Malignant transformation of white sponge nevus: a case report of a novel keratin 4 mutation.

BACKGROUND: White Sponge Nevus (WSN) is traditionally considered a benign genetic disorder affecting the oral mucosa, primarily caused by pathogenic mutations in keratin 4 (KRT4) or keratin 13 (KRT13). Despite its benign nature, recent evidence has begun to question the malignant potential of WSN. CASE PRESENTATION: We report a case involving a 70-year-old man who presented with a white lesion on the right floor of his mouth. Initial diagnostic evaluations confirmed the lesion as WSN. Over a one-year follow-up, the lesion underwent malignant transformation, evolving into local epithelial moderate-to-severe dysplasia. Exome sequencing identified a novel insertion mutation in exon 1 of the KRT4 gene, resulting in a deletion-insertion amino acid mutation involving glycine. Single-cell RNA sequencing further revealed altered epithelial proliferation and differentiation dynamics within the lesion. CONCLUSIONS: This case not only expands the known genetic spectrum of KRT4 mutations associated with WSN but also provides preliminary evidence suggesting the malignant potential of WSN. The novel pathogenic mutation in KRT4 is postulated to alter epithelial proliferation and differentiation, thereby raising concerns about the malignant transformation of WSN. Further studies are warranted to confirm these findings.

PA28γ coordinates the cross-talk between cancer-associated fibroblasts and tumor cells to promote OSCC progression via HDAC1/E2F3/IGF2 signaling.

PA28γ overexpression is aberrant and accompanied by poor patient prognosis in various cancers, the precise regulatory mechanism of this crucial gene in the tumor microenvironment remains incompletely understood. In this study, using oral squamous cell carcinoma as a model, we demonstrated that PA28γ exhibits high expression in cancer-associated fibroblasts (CAFs), and its expression significantly correlates with the severity of clinical indicators of malignancy. Remarkably, we found that elevated levels of secreted IGF2 from PA28γ+ CAFs can enhance stemness maintenance and promote tumor cell aggressiveness through the activation of the MAPK/AKT pathway in a paracrine manner. Mechanistically, PA28γ upregulates IGF2 expression by stabilizing the E2F3 protein, a transcription factor of IGF2. Further mechanistic insights reveal that HDAC1 predominantly mediates the deacetylation and subsequent ubiquitination and degradation of E2F3. Notably, PA28γ interacts with HDAC1 and accelerates its degradation via a 20S proteasome-dependent pathway. Additionally, PA28γ+ CAFs exert an impact on the tumor immune microenvironment by secreting IGF2. Excitingly, our study suggests that targeting PA28γ+ CAFs or secreted IGF2 could increase the efficacy of PD-L1 therapy. Thus, our findings reveal the pivotal role of PA28γ in cell interactions in the tumor microenvironment and propose novel strategies for augmenting the effectiveness of immune checkpoint blockade in oral squamous cell carcinoma.

Shaoxia: a web-based interactive analysis platform for single cell RNA sequencing data.

BACKGROUND: In recent years, Single-cell RNA sequencing (scRNA-seq) is increasingly accessible to researchers of many fields. However, interpreting its data demands proficiency in multiple programming languages and bioinformatic skills, which limited researchers, without such expertise, exploring information from scRNA-seq data. Therefore, there is a tremendous need to develop easy-to-use software, covering all the aspects of scRNA-seq data analysis. RESULTS: We proposed a clear analysis framework for scRNA-seq data, which emphasized the fundamental and crucial roles of cell identity annotation, abstracting the analysis process into three stages: upstream analysis, cell annotation and downstream analysis. The framework can equip researchers with a comprehensive understanding of the analysis procedure and facilitate effective data interpretation. Leveraging the developed framework, we engineered Shaoxia, an analysis platform designed to democratize scRNA-seq analysis by accelerating processing through high-performance computing capabilities and offering a user-friendly interface accessible even to wet-lab researchers without programming expertise. CONCLUSION: Shaoxia stands as a powerful and user-friendly open-source software for automated scRNA-seq analysis, offering comprehensive functionality for streamlined functional genomics studies. Shaoxia is freely accessible at http://www.shaoxia.cloud , and its source code is publicly available at https://github.com/WiedenWei/shaoxia .

Rapid Detection of Colletotrichum siamense from Infected Tea Plants Using Filter-Disc DNA Extraction and Loop-Mediated Isothermal Amplification.

