Background:Hepatocellular carcinoma (HCC) ranks among the world's most lethal cancers, with the majority of cases diagnosed at advanced stages. Accurate prognostic assessment is therefore essential for HCC management. This study utilized DNA methylation (MDGs) and RNA-sequencing data to develop and validate a predictive model for HCC. Methods:MDG profiles, RNA-seq data, and related clinical information were analyzed. Based on the Cancer Genome Atlas (TCGA) dataset, a prognostic signature was developed via univariable and multivariable Cox regression analyses in combination with LASSO regression. Subsequently, a nomogram model was constructed and calibrated using calibration curves. The predictive accuracy of the selected genes was tested through in vitro cellular experiments. In addition, the GDSC dataset was utilized to examine the association between the prognostic signature and drug resistance. Results:Three genes (GLS, TEAD4, and CLGN) were identified and incorporated into the prognostic signature. Low-risk patients exhibited notably improved overall survival (OS) in comparison to high-risk patients. A nomogram model was developed based on clinical variables associated with OS, and its predictive accuracy for OS in individuals with HCC was evaluated via calibration curves. In vitro experiments revealed that the proliferative capacity of cells was notably reduced in the knockout group. The GDSC database was utilized to examine the association between the identified prognostic features and drug resistance. Conclusion:Predictive risk scores were developed based on three candidate MDGs, and a nomogram model was built by integrating clinical variables with these scores. This model can provide personalized prognosis prediction and assess drug resistance among individuals with HCC.
Klebsiella pneumoniae is a Gram-negative, facultatively anaerobic member of the Enterobacteriaceae that functions both as a gut commensal and a major opportunistic pathogen implicated in severe hospital and community-acquired infections. The rapid global expansion of antimicrobial-resistant K. pneumoniae lineages, particularly ESBL- and carbapenemase-producing strains, poses an escalating public health threat by eroding available treatment options. This study investigated the genomic architecture and resistance mechanisms of K. pneumoniae isolates recovered from urinary tract infections, wound infections, and cervical cancer cases across Ghana, Togo, and Benin. Eight isolates were subjected to antimicrobial susceptibility profiling and whole genome sequencing using the Illumina MiSeq platform after DNA extraction via the Zymo protocol. Comprehensive genomic analyses including MLST, resistance gene detection (Abricate), phylogenetic reconstruction (iTOL), genomic island prediction (IslandViewer), genome structural analysis (Proksee), and statistical interrogation in R (v4.4.0) were performed to characterize genetic diversity and identify determinants of antimicrobial resistance. The isolates exhibited heterogeneous but overlapping resistance profiles, extensive carriage of AMR genes, and the presence of multiple genomic islands enriched for integrases, transposases, and antibiotic resistance cassettes. MLST and SNP-based comparisons revealed both clonal clusters and genetically divergent lineages, while recombination analysis indicated mutation-driven evolution with lineage-specific recombination hotspots. Conserved gene orientation patterns and regions of atypical GC content further suggested historical acquisition of mobile genetic elements, including plasmid integrations and resistance islands. Collectively, these findings demonstrate the high genomic plasticity, multidrug-resistant phenotypes, and dynamic evolutionary processes shaping K. pneumoniae populations circulating in West Africa. The study underscores the urgent need for continuous regional genomic surveillance to guide treatment policies and limit the further dissemination of high-risk AMR clones.
Colorectal cancer (CRC) remains a leading cause of cancer-related mortality worldwide, with tumor microenvironment (TME) heterogeneity playing a critical role in disease progression and therapeutic response. Immune escape (IE) mechanisms facilitate tumor evasion from host immune surveillance, yet their characterization at the single-cell level in CRC is incomplete. This study integrated single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic data from multiple public cohorts to systematically explore IE-related signatures in CRC. We identified major and minor cell populations within the TME and performed differential gene expression analysis. Using high-dimensional weighted gene coexpression network analysis (hdWGCNA), we identified gene modules correlated with IE activity. Subsequent survival analysis across six independent cohorts revealed Gamma-glutamylcyclotransferase (GGCT) as a novel prognostic biomarker associated with poor survival. Functional enrichment analysis indicated GGCT's involvement in critical oncogenic pathways. Furthermore, GGCT expression correlated with altered immune infiltration profiles and stromal components, suggesting its role in modulating the immunosuppressive TME. Additionally, GGCT demonstrated potential predictive value for response to immunotherapy across multiple datasets. Our findings highlight GGCT as a key player in CRC immune evasion and a promising therapeutic target.
