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Results for “spatial sequencing”

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At least 19 recordsLinked to original sources

PubMed1978

Temporal and spatial sequence of anterograde degeneration in the cochlear nerve fibers of the cat. A light microscopic study.

This study deals with anterograde degeneration in the cochlear nerve fibers following cochlear lesions. The observations are based on 2-mum thick sections of material embedded in resin according to procedures used in electron microscopy and stained with toluidine blue. Among the various operative approaches used in this study, sparing of the modiolus afforded the least local reaction and furnished the material best suited for anterograde degneration studies in this nerve only 2 mm long. The anterograde degeneration of the cochlear nerve is characterized by segmental swelling of myelinated nerve fibers followed by shrinkage of the axoplasm and collapse of the distended myelin sheaths. The swelling, which begins at the nodal-paranodal region of the axon, is preceded by accumulation in the cytoplasm of granular organelles, presumably mitochondria and lysosomes. The portions of the cochlear fibers situated in the nerve root, i.e., within the cochlear nuclei and including the axon terminals, follow essentially the same pattern of degeneration as those in the peripheral portion of the nerve. Both peripherally and centrally degenerative changes occur first in the basal, high frequency fibers and centrally degenerative changes occur first in the basal, high frequency fibers and progress to the apical, low frequency fibers. The difference between the two extremes in the onset of degeneration is, approximately, 24 hours. Once initiated, however, the pace of degeneration is the same along the whole fiber spectrum.

Animals↗

PubMed2026

Spatial proximity sequencing maps developmental dynamics in the germinal center.

Spatial profiling of proteins and protein interactions facilitates understanding of cell functions within tissues and is essential for studies in signaling, immunity, and cancer. We present spatial proximity sequencing (Sprox-seq) for simultaneous profiling of surface proteins, protein complexes, and mRNAs, recording the tissue location of each molecule. Sprox-seq profiled 32 proteins, 528 pairwise interactions, and thousands of mRNAs with spatial resolution across human tonsils and germinal centers. Mapping tissue-wide protein interactions recapitulated RNA-defined tissue architecture but also revealed higher interaction complexity in the light zone. Protein-interaction trajectories uncovered a B cell state transition distinct from that inferred by RNA. Integrated protein-complex and mRNA analysis related spatially enriched complexes with mitotic pathways. Sprox-seq captured cell-cell interactions, such as B cell-follicular dendritic cell interactions mediated by the receptor complex VLA-4-VCAM1. Sprox-seq provides a spatially resolved multi-modal view of cell states and an integrated study of protein and cellular interactions across tissues.

Humans↗

PubMed2026

Spatial isoform sequencing at single-cell resolution reveals cell-type-specific spatial isoform variability in multiple brain cell types.

Spatial long-read technologies are increasingly common but usually lack single-cell resolution. This leaves unanswered whether spatially variable isoforms reflect variability within one cell type or differences in region-specific cell-type composition. Here, we developed Spl-ISO-Seq2 (500-nm resolution) and accompanying software, Spl-IsoQuant-2 and Spl-IsoFind, enabling long-read sequencing of >450 million barcodes versus 80,000 previously. Applying this to the adult mouse brain, we compared differential isoform abundance between known regions and spatial isoform patterns independent of predefined regions. Both identified overlapping hits, for example, Rps24 in oligodendrocytes. For known Snap25 spatial isoform variation, we show that it occurs in excitatory neurons. The region-agnostic approach also uncovered patterns missed by region-based comparisons, for example, for Ighm. Notably, many spatial isoform signals are not driven by cell-type composition alone. Finally, our software is applicable to many spatial and single-cell protocols, demonstrating reproducibility between platforms (for example, Visium HD/Stereo-seq). Overall, our experimental/analytical methods enable a submicron-resolution-isoform view and open avenues for spatial isoform disease research.

Animals↗

PubMed2024

Integration of Imaging-based and Sequencing-based Spatial Omics Mapping on the Same Tissue Section via DBiTplus.

