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At least 235 records · Page 13Linked to original sources

Malignant epithelial states drive immune dysfunction in ampulla of Vater carcinoma.

BACKGROUND: Ampulla of Vater (AoV) carcinoma is a rare malignancy arising at the junction of intestinal and pancreatobiliary epithelium. Its heterogeneous clinical behavior and histological diversity have hindered therapeutic advances, and the cellular basis of this heterogeneity remains unclear. We aimed to construct a single-cell transcriptomic atlas of AoV carcinoma, with a focus on identifying epithelial subtypes and their interactions with the tumor microenvironment (TME). METHODS: We performed single-cell RNA sequencing on eight primary AoV tumors and four matched normal tissues. Comprehensive clustering and transcriptomic analyses identified cell-type composition, epithelial heterogeneity, and tumor-immune interactions. Findings were validated using deconvolution of bulk RNA-seq data from 62 AoV carcinoma patients. Results Malignant epithelial cells were categorized into four distinct subtypes: Int-Wnt, PB-KRAS, Int-Hypoxia, and Cycling stage. PB-KRAS cells exhibited stem-like transcriptional programs and high genomic instability. Deconvolution analysis of bulk RNA-seq data from the independent AoV cohort revealed that enrichment of the PB-KRAS subtype correlated with tumor recurrence and poor survival. Our immune profiling analysis discovered a significant association between PB-KRAS subtype and GZMK+ CD8+ T cells, which are in a pre-dysfunctional state, alongside SPP1+ macrophages exhibiting immunosuppressive traits. Spatial transcriptome data further supports the immunosuppressive natures of TME around PB-KRAS subtype malignant epithelial cells in AoV carcinoma. CONCLUSIONS: Our study presents a single-cell atlas of AoV carcinoma, highlighting the molecular diversity of malignant epithelium and its association with the immune microenvironment. The PB-KRAS subtype emerges as a stem-like, immunosuppressive tumor state associated with poor prognosis, providing insights for future therapeutic targeting.

Ampulla of Vater carcinoma↗

Direct amplification of single-stranded DNA for pyrosequencing using linear-after-the-exponential (LATE)-PCR.

Pyrosequencing is a highly effective method for quantitatively genotyping short genetic sequences, but it currently is hampered by a labor-intensive sample preparation process designed to isolate single-stranded DNA from double-stranded products generated by conventional PCR. Here linear-after-the-exponential (LATE)-PCR is introduced as an efficient and potentially automatable method of directly amplifying single-stranded DNA for pyrosequencing, thereby eliminating the need for solid-phase sample preparation and reducing the risk of laboratory contamination. These improvements are illustrated for single-nucleotide polymorphism genotyping applications, including an integrated single-cell-through-sequencing assay to detect a mutation at the globin IVS 110 site that frequently is responsible for beta-thalassemia.

Cell Line↗

Histological aspects of in situ hybridization. Detection of poly(A) nucleotide sequences in mouse liver sections as a model system.

This study examined the detection of cellular poly(A) sequences in mouse liver sections by in situ hybridization using a 3H-labelled poly(dT) probe. Parameters examined included possible losses of target poly(A) sequences from sectioned cells, access of probe to target sequences, section thickness, hybridization conditions, autoradiographic efficiency, specific activity of probes and specificity of reaction. An improved protocol was devised that resulted in good preservation of histological detail in sectioned tissue blocks, and a calculated hybridization efficiency of 50%-100%. With the use of probes of defined sequence, the protocol should allow detection of unique mRNA sequences within single cells with an estimated sensitivity of 6-12 unique mRNA molecules per sectioned cell.

Animals↗

Laser-capture microdissection: refining estimates of the quantity and distribution of latent herpes simplex virus 1 and varicella-zoster virus DNA in human trigeminal Ganglia at the single-cell level.

