| 1. |
- Zhang, Xueli, 1991-
(author)
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Biomarkers for Diagnosis, Therapy and Prognosis in Colorectal Cancer : a study from databases, machine learning predictions to laboratory confirmations
- 2020
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Doctoral thesis (other academic/artistic)abstract
- Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide. Early diagnosis and better therapy response have been believed to be associated with better prognosis. CRC biomarkers are considered as precise indicators for the early diagnosis and better therapy response. It is, therefore, of importance to find out, analyze and evaluate the CRC biomarkers to further provide the more precis evidence for predicting novel potential biomarkers and eventually to improve early diagnosis, personalized therapy and prognosis for CRC.In this study, we started with creating and establishing a CRC biomarker database. (CBD: http://sysbio.suda.edu.cn/CBD/index.html) In the CBD database, there were 870 reported CRC biomarkers collected from the published articles in PubMed. In this version of the CBD, CRC biomarker data was carefully collected, sorted, displayed, and analyzed. The major applications of the CBD are to provide 1) the records of CRC biomarkers (DNA, RNA, protein and others) concerning diagnosis, treatment and prognosis; 2) the basic and clinical research information concerning the CRC biomarkers; 3) the primary results for bioinformatics and biostatics analysis of the CRC biomarkers; 4) downloading/uploading the biomedicine information for CRC biomarkers.Based on our CBD and other public databases, we further analyzed the presented CRC biomarkers (DNAs, RNAs, proteins) and predicted novel potential multiple biomarkers (the combination of single biomarkers) with biological networks and pathways analysis for diagnosis, therapy response and prognosis in CRC. We found several hub biomarkers and key pathways for the diagnosis, treatment and prognosis in CRC. Receiver operating characteristic (ROC) test and survival analysis by microarray data revealed that multiple biomarkers could be better biomarkers than the single biomarkers for the diagnosis and prognosis of CRC.There are 62 diagnosis biomarkers for colon cancer in our CBD. In the previous studies, we found these present biomarkers were not enough to improve significantly the diagnosis of colon cancer. In order to find out novel biomarkers for the colon cancer diagnosis, we have performed /machine learning (ML) techniques such as support vector machine (SVM) and regression tree to predict candidate to discover diagnostic biomarkers for colon cancer. Based on the protein-protein interaction (PPI) network topology features of the identified biomarkers, we found 12 protein biomarkers which were considered as the candidate colon cancer diagnosis biomarkers. Among these protein biomarkers Chromogranin-A (CHGA) was the most powerful biomarker, which showed good performance in bioinformatics test and Immunohistochemistry(IHC). We are now expanding this study to CRC.Expression of CHGA protein in colon cancer was further verified with a novel logistic regressionbased meta-analysis, and convinced as a valuable diagnostic biomarker as compared with the typical diagnostic biomarkers, such as TP53, KRAS and MKI67.microRNAs (miRNAs/miRs) have been considered as potential biomarkers. A novel miRNA-mRNA interaction network-based model was used to predict miRNA biomarkers for CRC and found that miRNA-186-5p, miRNA-10b-5p and miRNA-30e-5p might be the novel biomarkers for CRC diagnosis. In conclusion, we have created a useful CBD database for CRC biomarkers and provided detailed information for how to use the CBD in CRC biomarker investigations. Our studies have been focusing on the biomarkers in diagnosis, therapy and prognosis. Based on our CBD and other powerful cancer associated databases, ML has been used to analyze the characteristics of the CRC biomarkers and predict novel potential CRC biomarkers. The predicted potential biomarkers were further confirmed at biomedical laboratory.
