Genes & genomics最新文献

Background: Lung adenocarcinoma (LUAD) frequently harbors activating mutations in the epidermal growth factor receptor (EGFR), making EGFR tyrosine kinase inhibitors (EGFR-TKIs) a critical component of targeted therapy. Although third-generation EGFR-TKIs, such as Furmonertinib, have improved outcomes for patients with EGFR-mutant LUAD, drug resistance and tumor adaptation remain major challenges. The cellular and molecular mechanisms underlying response and adaptation to Furmonertinib, particularly within the tumor microenvironment (TME), are not fully understood.

Methods: We performed single-cell RNA sequencing on tumor and paired paracancerous tissues from EGFR-positive LUAD patients before and after Furmonertinib treatment, integrating both public and in-house datasets. We systematically analyzed changes in cellular composition, gene expression profiles, pathway enrichment, and ligand-receptor-mediated cell-cell communication.

Results: Furmonertinib treatment led to a marked reduction in tumor cell proportion and profound remodeling of the TME. There was an increase in T cell infiltration, particularly CD4⁺ T cells, and a decrease in exhausted CD8⁺ T cells, indicating a shift toward a less immunosuppressive microenvironment. Cancer-associated fibroblasts and monocytes were also enriched post-treatment. Tumor cells exhibited increased EGFR expression, along with transcriptomic reprogramming characterized by upregulation of signaling, immune, and differentiation pathways, and downregulation of metabolic and protein synthesis genes. Cell-cell communication analysis revealed attenuation of immunosuppressive signaling (such as MIF axis) and enhancement of alternative ligand-receptor interactions, including LAMC1- and EGFR-related pathways.

Conclusions: Our integrative single-cell analysis reveals that Furmonertinib therapy induces significant cellular and molecular changes in EGFR-positive LUAD, including TME remodeling, transcriptomic adaptation, and reprogramming of intercellular communication networks. These findings provide insight into the mechanisms of Furmonertinib response and resistance, and may inform strategies to optimize EGFR-TKI therapy.

Background: Cuproptosis and oxidative stress (COS) are emerging regulators in cancer biology. However, their link to long non-coding RNAs (lncRNAs) and clinical outcomes in ovarian cancer remains unclear.

Objective: This study aimed to construct and validate a prognostic signature based on COS-related lncRNAs to improve risk stratification and provide insights into therapeutic strategies for ovarian cancer.

Methods: RNA-seq and clinical data from TCGA and GEO were analyzed to identify COS-related lncRNAs via WGCNA and Pearson correlation. Prognostic lncRNAs were screened using Cox regression and modeled using multiple machine learning algorithms. Immune profiles, mutation patterns, drug sensitivity, and experimental validation were performed.

Results: A 12-lncRNA signature was established that stratified patients into high- and low-risk groups with significant survival differences (HR = 22.6145, p < 0.001). The model showed strong predictive performance (AUCs: 0.91/0.967/0.974) and was validated externally. High-risk patients exhibited greater mutation burden, altered immune pathways (interferon, TGF-β), and differential predicted sensitivity to agents like Axitinib and Pazopanib. RT-qPCR confirmed the expression patterns of 11 out of 12 lncRNAs.

Conclusion: This study proposes a robust 12-lncRNA signature linking cuproptosis and oxidative stress with prognosis and therapy response in ovarian cancer, offering preliminary insights for personalized treatment guidance.

Background: Flowering time (referred to as heading date in rice) is a characteristic controlled by quantitative trait loci (QTLs). Heading date is an important agronomic trait that determines yield in rice and is precisely regulated by various exogenous and endogenous factors.

Objective: To investigate the role of the ascorbate peroxidase 9 (APX9) gene in the flowering mechanism, we examined the expression levels of flowering time regulators under long-day conditions (14 h light/10 hours dark) and natural long-day conditions.

Methods: A BC₄F₇ near-isogenic line (NIL), derived from an interspecific cross between the Korean elite japonica cultivar (cv. Hwaseong, Oryza sativa L.) and Oryza rufipogon (IRGC 105491), was used in this study to identify and characterize candidate genes associated with heading traits. The NIL contains a small O. rufipogon chromosome segment harboring the APX9 gene. In addition, overexpression and T-DNA insertion knockout transgenic lines were used to examine the function of APX9 gene.

Results: The NIL exhibited delayed flowering under both controlled and natural long-day conditions compared to Hwaseong. Real-time PCR analysis indicated that APX9 influences the upstream pathway of flowering time regulation. Over-expression lines showed delayed flowering relative to Hwaseong, whereas T-DNA mutants flowered earlier than the control cultivar, Dongjin. These findings support a role for APX9 in modulating flowering time in rice.

