Tumor Energy Metabolism and Potential of 3-Bromopyruvate as an Inhibitor of Aerobic Glycolysis: Implications in Tumor Treatment

Tumor formation and growth depend on various biological metabolism processes that are distinctly different with normal tissues. Abnormal energy metabolism is one of the typical characteristics of tumors. It has been proven that most tumor cells highly rely on aerobic glycolysis to obtain energy rather than mitochondrial oxidative phosphorylation (OXPHOS) even in the presence of oxygen, a phenomenon called "Warburg effect". Thus, inhibition of aerobic glycolysis becomes an attractive strategy to specifically kill tumor cells, while normal cells remain unaffected. In recent years, a small molecule alkylating agent, 3-bromopyruvate (3-BrPA), being an effective glycolytic inhibitor, has shown great potential as a promising antitumor drug. Not only it targets glycolysis process, but also inhibits mitochondrial OXPHOS in tumor cells. Excellent antitumor effects of 3-BrPA were observed in cultured cells and tumor-bearing animal models. In this review, we described the energy metabolic pathways of tumor cells, mechanism of action and cellular targets of 3-BrPA, antitumor effects, and the underlying mechanism of 3-BrPA alone or in combination with other antitumor drugs (e.g., cisplatin, doxorubicin, daunorubicin, 5-fluorouracil, etc.) in vitro and in vivo. In addition, few human case studies of 3-BrPA were also involved. Finally, the novel chemotherapeutic strategies of 3-BrPA, including wafer, liposomal nanoparticle, aerosol, and conjugate formulations, were also discussed for future clinical application.

The Potential of Lonidamine in Combination with Chemotherapy and Physical Therapy in Cancer Treatment

Lonidamine (LND) has the ability to resist spermatogenesis and was first used as an anti-spermatogenic agent. Later, it was found that LND has a degree of anticancer activity. Currently, LND is known to target energy metabolism, mainly involving the inhibition of monocarboxylate transporter (MCT), mitochondrial pyruvate carrier (MPC), respiratory chain complex I/II, mitochondrial permeability transition (PT) pore, and hexokinase II (HK-II). However, phase II clinical studies showed that LND alone had a weak therapeutic effect, and the effect was short and reversible. Interestingly, LND does not have the common side effects of traditional chemotherapeutic drugs, such as alopecia and myelosuppression. In addition, LND has selective activity toward various tumors, and its toxic and side effects do not overlap when combined with other chemotherapeutic drugs. Therefore, LND is commonly used as a chemosensitizer to enhance the antitumor effects of chemotherapeutic drugs based on its disruption of energy metabolism relating to chemo- or radioresistance. In this review, we summarized the combination treatments of LND with several typical chemotherapeutic drugs and several common physical therapies, such as radiotherapy (RT), hyperthermia (HT), and photodynamic therapy (PDT), and discussed the underlying mechanisms of action. Meanwhile, the development of novel formulations of LND in recent years and the research progress of LND derivative adjudin (ADD) as an anticancer drug were also discussed.

In Silico Prediction of O⁶-Methylguanine-DNA Methyltransferase Inhibitory Potency of Base Analogs with QSAR and Machine Learning Methods

O⁶-methylguanine-DNA methyltransferase (MGMT), a unique DNA repair enzyme, can confer resistance to DNA anticancer alkylating agents that modify the O⁶-position of guanine. Thus, inhibition of MGMT activity in tumors has a great interest for cancer researchers because it can significantly improve the anticancer efficacy of such alkylating agents. In this study, we performed a quantitative structure activity relationship (QSAR) and classification study based on a total of 134 base analogs related to their ED50 values (50% inhibitory concentration) against MGMT. Molecular information of all compounds were described by quantum chemical descriptors and Dragon descriptors. Genetic algorithm (GA) and multiple linear regression (MLR) analysis were combined to develop QSAR models. Classification models were generated by seven machine-learning methods based on six types of molecular fingerprints. Performances of all developed models were assessed by internal and external validation techniques. The best QSAR model was obtained with Q²Loo = 0.83, R² = 0.87, Q²ext = 0.67, and R²ext = 0.69 based on 84 compounds. The results from QSAR studies indicated topological charge indices, polarizability, ionization potential (IP), and number of primary aromatic amines are main contributors for MGMT inhibition of base analogs. For classification studies, the accuracies of 10-fold cross-validation ranged from 0.750 to 0.885 for top ten models. The range of accuracy for the external test set ranged from 0.800 to 0.880 except for PubChem-Tree model, suggesting a satisfactory predictive ability. Three models (Ext-SVM, Ext-Tree and Graph-RF) showed high and reliable predictive accuracy for both training and external test sets. In addition, several representative substructures for characterizing MGMT inhibitors were identified by information gain and substructure frequency analysis method. Our studies might be useful for further study to design and rapidly identify potential MGMT inhibitors.

