SEARCH · PubMed Health

Results for “Origin cell mapping”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed2026

Aqueous humour extracellular vesicle membrane protein profiling reveals pathological features of refractory macular edema.

BACKGROUND: Both diabetic macular edema (DME) and retinal vein occlusion-related macular edema (RVO-ME) can become refractory to anti-vascular endothelial growth factor (anti-VEGF) therapy, but the underlying mechanisms are unclear. Molecular discrimination of refractory disease could guide personalized treatment. This study examined whether aqueous humor-derived extracellular vesicle (EV) membrane proteins can characterize refractoriness and reveal etiology-specific pathways. METHODS: This prospective cohort study included 28 patients with DME or RVO-ME (14 each), further divided into treatment-naïve and refractory subgroups. Aqueous humour samples were collected before intravitreal anti-VEGF injection. EV membrane proteins were profiled using an EV Array chip targeting 435 antibodies. Differentially expressed proteins were analyzed by bioinformatics, including Gene Ontology, Kyoto encyclopaedia of genes and genomes (KEGG) pathway enrichment, Gene set enrichment analysis (GSEA), and cell-of-origin mapping using public single-cell RNA-seq data. RESULTS: VEGF/VEGFR2 were elevated in treatment-naïve DME and RVO-ME. Refractory DME showed upregulation of C5 and CD34 (complement/immune activation). Refractory RVO-ME exhibited increased CD68 and Annexin A1 with decreased PDGFR (chronic inflammation, vascular dysregulation). RANTES was commonly upregulated in refractory disease. Several EV proteins discriminated refractory cases with high accuracy (AUC 0.898-0.980). Cellular origin suggested immune cell-derived EVs in DME, retinal cell-derived EVs in RVO-ME. External validation confirmed key differences. CONCLUSION: Refractory ME involves distinct pathways: immune-inflammatory activation in DME versus chronic inflammation with vascular dysregulation in RVO-ME. EV membrane proteins from aqueous humor provide insights into therapeutic resistance and hold promise as biomarkers for personalized treatment decisions.

artificial intelligence↗

PubMed2025

MOADE: a multimodal autoencoder for dissociating bulk multi-omics data.

In single cell biology, the complexity of tissues may hinder lineage cell mapping or tumor microenvironment decomposition, requiring digital dissociation of bulk tissues. Many deconvolution methods focus on transcriptomic assay, not easily applicable to other omics due to ambiguous cell markers and reference-to-target difference. Here, we present MOADE, a multimodal autoencoder pipeline linking multi-dimensional features to jointly predict personalized multi-omic profiles and cellular compositions, using pseudo-bulk data constructed by internal non-transcriptomic reference and external scRNA-seq data. MOADE is evaluated through rigorous simulation experiments and real multi-omic data from multiple tissue types, outperforming nine deconvolution pipelines with superior generalizability and fidelity.

Humans↗

PubMed2025

CLADES: A Programmable Cascade of Genes for Cell Lineage Analysis and Manipulation.

In the Drosophila brain, neuronal diversity originates from approximately 100 neural stem cells, each dividing asymmetrically. Precise mapping of cell lineages at the single-cell resolution is crucial for understanding the mechanisms that direct neuronal specification. However, existing methods for high-resolution lineage tracing are notably time-consuming and labor-intensive. Here, we outline the best practices for lineage tracing using CLADES (cell lineage access driven by an edition sequence), a revolutionary approach to neuronal lineage tracing that addresses the limitations of previous methods. CLADES effectively traces the birth order of neurons using approximately 100 samples. The technique relies on a genetic cascade of reporter activations and deactivations that delineate lineage progression through color-coded markers. This system not only facilitates the detailed mapping of neuronal lineages but also holds the potential to be applied to tracking biological events and producing cell types for therapeutic purposes.

Animals↗

PubMed2026

The TRIM-cancer paradox: BCG as a programmable vaccine platform and a mechanistic probe for rational immunotherapy design.