There remains uncertainty and some controversy about the percentages and types of cells in human sensory nerve ganglia that harbor latent herpes simplex virus 1 (HSV-1) and varicella-zoster virus (VZV) DNA. We developed and validated laser-capture microdissection and real-time PCR (LCM/PCR) assays for the presence and copy numbers of HSV-1 gG and VZV gene 62 sequences in single cells recovered from sections of human trigeminal ganglia (TG) obtained at autopsy. Among 970 individual sensory neurons from five subjects, 2.0 to 10.5% were positive for HSV-1 DNA, with a median of 11.3 copies/positive cell, compared with 0.2 to 1.5% of neurons found to be positive by in situ hybridization (ISH) for HSV-1 latency-associated transcripts (LAT), the classical surrogate marker for HSV latency. This indicates a more pervasive latent HSV-1 infection of human TG neurons than originally thought. Combined ISH/LCM/PCR assays revealed that the majority of the latently infected neurons do not accumulate LAT to detectable levels. We detected VZV DNA in 1.0 to 6.9% of individual neurons from 10 subjects. Of the total 1,722 neurons tested, 4.1% were VZV DNA positive, with a median of 6.9 viral genomes/positive cell. After removal by LCM of all visible neurons on a slide, all surrounding nonneuronal cells were harvested and assayed: 21 copies of HSV-1 DNA were detected in approximately 5,200 nonneuronal cells, while nine VZV genomes were detected in approximately 14,200 nonneuronal cells. These data indicate that both HSV-1 and VZV DNAs persist in human TG primarily, if not exclusively, in a moderate percentage of neuronal cells.

Base Sequence↗

Intrinsic changes in cell differentiation and identity drive impaired wound healing in aged female murine skin.

Cellular and molecular mechanisms that drive a perturbed wound microenvironment and impaired healing in aged skin have not been fully delineated. To obtain a comprehensive understanding of cell-intrinsic changes acquired during ageing that impact early responses to injury, we performed single-cell RNA sequencing in young and aged intact female murine skin and wounds 3 days post-injury. We observed that substantial changes in the mean proportional distribution and transcriptomic state of skin resident subpopulations in aged, but not young, tissues accompany a global increase in basal inflammation. This is driven by an altered signalling environment leading to impaired keratinocyte differentiation, loss of fibroblast identity and defective macrophage function. Further, we show that ageing-induced changes in skin resident cells persist after injury, resulting in increased expression of senescence-related genes in wound fibroblasts and aberrant monocyte-to-macrophage transitioning coupled to an enhanced inflammatory signature and defective intercellular signalling in comparison to wounds in young mice. In summary, our data highlights a contribution of both cell-intrinsic changes and an altered tissue microenvironment to poor wound healing responses in aged mice.

Animals↗

Nonlinear transcriptional responses to gradual modulation of transcription factor dosage.

Genomic loci associated with common traits and diseases are typically non-coding and likely impact gene expression, sometimes coinciding with rare loss-of-function variants in the target gene. However, our understanding of how gradual changes in gene dosage affect molecular, cellular, and organismal traits is currently limited. To address this gap, we induced gradual changes in gene expression of four genes using CRISPR activation and inactivation. Downstream transcriptional consequences of dosage modulation of three master trans-regulators associated with blood cell traits (GFI1B, NFE2, and MYB) were examined using targeted single-cell multimodal sequencing. We showed that guide tiling around the TSS is the most effective way to modulate cis gene expression across a wide range of fold-changes, with further effects from chromatin accessibility and histone marks that differ between the inhibition and activation systems. Our single-cell data allowed us to precisely detect subtle to large gene expression changes in dozens of trans genes, revealing that many responses to dosage changes of these three TFs are nonlinear, including non-monotonic behaviours, even when constraining the fold-changes of the master regulators to a copy number gain or loss. We found that the dosage properties are linked to gene constraint and that some of these nonlinear responses are enriched for disease and GWAS genes. Overall, our study provides a straightforward and scalable method to precisely modulate gene expression and gain insights into its downstream consequences at high resolution.

Journal Article↗

Endocrine-disrupting chemical-induced gene networks confer coronary heart disease risk revealed by causal inference and single-cell analyses.