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| 2. |
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| 3. |
- Gnosa, Sebastian, 1984-
(author)
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Astrocyte elevated gene-1 in relation to colorectal cancer development and radiotherapy response
- 2015
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Doctoral thesis (other academic/artistic)abstract
- The incidence and death rate for colorectal cancer (CRC) decreased during the last decades as a result of improved diagnosis and treatment. However, CRC is still the third most common cancer in the world, and is responsible for about 700 000 deaths per year worldwide. Therefore, it is important to understand the mechanisms of the disease, and to find molecular markers in order to further improve prognosis, and to develop new treatment strategies. Astrocyte elevated gene-1 (AEG-1), encoded by the MTDH gene, is upregulated in a variety of cancers. AEG-1 is involved in cell survival, proliferation, migration, invasion, metastasis, angiogenesis, and apoptosis.The aim of this thesis was to investigate the role of AEG-1 in CRC development and the impact of AEG-1 on the response of radiation treatment. The AEG-1 expression, analysed in different CRC patient cohorts in paper I and III, was increased in the tumour tissue compared with the normal mucosa, and higher in the lymph node and liver metastases. Expression analyses in normal and cancer cell lines confirmed these results. In paper II, sequencing of the complete coding sequence of the MTDH gene in 356 patients revealed 50 single nucleotide variants of which 29 were novel. Eight exonic variants were detected, including three frameshift variants which were probably pathogenic, and two missense variants located in functional protein regions. There was no correlation of the MTDH variants or AEG-1 expression with the patient survival. In paper III, we also investigated the impact of AEG-1 on the response to radiation treatment. AEG-1 knockdown decreased the cellular survival upon radiation in several colon cancer cell lines. The AEG-1 expression was furthermore analysed in patients, which were randomised to either surgery alone or preoperative radiotherapy (RT), followed by surgery. The rectal cancer patients with high AEG-1 expression treated with RT had a significantly higher risk of developing distant recurrence and had a worse disease free survival, likely due to the metastasis promoting properties of AEG-1. In paper IV, the impact of AEG-1 knockdown and radiation on migration and invasion was analysed in colon cancer cell lines in vitro and in a novel zebrafish model in vivo. AEG-1 knockdown decreased migration and invasion, and radiation-enhanced migration and invasion in the cell lines tested.In conclusion, our data suggest that AEG-1 is involved in CRC development, while MTDH gene variants probably not have a high clinical importance in CRC. Furthermore, AEG-1 is a promising radiosensitising target and a valuable prognostic marker in CRC. We further showed that AEG-1 knockdown inhibits migration and invasion, as well as radiation-enhanced cell migration and invasion.
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| 4. |
- Yang, Hong
(author)
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Integrated understanding and targeting metabolic dysregulation in chronic liver disease : A multi-omics and systems biology perspective
- 2024
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Doctoral thesis (other academic/artistic)abstract
- The liver, vital for various metabolic functions in the body, is susceptible to genetic or environmental factors such as viral infections, diet, or alcohol consumption. These factors can trigger chronic liver disease (CLD), a condition that often progresses silently into more advanced stages, including liver fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). With increasing rates of alcohol consumption and metabolic disorders such as metabolic dysfunction-associated steatotic liver disease (MASLD), CLD has become a significant global health burden, contributing to high morbidity and mortality worldwide. This thesis employs systems biology approaches that integrate large-scale omics data to delve into the molecular mechanisms underpinning CLD and evaluate therapeutic interventions targeting metabolic dysfunctions associated with the disease.The first part of the thesis (Papers I and II) aims to enhance our understanding of the molecular basis of CLD using liver transcriptomics and proteomics data. To identify key pathogenic drivers of MASLD development, Paper I entails the deep characterization of transcriptomics data across large patient cohorts through integration analysis with biological networks, offering comprehensive insights into transcriptional dysregulation and its regulation in MASLD. Paper II extends this by combining transcriptomics and proteomics data to characterize both liver and plasma molecular pathophysiology associated with liver fibrosis in individuals with various causes of CLD, including those diagnosed with MASLD, chronic viral hepatitis, and alcohol-related liver disease.The studies in the second part of the thesis (Papers III to VI) aim to explore the systemic effects of potential therapeutic interventions—Combined Metabolic Activators (CMA) and JNK-IN-5A—in targeting metabolic dysfunction associated with MASLD in clinical and preclinical models. Papers III and IV present one-day double-blinded, placebo-controlled human clinical studies examining the acute effects of CMA administration with different formulations. Paper V investigates the effect of short-term CMA treatment on diet-induced liver steatosis in hamsters and characterizes liver transcriptomics changes in response to the treatment. Additionally, Paper VIinvestigates both hepatic and extrahepatic effects of JNK-IN-5A on metabolic dysfunction induced by sucrose overconsumption in rats.In summary, the work described here contributes to ongoing efforts in the molecular characterization of chronic liver diseases and the development of effective treatments for MASLD. The findings could help pave the way for new approaches in diagnosing and treating liver diseases, offering hope for better management strategies in the future.
