70 (HSP70), peroxiredoxin (PRDX1), keratin 13 (KRT13), and so on were overexpressed, and 14 proteins including cystatin B (CSTB), tropomyosin 2 (TPM2), annexin 1 (ANX1), transgelin (TAGLN), keratin 19 (KRT19), stratifin (SFN), and so on were down-expressed in ESCC. Biological functions of these proteins are associated with cell proliferation, cell motility, protein folding, oxidative stress, and signal transduction. In the subsequent study using immunoassay on ESCC serum samples and tissue-array slides, two representative proteins, HSP70 and HMGB1, were selected as examples for the purpose of validation. The results showed that both HSP70 and HMGB1 can induce autoantibody response in ESCC sera and have higher expression in ESCC tissues. Especially, the frequency of antibodies to HSP70 in ESCC sera was significantly higher than that in normal human sera. The preliminary results suggest that some of these identified proteins might contribute to esophageal cell differentiation and carcinogenesis, certain proteins could be used as tumor-associated antigen (TAA) biomarkers in cancer diagnosis, and further studies on these identified proteins should provide more evidence of how these proteins are involved in carcinogenesis of ESCC.

InCoB2010 - 9th International Conference on Bioinformatics at Tokyo, Japan, September 26-28, 2010

The International Conference on Bioinformatics (InCoB), the annual conference of the Asia-Pacific Bioinformatics Network (APBioNet), is hosted in one of countries of the Asia-Pacific region. The 2010 conference was awarded to Japan and has attracted more than one hundred high-quality research paper submissions. Thorough peer reviewing resulted in 47 (43.5%) accepted papers out of 108 submissions. Submissions from Japan, R.O. Korea, P.R. China, Australia, Singapore and U.S.A totaled 43.8% and contributed to 57.4% of accepted papers. Manuscripts originating from Taiwan and India added up to 42.8% of submissions and 28.3% of acceptances. The fifteen articles published in this BMC Bioinformatics supplement cover disease informatics, structural bioinformatics and drug design, biological databases and software tools, signaling pathways, gene regulatory and biochemical networks, evolution and sequence analysis.