BACKGROUND: Endocrine-disrupting chemicals (EDCs) are linked to coronary heart disease (CHD), but underlying mechanisms remain unclear. We aimed to identify EDC-related genes and evaluate their causal roles in CHD. METHODS: We curated EDC-related genes from a compound-gene interaction database and integrated them with CHD genome-wide association study (GWAS) summary statistics and tissue-specific expression quantitative trait loci (eQTL) data. Two-sample Mendelian randomization (MR) and Bayesian colocalization were applied to infer causality. Functional enrichment, single-cell RNA sequencing of human coronary arteries, and EDC-gene networks were further analyzed. RESULTS: After FDR correction, 39 genes were significantly associated with CHD risk via MR. Four genes-ZNF827, FCHO1, IPO9 (protective), and RPL13 (risk-increasing)-showed strong colocalization (PPH4 > 0.9). Pathway and single-cell analyses of coronary artery tissue indicated that vascular and immune pathways mediate these effects. An interaction network highlighted associations between specific EDCs and candidate genes implicated in CHD susceptibility. CONCLUSION: This integrative genomic study provides evidence that EDCs influence CHD susceptibility through distinct gene networks, revealing potential mechanisms and molecular targets for prevention and therapy.

Humans↗

FIERCE: reconstructing dynamic trajectories from the differentiation potency of single cells.

MOTIVATION: Since the introduction of single-cell RNA sequencing (scRNA-seq), numerous computational approaches have been developed to reconstruct dynamic cellular processes from static transcriptional profiles. These methods order cells along continuous trajectories by assessing their similarity in the gene-expression space. However, they rely on several assumptions, such as prior knowledge of the structure and directionality of the expected genealogy. These assumptions can limit their application to complex cellular systems with poorly understood developmental paths. RESULTS: To address this challenge, we introduce FIERCE (Framework for InfERence of the veloCity of Entropy), a novel computational pipeline designed to predict the changes in the differentiation potency of single cells during dynamic processes. Through a fully unsupervised approach, FIERCE enables the inference of cell lineages directly on the differentiation landscape of the biological system, thus eliminating the need for prior specification of developmental parameters. We demonstrate the efficacy of FIERCE by reconstructing three well-known mouse differentiation systems and by quantifying its accuracy on simulated data. AVAILABILITY AND IMPLEMENTATION: The FIERCE R package is available on GitHub at https://github.com/bicciatolab/FIERCE.

Cell Differentiation↗

Enhancing pan-cancer spatial transcriptomics at single-cell resolution with stPainter.

Subcellular spatial transcriptomics can resolve tissue architecture at cellular scale, but sparse gene panels and limited detection sensitivity constrain downstream analysis. Existing enhancement methods often require tissue-matched single-cell RNA sequencing (scRNA-seq) references and dataset-specific retraining. Here we show that stPainter, a conditional generative model pretrained on a pan-cancer scRNA-seq atlas, can enhance spatial transcriptomics data without matched references or retraining. Using a latent diffusion architecture guided by Stochastic Differential Equations (SDE), stPainter reconstructs expanded expression profiles from sparse measurements and produces latent representations for clustering and cell-state analysis. When we apply stPainter upon 6 spatial transcriptomics datasets of different cancer types, we demonstrate that our model empowers downstream biological analyses, including fine-grained subpopulation clustering and pathway enrichment. Comparison with spatially resolved proteomics (CODEX) provided independent support for regional agreement between imputed cellular compositions and protein-level tissue organization. These results establish stPainter as a scalable approach for analyzing tumor microenvironments without auxiliary sequencing data.

Spatial Transcriptomics↗

Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair.

The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from seventeen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, Hi-C, and karyotyping. These data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic variants. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.

Humans↗

Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair.

The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first to be explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from seventeen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, and Hi-C, and karyotyping. In future publications, these data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic mutations. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology.

Journal Article↗

Cellular transcriptomic signatures underpinning the heterogeneity of depression in Alzheimer's disease.