The pathogen Colletotrichum siamense causes tea anthracnose, resulting in economic losses to the Chinese tea industry. To effectively diagnose this pathogen in the field, we developed a loop-mediated isothermal amplification (LAMP) method using highly specific primers with a sensitivity of 1 pg/µl designed for amplifying the CAL gene, which was 10 times higher than that of conventional PCR. Additionally, to improve the method for obtaining DNA samples required for on-site diagnosis, we used the filter-disc DNA extraction method, which does not require special instruments and can be completed in a few minutes, and found that it effectively meets the requirements for the LAMP reaction. Finally, we combined LAMP with a filter-disc DNA extraction method (FDE-LAMP) to diagnose different degrees of disease in inoculated samples and 20 samples from the field. The results showed that the procedure had sufficient sensitivity for pathogen detection. Therefore, the FDE-LAMP procedure could greatly contribute to managing and preventing tea anthracnose in the field.

Mass cytometry and transcriptomic profiling reveal PD1 blockade induced alterations in oral carcinogenesis.

Oral squamous cell carcinoma is the predominant subtype of head and neck squamous cell carcinoma, characterized by a challenging prognosis. In this study, we established a murine model of oral carcinogenesis using 4-nitroquinoline-1-oxide (4-NQO) induction to investigate the impact of immunotherapy on microenvironmental alterations. Mice in the precancerous condition were randomly divided into two groups: one receiving programmed death-1 (PD1) monoclonal antibody treatment and the other, control immunoglobulin G. Our observations showed that while PD1 blockade effectively delayed the progression of carcinogenesis, it did not completely impede or reverse it. To unravel the underlying reasons for the limited effectiveness of PD1 blockade, we collected tongue lesions and applied mass cytometry (CyTOF) and RNA sequencing (RNA-seq) to characterize the microenvironment. CyTOF analysis revealed an increased macrophage subset (expressing high levels of IFNγ and iNOS) alongside a diminished Th1-like subset (exhibiting low expression of TCF7) and three myeloid-derived suppressor cell subsets (displaying low expression of MHC Class II or IFNγ) following anti-PD1 treatment. Notably, we observed an increased presence of cancer-associated fibroblasts (CAFs) expressing collagen-related genes after PD1 blockade. Furthermore, we found a negative correlation between the infiltration levels of CAFs and CD8+ T cells. These findings were validated in murine tongue tissue slides, and publicly available multi-omics datasets. Our results suggest that CAFs may impair the therapeutic efficacy of PD1 blockade in oral carcinogenesis by the remodeling of the extracellular matrix.

Single-Cell Transcriptomes and Immune Repertoires Reveal the Cell State and Molecular Changes in Pemphigus Vulgaris.

The etiology and pathogenesis of pemphigus vulgaris (PV) entail intricate interactions between immune cells and epithelial cells. However, the specific subtypes of immune cells involved in PV, along with their respective roles, remain elusive. Likewise, the precise functions and mechanisms by which glucocorticoids affect cell types within the disease context require further elucidation. To address these knowledge gaps, we performed 5' single-cell RNA sequencing, combined with V(D)J enrichment on buccal mucosal lesions and peripheral blood samples from treatment-naive patients with PV, in conjunction with post-treatment peripheral blood samples obtained after oral prednisone treatment. Our findings suggest that the IL-1α signaling pathway, myeloid APCs, inflammatory CD8+ resident memory T cells, and dysfunctional CD4+ regulatory T cells are involved in the pathogenesis of PV. Part of these findings were validated by immunohistochemical assays and multiplex immunofluorescence assays. Furthermore, our results highlight the significant impact of prednisone treatment on monocytes and mucosal-associated invariant T cells while revealing a limited effect on CD4+ regulatory T cells. Additionally, we present the CDR3 amino acid sequence of BCR related to PV disease and investigate the characteristics of TCR/BCR clonotypes. In conclusion, our study provides a comprehensive understanding of PV, particularly focusing on the mucosal-dominant type, and sheds light on the effects of glucocorticoids within the PV context. These insights hold promise for the development of new therapeutic strategies in this autoimmune disorder.

Single-cell assignment using multiple-adversarial domain adaptation network with large-scale references.

