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.

Small scale molecular network patterns and motifs are crucial for systems level understanding of cellular information transduction. Using randomizations, we statistically explored, previously overlooked basic patterns of mutually acting pairs, i.e. mutually positive (PP) or negative (NN) and positive-negative (PN) pairs, in two comprehensive and distinct large-scale molecular networks from literature; the human protein signaling network (PSN) and the human gene regulatory network (GRN). Only the positive and negative signs of all interacting pairs were randomized, while the gene pairs and the number of positive and negative signs in the original network were kept constant. While the numbers of NN and PN pairs were significantly higher, the number of PP pairs was significantly lower than randomly expected values. Genes participating in mutual pairs were more connected than other genes. NN genes were more connected than PP and PN in GRN for all types of degree values, including in, out, positive or negative connections, but less connected for in-degree and more connected for out-degree values in PSN. They also had significantly high number of intersections with each other and PN pairs than randomly expected values, indicating potential cooperative mechanisms. The three mutual interaction designs we examined had distinct RNA and protein expression correlation characteristics. NN protein pairs were uniquely over-represented across normal tissue samples, whose negative correlations were lost across cancer tissue samples. PP and PN pairs showed non-random positive RNA or protein expression correlation across normal or cancer tissue samples. Moreover, we developed an online tool, i.e. MGPNet, for further user specific analysis of mutual gene pairs. We identified SNCA with significantly enriched negatively correlated NN pairs. Unique non-random characteristics of mutual gene pairs identified in two different comprehensive molecular networks could provide valuable information for a better comparative understanding of molecular design principles between normal and cancer states. Insight Box/Paragraph Statement: This study provides a systems-level perspective on cellular information transduction by analyzing mutually acting pairs of genes. By examining mutually positive (PP), mutually negative (NN), and positive-negative (PN) pairs in the human protein signaling network (PSN) and the human gene regulatory network (GRN), we uncover significant variations in their connectivity and expression correlation. Our findings highlight the unique features of NN pairs across normal and cancer tissues and offer insights into molecular design principles. The development of the MGPNet tool further enhances user-specific analyses, enabling a deeper understanding of gene pair mechanisms and their potential cooperative roles in cellular processes.

Migration and scratch assays are helpful tools to investigate wound healing and tissue regeneration processes, especially under disease conditions such as diabetes. However, traditional migration (injury-free) assays and scratch (with injury) assays are limited in their control over cellular environments and provide only simplified read-outs of their results. On the other hand, microfluidic-based cell assays offer a distinct advantage in their integration and scalability for multiple modalities and concentrations in a single device. Additionally, in situ stimulation and detection helps to avoid variabilities between individual bioassays. To realize an enhanced, smarter migration assay, we leveraged our multilayered oxygen gradient (1%-16%) to study HaCaT migrations in diabetic conditions with spatial and metabolic read-outs. An analysis of spatial migration over time revealed a new dynamic between hypoxia (at 4.2%-9.1% O2) and hyperglycemia. Furthermore, in situ adenosine triphosphate (ATP) and reactive oxygen species (ROS) responses suggest that this dynamic represents a switch between stationary versus motile modes of metabolism. Thus, low glucose and hypoxia have synergistic effects promoting the migration of cells. These findings illustrate the benefits of spatial microfluidics for modeling complex diseases such as hypoxia and diabetes, where multimodal measurements provide a more deterministic view of the underlying processes.

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.