Search Results (23)

Background: Hippocampal neurogenesis in the dentate gyrus persists into adulthood and plays a crucial role in learning and memory. Early-life exposure to low-dose propofol has been reported to enhance neural development in rodent models, but detailed mechanisms remain unclear. To address this gap, we aimed to investigate how low-dose propofol alters neurogenic lineage differentiation, transcriptional programs, and underlying molecular mechanisms within the early postnatal hippocampal neurogenic niche. Results: We conducted an in-depth re-analysis of a published single-nucleus RNA-sequencing (snRNA-seq) dataset from hippocampal tissue of postnatal day 10 (PND10) mice, collected 3 days after low-dose propofol treatment. Uniform Manifold Approximation and Projection (UMAP)-based clustering revealed twelve major cell types, including a population of Ntng1⁺Fxyd7⁺Pcp1⁺ immature pyramidal neurons (imPYR), lacking the mature markers Meis2 and Spock1. Trajectory analysis revealed two neurogenic lineages (granule and pyramidal) and indicated that propofol biases progenitor fate commitment towards the granule lineage. CellChat analysis demonstrated that propofol enhances Neurexin (Nrxn) signaling to neural progenitor cells, suggesting increased synaptic adhesion and maturation. Differential expression analysis (|log₂FC| ≥ 0.26, adjusted p < 0.01) followed by pathway enrichment revealed that propofol upregulates neurogenic maturation pathways—including synaptogenesis, synaptic transmission, dendritic morphogenesis, and memory-related processes—specifically within neural intermediate progenitor cells (nIPC). Conclusions: Together, these findings delineate a coordinated transcriptional and intercellular mechanism by which low-dose propofol reprograms hippocampal neurogenesis during early postnatal development, highlighting progenitor-specific and synapse-oriented processes that may underlie its cognitive-enhancing effects. Full article

Sepsis is a severe systemic response to infection that may lead to the dysfunction of multiple organ systems and may even be life-threatening. Circadian rhythm-related genes (CRDRGs) regulate the circadian clock and affect many physiological processes, including immune responses. In patients with sepsis, circadian rhythms may be disrupted, thus leading to problems such as immune responses. RNA-seq datasets of sepsis and control groups were downloaded from the Gene Expression Omnibus (GEO) database, and two sepsis subtypes were identified based on differentially expressed CRDRGs. Two gene modules related to sepsis diagnosis and subtypes were obtained using the weighted co-expression network (WGCNA) algorithm. Subsequently, using four machine learning algorithms (random forest, support vector machine, a generalized linear model, and xgboost), genes related to sepsis diagnosis were identified from the intersection genes of the two modules, and a diagnostic model was constructed. Single-cell sequencing (scRNA-seq) data were obtained from the GEO database to explore the expression landscape of diagnostic-related genes in different cell types. Finally, an RT-qPCR analysis of diagnosis-related genes confirmed the differences in expression trends between the two groups. Multiple differentially expressed CRDRGs were observed in the sepsis and control groups, and two subtypes were identified based on their expression levels. There were apparent differences in the distribution of samples of the two subtypes in two-dimensional space and the pathways involved. Using multiple machine learning algorithms, the intersection genes in the two most relevant modules of the WGCNA were identified, and a robust diagnostic model was constructed with five genes (ARHGEF18, CHD3, PHC1, SFI1, and SPOCK2). The AUC of this model reached 0.987 on the validation set, showing an excellent prediction performance. In this study, two sepsis subtypes were identified, and a sepsis diagnostic model was constructed via consensus clustering and machine learning algorithms. Five genes were identified as diagnostic markers for sepsis and can thus assist in clinical diagnosis and guide personalized treatment. Full article

