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Identification of an anoikis-related gene signature and characterization of immune infiltration in skin cutaneous melanoma.
Anoikis is considered strongly associated with a biological procession of tumors. Herein, we utilized anoikis-related genes (ARGs) to predict the prognosis and immunotherapeutic efficacy for skin cutaneous melanoma (SKCM). RNA-seq data were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. After dividing patients into novel subtypes based on the expression of prognostic ARGs, K-M survival was conducted to compare the survival status. Subsequently, differentially expressed ARGs were identified and the predictive model was established. The predictive effects were validated using the areas under the curve about the receiver operating characteristic. Moreover, tumor mutation burden, the enriched functional pathway, immune cells and functions, and the immunotherapeutic response were also analyzed and compared. The distribution of model genes at cell level was visualized by the single-cell seq with tumor immune single-cell hub database. Patients of The Cancer Genome Atlas-SKCM cohort were divided into 2 clusters, the cluster 1 performed a better prognosis. Cluster 2 was more enriched in metabolism-related pathways whereas cluster 1 was more associated with immune pathways. A predictive risk model was established with 6 ARGs, showing the areas under the curves of 1-year, 3-year, and 5-year ROC were 0.715, 0,720, and 0.731, respectively. Moreover, risk score was negatively associated with tumor mutation burden and immune-related pathways enrichment. In addition, patients with high-risk scores performed immunosuppressive status but the decreasing scores enhanced immune cell infiltration, immune function activation, and immunotherapeutic response. In this study, we established a novel signature in predicting prognosis and immunotherapy. It can be considered reliable to formulate the complex treatment for SKCM patients.
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Single-cell multiomics gene regulatory landscape reveals impaired spermatogonial stem cells and macrophage-driven inflammaging during testicular aging.
Testicular aging is a key driver of declining male reproductive health, but a comprehensive understanding of its underlying epigenetic drivers is lacking. To address this, we construct a multiomics aging atlas by integrating single-cell RNA sequencing, single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq), and spatial transcriptomics of young and aged mouse testes. Our analysis reveals that altered chromatin accessibility accompanies transcriptional dysregulation and identifies spermatogonial stem cells (SSCs) as the most epigenetically vulnerable population. We further pinpoint ZFX as a consistently downregulated transcription factor in early germ cells, linking its decline to compromised SSC maintenance. In the somatic niche, we define disrupted regulatory networks that underpin impaired blood-testis barrier integrity in Sertoli cells and steroidogenic dysfunction in Leydig cells. Notably, we uncover an aberrant expansion of CD206+H2-Eb1- macrophages that propagates local inflammation via the secreted factor CXCL13, which we demonstrate is sufficient to disrupt the SSC niche. Cross-species analysis identifies conserved aging-associated regulons, including BRCA1 and E2F1. This work provides resources for understanding testicular senescence and nominates ZFX and CXCL13 as potential therapeutic targets for mitigating age-related reproductive decline.
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A molecularly defined and spatially resolved cell atlas of the whole mouse brain.
In mammalian brains, tens of millions to billions of cells form complex interaction networks to enable a wide range of functions. The enormous diversity and intricate organization of cells in the brain have so far hindered our understanding of the molecular and cellular basis of its functions. Recent advances in spatially resolved single-cell transcriptomics have allowed systematic mapping of the spatial organization of molecularly defined cell types in complex tissues1-3. However, these approaches have only been applied to a few brain regions1-11 and a comprehensive cell atlas of the whole brain is still missing. Here, we imaged a panel of >1,100 genes in ~8 million cells across the entire adult mouse brain using multiplexed error-robust fluorescence in situ hybridization (MERFISH)12 and performed spatially resolved, single-cell expression profiling at the whole-transcriptome scale by integrating MERFISH and single-cell RNA-sequencing (scRNA-seq) data. Using this approach, we generated a comprehensive cell atlas of >5,000 transcriptionally distinct cell clusters, belonging to ~300 major cell types, in the whole mouse brain with high molecular and spatial resolution. Registration of the MERFISH images to the common coordinate framework (CCF) of the mouse brain further allowed systematic quantifications of the cell composition and organization in individual brain regions defined in the CCF. We further identified spatial modules characterized by distinct cell-type compositions and spatial gradients featuring gradual changes in the gene-expression profiles of cells. Finally, this high-resolution spatial map of cells, with a transcriptome-wide expression profile associated with each cell, allowed us to infer cell-type-specific interactions between several hundred pairs of molecularly defined cell types and predict potential molecular (ligand-receptor) basis and functional implications of these cell-cell interactions. These results provide rich insights into the molecular and cellular architecture of the brain and a valuable resource for future functional investigations of neural circuits and their dysfunction in diseases.
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Identification of DNA damage and repair gene-related markers in pancreatic ductal adenocarcinoma by single-cell and bulk RNA sequencing.
