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Classification of Muscle-Invasive Bladder Cancer Based on Immunogenomic Profiling.
There is a significant heterogeneity in the immunotherapeutic responsiveness of each muscle-invasive bladder cancer (MIBC) patient. In our research, we aimed to identify a novel classification of MIBC based on immunogenomic profiling that may facilitate the reasonable stratification of prognosis and response to immunotherapy. The single-sample gene-set enrichment analysis (ssGSEA) was used to analyze the RNA-seq data of 29 important immune signatures from TCGA. Unsupervised hierarchical clustering was performed to identify an immunogenomic classification of MIBC. Then, we assessed the features of the classification in prognosis, immune infiltration, tumor-infiltration lymphocytes, HLA genes, and PD-L1 expression level. A total of 399 MIBC samples were included and three subtypes named Immunity_High, Immunity_Medium, and Immunity_Low were identified. The Immunity_High had a significant advantage in overall survival over the Immunity_Medium and Immunity_Low (p = 0.046 and p = 0.024). From Immunity_Low to Immunity_High, immune cell infiltration and stromal content showed an upward trend (p < 0.001). Meanwhile, Immunity_High was associated with a significantly higher proportion of TILs including dendritic cells resting, macrophages M1, mast cells resting, T cells CD4 memory activated, and T cells CD8+. And the expression levels of all HLA genes and PD-L1 of Immunity_High were the highest, consistent (p < 0.001). Two hundred ninety eight MIBC patients treated with immunotherapy from the IMvigor210 were included to form an independent validation cohort to verify the robustness of immunogenomic classification and the ability to predict the response to immunotherapy. This classification had potential clinical implications for predicting prognosis and immunotherapeutic responsiveness of MIBC patients.
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Unveiling anti-atherosclerotic targets of Perilla frutescens through a multi-scale computational framework integrating network pharmacology, single-cell analysis, machine learning, and molecular dynamics.
Medicinal plants have long served as important sources of therapeutic agents owing to their diverse bioactive constituents and multi-target pharmacological properties. In particular, plant-derived compounds have attracted increasing attention for the management of chronic inflammatory and metabolic diseases, including atherosclerosis. However, the molecular mechanisms by which medicinal plants modulate the cellular heterogeneity and intercellular communication networks within atherosclerotic plaques remain insufficiently understood. Despite the widespread implementation of lipid-lowering therapy, the persistence of residual inflammatory risk, driven by immunometabolic network dysregulation, remains a cardinal therapeutic challenge in atherosclerosis (AS) management. While Perilla frutescens exhibits well-documented anti-inflammatory properties, the precise molecular targeting within the atherosclerotic plaque microenvironment and the regulatory mechanisms governing intercellular communication networks remain poorly elucidated. To address this gap, we established a multi-scale integrative computational framework synergizing network pharmacology, human atherosclerotic plaque single-cell transcriptomic (scRNA-seq) profiling, and ensemble machine learning algorithms (LASSO and random forest) for systematic identification of robust therapeutic targets. Subsequently, molecular docking coupled with 100-ns all-atom molecular dynamics (MD) simulations validated the binding affinity and thermodynamic stability of drug-target complexes. The study successfully analyzed the cellular heterogeneity lineage of plaques and identified a core feature set of 10 genes including HIF1A, PPARG and ITGB1, which specifically mapped the differentiation trajectory of macrophages to foam cells. External validation in an independent cohort demonstrated superior diagnostic performance of this signature (AUC = 0.996). Cellular communication network dissection revealed the foam cell-driven SPP1-ITGB1 signaling axis as a pivotal conduit orchestrating inflammatory crosstalk. Molecular docking demonstrated pronounced binding affinity between luteolin, the principal bioactive constituent of Perilla frutescens, and ITGB1 (binding energy: - 8.9 kcal/mol). MD simulations further corroborated the efficacy of luteolin in stabilizing ITGB1 conformation via a "conformational-locking" mechanism (RMSD equilibration within 0.10-0.20 nm), thereby abrogating pathological cell adhesion signaling transduction. Collectively, this study provides a high-resolution molecular atlas of Perilla frutescens-mediated AS intervention, systematically elucidating the mechanistic paradigm whereby luteolin attenuates vascular inflammation through targeted disruption of the SPP1-ITGB1 communication axis. These findings underscore the therapeutic targeting of cell adhesion receptors as a translationally promising strategy for mitigating residual inflammatory risk in AS.
