Spatial Transcriptomics Unravel the Tissue Complexity of Oral Pathogenesis

Journal of Dental Research, Journal Year: 2024, Volume and Issue: 103(13), P. 1331 - 1339

Published: Oct. 9, 2024

Spatial transcriptomics (ST) is a cutting-edge methodology that enables the simultaneous profiling of global gene expression and spatial information within histological tissue sections. Traditional transcriptomic methods lack resolution required to sufficiently examine complex interrelationships between cellular regions in diseased healthy states. We review general workflows for ST, from specimen processing ST data analysis interpretations dataset using visualizations cell deconvolution approaches. show how recent studies used explore development or pathogenesis specific craniofacial regions, including cranium, palate, salivary glands, tongue, floor mouth, oropharynx, periodontium. Analyses cranial suture patency palatal fusion during identified patterns bone morphogenetic protein sutures osteogenic differentiation pathways addition discovery several genes expressed at critical locations development. glands patients with Sjögren's disease revealed co-localization autoimmune antigens ductal cells subpopulation acinar was specifically depleted by dysregulated response. head neck lesions, such as premalignant leukoplakia progressing established oral squamous carcinomas, cancers perineural invasions, oropharyngeal lesions associated HPV infection spatially profiled tumor microenvironment, showing functionally important signatures differentiation, invasion, nontumor dysregulation patient biopsies. also enabled localization periodontal disease-associated gingival tissues, involved inflammation, fibroblast subtype mediating transition innate adaptive immune responses periodontitis. The increased use especially conjunction single-cell analyses, promises improve our understandings unprecedented tissue-level both space time.

Language: Английский

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Integrating Spatially‐Resolved Transcriptomics Data Across Tissues and Individuals: Challenges and Opportunities

Small Methods, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 11, 2025

Advances in spatially-resolved transcriptomics (SRT) technologies have propelled the development of new computational analysis methods to unlock biological insights. The lowering cost SRT data generation presents an unprecedented opportunity create large-scale spatial atlases and enable population-level investigation, integrating across multiple tissues, individuals, species, or phenotypes. Here, unique challenges are described integration, where analytic impact varying resolutions is characterized explored. A succinct review spatially-aware integration strategies provided. Exciting opportunities advance algorithms amenable atlas-scale datasets along with standardized preprocessing methods, leading improved sensitivity reproducibility future further highlighted.

Language: Английский

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Comprehensive biomarker profiles in hematological malignancies: improving diagnosis, prognosis, and treatment

Biomarkers in Medicine, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 16

Published: Feb. 27, 2025

Hematological malignancies present substantial challenges in clinical practice due to their heterogeneity and complex biological profiles. In these diseases, biomarkers – measurable indicators of states are indispensable for diagnosis, prognosis, therapeutic decision-making. Emerging significantly improving outcomes hematological cancers by enhancing early detection, refining prognostic assessments, enabling personalized treatment approaches, optimizing overall patient management. This progress translates into better more effective strategies treat manage malignancies. The field biomarker discovery has developed from basic morphological cytogenetic markers advanced molecular techniques, including polymerase chain reaction (PCR) next-generation sequencing (NGS), which have enhanced diagnostic accuracy led the development targeted therapies. Additionally, recent advent technologies like mass spectrometry single-cell RNA enables comprehensive profiling reveals novel that were previously undetectable. Our aim this manuscript is provide a overview immunohematological biomarkers, applications, future directions field.

Language: Английский

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Inflammatory Cell Interactions in the Rotator Cuff Microenvironment: Insights From Single‐Cell Sequencing

International Journal of Genomics, Journal Year: 2025, Volume and Issue: 2025(1)

Published: Jan. 1, 2025

Rotator cuff injuries are a common cause of shoulder pain and dysfunction, with chronic inflammation complicating recovery. Recent advances in single‐cell RNA sequencing (scRNA‐seq) have provided new insights into the immune cell interactions within rotator microenvironment during injury healing. This review focuses on application scRNA‐seq to explore roles nonimmune cells, including macrophages, T‐cells, fibroblasts, myofibroblasts, driving inflammation, tissue repair, fibrosis. We discuss how crosstalk extracellular matrix influence progression healing or pathology. Single‐cell analyses identified distinct molecular signatures associated which may contribute persistent damage. Additionally, we highlight therapeutic potential targeting emphasizing personalized medicine approaches. Overall, integration studying enhances our understanding cellular mechanisms involved offers perspectives for developing targeted treatments regenerative medicine.