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| 5. |
- Zhang, Hong, 1957-
(author)
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Alloxan Toxicity to macrophages and Insulinoma Cells
- 1995
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Doctoral thesis (other academic/artistic)abstract
- Alloxan induces damage and death of pancreatic islet B-cells in severalexperimental animal models, thus causing insulin-dependent diabetes mellitus (IDDM or type I diabetes). This unique cytotoxicity of alloxan has been studied for more than fifty years. The mechanisms behind the cytotoxicity of alloxan have, however, never been fully understood, although an increasing number of authors now suggest formation of reactive oxygen species, targeting the plasma membrane, mitochondria and DNA. In the present study, we have investigated: (i) the production of superoxide and hydrogen peroxide during reactions between alloxan and reducing agents such as cysteine, reduced glutathione, and ascorbic acid; (ii) the cytotoxic effects of alloxan in the absence of reducing agents, on model systems of cultured macrophages and insulinoma cells; (iii) the cytotoxicity of alloxan together with the reducing agents on these cultured cells; (iv) the cytotoxicity of hydrogen peroxide, used at concentrations similar to those formed during the reactions of alloxan with reducing agents; (v) the influence of iron and the iron-chelator, desferrioxamine, on the alloxan-induced cytotoxicity; and (vi) the influence of starvation-induced autophagocytosis on the sensitivity of cells to hydrogen peroxide-induced oxidative stress. Cell viability was estimated by a delayed trypan blue dye exclusion test and plasma membrane permeability by a modified microfluorometric combined fluorescein diacetate-propidium iodide staining technique. Lysosomal membrane stability was microfluorometrically assayed by acridine orange and neutral red relocalization techniques. The intracellular amounts of iron, reduced glutathione, antioxidant enzymes, and ATP were biochemically and cytochemically studied under a variety of conditions. The results showed that: (i) superoxide artion radicals and hydrogen peroxide were produced by reactions between alloxan and several reducing agents (e.g. cysteine, reduced glutathione and ascorbic acid). Hydrogen peroxide readily diffused through cellular membranes into the lysosomes if it was not previously degraded by the cellular antioxidative defence systems. Hydroxyl radicals might be produced by intralysosornal Fenton reactions, if reactive iron was present, resulting in lysosomal membrane damage followed by a leakage of lysosomal lytic enzymes with ensuing cell degeneration and eventually cell death. (ii) If iron was adsorbed to plasma membranes, extracellularly produced superoxide anion radicals and hydrogen peroxide might cause the plasma membrane damage due to Fenton reactions. (iii) Preincubation with desferrioxamine, or the presence of catalase inhibited the cytotoxicity induced by alloxan and reducing agents. (iv) The antioxidative defence activity of insulinoma cells was low. (v) Starvation in PBS enhanced the sensitivity of both macrophages and insulinoma cells to oxidative stress induced by hydrogen peroxide mediated through increased activity of autophagocytotosis. Thus, the amount of intralysosomal reactive iron consequently resulted from the degradation of various iron-containing metallo-proteins. We conclude that the exposure of cells to alloxan together with a reducing agent created cellular oxidative stress through extracellular formation of superoxide anion radicals and hydrogen peroxide. The latter compound easily penetrated plasma and lysosomal membranes, reaching the lysosomal interior. If enough reactive iron was present within lysosomes and the hydrogen peroxide was not degraded by catalase or glutathione peroxidase before entering the acidic vacuolar apparatus hydroxyl radicals could be produced via intralysosomal Fenton reactions.The hydroxyl radicals, in turn, would attack and damage the lysosomalmembranes, causing a leakage of lysosomal enzymes to the cytosol and eventually leading to cell death. The sensitivity of cells to alloxan-induced cytotoxicity in the presence of reducing agents was therefore a function of (i) the rate of hydrogen peroxide production, (ii) the cellular antioxidative defence systems, (iii) the lysosomal amount of reactive iron, and (iv) the capacity of autophagocytosis.