Background: Sparc/osteonectin, cwcv, and kazal-like domains proteoglycan 1 (SPOCK1) is an oncogene that promotes tumor formation and progression in certain types of cancer and is associated with poor survival rates. However, there is limited information on the importance of SPOCK1 in gynecological cancers in the literature. The aim of this study was to explore the role of SPOCK1 in ovarian serous cystadenocarcinoma (OV), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), and uterine corpus endometrial carcinomas (UCEC). Methods: The data used in this study were obtained from the GEPIA2, TCGA, Kaplan–Meier Plotter, GeneMANIA, UALCAN, cBioPortal, and TIMER databases. Overall survival (OS) and relapse-free survival (RFS) rates were evaluated by Kaplan–Meier survival analysis. Spearman’s rho and statistical significance values were obtained for the correlation between SPOCK1 expression and tumor infiltration by different immune cells. Results: Lower SPOCK1 gene expression was observed in CESC and UCEC compared to normal tissue (p < 0.05), but the OV did not differ significantly (p > 0.05). In OV, SPOCK1 gene expression was solely linked to age; in CESC, it was linked to age, stage, weight, and histology; and in UCEC, it was linked to age, stage, weight, and menopausal status. Conclusions:SPOCK1 gene expression in UCEC showed weak positive correlations with CD8+ T cells and weak negative correlations with CD4+ T cells. SPOCK1 may be a potential prognostic and therapeutic target for gynecological cancers. Full article

Background: Lung cancer, including the major subtype lung adenocarcinoma (LUAD), is the leading cause of cancer deaths worldwide, largely due to metastasis. Improving survival rates requires new treatment strategies and a deeper understanding of the mechanisms that drive tumor progression within the tumor microenvironment (TME). This study investigated the impact of extracellular vesicles (EVs) derived from LUAD cells on lung fibroblasts. Methods: EVs were isolated from LUAD cell lines via ultracentrifugation and characterized using nanoparticle tracking analysis and Western blotting. Lung fibroblasts were treated with PBS, TGFβ, or EVs, and their activation was assessed through protein (Western blotting) and RNA analyses (RNA seq and RT-qPCR). Results: The results confirmed the TGFβ induced activation and showed that LUAD EVs could also activate fibroblasts, increasing cancer-associated fibroblast (CAF) markers. While EV-induced CAF activation displayed unique features, like an increase in proliferation-related genes, the EV and TGFβ treatments also shared some differentially expressed genes. The EV groups induced a higher expression of ECM remodeling and EMT-associated genes, but some of those genes were also upregulated in the TGFβ group. Mesenchymal genes POSTN and SPOCK1 were significantly upregulated in TGFβ- and EV-treated fibroblasts. Their secretion as proteins from the TGFβ- and EV-induced CAFs was not significant, confirmed through ELISA. Conclusions: These findings suggest that LUAD EVs play a role in CAF activation through both shared and distinct pathways compared to canonical TGFβ activation, potentially identifying novel gene expressions involved in CAF activation. Additionally, optimal protein secretion conditions of confirmed CAF-upregulated genes need to be established to determine their contribution to the TME. Full article

Aortic dissection (AD) is a life-threatening acute aortic syndrome. There are limitations and challenges in the discovery and application of biomarkers and drug targets for AD. Mendelian randomization (MR) analysis is a reliable analytical method to identify effective therapeutic targets. We aimed to identify novel therapeutic targets for AD and investigate their potential side-effects based on MR analysis. Data from protein quantitative trait loci (pQTLs) were used for MR analyses to identify potential therapeutic targets. We probed druggable proteins involved in the pathogenesis of aortic dissection from deCODE. In this study, a two-sample MR analysis was conducted, with druggable proteins as the exposure factor and data on genome-wide association studies (GWAS) of AD as the outcome. After conducting a two-sample MR, summary data-based Mendelian randomization (SMR) analysis and colocalization analysis were performed. A protein–protein interaction (PPI) network was also constructed to delve into the interactions between identified proteins. After MR analysis and the Steiger test, we identified five proteins as potential therapeutic targets for AD. SMR analysis and colocalization analysis also confirmed our findings. Finally, we identified ASPN (OR = 1.36, 95% CI: 1.20, 1.54, p = 4.22 × 10⁻⁵) and SPOCK2 (OR = 0.57, 95% CI: 0.41, 0.78, p = 4.52 × 10⁻⁴) as the core therapeutic targets. Through PPI network analysis, we identified six druggable targets, enabling the subsequent identification of six promising drugs from DrugBank for treating AD. This discovery of specific proteins as novel therapeutic targets represents a significant advancement in AD treatment. These findings provide more effective treatment options for AD. Full article