Background:Sjögren's syndrome (SS) is a chronic autoimmune disorder characterized by significant diagnostic challenges due to nonspecific symptoms and a lack of reliable biomarkers, often resulting in delayed diagnosis and suboptimal patient management. Objective:This study is aimed at identifying novel diagnostic biomarkers and elucidating the molecular mechanisms underlying SS pathogenesis through integrative bioinformatics and machine learning approaches. Methods:We analyzed three peripheral blood transcriptomic datasets (GSE51092, GSE66795, and GSE84844) comprising a total of 351 SS patients and 91 healthy controls. Differential expression analysis, weighted gene coexpression network analysis (WGCNA), and 12 machine learning algorithms were employed to identify robust diagnostic biomarkers. Immune cell infiltration was assessed using CIBERSORT, and single-cell RNA sequencing data (GSE157278) were analyzed to validate cell-type-specific expression patterns. Drug repurposing analysis was conducted using the L1000FWD platform. Results:We identified 12 hub genes (EPSTI1, IFIH1, CXCL10, TNFSF10, GBP5, PARP9, IFI44, LAP3, IFIT2, IFI44L, PARP12, and OAS1) with exceptional diagnostic performance (AUC = 0.994 in training, 0.838 in internal validation, and 0.825 in external validation). These biomarkers showed significant correlations with clinical indicators including ANA, Ro/SSA, and La/SSB (p < 0.05). Immune-infiltration analysis revealed pronounced immune dysregulation in SS patients, characterized by an imbalance between naive and memory B cells and reduced CD8+ T cells and regulatory T cells (Tregs). Single-cell transcriptomics confirmed predominant expression in monocytes and dendritic cells, with additional significant expression in B cells and CD4+ T cells. Virtual knockdown analysis implicated these genes in antigen presentation, interferon signaling, and leukocyte trafficking. Drug repurposing identified FDA-approved candidates such as nisoldipine and exemestane as potential therapeutics. Conclusion:Our integrative approach identifies 12 robust diagnostic biomarkers for SS, offering new insights into disease mechanisms and highlighting potential therapeutic targets for this challenging autoimmune disorder.
Background:Non-small cell lung cancer (NSCLC) accounts for over 80% of lung cancer cases. Further, the complex tumor immune microenvironment (TIME) is a critical factor in treatment resistance and poor prognosis associated with tumors. Tumor-associated macrophages (TAMs), a major component of the TIME, significantly promote tumor progression through their polarization toward the immunosuppressive M2 phenotype. Reportedly, NSCLC cells regulate TAM polarization by secreting extracellular vesicles (EVs) to deliver miRNAs; however, the specific underlying molecular mechanisms remain unclear. In this study, we aimed to elucidate the regulatory role of miRNAs derived from NSCLC EVs in TAM polarization and explore potential novel therapeutic targets. Methods:Through high-throughput sequencing and bioinformatics analysis, key regulatory targets were screened. Ki-67 staining was employed to detect cell proliferation, flow cytometry was performed to analyze cell apoptosis, RT-qPCR and Western blot were used to measure mRNA and protein expression levels, and Transwell assays were conducted to assess cell migration and invasion capabilities to investigate the molecular mechanisms underlying the miRNA-mediated regulation of TAM polarization by NSCLC-derived EVs. Results:NSCLC-derived EVs were successfully isolated and characterized. Bioinformatics analysis of EVs' miRNA sequencing data revealed that the hsa-let-7b-5p/Adaptor-Related Protein Complex 1 subunit sigma 1 (AP1S1) axis may be a key regulator of TAM polarization. In vitro experiments confirmed that the hsa-let-7b-5p mimic potentially suppressed M2 polarization of TAMs via the AP1S1/p53 signaling axis, thereby attenuating the proliferation, migration, and invasion capabilities of NSCLC cells. Conclusion:This study revealed the molecular mechanism by which hsa-let-7b-5p reshapes the immune microenvironment of NSCLC cells by targeting and inhibiting AP1S1 expression, thereby regulating the polarization of TAMs toward the M2 phenotype. Thus, the hsa-let-7b-5p/AP1S1 axis may serve as a potential therapeutic target for NSCLC immunotherapy, providing novel strategies for improving patient prognosis.