BACKGROUND: The DNA damage response (DDR) has a major impact on the development and progression of pancreatic ductal adenocarcinoma (PDAC). Investigating biomarkers linked to the DDR may facilitate prognostic assessment and prediction of immunological characteristics for patients with PDAC. METHODS: The single-cell RNA sequencing (scRNA-seq) dataset GSE212966 was obtained from the GEO database, whereas the bulk RNA-seq data were sourced from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Least absolute shrinkage and selection operator (LASSO) and univariate Cox regression analyses were used to select genes to construct a prognostic risk model. Finally, the correlations of the model score with drug sensitivity, immunological checkpoints, and immune infiltration were assessed. RESULTS: We used 16 DDR marker genes to construct a predictive model. Furthermore, we established that the model had strong performance in both the training and validation cohorts. For PDAC, the model risk score served as an independent predictor of prognosis. There were notable differences in the proportions of the immune cells in the tumor microenvironment and drug sensitivity between the high and low risk score groups. The study confirmed that the risk score model is useful for predicting the immunotherapy response. Our experiments verified that knockdown of LY6D inhibits cell proliferation, promotes apoptosis and DNA damage. CONCLUSION: Our creative integration of bulk RNA sequencing and scRNA-seq data allowed us to construct a DDR-related prognostic model. Our model can be used to predict the immunological features, treatment response and prognosis of PDAC with a relatively high degree of accuracy.
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Single-Cell Atlas of the Chinese Tongue Sole (Cynoglossus semilaevis) Ovary Reveals Transcriptional Programs of Oogenesis in Fish.
Oogenesis is a highly orchestrated process that depends on regulation by autocrine/paracrine hormones and growth factors. However, many details of the molecular mechanisms that regulate fish oogenesis remain elusive. Here, we performed a single-cell RNA sequencing (scRNA-seq) analysis of the molecular signatures of distinct ovarian cell categories in adult Chinese tongue sole (Cynoglossus semilaevis). We characterized the successive stepwise development of three germ cell subtypes. Notably, we identified the cellular composition of fish follicle walls, including four granulosa cell types and one theca cell type, and we proposed important transcription factors (TFs) showing high activity in the regulation of cell identity. Moreover, we found that the extensive niche-germline bidirectional communications regulate fish oogenesis, whereas ovulation in fish is accompanied by the coordination of simultaneous and tightly sequential processes across different granulosa cells. Additionally, a systems biology analysis of the homologous genes shared by Chinese tongue sole and macaques revealed remarkably conserved biological processes in germ cells and granulosa cells across vertebrates. Our results provide key insights into the cell-type-specific mechanisms underlying fish oogenesis at a single-cell resolution, which offers important clues for exploring fish breeding mechanisms and the evolution of vertebrate reproductive systems.
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The immunological paradox of tubal ectopic pregnancy: unraveling immune tolerance amidst inflammation via single-cell sequencing.
BACKGROUND: Tubal ectopic pregnancy (TEP) is a common and serious obstetric complication with unclear pathogenesis. This study aims to use single-cell RNA sequencing (scRNA-seq) to analyze immune cell composition and functional changes in implantation sites (IS) and non-implantation sites (NIS) of fallopian tube tissues from TEP patients, exploring potential pathogenesis. METHODS: We performed scRNA-seq on IS and NIS tubal tissues from TEP patients, constructing a high-resolution immune atlas. Differential expression and functional enrichment analysis were applied to reveal functional reprogramming in key immune subsets. RESULTS: We identified a total of 28 cell clusters encompassing 13 major cell types, and T/NK cells and macrophages as the predominant populations. Further subcluster analysis demonstrated CD4⁺ memory T cells (CD4⁺ Tm) enriched at the IS exhibited both pro-inflammatory and immune-tolerant function; CD8⁺ KLRC2⁺ effector T cells and CD8⁺ memory T cells (CD8⁺ Tm) were reduced in proportion and functionally impaired; monocyte numbers increased, contributing to chronic inflammation and abnormal angiogenesis; M1 macrophages decreased while M2 macrophages increased, promoting immune tolerance, angiogenesis, and extracellular matrix remodeling. Therefore, functional reprogramming and altered cellular composition of the TEP immune microenvironment underlie both transient ectopic embryo survival and tubal tissue damage. CONCLUSION: This study reveals the key roles of CD4⁺ Tm cells, CD8⁺ KLRC2⁺ Teff cells, CD8⁺ Tm cells, monocytes, and M1/M2 macrophages, offering insights into the pathogenesis of TEP and potential immunological interventions.
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Genome-wide profiling of circular RNAs, alternative splicing, and R-loops in stem-differentiating xylem of Populus trichocarpa.