BCG, a first-generation live vaccine, is being reconsidered as an immunological platform. Interest in its heterologous protection intensified during the pandemic. However, large-scale clinical trials revealed inconsistencies in the efficacy of native BCG. This review argues that BCG's main value lies in its potential as a modifiable vector platform and in its ability to reveal tractable molecular pathways for therapeutic design. This review summarizes the molecular basis of BCG-induced trained immunity (TRIM), focusing on PRR-driven signaling, metabolic rewiring, and epigenetic remodeling in innate immune cells and hematopoietic progenitors. It also maps their convergence with pathways that sustain pro-tumorigenic inflammation. The original conceptual paradigm of the "TRIM-Cancer Paradox" is presented. This paradigm posits that the same innate immune circuits that mediate protective heterologous responses can drive tumor-promoting inflammation and immune escape under conditions of chronic dysregulation. Recombinant BCG (rBCG) is further analyzed as a strategy to rationally amplify or redirect these circuits, the current clinical landscape of BCG-based interventions across various diseases and oncological malignancies is highlighted, and specific molecular nodes that could be exploited to increase the precision, efficacy, and safety of rBCG-based therapies are identified. Overall, this review proposes BCG a programmable immunological platform and to use the TRIM-Cancer Paradox as a novel design principle for next-generation rBCG platforms that transcend traditional vaccinology and cancer immunotherapy applications.

Humans↗

PubMed2025

Dynamic allelic expression in mouse mammary glands across the adult developmental cycle.

The mammary gland, which primarily develops postnatally, undergoes significant changes during pregnancy and lactation to facilitate milk production. Through the generation and analysis of 480 transcriptomes, we provide the most detailed allelic expression map of the mammary gland, cataloguing cell-type-specific expression from ex-vivo purified cell populations over 10 developmental stages, enabling comparative analysis. The work identifies genes involved in the mammary gland cycle, parental-origin-specific and genetic background-specific expression at cellular and temporal resolution, genes associated with human lactation disorders and breast cancer. Genomic imprinting, a mechanism regulating gene expression based on parental origin, is crucial for controlling gene dosage and stem cell potential throughout development. The analysis identified 25 imprinted genes monoallelically expressed in the mammary gland, with several showing allele-specific expression in distinct cell types. No novel imprinted genes were identified and the absence of biallelically expressed imprinted genes suggests that, unlike in brain, selective absence of imprinting does not regulate gene dosage in the mammary gland. This research highlights transcriptional dynamics within mammary gland cells and identifies novel candidate genes potentially significant in the tissue during pregnancy and lactation. Overall, this comprehensive atlas represents a valuable resource for future studies on expression and transcriptional dynamics in mammary cells.

Animals↗

PubMed2025

Integrative genomics elucidates the evolutionary, temporal, and developmental origins of a hydrocephalus risk gene.

INTRODUCTION: A prior integrative, multi-omics human genetics and functional genomics study identified maelstrom (MAEL), a gene involved in regulation of DNA transposon activity and genome structure, as a transcriptome-wide predictor of hydrocephalus (HC) in the brain cortex. Here we expand on this discovery and further characterize the evolutionary origin and expression of MAEL across developmental timescales and cell-lineages in the neonatal human brain towards a mechanistic understanding how variation in MAEL expression may cause HC. OBJECTIVE: To characterize the evolutionary, temporal, developmental, and lineages of MAEL expression in HC and the developing human brain. METHODS: Ensembl was used to delineate the evolution and taxonomy of MAEL across species. Analysis of single-cell RNA sequencing (scRNA-seq) of 49 brain regions across pre- and post-natal timescales from the Developing Human Brain Atlas (Allen Institute) identified temporal and spatial MAEL expression patterns. We quantified MAEL expression in primary cortical brain tissue obtained during the surgical treatment of HC. RESULTS: We performed taxonomic gene-mapping to define the evolutionary origin of MAEL to assess suitability for mechanistic characterization in vitro and in vivo across species. We find that MAEL is among the top 0.01% human-specific genes and < 50% sequence homology among commonly used model organisms with highly divergent functions, necessitating mechanistic validation in human tissue. scRNA-seq of the non-disease prenatal human brain identified MAEL expression enriched in cortical excitatory neurons, which was recapitulated in primary HC brain tissue obtained during surgery. Finally, using scRNA-seq of primary HC brain tissue, we functionally validated reduced MAEL expression, consistent with a prior human TWAS analysis. CONCLUSIONS: We identify the evolutionary, temporal, and developmental expression pattern of MAEL in the neonatal human brain. We also provide direct evidence for reduced MAEL expression in human HC brain tissue. These data, at least in part, implicate reduced MAEL expression underlying human HC across etiologies.