Spatially mapping the transcriptome and proteome in the same tissue section can significantly advance our understanding of heterogeneous cellular processes and connect cell type to function. Here, we present Deterministic Barcoding in Tissue sequencing plus (DBiTplus), an integrative multi-modality spatial omics approach that combines sequencing-based spatial transcriptomics and image-based spatial protein profiling on the same tissue section to enable both single-cell resolution cell typing and genome-scale interrogation of biological pathways. DBiTplus begins with in situ reverse transcription for cDNA synthesis, microfluidic delivery of DNA oligos for spatial barcoding, retrieval of barcoded cDNA using RNaseH, an enzyme that selectively degrades RNA in an RNA-DNA hybrid, preserving the intact tissue section for high-plex protein imaging with CODEX. We developed computational pipelines to register data from two distinct modalities. Performing both DBiT-seq and CODEX on the same tissue slide enables accurate cell typing in each spatial transcriptome spot and subsequently image-guided decomposition to generate single-cell resolved spatial transcriptome atlases. DBiTplus was applied to mouse embryos with limited protein markers but still demonstrated excellent integration for single-cell transcriptome decomposition, to normal human lymph nodes with high-plex protein profiling to yield a single-cell spatial transcriptome map, and to human lymphoma FFPE tissue to explore the mechanisms of lymphomagenesis and progression. DBiTplusCODEX is a unified workflow including integrative experimental procedure and computational innovation for spatially resolved single-cell atlasing and exploration of biological pathways cell-by-cell at genome-scale.

Journal Article↗

PubMed2024

Integration of Imaging-based and Sequencing-based Spatial Omics Mapping on the Same Tissue Section via DBiTplus.

Journal Article↗

PubMed1978

The role of frontal and parietal cortex in cognitive processing: tests of spatial and sequence functions.

Normal monkeys and monkeys with resection of anterior frontal or posterior parietal cortex were trained to press a panel next to a green panel as a test of extrapersonal spatial orientation and to press a panel next to their own prior press as a test of personal spatial orientation. All monkeys also learned two sets of sequence problems in which the solutions were made independent of spatial location by randomly shifting the locations of the stimuli after each response within a trial. The Parietal Group was significantly impaired on the extrapersonal 'next-to' task but not the more difficult personal 'next-to' task. The Frontal Group was impaired on both the personal and the extrapersonal 'next-to' tasks but only when the relevant cues shifted spatial locations from trial to trial. The performance of the Parietal Group completely overlapped that of the Normal Group on the sequence problems regardless of the level of testing sophistication the monkeys had attained. In contrast, the Frontal Group demonstrated a significant impairment in learning sequences but only when the monkeys were naive. Once they became sophisticated they learned each sequence at a normal rate. Their poor performance was attributed to the lack of stability in the spatial location of the stimuli. The data support the view that a distinction between personal and extrapersonal spatial orientation is relevant to posterior parietal function but indicate that neither sequencing per se nor personal spatial orientation or spatial memory per se is dependent on intact frontal functioning. Rather, the frontal cortex is involved with a higher-order control essential to allow the monkey to perceive the reliable aspects of stimuli contained in a stimulus context full of unreliable noise and to further allow for flexible response pattern appropriate to the demands of a variable context.

Animals↗

PubMed1975

Directionally sensitive ganglion cells in the rabbit retina: specificity for stimulus direction, size, and speed.

The receptive fields of directionally sensitive ganglion cells in the rabbit retina were analyzed. Several types of experiment showed that each point within the receptive field of the cell is inhibited by a fairly wide area of points around it, lying on each side of the preferred-null axis as well as along the preferred-null axis in the preferred direction. The excitatory or responsive receptive field of these cells has an inhibitory surround: this inhibitory surround appears to be simply an extension of the inhibition that occurs within the center of the receptive field. Points toward the edge of the responsive receptive field are inhibited from an area around them which extends into the center of the receptive field and also into the inhibitory surround. Directionally sensitive retinal ganglion cells respond to moving spots better than to moving bars. This is particularly true for objects moved perpendicularly to the preferred-null axis. In some cells a spot moved perpendicularly to the preferred-null axis will give a substantial response, whereas a bar moved in the same direction will give no response at all. This phenomenon can be explained by the inhibitory area which surrounds each point within the receptive field; since this inhibitory area is asymmetrical, it is also responsible for the cell's directional sensitivity. When two bars oriented perpendicular to the preferred null axis are flashed, one after the other, the response to the second bar is nearly always reduced by the presentation of the first bar. This is true for many temporal and spatial sequences corresponding to movement in the preferred direction, as well as those corresponding to movement in the null direction. However, there are temporal and spatial sequences, corresponding to movement in the preferred direction, for which the response to the second bar is unaffected by the presentation of the first bar. The time delay for this does not vary from cell to cell--it is always approximately 20 ms for on-off directionally sensitive cells and approximately 180 ms for on directionally sensitive cells. The spatial separation does vary from cell to cell, between 0.13 degrees and 1.2 degrees in 11 on-off directionally sensitive cells. This spatial separation, which gives linear summation of the response to two bars flashed 20 ms apart in the preferred direction, is correlated with the speed of movement which gives the best response for a bar moved through the receptive field in the preferred direction.