The rapid accumulation of single-cell RNA-seq data has provided rich resources to characterize various human cell populations. However, achieving accurate cell-type annotation using public references presents challenges due to inconsistent annotations, batch effects, and rare cell types. Here, we introduce SELINA (single-cell identity navigator), an integrative and automatic cell-type annotation framework based on a pre-curated reference atlas spanning various tissues. SELINA employs a multiple-adversarial domain adaptation network to remove batch effects within the reference dataset. Additionally, it enhances the annotation of less frequent cell types by synthetic minority oversampling and fits query data with the reference data using an autoencoder. SELINA culminates in the creation of a comprehensive and uniform reference atlas, encompassing 1.7 million cells covering 230 distinct human cell types. We substantiate its robustness and superiority across a multitude of human tissues. Notably, SELINA could accurately annotate cells within diverse disease contexts. SELINA provides a complete solution for human single-cell RNA-seq data annotation with both python and R packages.

An integrated multi-omics analysis of identifies distinct molecular characteristics in pulmonary infections of Pseudomonas aeruginosa.

Pseudomonas aeruginosa (P. aeruginosa) can cause severe acute infections, including pneumonia and sepsis, and cause chronic infections, commonly in patients with structural respiratory diseases. However, the molecular and pathophysiological mechanisms of P. aeruginosa respiratory infection are largely unknown. Here, we performed assays for transposase-accessible chromatin using sequencing (ATAC-seq), transcriptomics, and quantitative mass spectrometry-based proteomics and ubiquitin-proteomics in P. aeruginosa-infected lung tissues for multi-omics analysis, while ATAC-seq and transcriptomics were also examined in P. aeruginosa-infected mouse macrophages. To identify the pivotal factors that are involved in host immune defense, we integrated chromatin accessibility and gene expression to investigate molecular changes in P. aeruginosa-infected lung tissues combined with proteomics and ubiquitin-proteomics. Our multi-omics investigation discovered a significant concordance for innate immunological and inflammatory responses following P. aeruginosa infection between hosts and alveolar macrophages. Furthermore, we discovered that multi-omics changes in pioneer factors Stat1 and Stat3 play a crucial role in the immunological regulation of P. aeruginosa infection and that their downstream molecules (e.g., Fas) may be implicated in both immunosuppressive and inflammation-promoting processes. Taken together, these findings indicate that transcription factors and their downstream signaling molecules play a critical role in the mobilization and rebalancing of the host immune response against P. aeruginosa infection and may serve as potential targets for bacterial infections and inflammatory diseases, providing insights and resources for omics analyses.

Single-cell immune profiling reveals immune responses in oral lichen planus.

Introduction: Oral lichen planus (OLP) is a common chronic inflammatory disorder of the oral mucosa with an unclear etiology. Several types of immune cells are involved in the pathogenesis of OLP. Methods: We used single-cell RNA sequencing and immune repertoire sequencing to characterize the mucosal immune microenvironment of OLP. The presence of tissue-resident memory CD8+ T cells are validated by multiplex immunofluorescence. Results: We generated a transcriptome atlas from four OLP biopsy samples and their paired peripheral blood mononuclear cells (PBMCs), and compared them with two healthy tissues and three healthy PBMCs samples. Our analysis revealed activated tissue-resident memory CD8+ T cells in OLP tissues. T cell receptor repertoires displayed apperant clonal expansion and preferrential gene pairing in OLP patients. Additionally, obvious BCR clonal expansion was observed in OLP lesions. Plasmacytoid dendritic cells, a subtype that can promote dendritic cell maturation and enhance lymphocyte cytotoxicity, were identified in OLP. Conventional dendritic cells and macrophages are also found to exhibit pro-inflammatory activity in OLP. Cell-cell communication analysis reveals that fibroblasts might promote the recruitment and extravasation of immune cells into connective tissue. Discussion: Our study provides insights into the immune ecosystem of OLP, serving as a valuable resource for precision diagnosis and therapy of OLP.

SCREE: a comprehensive pipeline for single-cell multi-modal CRISPR screen data processing and analysis.

Single-cell CRISPR screens have been widely used to investigate gene regulatory circuits in diverse biological systems. The recent development of single-cell CRISPR screens has enabled multimodal profiling of perturbed cells with both gene expression, chromatin accessibility and protein levels. However, current methods cannot meet the analysis requirements of different types of data and have limited functions. Here, we introduce Single-cell CRISPR screens data analysEs and perturbation modEling (SCREE) as a comprehensive and flexible pipeline to facilitate the analyses of various types of single-cell CRISPR screens data. SCREE performs read alignment, sgRNA assignment, quality control, clustering and visualization, perturbation enrichment evaluation, perturbation efficiency modeling, gene regulatory score calculation and functional analyses of perturbations for single-cell CRISPR screens with both RNA, ATAC and multimodal readout. SCREE is available at https://github.com/wanglabtongji/SCREE.

