Integrative Biology最新文献

Integrins are transmembrane receptors that play a crucial role in cell adhesion and signaling by connecting the extracellular environment to the intracellular cytoskeleton. After binding with specific ligands in the extracellular matrix (ECM), integrins undergo conformational changes that transmit signals across the cell membrane. The integrin-mediated bidirectional signaling triggers various cellular responses, such as changes in cell shape, migration and proliferation. Irregular integrin expression and activity are closely linked to tumor initiation, angiogenesis, cell motility, invasion, and metastasis. Thus, understanding the intricate regulatory mechanism is essential for slowing cancer progression and preventing carcinogenesis. Among the four classes of integrins, the arginine-glycine-aspartic acid (RGD)-binding integrins stand out as the most crucial integrin receptor subfamily in cancer and its metastasis. Dysregulation of almost all RGD-binding integrins promotes ECM degradation in ovarian cancer, resulting in ovarian carcinoma progression and resistance to therapy. Preclinical studies have demonstrated that targeting these integrins with therapeutic antibodies and ligands, such as RGD-containing peptides and their derivatives, can enhance the precision of these therapeutic agents in treating ovarian cancer. Therefore, the development of novel therapeutic agents is essential for treating ovarian cancer. This review mainly discusses genes and their importance across different ovarian cancer subtypes, the involvement of RGD motif-containing ECM proteins in integrin-mediated signaling in ovarian carcinoma, ongoing, completed, partially completed, and unsuccessful clinical trials of therapeutic agents, as well as existing limitations and challenges, advancements made so far, potential strategies, and directions for future research in the field. Insight Box Integrin-mediated signaling regulates cell migration, proliferation and differentiation. Dysregulated integrin expression and activity promote tumor growth and dissemination. Thus, a proper understanding of this complex regulatory mechanism is essential to delay cancer progression and prevent carcinogenesis. Notably, integrins binding to RGD motifs play an important role in tumor initiation, evolution, and metastasis. Preclinical studies have demonstrated that therapeutic agents, such as antibodies and small molecules with RGD motifs, target RGD-binding integrins and disrupt their interactions with the ECM, thereby inhibiting ovarian cancer proliferation and migration. Altogether, this review highlights the potential of RGD-binding integrins in providing new insights into the progression and metastasis of ovarian cancer and how these integrins have been utilized to develop effective treatment plans.

The role of GTF2I (General Transcription Factor2I) alteration has already been reported in thymic cancer as a valuable biomarker. However, the association of GTF2I mutation with renal cancer for prognosis of immunotherapy is not yet examined. The biologic and oncologic significance of GTF2I in renal cancer was examined at multiomics level such as mutation, copy number alteration, structural variants. The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA) were used to retrieve the omics data. The expression of GTF2I mRNA was quite significant in case of renal caner. Correlation among the GTF2I mRNA, mutation, CNA and structural variants was also studied. Interactome of GTF2I was also constructed using STRING database. Gain, amplification, and missense mutation exhibited a positive correlation between GTF2I mRNA expression and non-structural variants. Similarly, GTF2I mRNA expression and copy number alterations from GISTIC were positively correlated. High expression of GTF2I was associated with better overall survival indicating the less aggressive clinical features. Insight Box Investigating GTF2I's complex function as a tumor suppressor transcription factor in renal carcinoma provides fresh insights into its biologic and oncologic importance, especially when considering the prognosis of immunotherapy. Little is known about its possible use as a biomarker for renal cancer. Using a multiomics approach and utilizing information from the Human Protein Atlas (HPA) and The Cancer Genome Atlas (TCGA), our study clarifies the intricate relationship between mRNA expression, GTF2I changes, and clinical outcomes in renal cancer. Our results indicate that GTF2I expression may be used as a prognostic indicator because it is positively correlated with favorable survival outcomes. Furthermore, the molecular interactions behind GTF2I's functional significance in renal cancer are revealed by interactome analysis utilizing the STRING database, providing important information for further study and treatment approaches.

Purpose: To develop efficient diagnostic and treatment approaches, gaining an in-depth knowledge of the molecular mechanisms and potential targets causing childhood asthma is of utmost significance.

Methods: Childhood asthma datasets were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between asthmatic child and healthy people were screened by the Limma package. DEGs were subjected to further analyses utilizing GO, KEGG and GSEA analysis. The hub genes associated with childhood asthma were discovered by PPI analysis. The drugs target hub genes were accessed from the DrugBank database. Autodock vina was used to explore the binding ability of targeted drugs to hub genes.