Animals↗

PubMed2026

SIVA: diagonal integration of spatial multi-omics data via spatially informed variational autoencoders and anchor guidance.

MOTIVATION: Understanding cellular states and regulatory programs requires integrative analysis of multiple omics layers. Although recent spatial sequencing technologies allow molecular profiling of cells within their tissue context, paired spatial multi-omics assays are still limited by technical complexity and cost. This creates a pressing need for diagonal integration methods that enable joint analysis of unpaired spatial omics datasets. RESULTS: We propose SIVA, a deep generative framework based on Spatially-Informed Variational Autoencoders with Anchor Guidance, for diagonal integration of spatial multi-modal data. SIVA employs modality-specific variational autoencoders (VAEs) with a hybrid latent embedding that integrates Gaussian process and standard Gaussian priors, enabling joint modeling of spatially structured variation and dominant underlying data distributions across modalities. To facilitate cross-modal alignment in the absence of one-to-one cell correspondence, SIVA adopts a dual integration strategy combining global distribution alignment via Maximum Mean Discrepancy and local correspondence guidance using mutual nearest neighbor anchors. Extensive experiments across multiple cross-slice integration scenarios demonstrate that SIVA achieves robust and accurate integration of unpaired spatial omics datasets, consistently outperforming existing methods. AVAILABILITY AND IMPLEMENTATION: The source codes are available at https://github.com/PelenJiang/SIVA.

Autoencoder↗

PubMed2026

Spatial Total RNA Sequencing of Formalin-Fixed Paraffin-Embedded Tissue by spRandom-seq.

The molecular pathogenesis of infectious diseases and cancer is orchestrated by nanoscale of host and microbial RNA transcripts within the tissue microenvironment. Nevertheless, spatially resolving the comprehensive transcriptional landscape within complex clinical tissues, like formalin-fixed paraffin-embedded (FFPE) specimens, still poses a formidable challenge. Here, we present spRandom-seq, a random primer-based spatial total RNA sequencing technology designed to spatially resolve complete transcriptomes from host, bacteria, and even nanoscale viruses in FFPE tissues. Capitalizing on the random primer design, our technology not only facilitated the discovery of specific lncRNAs and alternative splicing events in mouse brain and olfactory bulb, but also delineated pronounced spatial heterogeneity in clinical FFPE sections-across distinct tumor regions in breast cancer and microbial infection sites in Klebsiella pneumoniae-infected tissues. Importantly, integrated analysis of host and viral RNAs in FFPE samples from hepatitis B virus (HBV)‑positive hepatocellular carcinoma (HCC) demonstrated that complement and coagulation pathways were specifically activated across expansive HBV‑infected tumor areas, which also exhibited an increased burden of copy number variations (CNVs). Owing to its compatibility with existing spatial transcriptomics platforms and minimal operational complexity, spRandom-seq represents a practical and scalable approach for clinical pathology applications and infection diagnostics.

Paraffin Embedding↗

PubMed2026

A spatially coordinated keratinocyte-fibroblast circuit recruits MMP9+ myeloid cells to drive type I interferon-driven inflammation in photosensitive autoimmunity.

