Your browser does not allow saving data (e.g. private mode): bookmarks will be lost when the tab closes.
Search PubMed
Keywords, author, journal, years — results from PubMed, abstracts with Russian translation, bookmarks in your browser.
Found: 4 939
Page 411 of 494-
Multi-omics characterization of a GPRC5A+ epithelial subpopulation associated with malignant features in colorectal cancer.
BACKGROUND: Colorectal cancer (CRC) exhibits marked cellular heterogeneity, and the cellular context of malignancy-associated epithelial programs remains incompletely defined. METHODS: We integrated 2,993 CRC samples spanning bulk RNA-seq (n = 2,568; two OS/RFS cohorts), scRNA-seq (281,961 cells/152 specimens), spatial transcriptomics (n = 6), and proteomics (n = 267). Analyses included single-cell integration/annotation, GSVA/HALLMARK, interactome, pseudotime, and ligand-receptor mapping; functional CRISPR assays, EMT immunoblotting, and xenografts; TF profiling (SCENIC/JASPAR/ChIP-qPCR); and exploratory drug-response prediction (OncoPredict), cell-sensitivity assays, and docking/MD modeling. RESULTS: We constructed a stage-stratified single-cell atlas and resolved eleven malignant epithelial subsets, characterizing Epi_4 as late-stage-enriched with EMT, hypoxia, and inflammatory programs and adverse OS/RFS. GPRC5A marked this subset, which we define as GPRC5A+Epi; its expression rose from stage I→IV and was associated with poor outcomes across cohorts, with concordant spatial/proteomic observations. GPRC5A perturbation affected CRC proliferation, migration/invasion, EMT, and xenograft tumorigenicity, supporting a functionally important role in the tested models. SCENIC and ChIP-qPCR supported FOSL1 as an upstream regulator that occupies the GPRC5A promoter. Spatial and ligand-receptor analyses predicted close association and potentially reciprocal signaling between GPRC5A+Epi and POSTN+fibroblasts (COL1A1-SDC4, COL1A1/1A2-ITGA2/ITGB1, PPIA-BSG); concurrent high GPRC5A+Epi/POSTN+Fib signatures were associated with inferior OS/RFS. Drug-response analyses identified an association between GPRC5A status and trametinib sensitivity. Docking/MD produced a computational model of a possible trametinib-GPRC5A interaction, which remains experimentally unvalidated. CONCLUSIONS: GPRC5A⁺Epi is a malignancy-associated epithelial state in CRC, and GPRC5A is functionally important for malignant phenotypes in the tested models. Its inferred relationships with POSTN⁺ fibroblasts and the trametinib findings should be regarded as hypothesis-generating pending functional crosstalk, direct-binding, and therapeutic validation.
-
Single-nucleus transcriptomic landscape of primate hippocampal aging.
The hippocampus plays a crucial role in learning and memory, and its progressive deterioration with age is functionally linked to a variety of human neurodegenerative diseases. Yet a systematic profiling of the aging effects on various hippocampal cell types in primates is still missing. Here, we reported a variety of new aging-associated phenotypic changes of the primate hippocampus. These include, in particular, increased DNA damage and heterochromatin erosion with time, alongside loss of proteostasis and elevated inflammation. To understand their cellular and molecular causes, we established the first single-nucleus transcriptomic atlas of primate hippocampal aging. Among the 12 identified cell types, neural transiently amplifying progenitor cell (TAPC) and microglia were most affected by aging. In-depth dissection of gene-expression dynamics revealed impaired TAPC division and compromised neuronal function along the neurogenesis trajectory; additionally elevated pro-inflammatory responses in the aged microglia and oligodendrocyte, as well as dysregulated coagulation pathways in the aged endothelial cells may contribute to a hostile microenvironment for neurogenesis. This rich resource for understanding primate hippocampal aging may provide potential diagnostic biomarkers and therapeutic interventions against age-related neurodegenerative diseases.