Conclusion: The APX9 is known for its antioxidant activity and its response to various abiotic stresses. The APX9 may play a role in the upstream regulation of the flowering pathway. These findings will be valuable in understanding the effect of APX9 during flowering stages. It would also be interesting to explore the relationship between hydrogen peroxide (H₂O₂₎ levels and the APX9 gene in signaling events related to heading.

Background: Hypoxia is a significant manifestation of severe asthma in children. An early and accurate diagnosis is crucial for enhancing treatment outcomes and mitigating long-term complications. This study aims to utilize bioinformatics analysis to investigate hypoxia-related genes (HRGs) in childhood asthma.

Objective: This study aims to develop a diagnostic model and identify key hypoxia-related biomarkers in childhood asthma based on transcriptomic data analysis.

Methods: Hypoxia-related differentially expressed genes (HRDEGs) were identified from bronchial epithelial transcriptomes (GSE27011/GSE40732 datasets) using limma analysis. A diagnostic model was developed using LASSO regression, and hub genes were identified via protein-protein interaction (PPI) networks. Asthma subtyping and immune microenvironment characterization were conducted using ConsensusClusterPlus and CIBERSORTx, respectively. Experimental validation in house dust mite (HDM)-induced asthmatic mice confirmed transcriptional changes in candidate genes.

Results: We obtained 19 HRDEGs and 11 model genes (AHR, AKR1C3, ELP3, GNAL, GZMB, LPP, MAFG, PDGFD, PPP1R12B, SYNE2, and TAF15). Regression analyses demonstrated the model's robust diagnostic performance. PPI analysis identified 10 hub genes associated with asthma, with AKR1C3 showing high diagnostic accuracy for different molecular subtypes. Immune infiltration analysis indicated significant correlations between hub genes and eight immune cell types, including B cells, effector T cells, cytotoxic T cells, regulatory T cells (Tregs), monocytes, mast cells, eosinophils, and neutrophils.

Conclusions: In this study, a hypoxia-related gene signature associated with childhood asthma was identified. These findings not only highlight potential therapeutic targets for asthma but also offer new insights into its pathogenesis.

Background: Natriuretic peptide receptor 1 (NPR1) plays a crucial role in maintaining the functionality of vascular endothelial cells. However, its role in regulating DNA replication and genome stability in endothelial cells remains unexplored.

Objective: This study aimed to investigate whether NPR1 deficiency disrupts DNA replication and induces DNA damage in human umbilical vein endothelial cells (HUVECs), and to explore the mechanistic role of the E2F transcription factor 2 (E2F2) in this process.

Methods: RNA-sequencing analysis was performed in NPR1-deficient HUVECs. EdU incorporation assay quantified DNA replication activity. qPCR or RNA-seq evaluated expression of DNA replication-related genes. DNA damage levels were assessed via phosphorylated histone H2AX (γH2AX). The proteins of NPR1, E2F2 and γH2AX were examined by Western blot. E2F2 was knocked down or overexpressed in NPR1-deficient HUVECs to validate its regulatory role.

Results: DNA replication related genes were downregulated in NPR1-knockdown HUVECs. This result was supported by a decrease of EdU positive rate of HUVECs upon NPR1 deficiency. Downregulation of DNA replication genes (DSCC1, EXO1, MCM4, MCM6, TREX1 and CCNE2) was observed in NPR1-deficient cells. NPR1 knockdown increased γH2AX, particularly in EdU-positive cells. NPR1 silencing reduced the expression of E2F2. E2F2 knockdown mimicked NPR1 deficiency, suppressing DNA replication genes and increasing DNA damage. Additionally, overexpression of E2F2 recovered the DNA replication and mitigated DNA damage in NPR1-knockdown HUVECs.

Conclusions: NPR1 deficiency declines DNA replication activity and induces DNA damage in vascular endothelial cell by inhibiting E2F2 expression. This provides further insights into the underlying mechanism on NPR1 in the regulation of the functionality of vascular endothelial cells.

Backgound: It is known that in addition to environmental factors such as the athlete's own efforts or the qualities of the coach, genetic predisposition can also have a significant impact on achievements in the sports field.

Objective: For this reason, this study tried to analyze whether single nucleotide polymorphisms (SNPs) in the myostatin, hemochromatosis(HFE) and estrogen receptor 1 (ESR1) genes, which are known to affect muscular strength, cardiorespiratory endurance and flexibility, respectively, could significantly affect the athletic performance of endurance or power/sprint events in Korean population.

Methods: A total of 192 Korean unrelated participants were recruited in this study. They were divided into two groups: controls (n = 72) and track-field athletes (n = 120), which included throwing athletes (n = 39) and distance runners (n = 81). Also, the determination of the genotypes constituting the SNP markers in the three kinds of candidate genes mentioned above was performed using TaqMan method.

Results: Among the three kinds of SNP markers studied, only the rs1799945 polymorphism in the HFE gene was observed to be significantly associated with endurance performance in Korean athletes (p < 0.05).