Photosensitivity is central to cutaneous lupus erythematosus and dermatomyositis (DM), but the mechanisms linking UVB exposure to tissue-specific autoimmunity are poorly defined. Using single-cell RNA sequencing, spatial transcriptomics, proteomics, UVB provocation and in vitro modeling, we identify MMP9+CD14+ myeloid cells as critical mediators of photosensitivity. These cells expand significantly in lesional skin, produce interferon-β (IFNβ) and colocalize with cytotoxic CD4+ T cells at the dermal-epidermal junction. Keratinocytes activate fibroblasts in the superficial dermis, prompting them to release chemokines (CCL2, CCL19, CCL7, CCL8) that recruit MMP9+CD14+ cells. In vitro, type I interferon-primed keratinocytes exposed to UVB release cytokines activating dendritic cells, mirroring in vivo responses. UVB irradiation of non-lesional skin of patients with DM rapidly recruits these myeloid cells. In a clinical proof-of-concept study, anti-type I interferon treatment with anifrolumab prevented UVB-induced myeloid infiltration and reduced photosensitivity. Therefore, targeting MMP9+CD14+ cells may offer therapeutic potential for managing photosensitive autoimmune skin conditions.

Humans↗

PubMed2026

Omics in optic neuropathies: From molecular landscapes to personalized therapeutics.

Optic neuropathies comprise a heterogeneous group of disorders involving transient or permanent injury to retinal ganglion cells (RGCs) and their axons. Clinically, these neurodegenerative conditions manifest as dyschromatopsia, decreased visual acuity, and visual field defects, and in severe cases may ultimately lead to blindness and disability. The marked heterogeneity across disease subtypes, incompletely understood etiologies, and complex pathogenic mechanisms pose substantial challenges to precise diagnosis and effective treatment. Recent advances in omics technologies - including genomics, transcriptomics, proteomics, metabolomics, lipidomics, single-cell and spatial sequencing, and integrative multi-omics approaches - have ushered optic nerve degenerative disease research into an era of high-resolution comprehensive investigation. In this review, we summarize representative applications of omics approaches to elucidate genetic alterations, signaling dysregulation, metabolic reprogramming, and immune responses in optic neuropathies. We further discuss the emerging potential of multi-omics in identifying early diagnostic biomarkers and informing individualized therapeutic strategies. Finally, we provide a forward-looking perspective on the future trajectory of omics technologies and their prospects in both fundamental research and clinical translation, with the overarching aim of accelerating the bench-to-bedside transition in this critical eye disease field.

biomarkers↗

PubMed1979

Cell number in relation to primary pattern formation in the embryo of Xenopus laevis. II. Sequential cell recruitment, and control of the cell cycle, during mesoderm formation.

Morphological evidence is presented that definitive mesoderm formation in Xenopus is best understood as extending to the end of the neurula phase of development. A process of recruitment of cells from the deep neurectoderm layers into mesodermal position and behaviour, strictly comparable with that already agreed to occur around the internal blastoporal 'lip' during gastrula stage 20 (earliest tail bud). Spatial patterns of incidence of mitosis are described for the fifteen hours of development between the late gastrula and stage 20--22. These are related to the onset of new cell behaviours and overt cyto-differentiations characterizing the dorsal axial pattern, which occur in cranio-caudal and then medio-lateral spatial sequence as development proceeds. A relatively abrupt cessation of mitosis, among hitherto asynchronously cycling cells, precedes the other changes at each level in the presumptive axial pattern. The widespread incidence of cells still in DNA synthesis, anterior to the last mitoses in the posterior-to-anterior developmental sequence of axial tissue, strongly suggests that cells of notochord and somites in their prolonged, non-cycling phase are G2-arrested, and thus tetraploid. This is discussed in relation to what is known of cell-cycle control in other situations. Best estimates for cell-cycle time in the still-dividing, posterior mesoderm of the neurula lie between 10 and 15 h. The supposition of continuing recruitment from neurectoderm can resolve an apparent discrepancy whereby total mesodermal cell number nevertheless contrives to double over a period of approximately 12 h during neurulation when most of the cells are leaving the cycle. Because of pre-existing evidence that cells maintain their relative positions (despite distortion) during the movements that form the mesodermal mantle, the patterns presented in this paper can be understood in two ways: as a temporal sequence of developmental events undergone by individual, posteriorly recruited cells as they achieve their final positions in the body pattern, or alternatively as a succession of wavefronts with respect to changes of cell state, passing obliquely across the presumptive body pattern in antero-posterior direction. These concepts are discussed briefly in relation to recent ideas about pattern formation in growing systems.