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| 6. |
- Zhang, Hong
(author)
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HIV-1 reverse transcriptase as a target in the development of specific enzyme inhibitors
- 1997
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Doctoral thesis (other academic/artistic)abstract
- Human immunodeficiency virus type I (HIV-I), which causes the acquired immunodeficiency syndrome (AIDS), begins its intracellular infection life cycle with reverse transcription of its plus-strand RNA genome into a double-stranded proviral DNA intermediate which is integrated into the host chromosome inducing a persistent infection. A virally encoded enzyme, reverse transcriptase (RT), carries out the reverse transcription process by performing all three enzymatic activities, i.e. RNA-directed DNA synthesis, DNA-directed DNA synthesis and hydrolysis of the RNA strand from RNA-DNA hybrids. Hence, it is a major target for chemotherapy of HIV infections. The aims of the present studies are focused on the major intrinsic features of the reverse transcription process and possibilities to inhibit them. In order to understand the basis of viral resistance, several cloned recombinant RTs and RT mutants(genetic variants) that are associated with viral resistance to different classes of non-nucleoside RT inhibitors, have been prepared and characterised with respect to their catalytic properties. When comparing the catalytic specificity (kcal/Km)of wild type (parental) enzyme in steady state enzyme kinetics to different mutants, mutant RT with the double amino acid changes of Leu100-lle and Tyrl88-His displayed the most retarded catalytic properties on heteropolymeric RNA and DNA templates. Emergence of drug-resistant variants is a major obstacle in the development of anti-HlV agents. Different RTs were used as individual molecular targets in order to characterise the inhibitory profiles of NNRTls. These RT inhibitors, represented by 9-CI-TIBO, nevirapine, L-697,661, displayed different patterns of inhibitory activity against the activity of HIV-I RT and mutant RTs. The inhibitory effects were characterised by inhibition constants (Kis and Kii) in Michaelis & Menten enzyme kinetics. In general, inhibition of wild type RT exhibited exclusively non-competitive patterns giving Kis = Kii. Pure non-competitive inhibition was not observed for mutant enzymes giving Kis < Kii. A mixed inhibitory pattern was obtained reflecting a partial contribution of a competitive inhibition at an allosteric NNRTI binding site. Access to NNRTI-associated resistant enzymes is of importance in the evaluation of new antiviral agents, to determine common properties of resistance and thereby assist in the development of new drugs. The profile of an NNRTI can be determined rapidly by using different NNRTI resistant enzymes. A non-competitive pattern of inhibition gives a common feature of Kis = Kii = IC50 and thereby a rapid assessment of inhibitory potency. Feedback of biochemical and biological information to the chemical synthesis process was used extensively and led to the discovery of a new generation of PETT derivatives inhibitory to both wild type and mutant HIV-I RTs in the nanomolar range. The prototype PETT compound, trovirdine, inhibited HIV-I RT with an IC50 of 7nM, when employing heteropolymeric RNA template. Enzyme kinetic studies showed that inhibition of RT by trovirdine was purely non-competitive with regard to deoxynucleoside triphosphates. The allosteric binding to HIV-I RT resulted in a decelerated rate of DNA polymerisation and has been implicated as a major inhibitory functionality. The cross resistance profile and inhibitory mechanism on mutant RTs (181Tyr-Cys) and RT (100 Leu-Ile) has verified that trovirdine shares common features with other groups of non-nucleoside RT inhibitors having overlapping binding sites on RT. Combined chemotherapeutic approaches have been used extensively in order to reduce drug toxicity, possibly delaying development of viral resistance and achieving synergistic antiviral effects. This now represents the best anti-HIV strategy. Hence, it is important to evaluate the combination profile of a new inhibitor. Combinations of trovirdine with other RT inhibitors including AZT, ddC, ddI and their triphosphates, were studied in both cell-free HIV-I polymerase assays and HIV-I-infected MT-4 cell cultures. Synergistic and additive effects were observed both by using RT and HIV-I-infected MT-4 cells and by using different HIV-I RT mutants, as well as HIV-I drug resistant variants known to be resistant to the inhibitory effects of trovirdine. These studies indicate a potential for synergistic effects also in vivo when combining trovirdine and several clinically used anti-HIV drugs. The difference in inhibition by FLG-TP between HIV-I RT and cellular DNA polymerases make FLG a potentially useful HIV-I RT inhibitor. The emergence of resistant variants during in vitro selection was slower for FLG than for 3TC and similar to that observed with AZT. FLG inhibited HIV-I resistant to AZT and to non-nucleoside RT inhibitors and showed some cross-resistance to virus resistant to 3TC. The viral resistance was also manifest in HIV polymerase assays using virion-derived RT. The Ki value of FLG-resistant virion RT showed a 10 fold decreased ability to compete with the natural substrate. Chain elongation studies using M13mpl8 single-strand DNA showed that FLG-TP terminated RT-catalysed transcription at a base-specific site and this served as a major inhibitory functionality. A greater potential for interrupting the dynamic process of HIV replication can be achieved by combined antiviral therapy. Selection of drug regimens should be based on individual characteristics of the inhibitors in order to interrupt viral replication. Therefore, characterisation of different inhibitory mechanisms manuscripts and investigation of viral variants and associated enzyme properties in the optimisation of new inhibitory compound plays a fundamental role in the struggle to combat this devastating human disease.