HUSCH: an integrated single-cell transcriptome atlas for human tissue gene expression visualization and analyses.

Understanding gene expression patterns across different human cell types is crucial for investigating mechanisms of cell type differentiation, disease occurrence and progression. The recent development of single-cell RNA-seq (scRNA-seq) technologies significantly boosted the characterization of cell type heterogeneities in different human tissues. However, the huge number of datasets in the public domain also posed challenges in data integration and reuse. We present Human Universal Single Cell Hub (HUSCH, http://husch.comp-genomics.org), an atlas-scale curated database that integrates single-cell transcriptomic profiles of nearly 3 million cells from 185 high-quality human scRNA-seq datasets from 45 different tissues. All the data in HUSCH were uniformly processed and annotated with a standard workflow. In the single dataset module, HUSCH provides interactive gene expression visualization, differentially expressed genes, functional analyses, transcription regulators and cell-cell interaction analyses for each cell type cluster. Besides, HUSCH integrated different datasets in the single tissue module and performs data integration, batch correction, and cell type harmonization. This allows a comprehensive visualization and analysis of gene expression within each tissue based on single-cell datasets from multiple sources and platforms. HUSCH is a flexible and comprehensive data portal that enables searching, visualizing, analyzing, and downloading single-cell gene expression for the human tissue atlas.

TISCH2: expanded datasets and new tools for single-cell transcriptome analyses of the tumor microenvironment.

The Tumor Immune Single Cell Hub 2 (TISCH2) is a resource of single-cell RNA-seq (scRNA-seq) data from human and mouse tumors, which enables comprehensive characterization of gene expression in the tumor microenvironment (TME) across multiple cancer types. As an increasing number of datasets are generated in the public domain, in this update, TISCH2 has included 190 tumor scRNA-seq datasets covering 6 million cells in 50 cancer types, with 110 newly collected datasets and almost tripling the number of cells compared with the previous release. Furthermore, TISCH2 includes several new functions that allow users to better utilize the large-scale scRNA-seq datasets. First, in the Dataset module, TISCH2 provides the cell-cell communication results in each dataset, facilitating the analyses of interacted cell types and the discovery of significant ligand-receptor pairs between cell types. TISCH2 also includes the transcription factor analyses for each dataset and visualization of the top enriched transcription factors of each cell type. Second, in the Gene module, TISCH2 adds functions for identifying correlated genes and providing survival information for the input genes. In summary, TISCH2 is a user-friendly, up-to-date and well-maintained data resource for gene expression analyses in the TME. TISCH2 is freely available at http://tisch.comp-genomics.org/.

Single-cell transcriptomics reveals distinct cell response between acute and chronic pulmonary infection of Pseudomonas aeruginosa.

Knowledge of the changes in the immune microenvironment during pulmonary bacterial acute and chronic infections is limited. The dissection of immune system may provide a basis for effective therapeutic strategies against bacterial infection. Here, we describe a single immune cell atlas of mouse lungs after acute and chronic Pseudomonas aeruginosa infection using single-cell transcriptomics, multiplex immunohistochemistry, and flow cytometry. Our single-cell transcriptomic analysis revealed large-scale comprehensive changes in immune cell composition and high variation in cell-cell interactions after acute and chronic P. aeruginosa infection. Bacterial infection reprograms the genetic architecture of immune cell populations. We identified specific immune cell types, including Cxcl2+ B cells and interstitial macrophages, in response to acute and chronic infection, such as their proportions, distribution, and functional status. Importantly, the patterns of immune cell response are drastically different between acute and chronic infection models. The distinct molecular signatures highlight the importance of the highly dynamic cell-cell interaction process in different pathological conditions, which has not been completely revealed previously. These findings provide a comprehensive and unbiased immune cellular landscape for respiratory pathogenesis in mice, enabling further understanding of immunologic mechanisms in infection and inflammatory diseases.

Correction: High-efficiency and high-fidelity ssDNA circularisation via the pairing of five 3'-terminal bases to assist LR-LAMP for the genotyping of single-nucleotide polymorphisms.