Results: Total 80 DEGs were selected from GSE152004 and GSE65204 datasets. The cytokine-cytokine receptor interaction was the key pathway identified by functional enrichment analysis of shared DEGs. A total of 4 hub genes (CCL26, CXCR6, IL18RAP and CCL20) were identified by the constructed PPI network, among which CXCR6, IL18RAP and CCL20 were significantly decreased in childhood asthma datasets. Whereas, the CCL26 was significantly increased in childhood asthma datasets. Additionally, the extra dataset GSE19187 and GSE240567 were employed for validation. Ultimately, drugs (Cimetidine, Cefaclor and Propofol) that target hub genes have favorable combination ability.

Conclusions: We have determined that CCL26, CXCR6, IL18RAP and CCL20 might have crucial involvement in the advancement of childhood asthma, thus having the potential to be targeted therapeutically in order to enhance treatment choices for childhood asthma. Statement of Integration, Innovation and Insight: The cytokine-cytokine receptor interaction is a key pathway in the occurrence of childhood asthma. The hub genes (CCL26, CXCR6, IL18RAP and CCL20) affect the development of childhood asthma. The drugs (Cimetidine, Cefaclor and Propofol) that target hub genes have favorable combination ability.

Neurodegenerative disorders are characterised by progressive damage to neurons that leads to cognitive impairment and motor dysfunction. Current treatment options focus only on symptom management and palliative care, without addressing their root cause. In our previous study, we reported the upregulation of the CXC motif chemokine receptor 4 (CXCR4), in Alzheimer's disease (ad) and Parkinson's disease (PD). We reached this conclusion by analysing gene expression patterns of ad and PD patients, compared to healthy individuals of similar age. We used RNA sequencing data from Gene Expression Omnibus to carry out this analysis. Herein, we aim to identify natural compounds that have potential inhibitory activity against CXCR4 through cheminformatics-guided machine learning, to aid drug discovery for neurodegenerative disorders, especially ad and PD. Natural compounds are gaining prominence in the treatment of neurodegenerative disorders due to their biocompatibility and potential neuroprotective properties, including their ability to modulate CXCR4 expression. Recent advances in artificial intelligence (AI) and machine learning (ML) algorithms have opened new avenues for drug discovery research across various therapeutic areas, including neurodegenerative disorders. We aim to produce an ML model using cheminformatics-guided machine learning algorithms using data of compounds with known CXCR4 activity, retrieved from the Binding Database, to analyse various physicochemical attributes of natural compounds obtained from the COCONUT Database and predict their inhibitory activity against CXCR4. Insight Box This work extends our previous study published in Integrative Biology (DOI: 10.1093/intbio/zyad012). We aim to demonstrate the effectiveness of AI and ML in identifying potential treatment options for Alzheimer's and Parkinson's diseases. By analysing vast amounts of data and identifying patterns that may not be apparent to human researchers, AI-powered systems can provide valuable insight into potential treatment options that may have been overlooked through traditional research methods. Our study underscores the significance of interdisciplinary collaboration between computational and experimental scientists in drug discovery and in developing a robust pipeline to identify potential leads for drug development.

A critical phase of wound healing is the coordinated movement of keratinocytes. To this end, bioglasses show promise in speeding healing in hard tissues and skin wounds. Studies suggest that bioglass materials may promote wound healing by inducing positive cell responses in proliferation, growth factor production, expression of angiogenic factors, and migration. Precise details of how bioglass may stimulate migration are unclear, however, because the common assays for studying migration in wound healing focus on simplified outputs like rate of migration or total change in wound area. These outputs are limited in that they represent the average behavior of the collective, with no connection between the motion of the individual cells and the collective wound healing response. There is a need to apply more refined tools that identify how the motion of the individual cells changes in response to perturbations, such as by bioglass, and in turn affects motion of the cell collective. Here, we apply an integrative biology strategy that combines an in vitro wound healing assay using primary neonatal human keratinocytes with time lapse microscopy and quantitative image analysis. The resulting data set provides the cell velocity field, from which we define key metrics that describe cooperative migration phenotypes. Treatment with growth factors led to faster single-cell speeds compared to control, but the migration was not cooperative, with cells breaking away from their neighbors and migrating as individuals. Treatment with calcium or bioglass led to migration phenotypes that were highly collective, with greater coordination in space compared to control. We discuss the link between bioglass treatment and observed increases in free calcium ions that are hypothesized to promote these distinct coordinated behaviors in primary keratinocytes. These findings have been enabled by the unique descriptors developed through applying image analysis to interpret biological response in migration models. Insight Box/Paragraph Statement: Bioglasses are important materials for tissue engineering and have more recently shown promise in skin and wound healing by mechanisms tied to their unique ionic properties. The precise details, however, of how cell migration may be affected by bioglass are left unclear by traditional cell assay methods. The following describes the integration of migration assays of keratinocytes, cells critical for skin and wound healing, with the tools of time lapse microscopy and image analysis to generate a quantitative description of coordinated, tissue-like migration behavior, stimulated by bioglass, that would not have been accessible without the combination of these analytical tools.