Emerging evidence highlights the pivotal role of KISS1 in cancer metastasis; however, there remains a dearth of pancancer analyses, particularly concerning immunotherapy. Here, we conducted a comprehensive investigation of KISS1 across various cancers, with a specific focus on breast cancer, using TCGA and GTEx datasets. We observed a tissue context-dependent role function of KISS1 in tumor metastasis, which exhibited suppressive effects in various tumors but promoted the metastatic phenotype in breast cancer. Our study revealed a noteworthy disparity between KISS1 expression at the mRNA and protein levels, indicating potential posttranslational modifications within cancer cells. Moreover, KISS1 is significantly associated with immune cell infiltration and immunosuppressive cells, suggesting its crucial role in modulating tumor immunotherapy. Intriguingly, our investigation also elucidated KISS1’s involvement in promoting breast cancer metastasis, thereby providing valuable insights into the molecular underpinnings of this process. Furthermore, we validated the presence of posttranslational modifications of KISS1 in breast cancer, adding to our understanding of its role in tumorigenesis. By shedding light on the tissue context-dependent function of KISS1 and its implications for immunotherapy, our pancancer study offers novel perspectives on the oncogenic roles of KISS1 and provides potential avenues for the development of targeted therapies and diagnostic biomarkers.
Background:Hepatocellular carcinoma (HCC) carries a dismal prognosis, yet the contribution of deubiquitination-an essential posttranslational regulator-to its progression remains poorly defined. Methods:Single-cell RNA-seq profiles of 13 treatment-naïve HCC tumors were integrated with 374 TCGA and 243 ICGC bulk RNA-seq cohorts. Deubiquitinase (DUB) activity was quantified per cell with AUCell; pathway enrichment was performed with clusterProfiler. A LASSO-Cox machine learning pipeline was used to build a DUB-based risk signature, which was cross-validated internally and externally by time-dependent ROC analysis. Results:Malignant cells exhibited divergent DUB transcription relative to immune compartments (myeloid, B). DUB-high neoplastic subsets displayed heightened inflammatory and IFN-γ signaling, concordant with brisk immune infiltration. A 78-gene prognostic index robustly stratified survival in discovery and replication cohorts. Conclusions:This study highlights the role of deubiquitination in HCC progression and its potential as a prognostic biomarker. The developed model could serve as a valuable tool for patient stratification and personalized treatment strategies, although further experimental validation is needed to confirm these findings.
Cellular action potential is characterized by a particular sequence of depolarizing and repolarizing ion currents regulated by ion channels. Genetic mutations in these channels disrupt the essential movement of ions, such as Na+, Ca++, and K+, across the cell membrane, leading to dangerous arrhythmias and sudden cardiac death (SCD). Most cases of unexplained SCD are caused by pathogenic variants in genes linked to channelopathies and cardiomyopathy. Genetic investigations might aid in confirming the clinical diagnosis based solely on observations. Other advantages of genetic studies are clinical management of the patient, family screening, appropriate genetic counseling, and risk assessment for family members. This study was conducted to investigate the genetic cause of early-onset SCD in two Iranian families. Whole-exome sequencing was performed on the probands from each family, and the Illumina DRAGEN haplotype variant calling system was used to identify variants in each patient. Here, we identified rare heterozygous missense variants in the RYR2 and SCN5A genes, which are linked to cardiac channelopathies. Alignment studies reveal that the mutated residues are conserved across humans and primates, underscoring their crucial role in protein function. Previously reported associations between these mutations and channelopathy pathogenesis have been confirmed in the present study. This study provides valuable insights for genetic counseling of families with a history of sudden death.