Quantitative Structure-Activity Relationship (QSAR) Studies on the Toxic Effects of Nitroaromatic Compounds (NACs): A Systematic Review

Nitroaromatic compounds (NACs) are ubiquitous in the environment due to their extensive industrial applications. The recalcitrance of NACs causes their arduous degradation, subsequently bringing about potential threats to human health and environmental safety. The problem of how to effectively predict the toxicity of NACs has drawn public concern over time. Quantitative structure-activity relationship (QSAR) is introduced as a cost-effective tool to quantitatively predict the toxicity of toxicants. Both OECD (Organization for Economic Co-operation and Development) and REACH (Registration, Evaluation and Authorization of Chemicals) legislation have promoted the use of QSAR as it can significantly reduce living animal testing. Although numerous QSAR studies have been conducted to evaluate the toxicity of NACs, systematic reviews related to the QSAR modeling of NACs toxicity are less reported. The purpose of this review is to provide a thorough summary of recent QSAR studies on the toxic effects of NACs according to the corresponding classes of toxic response endpoints.

QSAR and Chemical Read-Across Analysis of 370 Potential MGMT Inactivators to Identify the Structural Features Influencing Inactivation Potency

O6-methylguanine-DNA methyltransferase (MGMT) constitutes an important cellular mechanism for repairing potentially cytotoxic DNA damage induced by guanine O6-alkylating agents and can render cells highly resistant to certain cancer chemotherapeutic drugs. A wide variety of potential MGMT inactivators have been designed and synthesized for the purpose of overcoming MGMT-mediated tumor resistance. We determined the inactivation potency of these compounds against human recombinant MGMT using [3H]-methylated-DNA-based MGMT inactivation assays and calculated the IC50 values. Using the results of 370 compounds, we performed quantitative structure-activity relationship (QSAR) modeling to identify the correlation between the chemical structure and MGMT-inactivating ability. Modeling was based on subdividing the sorted pIC50 values or on chemical structures or was random. A total of nine molecular descriptors were presented in the model equation, in which the mechanistic interpretation indicated that the status of nitrogen atoms, aliphatic primary amino groups, the presence of O-S at topological distance 3, the presence of Al-O-Ar/Ar-O-Ar/R..O..R/R-O-C=X, the ionization potential and hydrogen bond donors are the main factors responsible for inactivation ability. The final model was of high internal robustness, goodness of fit and prediction ability (R2pr = 0.7474, Q2Fn = 0.7375-0.7437, CCCpr = 0.8530). After the best splitting model was decided, we established the full model based on the entire set of compounds using the same descriptor combination. We also used a similarity-based read-across technique to further improve the external predictive ability of the model (R2pr = 0.7528, Q2Fn = 0.7387-0.7449, CCCpr = 0.8560). The prediction quality of 66 true external compounds was checked using the "Prediction Reliability Indicator" tool. In summary, we defined key structural features associated with MGMT inactivation, thus allowing for the design of MGMT inactivators that might improve clinical outcomes in cancer treatment.

The Study of Spatial Safety and Social Psychological Health Features of Deaf Children and Children with an Intellectual Disability in the Public School Environment Based on the Visual Access and Exposure (VAE) Model

Nowadays, there is increasing attention towards the safety and feelings of children in urban or architectural space. In this study, the authors suggest a new approach based on the Visual Access and Exposure (VAE) Model to evaluate the spatial safety and social psychological health features of deaf children and children with an intellectual disability in the public school environment. The authors present a preliminary study of deaf children and children with an intellectual disability in a primary school located in Deyang by measuring the visual exposure and visual access in the public environment. The results illustrate that there are a few spaces, such as a long corridor and the space behind the elevators, that are not very safe for deaf children and children with an intellectual disability. In terms of social psychosocial preference, this special group prefers to stay in low visual access areas, which may be influenced by their introverted and impaired social communication ability. This study could have implications for the existence and optimization of an architecture design for relevant groups. With the increase in school bullying incidents and public psychological health problems related to youth, this approach could be used widely in the area of school safety and public psychological health management.