INTRODUCTION: Late-onset Alzheimer's disease (LOAD) and major depressive disorder (MDD) share genetic etiologies. Here, we investigated brain transcriptomic landscapes to gain insights into shared and divergent molecular and biological etiologies across LOAD and MDD. METHODS: Brain single-nucleus RNA sequencing (snRNA-seq) datasets from cognitively normal older and young individuals and LOAD patients stratified by comorbid MDD were analyzed to identify differential expressed genes (DEGs). Using cell type-specific DEGs we performed biological pathway and intercellular-communication networks analyses. We investigated shared DEGs across MDD and LOAD cohorts and sex-specific DEGs. Results were validated by comparison with four transcriptomic and proteomic studies of MDD and depression. RESULTS: MDD-associated dysregulated genes and pathways were shared between LOAD and cognitive-normal individuals, including JUNB and DUSP1 in glutamatergic neurons, and PRAM1 and SNX9 in microglia. DEGs shared between the MDD and LOAD cohorts included HSPA1A and NDUFB7 in glutamatergic neurons. Sex interaction analysis identified numerous new DEGs in the MDD cohorts, whereas there were ≈5 to 10 times more DEGs in female than in male individuals. LOAD and MDD common microglial pathways included neuronal injury, stress, peroxisome proliferator-activated receptor (PPAR) signaling and interferon alpha/beta signaling. DISCUSSION: LOAD and MDD exhibited common molecular profiles, dysregulated pathways, and cellular communication changes. MDD develops earlier in life, thus, our findings provide a window into early molecular and biological processes preceding LOAD-onset.

Humans↗

Whole genome amplification from single cells in preimplantation genetic diagnosis and prenatal diagnosis.

The literature on whole genome amplification (WGA) techniques and their application to preimplantation genetic diagnosis (PGD) and prenatal diagnosis is reviewed. General polymerase chain reaction (PCR) fails to provide adequate information from limited cells in PGD and non-invasive prenatal diagnosis. Therefore several WGA techniques, such as primer extension preamplification (PEP) and degenerate oligonucleotide primed PCR (DOP-PCR), have been developed and successfully applied to clinical work during the past decade, especially in PGD and prenatal diagnosis. These techniques can provide ample amplification of genetic sequences from single cells for a series of subsequent PCR analyses such as restriction fragment length polymorphisms (RFLP) and comparative genomic hybridization (CGH), thus opening up a new area for prenatal diagnosis. However, several problems have been reported in the application of these techniques. The ideal WGA technique should have high yield, faithful representation of the original template, complete coverage of the genome, and simply performed procedure. In order to make good use of these techniques in future research and clinical work, it is undoubtedly necessary for an extensive understanding of the merits and pitfalls of these recently developed techniques.

Blastomeres↗

Changes in cytokine secretion induced by altered peptide ligands of myelin basic protein peptide 85-99.

Myelin basic protein (MBP)-specific T cells were isolated directly from peripheral blood by stimulation either with native MBPp85-99 or altered peptide ligands (APLs) in which substitutions of the lysine were made at position 93, a TCR contact residue. We report here that the APL 93A could alter the cytokine profile of some autoreactive MBPp85-99 reactive T cell clones, switching them from a Th0 phenotype secreting high concentrations of IL-4, IL-5, and IFN-gamma into Th2 cells secreting significantly less IFN-gamma. However, in vitro stimulation with the 93A peptide, in some instances, induced T cells that responded better to the native MBPp85-99 peptide. Functionally, the APL 93A was shown to act as an antagonist for IFN-gamma secretion. Based on TCR sequencing and single cell cloning, this alteration in cytokine profile was determined to be the result of the differential activation of individual T cell clones. We discuss the implications of these data for the strength of signal model of T cell activation.

Autoimmune Diseases↗

Telomere length dynamics in human lymphocyte subpopulations measured by flow cytometry.

To measure the average length of telomere repeats at chromosome ends in individual cells we developed a flow cytometry method using fluorescence in situ hybridization (flow FISH) with labeled peptide nucleic acid (PNA) probes. Results of flow FISH measurements correlated with results of conventional telomere length measurements by Southern blot analysis (R = 0.9). Consistent differences in telomere length in CD8+ T-cell subsets were identified. Naive and memory CD4+ T lymphocytes in normal adults differed by around 2.5 kb in telomere length, in agreement with known replicative shortening of telomeres in lymphocytes in vivo. T-cell clones grown in vitro showed stabilization of telomere length after an initial decline and rare clones capable of growing beyond 100 population doublings showed variable telomere length. These results show that flow FISH can be used to measure specific nucleotide repeat sequences in single cells and indicate that the very large replicative potential of lymphocytes is only indirectly related to telomere length.