-
[A risk prediction model for prognosis and immunotherapy response in prostate cancer patients based on immunosuppressive neutrophil Neu_2 subsets].
OBJECTIVES: To identify immunosuppressive neutrophil subsets in patients with prostate cancer (PCa) and construct a risk prediction model for prognosis and immunotherapy response of the patients based on these neutrophil subsets. METHODS: Single-cell and transcriptome data from PCa patients were collected from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Neutrophil subsets in PCa were identified through unsupervised clustering, and their biological functions and effects on immune regulation were analyzed by functional enrichment, cell interaction, and pseudo-time series analyses. Lasso-Cox regression was utilized to construct a prognostic risk model based on the immunosuppressive neutrophil subsets, and survival analysis and ROC curve analysis were used to compare the prognosis of PCa patients with high and low risks stratified using this model. The relationship of the prognostic risk model with PCa immune infiltration and immune response was evaluated using CIBERSORT and TIDE scores. RESULTS: PCa tissues showed a significantly greater proportion of infiltrating neutrophils than the adjacent normal tissues (P<0.05). PCa-associated neutrophils could be clustered into two independent cell subsets: Neu_1 and Neu_2. Neu_2 cells exhibited highly enriched immunoregulatory functions and were highly differentiated and mature, with upregulated immunosuppressive cytokines such as TGFB1, ITGB2, and LGALS3. Based on the genetic characteristics of Neu_2 cell subsets, the prognostic risk model was constructed. The patients in the high-risk group identified by the model had a shorter biochemical recurrence time (P<0.05) and a higher proportion of Tregs and M2-TAMs cell infiltration (P<0.05) with a higher risk of immune rejection and poorer immune response scores. CONCLUSIONS: PCa-associated neutrophils are highly heterogeneous. The prognostic risk model constructed based on the immunosuppressive neutrophil Neu_2 subset can effectively predict both the survival outcomes and immune response of PCa patients.
-
A novel association of pyroptosis-related gene signature with the prognosis of hepatocellular carcinoma.
BACKGROUND: Hepatocellular carcinoma (HCC) is one of the global leading lethal tumors. Pyroptosis has recently been defined as an inflammatory programmed cell death, which is closely linked to cancer progression. However, the significance of pyroptosis-related genes (PRGs) in the prognosis of HCC remains elusive. METHODS: RNA sequencing (RNA-seq) data of HCC cases and their corresponding clinical information were collected from the Cancer Genome Atlas (TCGA) database, and differential PRGs were explored. The prognostic PRGs were analyzed with univariate COX regression and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to build a prognostic model in the TCGA training cohort. The predictive model was further validated in the TCGA test cohort and ICGC validation cohort. Differential gene function and associated pathway analysis were performed by Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG). Single-sample gene set enrichment analysis (ssGSEA) was used to identify distinct immune cell infiltration. The mRNA and protein expression of prognostic PRGs was examined by quantitative RT-qPCR and immunohistochemistry. RESULTS: We identified 46 PRGs that were differentially expressed between normal and HCC tissues in a TCGA cohort, and HCC patients could be well categorized into two clusters associated with distinct survival rates based on expression levels of the PRGs. A three-PRG prognostic model comprising CHMP4A, HMGB1 and PLK1 was constructed in the training cohort, and HCC patients could be classified into the high- and low-risk subgroups based on the median risk score. High-risk patients exhibited shorter overall survival (OS) than low-risk ones, which was validated in the test cohort and ICGC validation cohort. The risk score of this model was confirmed as an independent prognostic factor to predict OS of HCC patients. GO, KEGG and ssGSEA demonstrated the differential immune cell infiltrations were associated with the risk scores. The higher expression of CHMP4A, HMGB1 and PLK1 were validated in HCC compared to normal in vivo and in vitro. CONCLUSION: The three-PRG signature (CHMP4A, HMGB1, and PLK1) could act as an independent factor to predict the prognosis of HCC patients, which would shed light upon a potent therapeutic strategy for HCC treatment.