Introduction:Anoikis, a type of programmed cell death induced by detachment from the extracellular matrix (ECM), is crucial in cancer progression. Resistance to anoikis often correlates with enhanced invasion, metastasis, treatment resistance, and tumor recurrence. However, no research has systematically explored anoikis-regulated tumor microenvironment (TME) in lung adenocarcinoma (LUAD). Methods:We used single-cell RNA sequencing (scRNA-seq) and spatial transcriptome RNA sequencing (stRNA-seq) analyses to reveal the subtype of anoikis-related epithelial cells, demonstrating its spatial location characteristics. With the maker genes of prognostic significance, we depicted the molecular landscapes of anoikis regulator patterns in RNA-seq data. We developed the anoikis-related signature (Anoikis.Sig) by integrating 10 machine learning (ML) algorithms to accurately predict prognosis in LUAD. Based on the median risk score computed by Anoikis.Sig, patients were divided into high- and low-risk groups. We employed extensive analysis between two risk groups, in terms of clinic implications, immune microenvironment, somatic mutations, immunotherapy, chemotherapy, and single-cell landscape. Finally, we verified the prognosis value of two Anoikis.Sig model genes. Results:By integrative analysis of scRNA-seq and stRNA-seq datasets, we defined diverse function subtypes of anoikis-related epithelial cells and investigated their spatial regulator patterns. Through its marker genes and leave-one-out cross-validation, we utilized the RSF algorithm to develop the Anoikis.Sig with a superior predictive ability, outperformed other LUAD signatures and clinical indicators. We categorized LUAD patients into high- and low-risk groups, which demonstrated the low-risk group had a better survival outcome, an ample immune infiltration, a distinct mutational landscape, and response to immunotherapy. ScRNA-seq analysis revealed biologically intercellular disparities delineated by Anoikis.Sig. qRT-PCR validated the prognostic value of two model genes of Anoikis.Sig in LUAD. Conclusion:Through multiomics analyses and ML algorithms, we succeeded in establishing the Anoikis.Sig to efficiently predict prognosis in Anoikis.Sig, which delineated molecular landscapes of anoikis regulator patterns and clinical applications of Anoikis.Sig.
Background:Despite extensive research, nasopharyngeal carcinoma (NPC) remains a complex malignancy with poorly understood cellular dynamics and risk factors. The relationship between allergic rhinitis and NPC development has been controversial. This study combined single-cell transcriptomics with Mendelian randomization to comprehensively map cellular heterogeneity and establish potential causal links between allergic rhinitis and NPC pathogenesis. Methods:Researchers performed single-cell RNA sequencing on NPC and adjacent normal tissue samples. Simultaneously, a two-sample Mendelian randomization approach was employed using allergic rhinitis-associated genetic variants as instrumental variables to investigate causality between allergic rhinitis and NPC risk. Integration of these genetic instruments with transcriptomic profiles enabled the identification of genetically influenced molecular pathways. Results:Comprehensive analysis revealed intricate cellular landscapes comprising epithelial, immune, endothelial, and stromal cell populations, each demonstrating unique transcriptional signatures. Mendelian randomization analysis provided evidence for a causal relationship between allergic rhinitis and NPC development (OR = 1.42, 95% CI: 1.18-1.76, p = 0.0003). Significant dysregulation was observed in critical signaling pathways, including mitochondrial processes, extracellular matrix-receptor interactions, and Wnt/Notch cascades. Genetic instruments for allergic rhinitis showed significant effects on inflammatory pathways within specific NPC cellular subpopulations, suggesting mechanistic links between allergic inflammation and carcinogenesis. Conclusion:By leveraging both single-cell transcriptomics and Mendelian randomization, this study provides unprecedented insights into NPC's cellular complexity and establishes causal pathways linking allergic rhinitis to NPC development. These findings identify genetically validated molecular mechanisms that could represent promising therapeutic targets for this challenging malignancy.
Objective:The objective was to analyze the effect of C-type lectin domain family 4 member G (CLEC4G) on hepatocellular carcinoma (HCC) and investigate its impact on lenvatinib (Lenva) resistance as well as the underlying action pathway. Methods:Differentially expressed genes (DEGs) were screened from the GSE101685 dataset, followed by functional enrichment analysis. Subsequently, CLEC4G was selected for subsequent experiments. The Lenva-resistant cell line PLC/PRF/5-R was established and transfected with a CLEC4G silencing expression vector to observe alterations in its biological behavior. Sample size was estimated based on a pilot experiment (n = 3 biological replicates) with 30 clinical samples/cell experiment in each group. Additionally, the expression of the Wnt/β-catenin pathway in PLC/PRF/5-R was examined, and PLC/PRF/5-R activity after intervention with LiCl, a Wnt/β-catenin pathway activator, was evaluated. Results:A total of 51 DEGs were identified in the GSE101685 dataset. After silencing CLEC4G expression, the activities of both PLC/PRF/5 and PLC/PRF/5-R, as well as the expression of PD-1, were decreased, while apoptosis was increased (p < 0.05). Moreover, silencing CLEC4G inhibited the expression of the Wnt/β-catenin pathway (p < 0.05). After LiCl intervention, the activity of PLC/PRF/5-R was enhanced, and the expression of PD-1 was elevated (p < 0.05). Silencing CLEC4G could reverse the effect of LiCl on PLC/PRF/5-R. Conclusion:CLEC4G modulates the PD-1 expression of HCC cells through the Wnt/β-catenin pathway, thereby reversing the resistance to Lenva.