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Evidence for Multiple Independent Expansions of Fox Gene Families Within Flatworms.
Expansion and losses of gene families are important drivers of molecular evolution. A recent survey of Fox genes in flatworms revealed that this superfamily of multifunctional transcription factors, present in all animals, underwent extensive losses and expansions during platyhelminth evolution. In this paper, I analyzed Fox gene complement in four additional species of platyhelminths, that represent early-branching lineages in the flatworm phylogeny: catenulids (Stenostomum brevipharyngium and Stenostomum leucops) and macrostomorphs (Macrostomum hystrix and Macrostomum cliftonense). Phylogenetic analysis of Fox genes from this expanded set of species provided evidence for multiple independent expansions of Fox gene families within flatworms. Notably, FoxG, a panbilaterian brain-patterning gene, appears to be the least susceptible to duplication, while FoxJ1, a conserved ciliogenesis factor, has undergone extensive expansion in various flatworm lineages. Analysis of the single-cell atlas of S. brevipharyngium, combined with RNA in situ hybridization, elucidated the tissue-specific expression of the selected Fox genes: FoxG is expressed in the brain, three of the Fox genes (FoxN2/3-2, FoxO4 and FoxP1) are expressed in the pharyngeal cells of likely glandular function, while one of the FoxQD paralogs is specifically expressed in the protonephridium. Overall, the evolution of Fox genes in flatworms appears to be characterized by an early contraction of the gene complement, followed by lineage-specific expansions that have enabled the co-option of newly evolved paralogs into novel physiological and developmental functions.
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A comparative single-cell transcriptomic atlas for diverse populations of vertebrate hair cells.
Mechanosensitive hair cells vary widely in morphology and regenerative capacity across vertebrate organs and species. To investigate their underlying transcriptomic diversity, we integrated human, mouse, chicken, and zebrafish single-cell and single-nucleus RNA sequencing datasets and assembled a cross-species atlas of hair cells spanning organs, developmental stages, and species. Analysis of 29 hair cell populations, encompassing the major cochlear, vestibular, and lateral-line hair cell types, identified approximately 5,000 genes enriched in at least one hair cell population compared to supporting cells from the same organs. Unsupervised clustering of these hair cell-enriched (HCE) genes defined species-, organ-, and hair cell state-associated cohorts as well as broadly conserved hair cell-enriched programs. Using an AUC-based scoring framework, we further defined 884 pan hair cell-enriched (pan-HCE) genes with elevated expression in most developing and/or mature hair cell populations, including genes implicated in deafness, mechanotransduction, and synaptic transmission, along with genes not previously linked to hair cell function. Independent analysis of developing hair cells using the same metrics stratified pan-HCE genes based on when they are first enriched and identified an additional 97 genes that are transiently enriched. We used the pan- and developing HCE gene sets to assess transcriptional similarity between baseline hair cell states and hair cells produced during avian hair cell regeneration and in mouse cochlear organoids, as well as hair cell-like populations produced by fibroblast reprogramming. HCE gene sets with different developmental dynamics identified young vs. more mature hair cells when projected onto independent single-cell RNA sequencing datasets from developing zebrafish, mouse, and human. We provide a web-based resource of all HCE metrics and expression profiles, enabling future exploration of vertebrate hair cell gene expression across organs, species, and experimental contexts.
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PTPRN Serves as a Prognostic Biomarker and Correlated with Immune Infiltrates in Low Grade Glioma.
BACKGROUND: Glioma is one of the most common malignant tumors of the central nervous system. Immune infiltration of tumor microenvironment was associated with overall survival in low grade glioma (LGG). However, effects of Tyrosine phosphatase receptor type N (PTPRN) on the progress of LGG and its correlation with tumor infiltration are unclear. METHODS: Here, datasets of LGG were from The Cancer Genome Atlas (TCGA) and normal samples were from GTEx dataset. Gepia website and Human Protein Atlas (HPA) Database were used to analyze the mRNA and protein expression of PTPRN. We evaluated the influence of PTPRN on survival of LGG patients. MethSurv was used to explore the expression and prognostic patterns of single CpG methylation of PTPRN gene in LGG. The correlations between the clinical information and PTPRN expression were analyzed using logistic regression and Multivariate Cox regression. We also explored the correlation between PTPRN expression and cancer immune infiltration by TIMER. Gene set enrichment analysis (GSEA) was formed using TCGA RNA-seq datasets. RESULTS: PTPRN mRNA and protein expression decreased in LGG compared to normal brain tissue in TCGA and HPA database. Kaplan-Meier analysis showed that the high expression level of PTPRN correlated with a good overall survival (OS) of patients with LGG. The Multivariate Cox analysis demonstrated that PTPRN expression and other clinical-pathological factors (age, WHO grade, IDH status, and primary therapy outcome) significantly correlated with OS of LGG patients. The DNA methylation pattern of PTPRN with significant prognostic value were confirmed, including cg00672332, cg06971096, cg01382864, cg03970036, cg10140638, cg16166796, cg03545227, and cg25569248. Interestingly, PTPRN expression level significantly negatively correlated with infiltrating level of B cell, CD4+ T cells, Macrophages, Neutrophils, and DCs in LGG. Finally, GSEA showed that signaling pathways, mainly associated with tumor microenvironment and immune cells, were significantly enriched in PTPRN high expression. CONCLUSION: PTPRN is a potential biomarker and correlates with tumor immune infiltration in LGG.