Conclusion: Therefore, our results suggest that the rs1799945 polymorphism in the HFE gene may be one of useful genetic markers for endurance performance in Korean athletes. Further studies using larger sample sizes and various sports events are needed to replicate our results.

Background: Predictive models using microbiome data often suffer from covariate imbalance and class imbalance, biasing results. Propensity Score Matching (PSM) balances covariates but reduces sample size, while borderline synthetic minority oversampling technique (borderline-SMOTE) oversamples minority classes but can generate uninformative examples.

Objective: To develop and evaluate PSM-SMOTE, a novel hybrid sampling method that integrates PSM and borderline-SMOTE to handle both covariate and class imbalance in microbiome data.

Methods: We developed PSM-SMOTE, a three-step hybrid sampling algorithm for microbiome data: (1) PSM at four caliper levels to balance covariates, (2) selection of at least ten robust differential markers via seven statistical tests with false discovery rate correction, and (3) application of borderline-SMOTE on the marker-based distance matrix to oversample minority classes. We evaluated PSM-SMOTE on three publicly available microbiome case-control datasets: pancreatic ductal adenocarcinoma (PDAC), colorectal cancer (CRC), and obesity, using logistic regression (LR), random forest (RF), and support vector machine (SVM) classifiers. Performance was assessed via area under the ROC curve (AUC).

Results: PSM-SMOTE improved test AUCs in multiple model-dataset combinations compared with using PSM alone. Notably, for the RF model, PSM-SMOTE consistently enhanced AUC across nearly all oversampling settings in the PDAC and obesity cohorts. For the SVM model, PSM-SMOTE also achieved a significant AUC increase in the CRC cohort. For the LR model, PSM-SMOTE showed modest improvement under strict matching.

Conclusion: PSM-SMOTE effectively addresses dual imbalance in microbiome data and consistently enhances performance, providing a practical solution for imbalanced data analyses.

Background: Identifying microbiome markers associated with ordered phenotypes, such as disease stages or severity levels, is crucial for understanding disease progression and advancing precision medicine. Despite this importance, most existing methods for differential abundance analysis are designed for binary group comparisons and do not incorporate ordinal information, limiting their ability to capture trends across ordered categories.

Objective: To develop and evaluate statistical methods that explicitly account for ordinal phenotype structure in microbiome data, addressing challenges such as sparsity and zero inflation, and improving the detection of meaningful microbial associations.

Methods: In this study, we propose and evaluate three novel approaches specifically tailored for microbiome association analysis with ordered groups: the binary optimal test, the linear trend test, and the proportional odds model-based permutation test (POMp). These methods explicitly account for the ordinal structure of phenotypes and address the sparsity and zero-inflation commonly observed in microbiome data through permutation-based inference. We applied the proposed methods to three publicly available gut microbiome datasets, including two related to obesity and one concerning colorectal cancer.

Results: All three proposed methods successfully identified differentially abundant features (DAFs) that exhibited stronger ordinal associations compared to those identified by existing methods. In particular, POMp consistently outperformed other approaches in terms of correlation with phenotype order, demonstrating its potential to identify biologically relevant markers.

Conclusion: The findings of this study highlight the importance of incorporating ordinal information in microbiome studies and provide robust statistical tools for advancing microbial biomarker discovery in complex disease contexts.

Background: Polypterus senegalus is a major actinopterygian fish that provides vital insights into vertebrate terrestrial adaptation. Advances in sequencing technologies have enabled improvements to the reference genome of P. senegalus, highlighting the need to expand research on this species.

Objective: In this study, we sought to construct high-quality, partially-phased, assemblies of the P. senegalus genome using high-fidelity long-read sequencing data.

Methods: First, partially-phased assemblies of P. senegalus genome using PacBio HiFi data. And then, our assemblies were compared with a previously published genome in terms of total length, contiguity, base-level accuracy, and Benchmarking Universal Single-Copy Orthologs (BUSCO) completeness, including resolution of repetitive regions and identification of telomere-telomere chromosomes.

Results: Compared with a previously published genome, our assemblies exhibit improved quality in overall quality. A total of 20,940 genes were annotated employing integrated short-read and long-read RNA sequencing data. Transcriptomics revealed the gene-expression relationships between 12 tissue types and the distinct expression patterns of genes associated with key evolutionary traits, such as aerial respiration, angiogenesis, and limb flexibility. Notably, several genes including Tcf21, Foxf1, and Tbx3a were coordinately expressed in the lungs and swim bladder, supporting shared origins and developmental patterns. Analyses of the correlations among tissues revealed physiological similarities between the lungs, kidneys, and spleen.

Conclusion: Our results provide a valuable genomic resource for P. senegalus and offer novel insights into the molecular basis of vertebrate organ evolution and adaptation.