LIM genes are essential for cytoskeletal organization and cellular stress responses in plants. This study conducted a comprehensive genome-wide investigation of LIM domain-associated genes in Phaseolus vulgaris. This study expands LIM gene classification beyond traditional domains to include LIM_bind factors, revealing that P. vulgaris has a more complex and functionally diverse regulatory toolkit than previously understood. Seventeen identified PvLIM genes are distributed across three families: LIM-LIM domain, LIM-DA1_like domain, and LIM_bind domain-containing. Following gene duplication, P. vulgaris LIM genes underwent subfunctionalization where ancestral functions were partitioned among copies, creating specialized tissue-specific and stress-responsive roles while maintaining complementary regulatory networks. PvLIM proteins form critical networks controlling cell wall metabolism, signaling pathways, actin cytoskeleton dynamics, and endocytosis. All PvLIM genes exhibit universal responsiveness to multiple stress stimuli including abscisic acid, ethylene, methyl jasmonate, wound, heat, and anaerobic stress conditions, confirming their central role in plant stress tolerance mechanisms. Gene expression analysis revealed tissue-specific functional specialization, with LIM-LIM and LIM_bind domain genes predominantly active in stem and leaf tissues, while PvLIM14 governs stem, pod, and leaf development and PvLIM16 modulates seed-related processes. PvLIM genes constitute essential molecular machinery governing plant growth, development, and stress adaptation through integrated phytohormone-mediated regulatory networks.
Background:Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer, where its complex tumor microenvironment (TME) significantly influences disease progression and treatment response. Inflammatory cancer-associated fibroblasts (iCAFs), as a key component of the TME, can promote tumor immune evasion and drug resistance. However, the characteristics of iCAFs in LUAD and their clinical significance have not been fully elucidated. Methods:The bulk RNA data and scRNA-seq data of LUAD from public databases were integrated to identify and characterize iCAFs subsets and screen their feature genes. iCAF-based signature (ICAFBS) was generated using multiple machine learning algorithms and confirmed in multiple independent cohorts. The relationship between ICAFBS and immune landscape as well as drug sensitivity was further analyzed. Finally, a series of functional studies were conducted to elucidate the role of PFN2 in LUAD cell lines. Results:The iCAF subtype identified by single-cell analysis was enriched in LUAD and closely linked to poor prognosis. Based on 145 iCAF characteristic genes, ICAFBS was finally screened out four key genes, MGP, LOXL2, FSTL3, and PFN2. ICAFBS demonstrated excellent prognostic predictive capabilities and was validated in multiple external datasets. Patients in the high ICAFBS group showed significant high expression of multiple immune checkpoints. Notably, silencing PFN2 inhibited cell viability and proliferation in LUAD cells, highlighting its potential as a therapeutic target. Conclusion:As a novel prognostic signature, ICAFBS can effectively predict the clinical outcome, immune landscape and treatment response of patients, providing an important reference for the individualized treatment of LUAD.
Objectives:The aim of this study was to understand the transcriptome and molecular pathways that drive unique functional characteristics of human gingiva. Materials and Methods:Gene expression data were obtained from the NCBI GEO database, including GSE38617 (connective tissue [CT]) and GSE7224 (gingival epithelium [GE]). Raw data were preprocessed and filtered for healthy samples. Differential gene expression analysis was performed using the limma package in R, with a significance cutoff of log2 fold change ≥ 1 and adjusted p value < 0.05. Results:The analysis highlighted 11,096 DEGs between the dissected tissues. In CT, 7564 genes were upregulated in extracellular matrix (ECM) organization, collagen synthesis, and immunomodulation. GE had a total of 3532 upregulated genes enriched in epithelial barrier integrity, antimicrobial defense, and keratinocyte differentiation. These patterns were confirmed using key markers (CT: COL1A1 and COL3A1 and GE: DEFB1 and KRT10). In CT, pathway enrichment showed PI3K-Akt signaling and ECM-receptor interaction, whereas GE was characterized by tight junctions and the IL-17 signaling pathway. Conclusion:The differences in transcriptional landscapes of CT and GE illustrate specialized functions of each tissue type in maintaining periodontal health. Whereas CT focuses on ECM preservation and its immunomodulatory role, GE emphasizes antimicrobial defense and barrier function.