Mechanical forces are of major importance in regulating vascular homeostasis by influencing endothelial cell behavior and functions. Adherens junctions are critical sites for mechanotransduction in endothelial cells. β-catenin, a component of adherens junctions and the canonical Wnt signaling pathway, plays a role in mechanoactivation. Evidence suggests that β-catenin is involved in flow sensing and responds to tensional forces, impacting junction dynamics. The mechanoregulation of β-catenin signaling is context-dependent, influenced by the type and duration of mechanical loads. In endothelial cells, β-catenin's nuclear translocation and signaling are influenced by shear stress and strain, affecting endothelial permeability. The study investigates how shear stress, strain, and surface topography impact adherens junction dynamics, regulate β-catenin localization, and influence endothelial barrier properties. Insight box Mechanical loads are potent regulators of endothelial functions through not completely elucidated mechanisms. Surface topography, wall shear stress and cyclic wall deformation contribute overlapping mechanical stimuli to which endothelial monolayer respond to adapt and maintain barrier functions. The use of custom developed flow chamber and bioreactor allows quantifying the response of mature human endothelial to well-defined wall shear stress and gradients of strain. Here, the mechanoregulation of β-catenin by substrate topography, wall shear stress, and cyclic stretch is analyzed and linked to the monolayer control of endothelial permeability.

Breast cancer, more prevalent in women, often arises due to abnormalities in the MRN-checkpoint sensor genes (MRN-CSG), responsible for DNA damage detection and repair. Abnormality in this complex is due to the suppression of various effectors such as siRNAs, miRNAs, and transcriptional factors responsible for breast tumor progression. This study analyzed breast tumor samples (n = 60) and identified four common miRNAs (miR-1-3p, miR-210-3p, miR-16-5p, miR-34a-5p) out of 12, exploring their interactions with MRN-CSG. The 3D structures of these miRNA-MRN-CSG complexes displayed strong thermodynamic stability. Screening 7711 natural compounds resulted in two natural compounds (F0870-0001 and F0922-0471) with the lowest ligand binding energies (ΔG = -8.4 to-11.6 kcal/mol), targeting two common miRNAs. Docking results showed that one natural compound (PubChem id-5 281 614) bound to all MRN-CSG components (ΔG = -6.2 to -7.3 kcal/mol), while F6782-0723 bound only to RAD50 and NBN. These compounds exhibited minimal dissociation constants (Kd and Ki) and thermodynamically stable minimum free energy (MMGBSA) values. Molecular dynamics simulations indicated highly stable natural compound-MRN-CSG complexes, with consistent RMSD, RMSF, and strong residual correlation. These top-selected compounds displayed robust intermolecular H-bonding, low carcinogenicity, low toxicity, and drug-like properties. Consequently, these compounds hold promise for regulating miRNA and MRN-CSG DNA repair mechanisms in breast cancer therapy. Insight Box: This study investigated breast tumor samples (n = 60) and identified four miRNAs (miR-1-3p, miR-210-3p, miR-16-5p, miR-34a-5p) that interact with MRN-checkpoint sensor genes (MRN-CSG), crucial for DNA damage repair. Screening 7711 natural compounds highlighted two compounds (F0870-0001 and F0922-0471) with the lowest binding energies (ΔG = -8.4 to -11.6 kcal/mol), targeting two common miRNAs (miR-1-3p and miR-34a-5p). Another natural compound (PubChem id-5 281 614, ΔG = -6.2 to -7.3 kcal/mol) bound all MRN-CSG components, while F6782-0723 targeted RAD50 and NBN. These compounds showed strong binding stability, favorable MMGBSA values, and minimal dissociation constants. Molecular dynamics simulations confirmed the stability and drug-like properties of these compounds, indicating their potential in breast cancer therapy by modulating miRNA and MRN-CSG DNA repair mechanisms.