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The value of EYA1/3/4 in clear cell renal cell carcinoma: a study from multiple databases.
There is evidence from multiple studies that dysregulation of the Eyes Absent (EYA) protein plays multiple roles in many cancers. Despite this, little is known about the prognostic significance of the EYAs family in clear cell renal cell carcinoma (ccRCC). We systematically analyzed the value of EYAs in Clear Cell Renal Cell Carcinoma. Our analysis included examining transcriptional levels, mutations, methylated modifications, co-expression, protein-protein interactions (PPIs), immune infiltration, single-cell sequencing, drug sensitivity, and prognostic values. We based our analysis on data from several databases, including the Cancer Genome Atlas database (TCGA), the Gene Expression Omnibus database (GEO), UALCAN, TIMER, Gene Expression Profiling Interactive Analysis (GEPIA), STRING, cBioPortal and GSCALite. In patients with ccRCC, the EYA1 gene was significantly highly expressed, while the expression of EYA2/3/4 genes showed the opposite trend. The level of expression of the EYA1/3/4 gene was significantly correlated with the prognosis and clinicopathological parameters of ccRCC patients. Univariate and multifactorial Cox regression analyses revealed EYA1/3 as an independent prognostic factor for ccRCC, establishing nomogram line plots with good predictive power. Meanwhile, the number of mutations in EYAs was also significantly correlated with poor overall survival (OS) and progression-free survival (PFS) of patients with ccRCC. Mechanistically, EYAs genes play an essential role in a wide range of biological processes such as DNA metabolism and double-strand break repair in ccRCC. The majority of EYAs members were related to the infiltration of immune cells, drug sensitivity, and methylation levels. Furthermore, our experiment confirmed that EYA1 gene expression was upregulated, and EYA2/3/4 showed low expression in ccRCC. The increased expression of EYA1 might play an important role in ccRCC oncogenesis, and the decreased expression of EYA3/4 could function as a tumor suppressor, suggesting EYA1/3/4 might serve as valuable prognostic markers and potential new therapeutic targets for ccRCC.
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Targeting PSMB5-induced PANoptosis in bladder cancer: multi-omics insights and TCM candidate discovery.
BACKGROUND: Bladder cancer (BLCA) is among the most common malignancies worldwide, with significant mortality rates. The function of PANoptosis in BLCA, as a controlled process of programmed cell death, remains largely unelucidated. The study aimed to elucidate the role of PANoptosis-related genes in BLCA and investigate their molecular mechanisms, prognostic significance, and therapeutic potential. METHODS: By analyzing differentially expressed genes in BLCA from The Cancer Genome Atlas (TCGA) and PANoptosis-associated genes, we discovered 98 genes associated with PANoptosis. Functional enrichment and consensus clustering identified molecular subtypes linked to these genes. A prognostic model was developed via LASSO regression based on these genes. Subsequent analyses assessed clinical significance, characteristics of the immunological milieu, and treatment responsiveness. Systematic screening with machine learning (ML) identified PSMB5 as a pivotal gene, with its functional importance further clarified using single-cell sequencing and Mendelian randomization analysis (MR). In vitro research confirmed the biological activities of PSMB5 in BLCA. Molecular docking demonstrated PSMB5's binding affinity with traditional Chinese medicines (TCMs). RESULTS: Clustering of 98 PANoptosis-associated genes revealed molecular subgroups A and B. A prognostic approach identified high-risk and low-risk cohorts, revealing considerable disparities in clinical characteristics and immunological landscapes across the groups. ML and MR identified PSMB5 as a risk factor in BLCA. Single-cell sequencing revealed that PSMB5 expression is predominantly associated with three cell lines linked to lymph node metastases. In vitro findings demonstrated that PSMB5 knockdown inhibited the proliferation and migration of BLCA cells while promoting apoptosis, whereas overexpression has the opposite effect. Molecular docking revealed a robust binding affinity between PSMB5 and five TCMs. CONCLUSIONS: A prognostic model incorporating PANoptosis-related genes was developed for stratifying BLCA risk and assessing the immune microenvironment. PSMB5 has been recognized as a crucial therapeutic target, exhibiting dual importance in the molecular etiology of BLCA and traditional Chinese medicine intervention.