Journal Article↗

PubMed2026

Single-cell multimodal profiling of pan-cancer cell lines uncovers gene regulatory principles underlying intrinsic cell states and environmental features.

Cancer arises from genetic and epigenetic alterations that reshape chromatin, transcriptional regulation, and malignant cell states. To chart cancer-intrinsic regulatory programs, we build a pan-cancer single-cell atlas of 60 cancer cell lines spanning 16 tissue origins and 20 cancer types, comprising 240,957 snRNA-seq and 223,347 snATAC-seq profiles. Integrative analyses reveal cell-state heterogeneity, core gene-regulatory networks, and a conserved EMT axis transcending tissue of origin; copy-number analysis identifies transcription factor amplification and hyperactivation as drivers of state reprogramming. Comparing cutaneous melanoma with acral melanoma, a rare subtype underrepresented in previous studies, uncovers a universal inflammation-suppressive program in acral and an inflamed landscape in cutaneous melanoma, with JAK-STAT activity as the central discriminator. Integrating data across models and patient cohorts links tumor-intrinsic regulation to microenvironmental composition and therapeutic response. By profiling rare alongside common subtypes, this atlas offers a resource for mapping pan-cancer and subtype-specific regulatory programs shaping cell-state plasticity.

Humans↗

PubMed2003

Embryonic origins of a motor system: motor dendrites form a myotopic map in Drosophila.

The organisational principles of locomotor networks are less well understood than those of many sensory systems, where in-growing axon terminals form a central map of peripheral characteristics. Using the neuromuscular system of the Drosophila embryo as a model and retrograde tracing and genetic methods, we have uncovered principles underlying the organisation of the motor system. We find that dendritic arbors of motor neurons, rather than their cell bodies, are partitioned into domains to form a myotopic map, which represents centrally the distribution of body wall muscles peripherally. While muscles are segmental, the myotopic map is parasegmental in organisation. It forms by an active process of dendritic growth independent of the presence of target muscles, proper differentiation of glial cells, or (in its initial partitioning) competitive interactions between adjacent dendritic domains. The arrangement of motor neuron dendrites into a myotopic map represents a first layer of organisation in the motor system. This is likely to be mirrored, at least in part, by endings of higher-order neurons from central pattern-generating circuits, which converge onto the motor neuron dendrites. These findings will greatly simplify the task of understanding how a locomotor system is assembled. Our results suggest that the cues that organise the myotopic map may be laid down early in development as the embryo subdivides into parasegmental units.

Animals↗

PubMed2026

Machine learning and multi-omics clustering to map cellular rewiring and immune evasion in ccRCC.

Immune checkpoint blockade (ICB) efficacy in clear cell renal cell carcinoma (ccRCC) is limited by tumor microenvironment (TME) heterogeneity. Because traditional bulk-derived models lack spatial resolution, we developed an integrated framework connecting macroscopic survival risks to microscopic TME structures. We applied ten algorithms to establish multi-omics subtypes and evaluated 101 machine-learning combinations across three independent cohorts to generate a Consensus Machine Learning-driven Signature (CMLS). The signature's spatial and cellular origins were decoded using spatial transcriptomics (ST) and a 140,000-cell scRNA-seq atlas. Expression of key genes was experimentally validated via RT-qPCR in 17 paired ccRCC clinical tissues. We identified two molecular subtypes with distinct clinical and epigenetic profiles. SuperPC optimization yielded a 24-gene CMLS serving as an independent prognostic factor. scRNA-seq and ST deconvolution revealed these signals predominantly originate from cancer-associated fibroblasts (CAFs) and malignant epithelial cells, which collaborate to drive spatial immune exclusion. RT-qPCR confirmed significant overexpression of five core CMLS genes in ccRCC versus adjacent normal tissues. Low CMLS scores correlated with enhanced ICB responsiveness, whereas high-CMLS tumors demonstrated specific vulnerability to dasatinib and dabrafenib. The CMLS translates spatial immune-exclusion dynamics into a quantifiable metric, outperforming tumor mutational burden in predicting ICB benefits, providing a robust tool for patient stratification in ccRCC.