Animals↗

PubMed1975

The macromolecular structure of the first component of complement.

The binding of C1 to IgG and the interactions between C1 subcomponents have been studied by affinity chromatography of serum C1 and purified C1 proteins on Sepharose-IgG. Affinity chromatography of serum on Sepharose-IgG resulted in the binding of C1; subsequent washing with EDTA removed only C1s and C1t. Affinity chromatography of serum-EDTA on Sepharose-IgG resulted in binding of only C1q and C1r. Affinity chromatography of serum on Sepharose-tryptophan-modified-IgG resulted in the binding of only C1r and C1s. By the use of purified C1 proteins and Sepharose-IgG in binding studies it was confirmed that both C1q and C1r bind independently to sites on IgG and hold C1s and C1t by Ca++-dependent bonds. Measurements of the hemolytic activity of various combinations of C1 subcomponents confirmed the data obtained by the affinity binding studies. Both C1t and C1r independently enhanced the C1 activity of C1q-C1s mixtures; maximal activity required all four subcomponents. Sucrose gradient ultracentrifugation of mixtures of C1 proteins showed formation of the following complexes: C1qs (12S), C1qrs (15S), C1qst (18-23S), and C1qrst (19S). The evidence suggests that the spatial sequence of the components of the Sepharose-IgG-Serum C1 complex is: Sepharose-IgG: C1q: C1t: C1s: C1r: IgG-Sepharose. The probable physiologic significance of this model is discussed.

Blood Proteins↗

PubMed2025

Balancing LncRNA H19 and miR-675 Bioconversion as a Key Regulator of Embryonic Myogenesis Under Maternal Obesity.

BACKGROUND: Maternal obesity (MO) impairs fetal skeletal muscle development, but the underlying mechanisms remain poorly defined. The regulatory roles of lncRNA H19 and its first exon derived microRNA675 (miR675) in prenatal muscle development remain to be examined. H19/Igf2 are in the same imprinting cluster with H19 expressed from the maternal allele while Igf2 expresses paternally. H19 contains a G-rich loop, and KH-type splicing regulatory protein (KHSRP) mediates the biogenesis of pre-miRNAs containing G-rich loops, which depends on its phosphorylation by AKT, a key mediator of IGF2 signalling. This study aims to depict the elusive function of these regulators that are affected by MO during embryonic myogenesis. METHODS: Single-cell transcriptomic sequencing and GeoMx spatial RNA sequencing were performed to identify the differentially expressed genes between embryos from MO and control (CT) mice. Both E11.5 and E13.5 embryos were collected and analysed to validate the sequencing data. The roles of H19 and miR657 in myogenesis were further analysed in P19 embryonic cells via CRISPR/dCas9-mediated H19 activation and inhibition. The epigenetic changes of H19 were analysed by methylated DNA immunoprecipitation, and allele-targeted analysis of H19 was performed by crossing C57BL/6J and CAST/EiJ mice. RESULTS: Transcriptomic analysis showed that MO embryos contained less differentiated myocytes (1.34%) than CT embryos (2.86%). Myogenesis-related GO biological processes were down-regulated in the MO embryonic myotome region. MO embryos showed lower expression of myogenic transcription factors such as Myf5, Myod1, Myog, Mef2c and Myh3 (p < 0.05). MO altered epigenetic modifications of the H19 genomic cluster, showing a decreased methylation level in H19 imprinting control region (p < 0.05) and a diallelic expression pattern of H19, which elevated its expression in MO embryos. Overexpression of H19 inhibited myogenesis in P19 cells, but miR675 promoted myogenesis, suggesting the critical regulatory roles of bioconversion of H19 to miR675. A KHSRP mediates the biogenesis of miR675, a process that relies on its phosphorylation by IGF2/AKT signalling. Knocking-down of KHSRP and inhibition of AKT abolished miR675 biogenesis. MO suppressed IGF2/AKT signalling and blocked KHSRP-dependent miR675 biogenesis in embryos. CONCLUSIONS: We found differential effects of H19 and miR675 on embryonic myogenesis. MO up-regulates H19 but blocks its miR675 bioconversion via suppressing IGF2/AKT/KHSRP signalling axis. Myogenesis in MO embryos was impeded due to the highly accumulated H19 and blocked miR675 biogenesis.