Purpose: Pancreatic cancer (PACA) is one of the most fatal malignancies worldwide. Immunotherapy is largely ineffective in patients with PACA. T-cell exhaustion contributes to immunotherapy resistance. We investigated the prognostic potential of T-cell exhaustion-related genes (TEXGs). Methods: A single-cell RNA (scRNA) sequencing dataset from Tumor Immune Single-Cell Hub (TISCH) and bulk sequencing datasets from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were used to screen differentially expressed TEXGs. Kaplan–Meier survival, LASSO regression, and univariate/multivariate Cox regression analyses were performed to construct a TEXG risk model. This model was used to predict the prognosis, tumor immune microenvironment, and immunotherapy response. The PACA cohorts from the ICGC and GSE71729 datasets were used to validate the risk model. Pan-cancer expression of SPOCK2 was determined using the TISCH database. Results: A six-gene (SPOCK2, MT1X, LIPH, RARRES3, EMP1, and MEG3) risk model was constructed. Patients with low risk had prolonged survival times in both the training (TCGA-PAAD, n = 178) and validation (ICGC-PACA-CA, ICGC-PAAD-US, and GSE71729, n = 412) datasets. Multivariate Cox regression analysis demonstrated that the risk score was an independent prognostic variable for PACA. High-risk patients correlated with their immunosuppressive status. Immunohistochemical staining confirmed the changes in TEXGs in clinical samples. Moreover, pan-cancer scRNA sequencing datasets from TISCH analysis indicated that SPOCK2 may be a novel marker of exhausted CD8⁺ T-cells. Conclusion: We established and validated a T-cell exhaustion-related prognostic signature for patients with PACA. Moreover, our study suggests that SPOCK2 is a novel marker of exhausted CD8+ T cells. Full article

Tumors are intricate ecosystems where cancer cells and non-malignant stromal cells, including cancer-associated fibroblasts (CAFs), engage in complex communication. In this study, we investigated the interaction between poorly (HLE) and well-differentiated (HuH7) hepatoma cells and LX2 fibroblasts. We explored various communication channels, including soluble factors, metabolites, extracellular vesicles (EVs), and miRNAs. Co-culture with HLE cells induced LX2 to produce higher levels of laminin β1, type IV collagen, and CD44, with pronounced syndecan-1 shedding. Conversely, in HuH7/LX2 co-culture, fibronectin, thrombospondin-1, type IV collagen, and cell surface syndecan-1 were dominant matrix components. Integrins α6β4 and α6β1 were upregulated in HLE, while α5β1 and αVβ1 were increased in HuH7. HLE-stimulated LX2 produced excess MMP-2 and 9, whereas HuH7-stimulated LX2 produced excess MMP-1. LX2 activated MAPK and Wnt signaling in hepatoma cells, and conversely, hepatoma-derived EVs upregulated MAPK and Wnt in LX2 cells. LX2-derived EVs induced over tenfold upregulation of SPOCK1/testican-1 in hepatoma EV cargo. We also identified liver cancer-specific miRNAs in hepatoma EVs, with potential implications for early diagnosis. In summary, our study reveals tumor type-dependent communication between hepatoma cells and fibroblasts, shedding light on potential implications for tumor progression. However, the clinical relevance of liver cancer-specific miRNAs requires further investigation. Full article

Despite advances in non-small cell lung cancer (NSCLC) research, this is still the most common cancer type that has been diagnosed up to date. microRNAs have emerged as useful clinical biomarkers in both tissue and liquid biopsy. However, there are no reliable predictive biomarkers for clinical use. We evaluated the preclinical use of seven candidate miRNAs previously identified by our group. We collected a total of 120 prospective samples from 88 NSCLC patients. miRNA levels were analyzed via qRT-PCR from tissue and blood samples. miR-124 gene target prediction was performed using RNA sequencing data from our group and interrogating data from 2952 NSCLC patients from two public databases. We found higher levels of all seven miRNAs in tissue compared to plasma samples, except for miR-124. Our findings indicate that levels of miR-124, both free-circulating and within exosomes, are increased throughout the progression of the disease, suggesting its potential as a marker of disease progression in both advanced and early stages. Our bioinformatics approach identified KPNA4 and SPOCK1 as potential miR-124 targets in NSCLC. miR-124 levels can be used to identify early-stage NSCLC patients at higher risk of relapse. Full article