Circular RNAs (circRNAs) are a recently discovered type of non-coding RNA derived from pre-mRNAs. R-loops consist of a DNA:RNA hybrid and the associated single-stranded DNA. In Arabidopsis thaliana, circRNA:DNA R-loops regulate alternative splicing (AS) of SEPALLATA3 (SEP3). However, the occurrence and functions of circRNAs and R-loops in Populus trichocarpa are largely unexplored. Here, we performed circRNA-enriched sequencing in the stem-differentiating xylem (SDX) of P. trichocarpa and identified 2,742 distinct circRNAs, including circ-CESA4, circ-IRX7, and circ-GUX1, which are generated from genes involved in cellulose, and hemicellulose biosynthesis, respectively. To investigate the roles of circRNAs in modulating alternative splicing (AS), we detected 7,836 AS events using PacBio Iso-Seq and identified 634 circRNAs that overlapped with 699 AS events. Furthermore, using DNA:RNA hybrid immunoprecipitation followed by sequencing (DRIP-seq), we identified 8,932 R-loop peaks that overlapped with 181 circRNAs and 672 AS events. Notably, several SDX-related circRNAs overlapped with R-loop peaks, pointing to their possible roles in modulating AS in SDX. Indeed, overexpressing circ-IRX7 increased the levels of R-loop structures and decreased the frequency of intron retention in linear IRX7 transcripts. This study provides a valuable R-loop atlas resource and uncovers the interplay between circRNAs and AS in SDX of P. trichocarpa.
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Systematic analysis of expression signatures of neuronal subpopulations in the VTA.
Gene expression profiling across various brain areas at the single-cell resolution enables the identification of molecular markers of neuronal subpopulations and comprehensive characterization of their functional roles. Despite the scientific importance and experimental versatility, systematic methods to analyze such data have not been established yet. To this end, we developed a statistical approach based on in situ hybridization data in the Allen Brain Atlas and thereby identified specific genes for each type of neuron in the ventral tegmental area (VTA). This approach also allowed us to demarcate subregions within the VTA comprising specific neuronal subpopulations. We further identified WW domain-containing oxidoreductase as a molecular marker of a population of VTA neurons that co-express tyrosine hydroxylase and vesicular glutamate transporter 2, and confirmed their region-specific distribution by immunohistochemistry. The results demonstrate the utility of our analytical approach for uncovering expression signatures representing specific cell types and neuronal subpopulations enriched in a given brain area.
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HeLa nucleic acid contamination in the cancer genome atlas leads to the misidentification of human papillomavirus 18.
UNLABELLED: We searched The Cancer Genome Atlas (TCGA) database for viruses by comparing non-human reads present in transcriptome sequencing (RNA-Seq) and whole-exome sequencing (WXS) data to viral sequence databases. Human papillomavirus 18 (HPV18) is an etiologic agent of cervical cancer, and as expected, we found robust expression of HPV18 genes in cervical cancer samples. In agreement with previous studies, we also found HPV18 transcripts in non-cervical cancer samples, including those from the colon, rectum, and normal kidney. However, in each of these cases, HPV18 gene expression was low, and single-nucleotide variants and positions of genomic alignments matched the integrated portion of HPV18 present in HeLa cells. Chimeric reads that match a known virus-cell junction of HPV18 integrated in HeLa cells were also present in some samples. We hypothesize that HPV18 sequences in these non-cervical samples are due to nucleic acid contamination from HeLa cells. This finding highlights the problems that contamination presents in computational virus detection pipelines. IMPORTANCE: Viruses associated with cancer can be detected by searching tumor sequence databases. Several studies involving searches of the TCGA database have reported the presence of HPV18, a known cause of cervical cancer, in a small number of additional cancers, including those of the rectum, kidney, and colon. We have determined that the sequences related to HPV18 in non-cervical samples are due to nucleic acid contamination from HeLa cells. To our knowledge, this is the first report of the misidentification of viruses in next-generation sequencing data of tumors due to contamination with a cancer cell line. These results raise awareness of the difficulty of accurately identifying viruses in human sequence databases.
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An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus.
The hippocampus contains many unique cell types, which serve the structure's specialized functions, including learning, memory and cognition. These cells have distinct spatial organization, morphology, physiology, and connectivity, highlighting the importance of transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus in ten adult neurotypical donors to define molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization (NMF) and label transfer, we integrated these data by defining gene expression patterns within the snRNA-seq data and inferring their expression in the SRT data. We identified NMF patterns that captured transcriptional variation across neuronal cell types and indicated that the response of excitatory and inhibitory postsynaptic specializations were prioritized in different SRT spatial domains. We used the NMF and label transfer approach to leverage existing rodent datasets, identifying patterns of activity-dependent transcription and subpopulations of dentate gyrus granule cells in our SRT dataset that may be predisposed to participate in learning and memory ensembles. Finally, we characterized the spatial organization of NMF patterns corresponding to non-cornu ammonis pyramidal neurons and identified snRNA-seq clusters mapping to distinct regions of the retrohippocampus, to three subiculum layers, and to a population of presubiculum neurons. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.