Frontiers in Molecular Biosciences最新文献

Objective: This study aims to perform a comprehensive bibliometric analysis of global research on BRAF and MEK inhibitor resistance in melanoma, identifying key research trends, influential contributors, and emerging themes from 2003 to 2024.

Methods: A systematic search was conducted in the Web of Science Core Collection (WoSCC) database to retrieve publications related to BRAF and MEK inhibitor resistance from 1 January 2003, to 1 September 2024. Bibliometric analyses, including publication trends, citation networks, and keyword co-occurrence patterns, were performed using VOSviewer and CiteSpace. Collaborative networks, co-cited references, and keyword burst analyses were mapped to uncover shifts in research focus and global cooperation.

Results: A total of 3,503 documents, including 2,781 research articles and 722 review papers, were analyzed, highlighting significant growth in this field. The United States, China, and Italy led in publication volume and citation impact, with Harvard University and the University of California System among the top contributing institutions. Research output showed three phases of growth, peaking in 2020. Keyword and co-citation analyses revealed a transition from early focus on BRAF mutations and MAPK pathway activation to recent emphasis on immunotherapy, combination therapies, and non-apoptotic cell death mechanisms like ferroptosis and pyroptosis. These trends reflect the evolving priorities and innovative approaches shaping the field of resistance to BRAF and MEK inhibitors in melanoma.

Conclusion: Research on BRAF and MEK inhibitor resistance has evolved significantly. This analysis provides a strategic framework for future investigations, guiding the development of innovative, multi-modal approaches to improve treatment outcomes for melanoma patients.

Introduction: Colorectal cancer (CRC) is characterized by an extremely high mortality rate, mainly caused by the high metastatic potential of this type of cancer. To date, chemotherapy remains the backbone of the treatment of metastatic colorectal cancer. Three main chemotherapeutic drugs used for the treatment of metastatic colorectal cancer are 5-fluorouracil, oxaliplatin and irinotecan which is metabolized to an active compound SN-38. The main goal of this study was to find the genes connected to the resistance to the aforementioned drugs and to construct a predictive gene expression-based classifier to separate responders and non-responders.

Methods: In this study, we analyzed gene expression profiles of seven patient-derived CRC organoids and performed correlation analyses between gene expression and IC50 values for the three standard-of-care chemotherapeutic drugs. We also included in the study publicly available datasets of colorectal cancer cell lines, thus combining two different in vitro models relevant to cancer research. Logistic regression was used to build gene expression-based classifiers for metastatic Stage IV and non-metastatic Stage II/III CRC patients. Prognostic performance was evaluated through Kaplan-Meier survival analysis and log-rank tests, while independent prognostic significance was assessed using multivariate Cox proportional hazards modeling.

Results: A small set of genes showed consistent correlation with resistance to chemotherapy across different datasets. While some genes were previously implicated in cancer prognosis and drug response, several were linked to drug resistance for the first time. The resulting gene expression signatures successfully stratified Stage II/III and Stage IV CRC patients, with potential clinical utility for improving treatment outcomes after further validation.

Discussion: This study highlights the advantages of integrating diverse experimental models, such as organoids and cell lines, to identify novel prognostic biomarkers and enhance the understanding of chemotherapy resistance in CRC.

Introduction: Gestational diabetes mellitus (GDM) is a global health concern with significant short and long-term complications for both mother and baby. Early prediction of GDM, particularly late-onset, is crucial for implementing timely interventions to mitigate adverse outcomes. In this study, we conducted a comprehensive metabolomic analysis to explore potential biomarkers for early GDM prediction.

Methods: Plasma samples were collected during the first trimester from 60 women: 20 with early-onset GDM, 20 with late-onset GDM, and 20 with normal glucose tolerance. Using advanced analytical techniques, including liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-mass spectrometry (GC-MS), we profiled over 150 lipid species and central carbon metabolism intermediates.

Results: Significant metabolic alterations were observed in both early- and late-onset GDM groups compared to healthy controls, with a specific focus on glycerolipids, fatty acids, and glucose metabolism. Key findings revealed a 4.0-fold increase in TG(44:0), TG(46:0), TG(46:1) with p-values <0.001 and TG(46:2) with 4.7-fold increase and p-value <0.0001 as well as changes in several phospholipids as PC(38:3), PC(40:4) with 1.4-fold increase, p < 0.001 and PE(34:1), PE(34:2) and PE(36:2) with 1.5-fold change, p < 0.001 in late-onset GDM.