The calcification of the aortic valve causes increased leaflet stiffness and leads to the development and progression of stenotic aortic valve disease. However, the molecular and cellular mechanisms underlying stenotic calcification remain poorly understood. Herein, we examined the gene expression associated with valve calcification and the progression of calcific aortic valve stenosis. We downloaded two publicly available gene expression profiles (GSE83453 and GSE51472) from NCBI-Gene Expression Omnibus database for the combined analysis of samples from human aortic stenosis and normal aortic valve tissue. After identifying the differentially expressed genes (DEGs) using the GEO2R online tool, we performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. We also analyzed the protein–protein interactions (PPIs) of the DEGs using the NetworkAnalyst online tool. We identified 4603 upregulated and 6272 downregulated DEGs, which were enriched in the positive regulation of cell adhesion, leukocyte-mediated immunity, response to hormones, cytokine signaling in the immune system, lymphocyte activation, and growth hormone receptor signaling. PPI network analysis identified 10 hub genes: VCAM1, FHL2, RUNX1, TNFSF10, PLAU, SPOCK1, CD74, SIPA1L2, TRIB1, and CXCL12. Through bioinformatic analysis, we identified potential biomarkers and therapeutic targets for aortic stenosis, providing a theoretical basis for future studies. Full article

Purpose: Sparc/osteonectin, cwcv, and kazal-like domains proteoglycan 1 (SPOCK1) has been found in a variety of malignant tumors and is associated with a poor prognosis. We aimed to explore the role of SPOCK1 in ovarian cancer. Methods: Ovarian cancer cell lines SKOV3 and SW626 were transfected with SPOCK1 overexpressing or empty vector using electroporation. Cells were studied by immunostaining and an automated Western blotting system. BrdU uptake and wound healing assays assessed cell proliferation and migration. SPOCK1 expression in human ovarian cancer tissues and in blood samples were studied by immunostaining and ELISA. Survival of patients with tumors exhibiting low and high SPOCK1 expression was analyzed using online tools. Results: Both transfected cell lines synthesized different SPOCK1 variants; SKOV3 cells also secreted the proteoglycan. SPOCK1 overexpression stimulated DNA synthesis and cell migration involving p21^CIP1. Ovarian cancer patients had increased SPOCK1 serum levels compared to healthy controls. Tumor cells of tissues also displayed abundant SPOCK1. Moreover, SPOCK1 levels were higher in untreated ovarian cancer serum and tissue samples and lower in recipients of chemotherapy. According to in silico analyses, high SPOCK1 expression was correlated with shorter survival. Conclusion: Our findings suggest SPOCK1 may be a viable anti-tumor therapeutic target and could be used for monitoring ovarian cancer. Full article

Sparc/osteonectin, cwcv, and kazal-like domains proteoglycan 1 (SPOCK1) has been reported to play an oncogenic role in certain cancer types; however, the role of SPOCK1 in the progression of clear cell renal cell carcinoma (ccRCC) remains elusive. Here, higher SPOCK1 transcript and protein levels were observed in ccRCC tissues compared to normal tissues and correlated with advanced clinical stages, larger tumor sizes, and lymph node and distal metastases. Knockdown and overexpression of SPOCK1 in ccRCC cells led to decreased and increased cell clonogenic and migratory/invasive abilities in vitro as well as lower and higher tumor growth and invasion in vivo, respectively. Mechanistically, the gene set enrichment analysis (GSEA) database was used to identify the gene set of epithelial-to-mesenchymal transition (EMT) pathways enriched in ccRCC samples with high SPOCK1 expression. Further mechanistic investigations revealed that SPOCK1 triggered the Snail/Slug–matrix metalloproteinase (MMP)-2 axis to promote EMT and cell motility. Clinical ccRCC samples revealed SPOCK1 to be an independent prognostic factor for overall survival (OS), and positive correlations of SPOCK1 with MMP-2 and mesenchymal-related gene expression levels were found. We observed that patients with SPOCK1^high/MMP2^high tumors had the shortest OS times compared to others. In conclusion, our findings reveal that SPOCK1 can serve as a useful biomarker for predicting ccRCC progression and prognosis, and as a promising target for treating ccRCC. Full article

Using large constellations of smallsats, mission designers can improve sampling density and coverage. We develop performance metrics that characterize key sampling properties for applications in numerical weather prediction and optimize orbit design parameters of the constellation with respect to those metrics. Orbits are defined by a set of Keplerian elements, and the relationship between those elements and the spatial and temporal coverage metrics are examined in order to maximize global and zonal (latitude-dependent) coverage. Additional optimization is performed by dividing a constellation into multiple orbit planes. An iterative method can be applied to this design process to compare the performance of current and previous designs. The main objective of this work is the design of optimized configurations of satellites in low Earth orbiting constellations to maximize the spatial and temporal sampling and coverage provided by its sensors. The key innovations developed are a new cost function which measures the temporal sampling properties of a satellite constellation, and the use of it together with existing cost functions for spatial sampling to design satellite constellations that optimize performance with respect to both performance metrics. Full article