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Hepatocellular carcinoma resistance to tyrosine kinase inhibitors: Current status and perspectives.
The study conducted by Wang et al, focuses on the role of Rho GTPase activating protein 12 (ARHGAP12), in hepatocellular carcinoma (HCC). This research reveals that ARHGAP12 expression, markedly elevated in malignant cells of HCC, correlates strongly with adverse outcomes for patients. Furthermore, the study illustrates that ARHGAP12 enhances the ability of HCC cells to invade and contributes to their resistance to tyrosine kinase inhibitors (TKIs) through modulation of the focal adhesion pathway. To comprehensively investigate the relationship between ARHGAP12 and TKI resistance, this study integrates single-cell and bulk RNA sequencing methodologies along with data from tumor immune single-cell hub 2, Gene Expression Omnibus, The Cancer Genome Atlas, CellMiner, Genomics of Drug Sensitivity in Cancer 2, as well as immunohistochemical staining and proteomic analyses. Statistical analyses, including the Wilcoxon rank-sum test and receiver operating characteristic curve analysis, were employed to evaluate the correlation between ARHGAP12 expression levels and clinical parameters, as well as drug sensitivity. It is evident that a more profound exploration of the molecular dynamics of HCC, especially those related to resistance against TKIs, is essential.
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T cell receptor-centric perspective to multimodal single-cell data analysis.
The T cell receptor (TCR), despite its importance, is underutilized in single-cell analysis, with gene expression features solely driving current strategies. Here, we argue for a TCR-first approach, more suited toward T cell repertoires. To this end, we curated a large T cell atlas from 12 prominent human studies, containing in total 500,000 T cells spanning multiple diseases, including melanoma, head and neck cancer, blood cancer, and lung transplantation. Here, we identified severe limitations in cell-type annotation using unsupervised approaches and propose a more robust standard using a semi-supervised method or the TCR arrangement. We showcase the utility of a TCR-first approach through application of the STEGO.R tool for the identification of treatment-related dynamics and previously unknown public T cell clusters with potential antigen-specific properties. Thus, the paradigm shift to a TCR-first can highlight overlooked key T cell features that have the potential for improvements in immunotherapy and diagnostics.
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Galectin-9/TIM-3 as a Key Regulator of Immune Response in Gliomas With Chromosome 1p/19q Codeletion.
Gliomas with chromosome 1p/19q codeletion were considered a specific tumor entity. This study was designed to reveal the biological function alterations tightly associated with 1p/19q codeletion in gliomas. Clinicopathological and RNA sequencing data from glioma patients were obtained from The Cancer Genome Atlas and Chinese Glioma Genome Atlas databases. Gene set variation analysis was performed to explore the differences in biological functions between glioma subgroups stratified by 1p/19q codeletion status. The abundance of immune cells in each sample was detected using the CIBERSORT analytical tool. Single-cell sequencing data from public databases were analyzed using the t-distributed stochastic neighbor embedding (t-SNE) algorithm, and the findings were verified by in vitro and in vivo experiments and patient samples.We found that the activation of immune and inflammatory responses was tightly associated with 1p/19q codeletion in gliomas. As the most important transcriptional regulator of Galectin-9 in gliomas, the expression level of CCAAT enhancer-binding protein alpha in samples with 1p/19q codeletion was significantly decreased, which led to the downregulation of the immune checkpoints Galectin-9 and TIM-3. These results were validated in three independent datasets. The t-SNE analysis showed that the loss of chromosome 19q was the main reason for the promotion of the antitumor immune response. IHC protein staining, in vitro and in vivo experiments verified the results of bioinformatics analysis. In gliomas, 1p/19q codeletion can promote the antitumor immune response by downregulating the expression levels of the immune checkpoint TIM-3 and its ligand Galectin-9.