Humans↗

PubMed2026

Spatial transcriptomics of Ciona adult brains reveals functional zonalization and insights into neural gland function.

The ascidian Ciona is a pivotal chordate model for illuminating the evolutionary origins of the vertebrate brain. Here, spatial transcriptomics of the adult Ciona neural complex, combined with image-based computational super-resolution mapping, resolved distinct tissue domains including the cerebral ganglion, neural gland, ciliated funnel, neural gland duct/dorsal strand, and body wall muscle. Within the cerebral ganglion, high-resolution mapping revealed clear molecular zonalization separating the cortex and medulla, alongside regional specialization within the cortex itself. The neural gland exhibited localized enrichment of genes associated with extracellular matrix and cell-cell interactions. These spatial features suggest that the neural gland functions as a homeostatic and signaling interface, reminiscent of primitive vertebrate meninges or choroid plexus. Overall, this spatially defined gene expression map provides a foundational framework for understanding functional regionalization in the tunicate brain and its evolutionary relationship to vertebrate nervous systems.

Ciona↗

PubMed2025

ASGCL: Adaptive Sparse Mapping-based graph contrastive learning network for cancer drug response prediction.

Personalized cancer drug treatment is emerging as a frontier issue in modern medical research. Considering the genomic differences among cancer patients, determining the most effective drug treatment plan is a complex and crucial task. In response to these challenges, this study introduces the Adaptive Sparse Graph Contrastive Learning Network (ASGCL), an innovative approach to unraveling latent interactions in the complex context of cancer cell lines and drugs. The core of ASGCL is the GraphMorpher module, an innovative component that enhances the input graph structure via strategic node attribute masking and topological pruning. By contrasting the augmented graph with the original input, the model delineates distinct positive and negative sample sets at both node and graph levels. This dual-level contrastive approach significantly amplifies the model's discriminatory prowess in identifying nuanced drug responses. Leveraging a synergistic combination of supervised and contrastive loss, ASGCL accomplishes end-to-end learning of feature representations, substantially outperforming existing methodologies. Comprehensive ablation studies underscore the efficacy of each component, corroborating the model's robustness. Experimental evaluations further illuminate ASGCL's proficiency in predicting drug responses, offering a potent tool for guiding clinical decision-making in cancer therapy.

Humans↗

PubMed2015

Ptpn22 and Cd2 Variations Are Associated with Altered Protein Expression and Susceptibility to Type 1 Diabetes in Nonobese Diabetic Mice.

By congenic strain mapping using autoimmune NOD.C57BL/6J congenic mice, we demonstrated previously that the type 1 diabetes (T1D) protection associated with the insulin-dependent diabetes (Idd)10 locus on chromosome 3, originally identified by linkage analysis, was in fact due to three closely linked Idd loci: Idd10, Idd18.1, and Idd18.3. In this study, we define two additional Idd loci--Idd18.2 and Idd18.4--within the boundaries of this cluster of disease-associated genes. Idd18.2 is 1.31 Mb and contains 18 genes, including Ptpn22, which encodes a phosphatase that negatively regulates T and B cell signaling. The human ortholog of Ptpn22, PTPN22, is associated with numerous autoimmune diseases, including T1D. We, therefore, assessed Ptpn22 as a candidate for Idd18.2; resequencing of the NOD Ptpn22 allele revealed 183 single nucleotide polymorphisms with the C57BL/6J (B6) allele--6 exonic and 177 intronic. Functional studies showed higher expression of full-length Ptpn22 RNA and protein, and decreased TCR signaling in congenic strains with B6-derived Idd18.2 susceptibility alleles. The 953-kb Idd18.4 locus contains eight genes, including the candidate Cd2. The CD2 pathway is associated with the human autoimmune disease, multiple sclerosis, and mice with NOD-derived susceptibility alleles at Idd18.4 have lower CD2 expression on B cells. Furthermore, we observed that susceptibility alleles at Idd18.2 can mask the protection provided by Idd10/Cd101 or Idd18.1/Vav3 and Idd18.3. In summary, we describe two new T1D loci, Idd18.2 and Idd18.4, candidate genes within each region, and demonstrate the complex nature of genetic interactions underlying the development of T1D in the NOD mouse model.