Background:The escalating threats of global warming and the increasing demand for sustainable resources have driven research towards identifying resilient organisms capable of thriving under changing environmental conditions. A recently identified strain of Neopyropia yezoensis from Daebudo has demonstrated the ability to grow even under elevated temperatures. Understanding the genetic and molecular mechanisms underlying this resilience is crucial for the development of heat-tolerant cultivars. Methods:This study investigates the characteristics of the newly isolated strain N. yezoensis (Daebudo) through comprehensive transcriptome analysis on samples cultivated at various temperatures. Transcript reads were aligned to the genome sequences of N. yezoensis (susabi-nori) and Neoporphyra haitanensis. Aligned and unaligned reads were assembled separately, generating 45,089 transcripts and 105,750 transcripts, respectively. The transcripts were annotated using homologous sequences from the Swiss-Prot, NCBI NR, Pfam, SignalP, and KEGG databases. Differentially expressed gene (DEG) analysis was performed, and gene function classification (Gene Ontology) was conducted using BLASTX and BLASTP results from the Swiss-Prot database. Results:Some transcripts that were upregulated under higher temperatures were found to be involved in key metabolic pathways such as glycolysis or photosynthesis. Also, several DEGs, including heat shock proteins and elongation factor 1 alpha, were identified as potential contributors to high-temperature tolerance. These DEGs are likely involved in cellular stress response and protein synthesis, facilitating growth under elevated temperatures. Conclusion:The findings provide new molecular-level insights into the growth mechanisms of N. yezoensis under heat stress. This information can be applied to the development of new cultivars with enhanced growth and heat tolerance, supporting sustainable aquaculture in the face of climate change.
Background:Due to the growth in the global consumption of assisted reproductive technology (ART), it is possible that long-term health impacts on offspring have come into focus. ART has offered a welcome solution to infertility, but the fear has been on its effect on the metabolic health of children born on their behalf. Past studies indicate that ART-conceived individuals can have characteristic metabolic profiles relative to their naturally conceived (NC) peers and are therefore potentially predisposed to changes in lipid and glucose handling. Physiopathological glycolipid metabolism, a hallmark of cardiometabolic health, is believed to be modulated not only by environmental and other external factors but also by intracellular regulation proteins, including sterol regulatory element-binding protein (SREBP) and miR-33, although there is little evidence on the effects of ART on these regulatory pathways in early childhood. Objective:This paper sought to compare the glycolipid metabolic profile of the kids who are in preschool age and who were conceived through ART and kids who were NC. The second aim was to study the expression of SREBP-1/2 and miR-33 in peripheral blood and the possible nature of the role of these players in regulating early-life metabolism. Subject and Methodology:A total of 220 children aged between 3 and 6 years were recruited of which complete data has been obtained from 206 children out of 98 that were conceived via in vitro fertilization/intracytoplasmic sperm injection (ICSI) (ART group) and 108 that were conceived naturally (NC group). Anthropometric measures-such as body weight, height, and waist circumference-to determine physical growth and obesity status were taken. Biochemical variables, triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), fasting serum insulin (FINS), and homeostatic model assessment of insulin resistance (HOMA-IR) were determined. A centrifugal column was used to obtain peripheral blood RNA, and relative gene expression levels of SREBP-1, SREBP-2, miR-33a, and miR-33b were measured by qPCR. Results:Compared with the IVF group, children in the ICSI group had significantly lower weight, height, and waist circumference (p < 0.05). In contrast, children in the NC group had significantly lower weight, BMI, and waist circumference, with all differences being statistically significant (p < 0.05). Additionally, compared with the IVF group, the NC group showed significantly increased levels of HDL-C and ApoA1 (p < 0.05). Meanwhile, the ICSI group had significantly higher ApoB levels and HOMA-IR scores (p < 0.05). Compared with