Adult↗

Multi-omics identification and functional validation of signal regulatory protein gamma as a prognostic biomarker and immune regulator in head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) comprises biologically diverse tumors, and durable responses to immune-checkpoint blockade are achieved by only a subset of patients. There remains a need for markers that connect clinical outcome with malignant-cell phenotypes and tissue-level immune organization. METHODS: We integrated The Cancer Genome Atlas HNSCC cohort (TCGA-HNSC), five Gene Expression Omnibus (GEO) validation cohorts, single-cell RNA sequencing, Visium spatial transcriptomics, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq)-informed protein-potential inference, pharmacogenomic screening, genetic-risk analysis and experimental validation. A reconstructed 296-pipeline survival modelling framework was used to prioritize prognostic hub genes across validation-cohort-specific analyses. RESULTS: SIRPG was repeatedly ranked among the top ten selected genes in all five validation cohorts. At single-cell resolution, SIRPG-high tumor cells showed stronger malignant-cell features, immune-inhibitory and metabolic programs, Scissor-positive risk association, CLCA2/P53-related perturbation signals and inferred SIRPG-CD47/signal regulatory protein (SIRP) communication. Spatial analyses placed this axis within an immune-checkpoint-coupled niche, supported by Maxspin/multiview intercellular spatial modelling (MISTy) spatial coupling, communication analysis by optimal transport (COMMOT)-inferred CD47-SIRPG communication and scProTrans-inferred CD47/SIRPG protein-potential overlap. Functionally, SIRPG knockdown reduced HNSCC cell viability and increased apoptosis, whereas re-expression of short hairpin RNA (shRNA)-resistant SIRPG restored the CLCA2-BAX/BCL2 protein response. CONCLUSION: Together, these findings identify SIRPG as an immune-related prognostic hub and context-dependent tumor-cell regulator associated with apoptosis, immune communication and spatial microenvironmental organization in HNSCC.

Humans↗

PseudotimeDE-fast: fast testing of differential gene expression along cell pseudotime.

SUMMARY: Identifying differentially expressed (DE) genes along cell pseudotime is crucial for understanding dynamic biological processes captured by single-cell RNA sequencing. However, existing DE methods either produce invalid P-values by ignoring the uncertainty in pseudotime inference or struggle to scale with the growing size of modern datasets. To address these limitations, we introduce PseudotimeDE-fast, a scalable method for detecting DE genes along pseudotime with well-calibrated P-values. Through comprehensive simulations and real-data analyses, we demonstrate that PseudotimeDE-fast delivers comparable or superior performance to existing approaches while offering substantial improvements in computational efficiency. AVAILABILITY AND IMPLEMENTATION: PseudotimeDE-fast is implemented in R with Rcpp acceleration and released under the MIT license. The source code is available at: https://github.com/dsong-lab/PseudotimeDE.

Single-Cell Analysis↗

The extracellular matrix in cancer-associated fibrosis: molecular mechanisms and clinical relevance.

The ECM is a dynamic component of the tumor microenvironment with a critical role in cancer progression, invasion, metastasis, immune exclusion, and response to therapy. Recent advances in proteomic analyses investigating the insoluble ECM fractions (termed "matrisome analysis"), along with single-cell RNA sequencing and spatial transcriptomics, have revealed cancer-specific patterns of ECM remodeling. These studies have identified a panel of recurrently upregulated ECM proteins, including annexin A1, fibrillin-1, fibronectin, periostin, and tenascin-C, actively contributing to tumor growth, invasion, angiogenesis, and immune exclusion. The expression of the cancer-associated ECM is largely driven by cancer-associated fibroblasts (CAFs), whose molecular diversity has been dissected through single-cell profiling and consolidated in emerging CAF atlases across cancers. By investigating the matrisome composition and CAF heterogeneity, these studies have unraveled the pivotal role of the stroma in shaping tumor biology. Based on these discoveries, ECM proteins and CAFs are now being explored as biomarkers and therapeutic targets. Future integration of multi-omics datasets with clinical outcomes will help to translate these insights into novel biomarkers for patient stratification and stroma-directed therapeutic interventions.

Humans↗