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| 7. |
- Zhang, Han
(author)
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Optimizing Networked Systems and Inverse Optimal Control
- 2019
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Doctoral thesis (other academic/artistic)abstract
- This thesis is concerned with the problems of optimizing networked systems, including designing a distributed energy optimal consensus controller for homogeneous networked linear systems, maximizing the algebraic connectivity of a network by projected saddle point dynamics. In addition, the inverse optimal control problems for discrete-time finite time-horizon Linear Quadratic Regulators (LQRs) are considered. The goal is to infer the Q matrix in the quadratic cost function using the observations (possibly noisy) either on the optimal state trajectories, optimal control input or the system output.In Paper A, an optimal energy cost controller design for identical networked linear systems asymptotic consensus is considered. It is assumed that the topology of the network is given and the controller can only depend on relative information of the agents. Since finding the control gain for such a controller is hard, we focus on finding an optimal controller among a classical family of controllers which is based on the Algebraic Riccati Equation (ARE) and guarantees asymptotic consensus. We find that the energy cost is bounded by an interval and hence we minimize the upper bound. Further, the minimization for the upper bound boils down to optimizing the control gain and the edge weights of the graph separately. A suboptimal control gain is obtained by choosing Q=0 in the ARE. Negative edge weights are allowed, meaning that "competitions" between the agents are allowed. The edge weight optimization problem is formulated as a Semi-Definite Programming (SDP) problem. We show that the lowest control energy cost is reached when the graph is complete and with equal edge weights. Furthermore, two sufficient conditions for the existence of negative optimal edge weights realization are given. In addition, we provide a distributed way of solving the SDP problem when the graph topology is regular.In Paper B, a projected primal-dual gradient flow of augmented Lagrangian is presented to solve convex optimization problems that are not necessarily strictly convex. The optimization variables are restricted by a convex set with computable projection operation on its tangent cone as well as equality constraints. We show that the projected dynamical system converges to one of the saddle points and hence finding an optimal solution. Moreover, the problem of distributedly maximizing the algebraic connectivity of an undirected network by optimizing the "port gains" of each nodes is considered. The original SDP problem is relaxed into a nonlinear programming (NP) problem that will be solved by the aforementioned projected dynamical system. Numerical examples show the convergence of the aforementioned algorithm to one of the optimal solutions. The effect of the relaxation is illustrated empirically with numerical examples. A methodology is presented so that the number of iterations needed to converge is reduced. Complexity per iteration of the algorithm is illustrated with numerical examples.In Paper C and D, the inverse optimal control problems over finite-time horizon for discrete-time LQRs are considered. The well-posedness of the inverse optimal control problem is first justified. In the noiseless case, when these observations of the optimal state trajectories or the optimal control input are exact, we analyze the identifiability of the problem and provide sufficient conditions for uniqueness of the solution. In the noisy case, when the observations are corrupted by additive zero-mean noise, we formulate the problem as an optimization problem and prove that the solution to this problem is statistically consistent. The following two scenarios are further considered: 1) the distributions of the initial state and the observation noise are unknown, yet the exact observations on the initial states and the noisy observations on the system output are available; 2) the exact observations on the initial states are not available, yet the observation noises are known to be white Gaussian and the distribution of the initial state is also Gaussian (with unknown mean and covariance). For the first scenario, we show statistical consistency for the estimation. For the second scenario, we fit the problem into the framework of maximum-likelihood and Expectation Maximization (EM) algorithm is used to solve this problem. The performance of the proposed method is illustrated through numerical examples.