the NC group, children in the ICSI group showed significantly higher levels of TG, ApoB, FINS, and HOMA-IR (p < 0.05), while ApoA1 levels were significantly lower (p < 0.05). When comparing clinical outcomes related to blood pressure, blood glucose, and blood lipids for abnormalities, there was no difference in incidence between the ART group and the NC group (p > 0.05). In addition, the expression of peripheral blood SREBP-1 mRNA, SREBP-2 mRNA, miR-33a, and miR-33b was compared. Compared with the IVF group, SREBP-1 mRNA and miR-33b levels in the NC group were significantly reduced, while miR-33a levels in the ICSI group were significantly decreased (p < 0.05). Compared with the NC group, SREBP-1 mRNA and SREBP-2 mRNA were significantly increased in the ICSI group (p < 0.05), while miR-33a was significantly decreased (p < 0.05). Correlation analysis showed that in the ART group, SREBP-1 mRNA expression levels were positively correlated with BMI, ApoB, fasting blood glucose, FINS, and HOMA-IR and negatively correlated with ApoA1. SREBP-2 mRNA levels were positively correlated with HOMA-IR and negatively correlated with ApoA1. Additionally, the expression levels of miR-33a were negatively correlated with HDL-C, while miR-33b levels were negatively correlated with both HDL-C and FINS. Conclusion:Our data suggest that although children born by means of ART are otherwise normal in their glycolipid metabolism, they are more prone to overweight and obesity and have different biochemical and molecular characteristics than NC children. The upregulation of miR-33b, SREBP-1, and SREBP-2 observed indicates that ART can play a role in regulating the process of glycolipid metabolism during early childhood at a molecular level. Such alterations might not present the form of a blatant metabolic condition at this age but may consist of initial symptoms of future troublesome metabolic health. Prolonged follow-up of the ART offspring and additional mechanistic work are desirable to be able to determine whether these early changes are the underlying reasons behind higher metabolic risk as adults.
Objective:The objective of this study is to explore mitochondria-associated programmed cell death (mtPCD)-related key biomarkers for patients with colorectal cancer (CRC). Methods:CRC-related datasets were obtained from the GEO and TCGA databases, and mitochondria-related genes (MitoRGs) and PCD-related genes (PCDRGs) were acquired from the MitoCarta database or pertinent literature. After differentially expressed gene (DEG) screening, the DEmtPCD coexpressed genes were identified. Then, consensus clustering analysis was conducted, followed by GSEA and immune infiltration analysis. In addition, a prognostic model was constructed, and then, immune infiltration analysis, GSEA, and drug sensitivity analysis were carried out. The qRT-PCR and western blot were employed to determine the expression of key genes. Finally, a loss-of-function experiment was applied to investigate the influence of INHBB on CRC in vitro. Results:A total of 2118 DEGs were screened, and then, 64 DEmtPCD coexpressed genes were obtained. Subsequently, two clusters, including C1 and C2, were identified, and patients in the C1 group had better survival outcomes. In addition, a prognostic model was constructed based on four key genes, namely, ACSL6, INHBB, GPR15, and SRPX. Also, the area under the curves (AUCs) for overall survival (OS) at 1, 3, and 5 years were 0.667, 0.665, and 0.603 in the TCGA set, separately, and 0.759, 0.766, and 0.662, separately, in the GSE17537 dataset. The total fraction of nine immune cells showed a significant difference between the low- (L) and high (H)-risk groups, such as neutrophils, activated NK cells, and activated dendritic cells. Also, there was a significant difference in TIDE scores between the H- and L-risk groups, and APC was the most significantly mutated gene in both the H- and L-risk groups. IC50 value of some chemotherapeutic agents showed a significant difference between the L- and H-risk groups, containing AZD1332-1463, IGF1R-3801-1738, and XAV939-1268. The expression levels of ACSL6, GPR15, and INHBB were significantly elevated in CRC cells compared to those in NCM460 cells, while SRPX significantly decreased. Notably, downregulation of INHBB effectively alleviated the tumorigenesis of SW620 cells. Conclusion:A prognostic model was constructed based on four key mtPCD-associated genes, namely, ACSL6, INHBB, GPR15, and SRPX. INHBB was upregulated in CRC, and the alleviation of INHBB suppressed the proliferation and migration of CRC cells.