Cosmic radiation, composed of high charge and energy (HZE) particles, causes cellular DNA damage that can result in cell death or mutation that can evolve into cancer. In this work, a cell death model is applied to several cell lines exposed to HZE ions spanning a broad range of linear energy transfer (LET) values. We hypothesize that chromatin movement leads to the clustering of multiple double strand breaks (DSB) within one radiation-induced foci (RIF). The survival probability of a cell population is determined by averaging the survival probabilities of individual cells, which is function of the number of pairwise DSB interactions within RIF. The simulation code RITCARD was used to compute DSB. Two clustering approaches were applied to determine the number of RIF per cell. RITCARD outputs were combined with experimental data from four normal human cell lines to derive the model parameters and expand its predictions in response to ions with LET ranging from ~0.2 keV/μm to ~3000 keV/μm. Spherical and ellipsoidal nuclear shapes and two ion beam orientations were modeled to assess the impact of geometrical properties on cell death. The calculated average number of RIF per cell reproduces the saturation trend for high doses and high-LET values that is usually experimentally observed. The cell survival model generates the recognizable bell shape of LET dependence for the relative biological effectiveness (RBE). At low LET, smaller nuclei have lower survival due to increased DNA density and DSB clustering. At high LET, nuclei with a smaller irradiation area-either because of a smaller size or a change in beam orientation-have a higher survival rate due to a change in the distribution of DSB/RIF per cell. If confirmed experimentally, the geometric characteristics of cells would become a significant factor in predicting radiation-induced biological effects. Insight Box: High-charge and energy (HZE) ions are characterized by dense linear energy transfer (LET) that induce unique spatial distributions of DNA damage in cell nuclei that result in a greater biological effect than sparsely ionizing radiation like X-rays. HZE ions are a prominent component of galactic cosmic ray exposure during human spaceflight and specific ions are being used for radiotherapy. Here, we model DNA damage clustering at sub-micrometer scale to predict cell survival. The model is in good agreement with experimental data for a broad range of LET. Notably, the model indicates that nuclear geometry and ion beam orientation affect DNA damage clustering, which reveals their possible role in mediating cell radiosensitivity.

Oxygen levels vary in the environment. Oxygen availability has a major effect on almost all organisms, and oxygen is far more than a substrate for energy production. However, less is known about related biological processes under hypoxic conditions and about the adaptations to changing oxygen concentrations. The yeast Saccharomyces cerevisiae can adapt its metabolism for growth under different oxygen concentrations and can grow even under anaerobic conditions. Therefore, we developed a microfluidic device that can generate serial, accurately controlled oxygen concentrations for single-cell studies of multiple yeast strains. This device can construct a broad range of oxygen concentrations, [O2] through on-chip gas-mixing channels from two gases fed to the inlets. Gas diffusion through thin polydimethylsiloxane (PDMS) can lead to the equilibration of [O2] in the medium in the cell culture layer under gas cover regions within 2 min. Here, we established six different and stable [O2] varying between ~0.1 and 20.9% in the corresponding layers of the device designed for multiple parallel single-cell culture of four different yeast strains. Using this device, the dynamic responses of different yeast transcription factors and metabolism-related proteins were studied when the [O2] decreased from 20.9% to serial hypoxic concentrations. We showed that different hypoxic conditions induced varying degrees of transcription factor responses and changes in respiratory metabolism levels. This device can also be used in studies of the aging and physiology of yeast under different oxygen conditions and can provide new insights into the relationship between oxygen and organisms. Integration, innovation and insight: Most living cells are sensitive to the oxygen concentration because they depend on oxygen for survival and proper cellular functions. Here, a composite microfluidic device was designed for yeast single-cell studies at a series of accurately controlled oxygen concentrations. Using this device, we studied the dynamic responses of various transcription factors and proteins to changes in the oxygen concentration. This study is the first to examine protein dynamics and temporal behaviors under different hypoxic conditions at the single yeast cell level, which may provide insights into the processes involved in yeast and even mammalian cells. This device also provides a base model that can be extended to oxygen-related biology and can acquire more information about the complex networks of organisms.