Logic Analysis of How the Emergency Management Legal System Used to Deal with Public Emerging Infectious Diseases under Balancing of Competing Interests-The Case of COVID-19

Development of measures for mitigating public emerging infectious diseases is now a focal point for emergency management legal systems. COVID-19 prevention and containment policies can be considered under the core goal of social and individual interests. In this study we analyzed the complexity between individual and public interests as they conflict when implementing disease preventative measures on an epidemic scale. The analysis was used to explore this complex landscape of conflicting social, public, and legal interests to quantify the potential benefits of public acceptance. Here we use the large-scale COVID-19 epidemic backdrop to examine legal norms of the emergency management legal framework. We find that the implementation of emergency management legal system measures involves the resolution of both direct and indirect conflicts of interest among public groups, individual groups, and various subsets of each. When competing interests are not balanced, optimal policies cannot be achieved to serve and safeguard shared social and community stability, whereas effective social outcomes are obtainable through the development of targeted policies as defined within the emergency management legal system. A balanced legal framework in regards to emergency management legal norms can more effectively serve to mitigate and prevent the continued spread of emerging infectious diseases. Further developing innovative procedural mechanisms as a means to ensure emergency response intervention should take into account the weighted interest of the different social parties to determine priorities and aims to protect legitimate public interests.

Using Grounded Theory to Identify Online Public Opinion in China to Improve Risk Management-The Case of COVID-19

BACKGROUND

During the outbreak of COVID-19, online public opinion related to the epidemic was rapidly generated and developed rapidly. If some online public opinions cannot be effectively responded to and guided, it will bring risks to social order. The government should understand how to use information on social media to grasp public demands, provide useful information in a timely manner and take countermeasures. Studying the formation mechanism of online public opinion during the outbreak can help the government make scientific decisions and improve risk management capabilities.

METHODS

The research selects the public opinion information of online platforms represented by WeChat, online communities, Sina Weibo and search engines, involving 75 relevant texts (1 January to 31 March 2022). According to the grounded theory method, using the QSR NVivo12 qualitative research software, the collected network texts were successively researched using open coding, axial coding and theoretical coding.

RESULTS

The structure of online public opinion during the COVID-19 epidemic was obtained. The operation mechanism of the online public opinion system about COVID-19 was mainly affected by the interaction of online public opinion objects, online public opinion subjects, online public opinion intermediaries and government forces. It was based on social facts and citizens' appeals as the starting point, subject behaviors and prevention and control measures as the focus, government's governance as macro-control and citizens' evaluation as the guide.

CONCLUSIONS

Scientific analysis of online public opinion is an important tool to identify and manage risks and improve the quality of government activities. Online public opinion has the function of assisting government decision-making, and the government can identify the important information reflected in it, especially the mainstream public opinion, as a reference for decision-making. By taking effective measures and properly responding to citizens' reasonable demands, the government can prevent social risks and avoid new negative public opinions. Contributions: According to the characteristics of the basic model of online public opinion, this study provides risk mitigation suggestions for Chinese public sectors to use online public opinion, optimize epidemic prevention policies and formulate strategic measures.

Lonidamine Increases the Cytotoxic Effect of 1-[(4-Amino-2-methyl-5-pyrimidinyl)methyl]-3-(2-chloroethyl)-3-nitrosourea via Energy Inhibition, Disrupting Redox Homeostasis, and Downregulating MGMT Expression in Human Lung Cancer Cell Line

Lung cancer ranks as the second most diagnosed cancer and the leading cause of cancer-related deaths worldwide. Novel chemotherapeutic strategies are crucial to efficiently target tumor cells while minimizing toxicity to normal cells. In this study, we proposed a combination strategy using energy blocker lonidamine (LND) and cytotoxic drug nimustine (ACNU, 1-[(4-amino-2-methyl-5-pyrimidinyl)methyl]-3-(2-chloroethyl)-3-nitrosourea) to enhance the killing of a human lung cancer cell line and investigated the potential chemo-sensitizing mechanism of LND. LND was found to remarkably increase the cytotoxicity of ACNU to A549 and H1299 cells without significantly affecting normal lung BEAS2B cells. The combination of LND and ACNU also produced significant effects on cell apoptosis, colony formation, cell migration, and invasion assays compared to single drug treatment. Mechanistically, LND decreased intracellular ATP levels by inhibiting glycolysis and inducing mitochondrial dysfunction. Furthermore, the combination of LND and ACNU could intensify cellular oxidative stress, decrease cellular GSH contents, and increase reactive oxygen species (ROS) production. Notably, LND alone dramatically downregulated the expression of DNA repair protein MGMT (O6-methylguanine-DNA methyltransferase), enhancing DNA interstrand cross-link formation induced by ACNU. Overall, LND represents a potential chemo-sensitizer to enhance ACNU therapy through energy inhibition, disrupting redox homeostasis and downregulating MGMT expression in human lung cancer cell line under preclinical and clinical background.

Molecular Toxicology and Cancer Prevention

Molecular toxicology is a field that investigates the interactions between chemical or biological molecules and organisms at the molecular level [...].