Alleles↗

PubMed2005

A molecular map of mesenchymal tumors.

BACKGROUND: Bone and soft tissue tumors represent a diverse group of neoplasms thought to derive from cells of the mesenchyme or neural crest. Histological diagnosis is challenging due to the poor or heterogenous differentiation of many tumors, resulting in uncertainty over prognosis and appropriate therapy. RESULTS: We have undertaken a broad and comprehensive study of the gene expression profile of 96 tumors with representatives of all mesenchymal tissues, including several problem diagnostic groups. Using machine learning methods adapted to this problem we identify molecular fingerprints for most tumors, which are pathognomonic (decisive) and biologically revealing. CONCLUSION: We demonstrate the utility of gene expression profiles and machine learning for a complex clinical problem, and identify putative origins for certain mesenchymal tumors.

Gene Expression Profiling↗

PubMed2026

Beyond Canonical Neoantigens: Emerging Technologies for Identification of Noncanonical Antigens and Implications for Personalized Cancer Vaccines.

Over the past decade, advances in sequencing technologies and computational pipelines enabled the development of personalized cancer vaccines (PCVs). Current PCV strategies primarily target cancer neoantigens generated by non-synonymous DNA mutations, which can result in altered amino acid sequences capable of eliciting tumor-specific immune responses. More recently, a distinct class of tumor-specific antigens (TSA), termed noncanonical or cryptic antigens, has emerged as an additional source of immunogenic targets. Unlike canonical neoantigens, noncanonical antigens typically cannot be identified by tumor/normal whole-exome sequencing, as they do not arise from classical DNA mutations. Instead, they are often associated with less well recognized and/or aberrant processes in the pathways from DNA to human leukocyte antigen (HLA)-presented peptides. Examples include transposable elements, circular RNA, translation of alternative open reading frames and/or long non-coding RNA, among others. Emerging evidence suggests that noncanonical antigens represent a substantial portion of the tumor-specific immunopeptidome and, similar to canonical neoantigens, are absent during thymic selection and can evade central tolerance and elicit T cell responses. Technological advances have increasingly facilitated the identification of noncanonical antigens. Long-read RNA sequencing reveals noncanonical transcripts by improving transcriptome assembly, while ribosome profiling provides genome-wide maps of actively translated regions, facilitating the discovery of peptides from aberrant translation events. Specialized molecular approaches enable enrichment and sequencing of circular RNAs, and immunopeptidomics using mass spectrometry allows for direct characterization of HLA-presented peptides. Together, these technological advances have led to an increasing interest in prioritizing and targeting noncanonical antigens in the next generation of PCVs. This review provides an overview of the diverse origins of TSAs beyond classical neoantigens and discusses emerging approaches that may enable the integration of these antigens in future clinical trials.

circular RNA↗

PubMed2025

AQuA Tools: clear and reliable BEDPE operations for 3D genomics.

MOTIVATION: The genome interacts with itself within the volume of the cell nucleus to process information. These interactions mediate signal integration, gene regulation, and cell identity. The identification of new therapeutic targets from non-coding disease-associated variants relies critically on correctly assigning variants to genes through 3D interactions. Experimental techniques in 3D genomics, such as HiC and HiChIP, allow the mapping of interactions through sequencing. Bioinformatics for 3D genomics contends primarily with contact matrices that contain interaction frequencies for all possible element pairs, and BEDPE files that store element pairs that interact. Whereas the tools available for processing linear genomic data are mature, operating on contact matrices and BEDPE files remains cumbersome, opaque, and error-prone, as researchers have had to shoehorn tools originally designed for linear data. A genome arithmetic designed from the ground up for 3D genomics does not yet exist. RESULTS: We present AQuA Tools, a suite of shell- and R-based command-line tools that provide a set of core operations on contact matrices and BEDPE files motivated by key questions in population genetics, cancer research, and precision medicine. We have designed our core operations to be clear, reliable, intuitive and versatile. Core operations can be chained together along with standard UNIX commands. Our goal is to make AQuA Tools easy for the novice to learn and the go-to choice for power users. We hope our tools will motivate more researchers to use 3D genomic data in their projects. AVAILABILITY AND IMPLEMENTATION: We provide and maintain AQuA Tools at https://github.com/axiotl/aqua-tools.