-
Unveiling the role of RARs in stomach adenocarcinoma: clinical implications and prognostic biomarkers.
BACKGROUND: Retinoic acid receptors (RARs) family are known to play a significant role in the occurrence and development of tumors. However, the relationship between RARs and stomach adenocarcinoma (STAD) has not yet been clearly identified. The aim of this study is to evaluate the expression profile and clinical value of the RARs family in STAD. METHODS: The expression level, clinical characteristics, prognostic value, immunity-related evaluations, genetic alteration and methylation site of RARs in STAD were explored using a series of online databases including gene expression profiling interactive analysis (GEPIA), tumor immune estimation resource (TIMER), University of Alabama at Birmingham cancer data (UALCAN), Human Protein Atlas (HPA), Kaplan-Meier plotter, gene set cancer analysis (GSCA), cBioPortal, MethSurv, GeneMANIA, LinkedOmics, Metascape, Search tool for the retrieval of interacting genes (STRING), tumor immune single-cell hub (TISCH) and cancer cell line encyclopedia (CCLE). RESULTS: We discovered dramatically increased expression of RARA and decreased expression of RARB in STAD tissues, and many clinical variables were closely related to RARs. Notably, higher expressions of RARA and RARB as well as lower expression of RARG correlated with worse overall survival (OS) for STAD patients. The clinical value of prognostic model indicated that RARs were identified to be potential prognostic biomarkers for STAD patients. Moreover, RARB was closely related to immune cell infiltration, which had effect on the role of RARB in STAD prognosis. And the genetic alteration of RARB was significantly associated with the longer disease-free survival (DFS) of STAD patients. Additionally, some CpG sites of the RARs family were related with the prognosis of STAD patients. Functional enrichment analyses indicated that several pathways in STAD might be pivotal pathways regulated by RARs. At the single-cell level, there was some extent of infiltration of tumor microenvironment-related cells in the RARs expression in STAD. CONCLUSIONS: Our results evaluated the expression profile and clinical values of RARs in patients with STAD, which provided a basis for future in-depth exploration of the specific mechanisms of each member of RARs in STAD.
-
Construction and validation of an EGFR-related risk signature identified SHC1 as a prognostic biomarker for lung adenocarcinoma.
BACKGROUND: Lung adenocarcinoma (LUAD) is a significant subtype of lung cancer, contributing to high mortality rates and posing substantial challenges to public health. This study aims to explore the significance of the epidermal growth factor receptor (EGFR)-related gene SHC1 in the progression and prognosis of LUAD. METHODS: Patient RNA sequencing (RNA-seq) and clinical data were acquired from The Cancer Genome Atlas (TCGA) database. Using the least absolute shrinkage and selection operator (LASSO) Cox regression, we then generated a multigene signature of EGFR signaling-related genes (ESRGs) for the prognostic prediction of LUAD. We investigated the relationship between SHC1 gene expression and immune cell infiltration by employing single-sample gene set enrichment analysis (ssGSEA). The potential functional role of the SHC1 gene was evaluated through GSEA. Additionally, the association between SHC1 expression and clinical data was investigated. Immunohistochemistry was utilized to assess SHC1 expression in 88 cases of invasive pulmonary adenocarcinoma. RESULTS: Univariate Cox regression analysis identified that increased expression of SHC1 correlated with poorer overall survival (OS). SHC1 exhibited significantly elevated expression levels in LUAD tissues. Moreover, elevated levels of SHC1 gene expression correlated strongly with advanced tumor (T), node (N), and metastasis (M) stages and were significantly associated with immune cell infiltration in LUAD. Furthermore, marked increases in SHC1 protein expression were observed in patients diagnosed with invasive pulmonary adenocarcinoma. CONCLUSIONS: These findings suggest that SHC1 plays a crucial oncogenic role in LUAD. Increased SHC1 expression in LUAD was associated with disease progression, an unfavorable prognosis, and dysregulated immune cell infiltration.