Discussion: Observed lipid changes highlight disruptions in energy metabolism and inflammatory pathways. It is suggested that lipid profiles with distinct fatty acid chain lengths and degrees of unsaturation can serve as early biomarkers of GDM risk. These findings underline the importance of integrating metabolomic insights with clinical data to develop predictive models for GDM. Such models could enable early risk stratification, allowing for timely dietary, lifestyle, or medical interventions aimed at optimizing glucose regulation and preventing complications such as preeclampsia, macrosomia, and neonatal metabolic disorders. By focusing on metabolic disruptions evident in the first trimester, this approach addresses a critical window for improving maternal and fetal outcomes. Our study demonstrates the value of metabolomics in understanding the metabolic perturbations associated with GDM. Future research is needed to validate these biomarkers in larger cohorts and assess their integration into clinical workflows for personalized pregnancy care.

Introduction: Current in vitro intestinal models lack the mechanical forces present in the physiological environment, limiting their reliability for nanotoxicology studies. Here, we developed an enhanced Caco-2/HT29-MTX-E12 co-culture model incorporating orbital mechanical stimulation to better replicate intestinal conditions and investigate nanoparticle interactions.

Methods: We established co-cultures under static and dynamic conditions, evaluating their development through multiple approaches including barrier integrity measurements, gene expression analysis, and confocal microscopy. We introduced novel quantitative analysis of dome formation as a differentiation marker and demonstrated the model application by investigating cellular responses to titanium dioxide (TiO₂) nanoparticles in a digested food matrix.

Results: Dynamic conditions accelerated epithelial differentiation, achieving functional barrier properties by day 14 rather than day 21, with enhanced mucin production and more organized three-dimensional structure. Mechanical stimulation selectively promoted goblet cell differentiation without affecting general epithelial markers. The optimized model successfully detected concentration-dependent oxidative stress responses to TiO₂ exposure, revealing cellular dysfunction preceding membrane damage.

Discussion: This improved co-culture system provides a better physiological platform for nanotoxicology studies. By incorporating mechanical forces, each cell type exhibits more representative behavior, creating a more realistic experimental setup. The model bridges the gap between simple monocultures and complex 3D systems, offering a practical approach for investigating nanoparticle-epithelium interactions in a food-relevant context.

Background: Breast cancer is one of the most prevalent malignancies and a leading cause of death among women worldwide. Among its subtypes, triple-negative breast cancer (TNBC) poses significant clinical challenges due to its aggressive behavior and limited treatment options. This study aimed to investigate the effects of doxorubicin (DOX) and 5-fluorouracil (5-FU) as monotherapies and in combination using an established MDA-MB-231 xenograft model in female BALB/C nude mice employing advanced metabolomics analysis to identify molecular alterations induced by these treatments.

Methods: We conducted comprehensive plasma and tumor tissue sample profiling using ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS).

Results: Each treatment group exhibited unique metabolic profiles in plasma and tumor analysis. Univariate and enrichment analyses identified alterations in metabolic pathways. The combination treatment of DOX + 5-FU induced the most extensive metabolic alterations disrupting key pathways including purine, pyrimidine, beta-alanine, and sphingolipid metabolism. It significantly reduced critical metabolites such as guanine, xanthine, inosine, L-fucose, and sphinganine, demonstrating enhanced cytotoxic effects compared to individual treatments. The DOX treatment uniquely increased ornithine levels, while 5-FU altered sphingolipid metabolism, promoting apoptosis.

Significance: This in vivo study highlights TNBC's metabolic alterations to chemotherapeutics, identifying potential biomarkers like L-fucose and beta-alanine, and provides insights for improving treatment strategies.

Background: Polycystic ovary syndrome (PCOS) is a common endocrine and metabolic condition impacting millions of women worldwide. This study sought to identify granulosa cell endoplasmic reticulum stress (GCERS)-related differentially expressed genes (DEGs) between women with PCOS and those without PCOS using bioinformatics and to investigate the related molecular mechanisms.

Methods: Two datasets were downloaded from GEO and analysed using the limma package to identify DEGs in two groups-PCOS and normal granulosa cells. Enrichment analyses, including GO, KEGG, and GSEA, were then conducted on the DEGs. Differential immune infiltration was assessed using CIBERSORT and correlations with immune cell biomarkers were evaluated. Networks for protein-protein interactions, transcription factor-target genes, miRNA-target genes, and drug-target genes were constructed and visualized using Cytoscape to identify key hub gene nodes. Finally, key genes were analysed for differential expression and correlated.