Bone metastatic (BM) prostate cancer (PCa) belongs to the most lethal form of PCa, and therapeutic options are limited. Molecular profiling of metastases contributes to the understanding of mechanisms defining the bone metastatic niche. Our aim was to explore the transcriptional profile of PCa BM and to identify genes that drive progression. Paraffin-embedded tissues of 28 primary PCa and 30 BM were submitted to RNA extraction and analyzed by RNA sequencing using the Nanostring nCounter gene expression platform. A total of 770 cancer-related genes were measured using the Nanostring™ PanCancer progression panel. Gene Ontology (GO), KEGG, Reactome, STRING, Metascape, PANTHER, and Pubmed were used for data integration and gene annotation. We identified 116 differentially expressed genes (DEG) in BM compared to primaries. The most significant DEGs include CD36, FOXC2, CHAD, SPP1, MMPs, IBSP, and PTX3, which are more highly expressed in BM, and ACTG2, MYH11, CNN1, FGF2, SPOCK3, and CHRDL1, which have a lower expression. DEGs functionally relate to extracellular matrix (ECM) proteoglycans, ECM-receptors, cell-substrate adhesion, cell motility as well as receptor tyrosine kinase signaling and response to growth factors. Data integration and gene annotation of 116 DEGs were used to build a gene platform which we termed “Manually Annotated and Curated Nanostring-data Platform”. In summary, our results highlight the significance of certain genes in PCa BM to which essential pro-metastatic functions could be ascribed. Data from this study provide a comprehensive platform of genes that are related to PCa BM and provide evidence for further investigations. Full article

Background: Brain metastasis is considered one of the major causes of mortality in breast cancer patients. To invade the brain, tumor cells need to pass the blood-brain barrier by mechanisms that are partially understood. In primary ER-negative breast cancers that developed brain metastases, we found that some of the differentially expressed genes play roles in the T cell response. The present study aimed to identify genes involved in the formation of brain metastasis independently from the T cell response. Method: Previously profiled primary breast cancer samples were reanalyzed. Genes that were found to be differentially expressed were confirmed by RT-PCR and by immunohistochemistry using an independent cohort of samples. Results: BOC, SPOCK2, and GJD3 were overexpressed in the primary breast tumors that developed brain metastasis. BOC expression was successfully validated at the protein level. SPOCK2 was validated at both mRNA and protein levels. SPOCK2 and GJD3 mRNA overexpression were also found to be associated with cerebral metastasis in an external online database consisting of 204 primary breast cancers. Conclusion: The overexpression of BOC, SPOCK2, and GJD3 is associated with the invasion of breast cancer into the brain. Further studies to determine their specific function and potential value as brain metastasis biomarkers are required. Full article

Glioblastoma is one of the deadliest human cancers. Its malignancy depends on cytoskeleton reorganization, which is related to, e.g., epithelial-to-mesenchymal transition and metastasis. The malignant phenotype of glioblastoma is also affected by the WWOX gene, which is lost in nearly a quarter of gliomas. Although the role of WWOX in the cytoskeleton rearrangement has been found in neural progenitor cells, its function as a modulator of cytoskeleton in gliomas was not investigated. Therefore, this study aimed to investigate the role of WWOX and its collaborators in cytoskeleton dynamics of glioblastoma. Methodology on RNA-seq data integrated the use of databases, bioinformatics tools, web-based platforms, and machine learning algorithm, and the obtained results were validated through microarray data. PLEK2, RRM2, and GCSH were the most relevant WWOX-dependent genes that could serve as novel biomarkers. Other genes important in the context of cytoskeleton (BMP4, CCL11, CUX2, DUSP7, FAM92B, GRIN2B, HOXA1, HOXA10, KIF20A, NF2, SPOCK1, TTR, UHRF1, and WT1), metabolism (MTHFD2), or correlation with WWOX (COL3A1, KIF20A, RNF141, and RXRG) were also discovered. For the first time, we propose that changes in WWOX expression dictate a myriad of alterations that affect both glioblastoma cytoskeleton and metabolism, rendering new therapeutic possibilities. Full article