-
STEA: Histologically Validated and Reference-Independent Major Cell-Type Annotation for Spatial Transcriptomics Reveals Relevant Cellular Organization and Architecture of Tumor Microenvironment.
BACKGROUND: Recent advances in spatial transcriptomic technologies enable in situ gene expression profiling while preserving spatial context. This capability is particularly important for studying the tumor microenvironment (TME), where diverse and admixed cell populations interact within highly organized spatial niches that influence tumor progression and therapeutic response. However, the limited resolution of early spatial transcriptomic platforms results in each spatial spot capturing transcripts from multiple cell types, making accurate spot deconvolution or annotation a critical yet challenging step in downstream data analysis. The level of complexity will be particularly prominent in heterogeneous samples like the tumor microenvironments where multiple cell types are highly admixed and reliable single-cell reference atlases may usually be unavailable. METHODS: In this paper, we developed our method called STEA, which is a novel and accurate reference-independent enrichment-based annotation algorithm for major cell type. Unlike the existing approaches, STEA does not require single-cell RNA sequencing datasets as reference, offering both flexibility and computational efficiency in execution. RESULTS: We performed comprehensive benchmarking using a variety of simulated datasets across different platforms and scenarios and demonstrated the superior accuracy of STEA. Apart from synthetic data, we also evaluated multiple real datasets to further exemplify its practical applicability on both oncology-related and oncology-unrelated data. More importantly, we could confidently demonstrate the high concordance between prediction of STEA and histological classification by experienced pathologist. CONCLUSION: Our STEA algorithm provides a practical reference-independent framework to complement the cutting-edge spatial transcriptomics in genomics studies, facilitating accurate downstream high-dimensional spatial characterization of cellular and molecular landscapes, reconstruction of tissue architecture as well as cell-cell communication in malignant and non-malignant scenarios. Taken together, our comprehensive evaluation demonstrates the robustness and reliability of STEA, highlighting its potential as a valuable tool for studying complex tissue organization, particularly within heterogeneous TME.
-
Developing a novel aging assessment model to uncover heterogeneity in organ aging and screening of aging-related drugs.
BACKGROUND: The decline in organ function due to aging significantly impacts the health and quality of life of the elderly. Assessing and delaying aging has become a major societal concern. Previous studies have largely focused on differences between young and old individuals, often overlooking the complexity and gradual nature of aging. METHODS: In this study, we constructed a comprehensive multi-organ aging atlas in mice and systematically analyzed the aging trajectories of 16 organs to elucidate their functional specificity and identify organ-specific aging trend genes. Cross-organ association analysis was employed to identify global aging regulatory genes, leading to the development of a multi-organ aging assessment model, hereafter referred to as the 2A model. The model's validity was confirmed using single-cell RNA sequencing data from aging mouse lungs, cross-species gene expression profiles, and pharmacogenomic data. Furthermore, a random walk algorithm and a weighted integration approach combining gene set enrichment analysis were implemented to systematically screen potential drugs for mitigating multi-organ aging. RESULTS: The 2A model effectively assessed aging states in both human and mouse tissues and demonstrated predictive capability for senescent cell clearance rates. Compared to the sc-ImmuAging and SCALE clocks, the 2A model exhibited superior predictive accuracy at the single-cell level. Organ-specific analyses identified the lungs and kidneys as particularly susceptible to aging, with immune dysfunction and programmed cell death emerging as key contributors. Notably, single-cell data confirmed that plasma cell accumulation and naive-like cell reduction showed linear changes during organ aging. Aging trend genes identified in each organ were significantly enriched in aging-related functional pathways, enabling precise assessment of the aging process and determination of organ-specific aging milestones. Additionally, drug screening identified Fostamatinib, Ranolazine, and Metformin as potential modulators of multi-organ aging, with mechanisms involving key pathways such as longevity regulation and circadian rhythm. CONCLUSIONS: The 2A model represents a significant advancement in aging assessment by integrating multi-dimensional validation strategies, enhancing its accuracy and applicability. The identification of organ-specific aging pathways and candidate pharmacological interventions provides a theoretical foundation and translational framework for precision anti-aging therapies.