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| 8. |
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| 9. |
- Zhang, Jin, 1987-
(author)
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In silico Identification of Thyroid Disrupting Chemicals : among industrial chemicals and household dust contaminants
- 2016
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Doctoral thesis (other academic/artistic)abstract
- Thyroid disruptions by xenobiotics have been associated with a broad spectrum of severe adverse human health effects, such as impaired brain development and metabolic syndrome. Ingestion of indoor dust and contact with industrial chemicals are two significant human exposure routes of thyroid hormone disrupting chemicals (THDCs), raising serious concerns for human health. However, it is a laborious and costly process to identify THDCs using conventional experimental methods, due to the number of chemicals in commerce and the varieties of potential disruption mechanisms.In this thesis, we are aimed at in silico identification of novel THDCs targeting transthyretin (TTR) and thyroid hormone receptor (THR) among dust contaminants and commonly used industrial chemicals. In vitro assays were used to validate the in silico prediction results. Co-crystallization and molecular dynamics (MD) simulations were applied to reveal binding modes of THDCs at the studied biological targets and to explain their intermolecular recognition.The main findings presented in this thesis are:1. Over 144 environmental pollutants have been confirmed as TTR-binders in vitro and these cover a wide range of environmental pollutants and show distinct chemical profiles including a large group of halogenated aromatic compounds and a second group of per- and polyfluoroalkyl substances. (Paper I)2. In total 485 organic contaminants have been reported to be detected in household dust. The developed QSAR classification model predicted 7.6% of these dust contaminants and 53.1% of their metabolites as potential TTR-binders, which emphasizes the importance of metabolic bioactivation. After in vitro validation, four novel TTR binders with IC50 ≤ 10 µM were identified, i.e. perfluoroheptanesulfonic acid, 2,4,2',4'-tetrahydroxybenzophenone (BP2), 2,4,5-trichlorophenoxyacetic acid, and 3,5,6-trichloro-2-pyridinol. (Paper II)3. The development of a robust structure-based virtual screening (VS) protocol resulted in the prediction of 31 dust contaminants as potential binders to THRβ1 including musk compounds, PFASs, and bisphenol A derivatives. The in vitro experiments confirmed four compounds as weak binders to THRβ1, i.e. 2,4,5-trichlorophenoxyacetic acid, bisphenol A (3-chloro-2-hydroxypropyl) (2,3-dihydroxypropyl) ether, 2,4,2',4'-tetrahydroxybenzophenone, and 2,4-dichlorophenoxyacetic acid. (Paper III)4. We revealed the binding conformations of perfluorooctanesulfonic acid, perfluorooctanoic acid, and BP2 in the thyroxine binding sites (TBSs) of TTR by co-crystallizing TTR with the three compounds. A VS protocol was developed based on the TTR complex structures that predicted 192 industrial chemicals as potential binders to TTR. Seven novel TTR binders were confirmed by in vitro experiments including clonixin, 2,6-dinitro-p-cresol (DNPC), triclopyr, fluroxypyr, bisphenol S, picloram, and mesotrione. We further co-crystallized TTR with PBS, clonixin, DNPC, and triclopyr, and their complex structures showed that the compounds bind in the TBSs as proposed by the VS protocol.In summary, 13 indoor dust contaminants and industrial chemicals were identified as THDCs using a combination of in silico and in vitro approaches. To the best of our knowledge, none of these compounds has previously been reported to bind to TTR or THR. The identifications of these THDCs improve our understanding on the structure-activity relationships of THDCs. The crystal structures of TTR-THDC complexes and the information on THDC-Target intermolecular interactions provide a better understanding on the mechanism-of-actions behind thyroid disruption. The dataset compiled and in silico methods developed serve as a basis for identification of more diverse THDCs in the future and a tool for guiding de novo design of safer replacements.
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