Correction for 'High-efficiency and high-fidelity ssDNA circularisation via the pairing of five 3'-terminal bases to assist LR-LAMP for the genotyping of single-nucleotide polymorphisms' by Taiwen Li et al., Analyst, 2022, https://doi.org/10.1039/d2an01042a.

Single-cell transcriptomics dissects premalignant progression in proliferative verrucous leukoplakia.

OBJECTIVE: Proliferative verrucous leukoplakia (PVL) is characterized by a spectrum of clinicopathological features and a high risk of malignant transformation. In this study, we aimed to delineate the dynamic changes in molecular signature during PVL progression and identify the potential cell subtypes that play a key role in the premalignant evolution of PVL. METHODS: We performed single-cell RNA sequencing on three biopsy samples from a large PVL lesion. These samples exhibited a histopathological continuum of PVL progression. RESULTS: By analyzing the transcriptome profiles of 27,611 cells from these samples, we identified ten major cell lineages and revealed that cellular remodeling occurred during the progression of PVL lesions, including epithelial, stromal, and immune cells. Epithelial cells are shifted to tumorigenic states and secretory patterns at the premalignant stage. Immune cells showed growing immunosuppressive phenotypes during PVL progression. Remarkably, two novel cell subtypes INSR+ endothelial cells and ASPN+ fibroblasts, were discovered and may play vital roles in microenvironment remodeling, such as angiogenesis and stromal fibrosis, which are closely involved in malignant transformation. CONCLUSION: Our work is the first to depict the cellular landscape of PVL and speculate that disease progression may be driven by functional remodeling of multiple cell subtypes.

Identification of a BRAF/PA28γ/MEK1 signaling axis and its role in epithelial-mesenchymal transition in oral submucous fibrosis.

Oral submucous fibrosis (OSF) is a chronic and insidious oral potentially malignant disorder associated with a 4-17% risk of oral squamous cell carcinoma (OSCC). Our previous study found that proteasomal activator 28 gamma (PA28γ) is frequently overexpressed in oral squamous cell carcinoma and negatively correlated with poor patient prognosis. However, the role of PA28γ in the occurrence and development of OSF remains unclear. Here, we screened PA28γ-related genes and investigated their function in OSF. We demonstrated that the expression of PA28γ was positively associated with MEK1 and gradually elevated from normal to progressive stages of OSF tissue. Arecoline, a pathogenic component of OSF, could upregulate the protein levels of PA28γ and phosphorylated MEK1 and contribute to epithelial to mesenchymal transition (EMT) in epithelial cells. Notably, PA28γ could interact with MEK1 and upregulate its phosphorylation level. Furthermore, arecoline upregulated BRAF, which can interact with PA28γ and upregulate its protein level. Additionally, BRAF, PA28γ, and MEK1 could form protein complexes and then enhance the MEK1/ERK signaling pathways. The concrete mechanism of the protein stability of PA28γ is that BRAF mediates its degradation by inhibiting its ubiquitination. These findings underscore the instrumental role of PA28γ in the BRAF/MEK1 pathway and enhanced EMT through MEK1/ERK activation in OSF.

High-efficiency and high-fidelity ssDNA circularisation via the pairing of five 3'-terminal bases to assist LR-LAMP for the genotyping of single-nucleotide polymorphisms.

The poor fidelity of T4 DNA ligase has always limited the simple detection of single-nucleotide polymorphisms (SNPs) and is only applicable to some special SNP types. This study developed a highly sensitive and specific detection method for SNPs based on high-fidelity single-stranded circularisation. It used T4 DNA ligase and rolling circle amplification (RCA) plus loop-mediated isothermal amplification (LAMP). Surprisingly, the cyclisation stage's efficiency greatly improved. The ligation fidelity was almost perfect via the unique pairing pattern between a long-paired base at the 5' terminus and only five bases at the 3' terminus on linear single-stranded DNA (l-DNA). Subsequently, LR-LAMP was performed and combined with the circularisation step for the simple detection of SNPs. The results showed that even 100 aM targets could be detected correctly and that a mutation rate of 0.1% or even 0.01% could be analysed via naked-eye visualisation or fluorescence detection, respectively. In addition, genomic DNA samples were used to evaluate the method, which indicated that it could effectively distinguish the SNPs of RPA190-T1145A in Phytophthora infestans. This strategy may play an important role in both circularisation of single-stranded DNA and detecting arbitrary SNPs.