-
Unveiling a unique microglial phenotype promoting oxidation in the iBRB: insights from single-cell transcriptomics in the NPDR rat model.
BACKGROUND: Early diagnosis and targeted treatment of inner blood-retinal barrier (iBRB) impairment in non-proliferative diabetic retinopathy (NPDR) present significant challenges. This study investigates the cellular heterogeneity and early lesions in the iBRB microenvironment. METHODS: We created a single-cell transcriptional atlas of NPDR using retinas from Zucker Diabetic Fatty rats, focusing on the expression of cells within the iBRB microenvironment, particularly microglia. We performed cell-cell gene interaction analyses to investigate intercellular communications among different cell types in the iBRB. Additionally, we conducted differentiation potential and trajectory analysis, transcription factor regulatory network characterization, and enrichment analysis of microglia. We also employed transmission electron microscopy, immunofluorescence, and histological analysis to validate the hypothesis. RESULTS: Based on retinal samples from NPDR rats which had retinal edema and kidney damage, and normal rats, we selected 36,821 cells for subsequent analysis using single-cell sequencing. We identified 669 cells in iBRB and microglia had the highest connectivity value by enrichment analysis. 980 differentially expressed genes related to microglia divide it into 4 subtypes. Among them, Spp1 highly expressed microglia subtype 2 had the highest differentiation potential and was significantly upregulated after NPDR lesions. By integrating histological and biochemical analysis results, the roles of the subtype in the differentiation of microglia in the iBRB microenvironment, such as oxidative stress and apoptosis, were well validated. CONCLUSION: This study identified a novel microglia type in NPDR rats, offering valuable insight into targeted therapeutic strategies for NPDR patients and enhancing our understanding of microglial regulation within the iBRB.
-
High Expression of CISD2 in Relation to Adverse Outcome and Abnormal Immune Cell Infiltration in Glioma.
Glioma is a serious disease burden globally, with high mortality and recurrence rates. CDGSH iron sulfur domain 2 (CISD2) is an evolutionarily conserved protein that is involved in several cancers. However, its role in the prognosis and immune infiltration in glioma remains unclear. In our research, RNA-seq matrix and clinicopathological relevant data for CISD2 were downloaded from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Human Protein Atlas was used to verify the CISD2 protein level in glioma, and STRING was used to establish relative coexpression gene network. The Kaplan-Meier plotter was adopted to analyze the effect of CISD2 on prognosis. The connection between CISD2 expression and immune infiltration was analyzed using single-sample GSEA (ssGSEA), TIMER, and GEPIA. In contrast to normal tissues, CISD2 expression was significantly higher in glioma tissues, and CISD2 presented a certain diagnostic value in distinguishing glioma tissues from normal tissues. Furthermore, the CISD2 level was correlated with age, histologic grade, histological type, isocitrate dehydrogenase (IDH) status, 1p/19q codeletion status, and primary therapy outcome of glioma, while high CISD2 mRNA expression was correlated with grave overall survival. Multivariate analysis demonstrated that CISD2 was an independent risk factor for patients with glioma. Functional enrichment analysis indicated that CISD2 could regulate proliferation, immune reaction, and mitochondrial function. The results from the ssGSEA and TIMER databases confirmed that CISD2 acts a prominent role in immune cell infiltration in the tumor microenvironment, especially in low-grade glioma (LGG). Furthermore, CISD2 expression was observably correlated to M2 polarization in macrophages with glioma progression. This is the first research to investigate the immune role of CISD2 in glioma. CISD2 may be an innovative prognostic biomarker and can act as a potential target for future therapy for glioma.