Background:Chaperonins are crucial regulators of tumor biology by controlling the stability and function of oncogenic and tumor-suppressor proteins, influencing various tumorigenic signaling pathways. Although chaperonins have been widely discussed in various cancers, including hepatocellular carcinoma (HCC), the complex mechanisms by which they contribute to HCC progression remain insufficiently explored and require further investigation. Methods:Based on data from public databases, we screened chaperonin members from the Human Genome Organisation (HUGO) Gene Nomenclature Committee (HGNC) database. The screened genes were subjected to differential expression analysis, survival analysis, clinical correlation, and univariate Cox regression. Results were validated using single-cell RNA (scRNA) and spatial transcriptomics (ST) data. Functional enrichment and in vitro assays were also performed. Results:Chaperonins, particularly CCT6B, were significantly overexpressed in HCC tissues, with higher expression correlating with poor prognosis in HCC patients. CCT6B was found to be involved in cell cycle regulation, promoting tumor cell proliferation. Additionally, CCT6B contributed to M2 macrophage infiltration, potentially through CCL20 signaling. Moreover, the expression levels of chaperonins were associated with β-catenin activation in malignant cells, suggesting their collective involvement in HCC progression. Conclusion:This study elucidates a substantial association between dysregulated chaperonin expression profiles and genomic aberrations in pan-cancer, underscoring the functional significance of these chaperonin molecules in understanding cell cycle regulation. Systematic characterization of chaperonin-mediated regulatory networks enhances mechanistic insights into oncogenic processes and aberrant cellular proliferation, thereby informing the rational design of precision therapeutic interventions.
Keloid is a common pathological scar tissue, which invades the surrounding normal skin and leads to symptoms such as pain, pruritus, erythema, and edema, thereby impacting the quality of life. In this study, we conducted bioinformatics analysis of keloid fibroblasts and normal skin tissue to identify DEGs and the pathways involved in the mechanism of keloid fibroblast proliferation. GSE145725 was downloaded from the Gene Expression Omnibus (GEO) database, including nine keloid fibroblasts and 10 normal tissue fibroblast samples. GSE158395 included four lesional and three nonlesional samples from keloid patients, and six normal skin tissue samples were also evaluated. Through bioinformatics analysis, we established diagnosis model, and at the same time, we predicted therapeutic targets in the DSigDB database. Six key genes were screened out by bioinformatics analysis, including BMP4, SPP1, HIF1 α , POSTN, WNT5A, and SMAD3. Subsequently, three of these genes (BMP4, POSTN, and WNT5A) were found to be significantly associated with keloids. Paricalcitol and phosphine were identified as potential therapeutic candidates. This study identified three hub genes—BMP4, POSTN, and WNT5A—that are closely linked to keloid fibroblast hyperplasia and may serve as potential biomarkers for inhibiting keloid fibroblast hyperplasia. Further molecular and animal studies are needed to fully understand the mechanisms of keloid development.
Hyperuricemia (HUA) is a metabolic disorder characterized by elevated serum uric acid (UA) level, which would trigger inflammatory processes contributing to kidney damage. Acupuncture stimulation of BL23, a therapeutic strategy in traditional Chinese medicine (TCM), has been reported to promote diuresis and suppress the immune system and seems to be efficacious in HUA. In this study, we aimed to investigate the effect of electroacupuncture (EA) at BL23 on HUA and HUA-induced kidney inflammation and dysfunction in mice. Mice received EA once daily after being given intragastric potassium oxonate (500 mg/kg) and adenine (100 mg/kg). EA administration not only decreased the levels of serum UA, creatinine, blood urea nitrogen, urinary UA, and protein, along with increased urinary CREA excretion, but also decreased the inflammatory cytokines productions (IL-1β, IL-6, and TNF-α) in serum. scRNA-seq of treated kidneys revealed that EA at BL23 suppressed the NLRP3 inflammasome complex, the IL-6/JAK/STAT3 signaling pathway, and the production of IL-6 and IL-1β in HUA mice. Western blot analyses verified that EA suppressed the HUA-induced NLRP3 inflammasome activation by promoting autophagy. In conclusion, the study demonstrated that EA at BL23 exhibited anti-HUA and nephroprotective effects by inhibiting both the NLRP3 inflammasome and the IL-6/JAK/STAT3 signaling pathway, reducing renal inflammation and supporting its therapeutic potential for HUA-associated kidney injury.