Genomics↗

PubMed2026

Fetal signatures in the 3D genome of iPSC-derived neurons and their implications for disease modeling.

Induced pluripotent stem cells (iPSCs) have revolutionized neuroscience, providing an approach to generate patient-specific neurons for modeling of neurological diseases. However, it remains unclear how closely iPSC-derived neurons replicate the chromatin architecture of authentic brain neurons. Here, we uniformly processed newly generated Hi-C data from iPSC-derived neurons and neurons isolated from the human postmortem brain, together with previously published data sets comprising 228 human and 89 mouse Hi-C and snm3C-seq samples from different cell subtypes. These data were merged into 96 high-coverage contact maps used to examine chromatin features ranging from chromatin compartments and topologically associating domains (TADs) to chromatin loops, Polycomb-mediated contacts, and frequently interacting regions (FIREs). We find that iPSC-derived neurons largely retain the chromatin state of undifferentiated cells and resemble fetal rather than mature neurons. iPSC-derived neurons exhibit unusually strong compartmentalization, an enrichment of developmental genes at TAD borders, and a marked reduction of long-range repressive Polycomb-mediated contacts that typically silence early fetal programs. Although immature, iPSC-derived neurons offer advantages for modeling interactions between disease-associated SNPs and target genes, as many psychiatric disorders have neurodevelopmental origins. Integrating iPSC-derived and postmortem neuronal data sets therefore provides complementary insights into the chromatin landscape underlying disease-associated interactions. Our study offers a valuable Hi-C resource for the community and provides a detailed comparison of chromatin architecture throughout neuronal maturation, underscoring its importance for validating neuronal models and providing a robust framework for future studies.

Journal Article↗

PubMed2026

Hox/Meis-dependent gene-regulatory transition underlies cardiopharyngeal neural crest diversification.

Neural crest cells (NCCs) are multipotent migratory cells essential for cardiac development, yet the lineage trajectories and gene regulatory networks underlying their differentiation in the cardiopharyngeal region remain unclear. Here, we integrate single-cell RNA-seq, spatial transcriptomics, and multiomic analyses to construct a comprehensive map of NCC lineages in developing mouse cardiopharyngeal tissues. We identify a transition from Hox-positive pharyngeal NCCs to Hox-negative intracardiac populations associated with the outflow tract cushion, accompanied by a shift in Meis transcription factor binding and gene-regulatory network architecture. By contrast, NCCs forming the aorticopulmonary septum and great vessel smooth muscle retain distinct Hox-codes. A Meis2-Sox9-Scx gene-regulatory network defines a skeletogenic progenitor-like intermediate state that gives rise to coronary artery smooth muscle and semilunar valves. Our findings suggest that the loss of Hox-dependent regional identity enables pharyngeal NCCs to acquire new fates upon entering the cardiac cushion, providing insight into the developmental origins of coronary and valvular calcification.

Journal Article↗

PubMed2025

Sex differences in the developing human cortex intersect with genetic risk of neurodevelopmental disorders.

Autism is highly heritable and diagnosed more frequently in males than females. To identify neurodevelopmental processes that might present sex-biased vulnerability, we generated transcriptomic and epigenomic profiles of cell types present in the prenatally developing human cerebral cortex of 27 males and 21 females. By intersecting sex-biased molecular signatures and genes with de novo mutations in male and female autistic probands, we reveal two points of vulnerability contributing to the sex-biased penetrance in neurodevelopmental disorders (NDDs). First, we show that NDD risk genes are biased towards higher expression in females, identifying the NDD gene MEF2C as a critical transcription factor for female-biased expression. Second, we identify a significant contribution of X chromosome genes to NDD pathobiology. We construct a gene regulatory map of X-linked risk genes to enable functional studies of genetic variants that likely disrupt gene expression in the developing brains of autistic males. Together, these results point towards an outsized contribution of the X-chromosome to both the origin of sex differences in the developing human cortex and NDD vulnerability. We propose a model where female-biased vulnerability is driven by coding variation within genes while male-biased vulnerability is driven by noncoding variation in regulatory elements that affect gene expression.

Sex differences↗