The risk factors associated with geographic tongue in a southwestern Chinese population.

OBJECTIVE: The goal of this study was to look into age, genetics,sex, oral mucosa diseases, and systemic diseases as potential risk factors for the geographic tongue (GT) in a Chinese population. STUDY DESIGN: This retrospective cross-sectional study used the demographic and medical data of 3400 patients between March 2021 and August 2021 from the Department of Oral Medicine at West China Hospital of Stomatology. Binary logistic regression was conducted to analyze the association of GT and age, fissured tongue (FT), burning mouth syndrome (BMS), oral lichen planus (OLP), gastrointestinal disorders, and hematologic disorders and to acquire the adjusted odds ratio (AOR). RESULTS: GT occurred in 3.6% of patients, with 15 out of 123 (12.2%) patients with GT having a family history. Binary logistic regression found age <30 years (AOR: 4.4; [95% CI: 2.8-6.9]), FT (28.8 [17.1-48.4]), BMS (0.3 [0.1-0.6]), OLP (0.2 [0.0-0.5]), and gastrointestinal disorders (4.3 [2.7-6.7]) were significantly associated with GT, and GT was unrelated to recurrent aphthous ulcer (RAU) or systemic diseases such as cardiovascular diseases. CONCLUSION: In the Chinese population, GT was more prevalent in patients with <30 years of age, FT, and gastrointestinal disorders, and it was less prevalent in BMS and OLP.

Direct immunofluorescence and immune function in patients with oral lichen planus.

Background/Purpose: Direct immunofluorescence and immune function and patients with oral lichen planusThe etiology of oral lichen planus (OLP) is unknown, our purpose was to evaluate the diagnostic value of direct immunofluorescence (DIF) and to investigate the immune functions in OLP. Materials and methods: We enrolled 65 patients with suspected lesions of OLP and 47 controls. In all participants, clinical and serologic testing were conducted. The histopathologic and DIF tests were conducted in 65 patients. The severity of OLP was evaluated by reticular/hyperkeratotic, erosive/erythematous, ulcerative (REU) scoring system. Results: By hematoxylin and eosin (H&E) staining and DIF examination, 71.2% (42/59) were diagnosed as OLP, 28.8% (17/59) were diagnosed as non-OLP. DIF demonstrated 64.3% positive reactivity with 2 distinct distribution patterns and 8 staining patterns. Compared to the controls, serum IgA in OLP was higher (P < 0.01), and serum CD3+ cells, IgM, IgE, C3 and C4 were lower (P < 0.05). Pearson correlation analysis in OLP revealed correlations between REU score and IgM, IgA of DIF (r = 0.54, P = 0.026; and r = 0.56, P = 0.020, respectively), between serum IgG and IgG of DIF (r = 0.51, P = 0.038), between serum CD4+ and the ratio of CD4+/CD8+, IgM in DIF (r = -0.50, P = 0.048; and r = -0.54, P = 0.031, respectively), between serum CD8+ and IgM, IgA in DIF (r = 0.52, P = 0.038; and r = -0.50, P = 0.047, respectively). Conclusion: A combination of H&E test and DIF is useful for the diagnosis of OLP. Compared to controls, immune changes happen to patients with OLP. There are significant associations between the OLP lesions and general cellular and humoral immune status, localized humoral immune response.

STRIDE: accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing.

The recent advances in spatial transcriptomics have brought unprecedented opportunities to understand the cellular heterogeneity in the spatial context. However, the current limitations of spatial technologies hamper the exploration of cellular localizations and interactions at single-cell level. Here, we present spatial transcriptomics deconvolution by topic modeling (STRIDE), a computational method to decompose cell types from spatial mixtures by leveraging topic profiles trained from single-cell transcriptomics. STRIDE accurately estimated the cell-type proportions and showed balanced specificity and sensitivity compared to existing methods. We demonstrated STRIDE's utility by applying it to different spatial platforms and biological systems. Deconvolution by STRIDE not only mapped rare cell types to spatial locations but also improved the identification of spatially localized genes and domains. Moreover, topics discovered by STRIDE were associated with cell-type-specific functions and could be further used to integrate successive sections and reconstruct the three-dimensional architecture of tissues. Taken together, STRIDE is a versatile and extensible tool for integrated analysis of spatial and single-cell transcriptomics and is publicly available at https://github.com/wanglabtongji/STRIDE.