RNA, Long Noncoding↗

PubMed2026

Mapping antibody sequences and effector functions across spatial niches.

Antibodies are fundamental to human health but can also drive pathology. Each antibody has a molecular specificity, encoded by their clonally heritable B cell receptor (BCR). Recent advances in spatial transcriptomics coupled with repertoire sequencing have enabled capturing antibody-secreting cells (ASCs) and their clonal BCR within their tissue microenvironment. However, our understanding of antibody production niches remains limited. Furthermore, where antibodies are produced can be distinct from where antibodies exert their effector function. Here, we propose a conceptual spatial framework to distinguish between 'antibody production niches', defined by the ASC, BCR, and niche composition, versus 'antibody functional niches', composed of the antibody, antigen, and effector landscape. We then examine the possibilities and challenges to map and link antibody-encoding sequences and antibody effector functions using current and emerging technologies. Combined, we argue that integrating spatial sequence data with the antibody functional context is essential to decode the architecture of antibody-mediated immunity.

Humans↗

PubMed2025

Colorectal Liver Metastasis Pathomics Model: Integrating Single-Cell and Spatial Transcriptome Analysis With Pathomics for Predicting Liver Metastasis in Colorectal Cancer.

The liver is the primary target organ for hematologic metastasis of colorectal cancer (CRC), and CRC liver metastasis (CRLM) often precludes radical resection, making it the leading cause of death in patients with CRC. To improve the identification and prediction of liver metastasis risk, we identified a cell type of liver metastasis--triggering malignant cells (LMTMCs) through integrating single-cell RNA sequencing and spatial transcriptome analysis. Multiomics cell communication analysis indicated that the interaction between fibroblasts and LMTMCs through the COL1A1-CD44/SDC4 and LAMA4-CD44 signaling axes could promote CRLM. By applying the one-class logistic regression algorithm, we developed a CRLM scoring system in the bulk RNA-sequencing data according to the abundance of LMTMCs in each individual. Using the grouping labels derived from the CRLM scoring system in the bulk data and the corresponding whole-slide images without any manual annotations at the region or pixel level, processed via slide-level weakly supervised learning, a deep-learning model based on the ResNet18 architecture, called Colorectal Liver Metastasis Pathomics Model, was developed to predict the risk of liver metastasis in patients with CRC. The Colorectal Liver Metastasis Pathomics Model achieved an area under the curve of 0.84 at the internal test set of The Cancer Genome Atlas-CRC histology images. In the external independent validation sets, namely the Affiliated Hospital of Southwest Medical University and the Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University cohorts, the areas under the curve were 0.89 and 0.72, respectively, indicating effective classification performances. This study provided new insights and tools for the early identification of CRLM and demonstrated the potential of combining multiomics with deep learning-based pathomics in cancer research.

Humans↗

PubMed2026

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↗

PubMed2025

BISON: bi-clustering of spatial omics data with feature selection.

MOTIVATION: The advent of next-generation sequencing-based spatially resolved transcriptomics (SRT) techniques has reshaped genomic studies by enabling high-throughput gene expression profiling while preserving spatial and morphological context. Understanding gene functions and interactions in different spatial domains is crucial, as it can enhance our comprehension of biological mechanisms, such as cancer-immune interactions and cell differentiation in various regions. It is necessary to cluster tissue regions into distinct spatial domains and identify discriminating genes (DGs) that elucidate the clustering result, referred to as spatial domain-specific DGs. Existing methods for identifying these genes typically rely on a two-stage approach, which can lead to the phenomenon known as double-dipping. RESULTS: To address the challenge, we propose a unified Bayesian latent block model that simultaneously detects a list of DGs contributing to spatial domain identification while clustering these DGs and spatial locations. The efficacy of our proposed method is validated through a series of simulation experiments, and its capability to identify DGs is demonstrated through applications to benchmark SRT datasets. AVAILABILITY AND IMPLEMENTATION: The R/C++ implementation of BISON is available at https://github.com/new-zbc/BISON.

Software↗