Energy Blocker Lonidamine Reverses Nimustine Resistance in Human Glioblastoma Cells through Energy Blockade, Redox Homeostasis Disruption, and O6-Methylguanine-DNA Methyltransferase Downregulation: In Vitro and In Vivo Validation

Tumor resistance seriously hinders the clinical application of chloroethylnitrosoureas (CENUs), such as O6-methylguanine-DNA methylguanine (MGMT), which can repair O6-alkyl lesions, thereby inhibiting the formation of cytotoxic DNA interstrand cross-links (ICLs). Metabolic differences between tumor and normal cells provide a biochemical basis for novel therapeutic strategies aimed at selectively inhibiting tumor energy metabolism. In this study, the energy blocker lonidamine (LND) was selected as a chemo-sensitizer of nimustine (ACNU) to explore its potential effects and underlying mechanisms in human glioblastoma in vitro and in vivo. A series of cell-level studies showed that LND significantly increased the cytotoxic effects of ACNU on glioblastoma cells. Furthermore, LND plus ACNU enhanced the energy deficiency by inhibiting glycolysis and mitochondrial function. Notably, LND almost completely downregulated MGMT expression by inducing intracellular acidification. The number of lethal DNA ICLs produced by ACNU increased after the LND pretreatment. The combination of LND and ACNU aggravated cellular oxidative stress. In resistant SF763 mouse tumor xenografts, LND plus ACNU significantly inhibited tumor growth with fewer side effects than ACNU alone. Finally, we proposed a new "HMAGOMR" chemo-sensitizing mechanism through which LND may act as a potential chemo-sensitizer to reverse ACNU resistance in glioblastoma: moderate inhibition of hexokinase (HK) activity (H); mitochondrial dysfunction (M); suppressing adenosine triphosphate (ATP)-dependent drug efflux (A); changing redox homeostasis to inhibit GSH-mediated drug inactivation (G) and increasing intracellular oxidative stress (O); downregulating MGMT expression through intracellular acidification (M); and partial inhibition of energy-dependent DNA repair (R).

Examining the Human Activity-Intensity Change at Different Stages of the COVID-19 Pandemic across Chinese Working, Residential and Entertainment Areas

The COVID-19 pandemic has already resulted in more than 6 million deaths worldwide as of December 2022. The COVID-19 has also been greatly affecting the activity of the human population in China and the world. It remains unclear how the human activity-intensity changes have been affected by the COVID-19 spread in China at its different stages along with the lockdown and relaxation policies. We used four days of Location-based services data from Tencent across China to capture the real-time changes in human activity intensity in three stages of COVID-19-namely, during the lockdown, at the first stage of work resuming and at the stage of total work resuming-and observed the changes in different land use categories. We applied the mean decrease Gini (MDG) approach in random forest to examine how these changes are influenced by land attributes, relying on the CART algorithm in Python. This approach was also compared with Geographically Weighted Regression (GWR). Our analysis revealed that the human activity intensity decreased by 22-35%, 9-16% and 6-15%, respectively, in relation to the normal conditions before the spread of COVID-19 during the three periods. The human activity intensity associated with commercial sites, sports facilities/gyms and tourism experienced the relatively largest contraction during the lockdown. During the relaxations of restrictions, government institutions showed a 13.89% rise in intensity at the first stage of work resuming, which was the highest rate among all the working sectors. Furthermore, the GDP and road junction density were more influenced by the change in human activity intensity for all land use categories. The bus stop density was importantly associated with mixed-use land recovery during the relaxing stages, while the coefficient of density of population in entertainment land were relatively higher at these two stages. This study aims to provide additional support to investigate the human activity changes due to the spread of COVID-19 at different stages across different sectors.

Recent advances in chemometric modelling of inhibitors against SARS-CoV-2

The outbreak of the novel coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused great harm to all countries worldwide. This disease can be prevented by vaccination and managed using various treatment methods, including injections, oral medications, or aerosol therapies. However, the selection of suitable compounds for the research and development of anti-SARS-CoV-2 drugs is a daunting task because of the vast databases of available compounds. The traditional process of drug research and development is time-consuming, labour-intensive, and costly. The application of chemometrics can significantly expedite drug R&D. This is particularly necessary and important for drug development against pandemic public emergency diseases, such as COVID-19. Through various chemometric techniques, such as quantitative structure-activity relationship (QSAR) modelling, molecular docking, and molecular dynamics (MD) simulations, compounds with inhibitory activity against SARS-CoV-2 can be quickly screened, allowing researchers to focus on the few prioritised candidates. In addition, the ADMET properties of the screened candidate compounds should be further explored to promote the successful discovery of anti-SARS-CoV-2 drugs. In this case, considerable time and economic costs can be saved while minimising the need for extensive animal experiments, in line with the 3R principles. This paper focuses on recent advances in chemometric modelling studies of COVID-19-related inhibitors, highlights current limitations, and outlines potential future directions for development.