Results: Overall, 127 co-DEGs were identified in the two datasets. Our study revealed that these DEGs were primarily associated with cell cycle arrest, p53-mediated signal transduction, drug response, and gland development, with molecular functions enriched in growth factor binding, collagen binding, and receptor protein kinase activity. GSEA revealed that the co-DEGs were primarily associated with immune and inflammatory pathways. Eleven hub genes-MMP9, SPI1, IGF2R, GPBAR1, PDGFA, BMPR1A, LIFR, PRKAA1, MSH2, CDC25C, and KCNH2-were identified through the PPI, TF target genes, miRNA target genes, and drug target gene networks.

Conclusion: We identified several crucial genes and pathways linked to the onset and development of PCOS. Our findings offer a clear connection between PCOS and GCERS, clarify the molecular mechanisms driving PCOS progression, and offer new perspectives for discovering valuable therapeutic targets and potential biomarkers for the condition.

Lysine lactylation is a newly discovered protein post-translational modification that plays regulatory roles in cell metabolism, growth, reprogramming, and tumor progression. It utilizes lactate as the modification precursor, which is an end product of glycolysis while functioning as a signaling molecule in cells. Unlike previous reviews focused primarily on eukaryotes, this review aims to provide a comprehensive summary of recent knowledge about lysine lactylation in prokaryotes and eukaryotes. The current identification and enrichment strategies for lysine lactylation are introduced, and the known readers, writers, and erasers of this modification are summarized. In addition, the physiological and pathological implications of lysine lactylation are reviewed for different organisms, especially in prokaryotic cells. Finally, we end with a discussion of the limitations of the studies so far and propose future directions for lysine lactylation investigations.

This study investigates the dynamics of oleate hydratase (OhyA), a bacterial flavoenzyme from Staphylococcus aureus, and its interactions with lipid membranes, focusing on the factors influencing membrane binding and oligomerization. OhyA catalyzes the hydration of unsaturated fatty acids, playing a key role in bacterial pathogenesis by neutralizing host antimicrobial fatty acids. OhyA binds the membrane bilayer to access membrane-embedded substrates for catalysis, and structural studies have revealed that OhyA forms oligomers on membrane surfaces, stabilized by both protein-protein and protein-lipid interactions. Using fluorescence correlation spectroscopy (FCS), we examined the effects of membrane curvature and lipid availability on OhyA binding to phosphatidylglycerol unilamellar vesicles. Our results reveal that OhyA preferentially binds to vesicles with moderate curvature, while the presence of substrate fatty acids slightly enhanced the overall interaction despite reducing the binding affinity by 3- to 4-fold. Complementary phosphorus-31 (³¹P) NMR spectroscopy further demonstrated two distinct binding modes: a fast-exchange interaction at lower protein concentrations and a longer lasting interaction at higher protein concentrations, likely reflecting cooperative oligomerization. These findings highlight the reversible, non-stoichiometric nature of OhyA•membrane interactions, with dynamic binding behaviors influenced by protein concentration and lipid environment. This research provides new insights into the dynamic behavior of OhyA on bacterial membranes, highlighting that initial interactions are driven by lipid-mediated protein binding, while sustained interactions are primarily governed by the protein:lipid molar ratio rather than the formation of new, specific lipid-protein interactions. These findings advance our understanding of the biophysical principles underlying OhyA's role in bacterial membrane function and virulence.

Molecular motors are the cornerstone for the maintenance of living systems and mediate almost all fundamental processes involved in cellular trafficking. The intricate mechanisms underlying natural molecular motors have been elucidated in detail, inspiring researchers in various fields to construct artificial systems with multi-domain applications. This review summarises the characteristics of molecular motors, biomimetic approaches for their design and operation, and recent biological applications.

Olfactory receptors, classified as G-protein coupled receptors (GPCRs), have been a subject of scientific inquiry since the early 1950s. Historically, investigations into the sensory mechanisms of olfactory receptors were often confined to behavioral characteristics in model organisms or the expression of related proteins and genes. However, with the development of cryo-electron microscopy techniques, it has gradually become possible to decipher the specific structures of olfactory receptors in insects and humans. This has provided new insights into the binding mechanisms between odor molecules and olfactory receptors. Furthermore, due to the rapid advancements in related fields such as computer simulations, the prediction and exploration of odor molecule binding to olfactory receptors have been progressively achieved through molecular dynamics simulations. Through this comprehensive review, we aim to provide a thorough analysis of research related to the binding mechanisms between odor molecules and olfactory receptors from the perspectives of structural biology and molecular dynamics simulations. Finally, we will provide an outlook on the future of research in the field of olfactory receptor sensory mechanisms.