Language: Английский

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Integrated Analyses of the Transcriptome and Metabolome Revealed the Coloring Mechanism of Red-pericarp Wampee (Clausena lansium)

Plant Physiology and Biochemistry, Journal Year: 2025, Volume and Issue: 224, P. 109959 - 109959

Published: April 26, 2025

Language: Английский

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Advancements in pathology: Digital transformation, precision medicine, and beyond

Journal of Pathology Informatics, Journal Year: 2024, Volume and Issue: 16, P. 100408 - 100408

Published: Nov. 19, 2024

Pathology, a cornerstone of medical diagnostics and research, is undergoing revolutionary transformation fueled by digital technology, molecular biology advancements, big data analytics. Digital pathology converts conventional glass slides into high-resolution images, enhancing collaboration efficiency among pathologists worldwide. Integrating artificial intelligence (AI) machine learning (ML) algorithms with improves diagnostic accuracy, particularly in complex diseases like cancer. Molecular pathology, facilitated next-generation sequencing (NGS), provides comprehensive genomic, transcriptomic, proteomic insights disease mechanisms, guiding personalized therapies. Immunohistochemistry (IHC) plays pivotal role biomarker discovery, refining classification prognostication. Precision medicine integrates pathology's findings individual genetic, environmental, lifestyle factors to customize treatment strategies, optimizing patient outcomes. Telepathology extends services underserved areas through remote pathology. Pathomics leverages analytics extract meaningful from advancing our understanding therapeutic targets. Virtual autopsies employ non-invasive imaging technologies revolutionize forensic These innovations promise earlier diagnoses, tailored treatments, enhanced care. Collaboration across disciplines essential fully realize the transformative potential these advancements practice research.

Language: Английский

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STMiner: Gene-centric spatial transcriptomics for deciphering tumor tissues

Cell Genomics, Journal Year: 2025, Volume and Issue: 5(2), P. 100771 - 100771

Published: Feb. 1, 2025

Highlights•Spot-based methods struggle to handle the complexity of tumor samples•STMiner avoids background bias by optimal transport theory•STMiner retains both high- and low-expression genes based on spatial distribution•STMiner identifies overlapping regions from a gene-based perspectiveSummaryAnalyzing transcriptomics data tissues poses several challenges beyond those healthy samples, including unclear boundaries between different regions, uneven cell densities, relatively higher cellular heterogeneity. Collectively, these against which spatially variable are identified, can result in misidentification structures hinder potential insight into complex pathologies. To overcome this problem, STMiner leverages 2D Gaussian mixture models theory directly characterize distribution rather than capture locations cells expressing them (spots). By effectively mitigating impacts sparsity, reveals key gene sets overlooked spot-based analytic tools, facilitating novel biological discoveries. The core concept analyzing overall expression patterns also allows for broader application transcriptomics, positioning continuous expansion as omics technologies evolve.Graphical abstract

Language: Английский

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Single-cell genomics and spatial transcriptomics in islet transplantation for diabetes treatment: advancing towards personalized therapies

Frontiers in Immunology, Journal Year: 2025, Volume and Issue: 16

Published: Feb. 20, 2025

Diabetes mellitus (DM) is a global health crisis affecting millions, with islet transplantation emerging as promising treatment strategy to restore insulin production. This review synthesizes the current research on single-cell and spatial transcriptomics in context of transplantation, highlighting their potential revolutionize DM management. Single-cell RNA sequencing, offers detailed look into diversity functionality within grafts, identifying specific cell types states that influence graft acceptance function. Spatial complements this by mapping gene expression tissue's context, crucial for understanding microenvironment surrounding transplanted islets interactions host tissues. The integration these technologies comprehensive view cellular microenvironments, elucidating mechanisms underlying function, survival, rejection. instrumental developing targeted therapies enhance performance patient outcomes. emphasizes significance avenues informing clinical practices improving outcomes patients through more effective strategies. Future directions include application personalized medicine, developmental biology, regenerative predict disease progression responses. Addressing ethical technical challenges will be successful implementation integrated approaches practice, ultimately enhancing our ability manage improve quality life.

Language: Английский

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A comprehensive review: synergizing stem cell and embryonic development knowledge in mouse and human integrated stem cell-based embryo models

Frontiers in Cell and Developmental Biology, Journal Year: 2024, Volume and Issue: 12

Published: April 22, 2024

Mammalian stem cell-based embryo models have emerged as innovative tools for investigating early embryogenesis in both mice and primates. They not only reduce the need sacrificing but also overcome ethical limitations associated with human research. Furthermore, they provide a platform to address scientific questions that are otherwise challenging explore vivo . The usefulness of model depends on its fidelity replicating development, efficiency reproducibility; all essential addressing biological queries quantitative manner, enabling statistical analysis. Achieving such requires robust systems demand extensive optimization efforts. A profound understanding pre- post-implantation cellular plasticity, lineage specification, existing is imperative making informed decisions constructing these models. This review aims highlight differences development cell biology between humans, assess how variances influence formation partially fully integrated models, identify critical challenges field.

Language: Английский

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Emerging measurements for tumor-infiltrating lymphocytes in breast cancer

Japanese Journal of Clinical Oncology, Journal Year: 2024, Volume and Issue: 54(6), P. 620 - 629

Published: March 23, 2024

Abstract Tumor-infiltrating lymphocytes are a general term for or immune cells infiltrating the tumor microenvironment. Numerous studies have demonstrated tumor-infiltrating to be robust prognostic and predictive biomarkers in breast cancer. Recently, checkpoint inhibitors, which directly target lymphocytes, become part of standard care treatment triple-negative Surprisingly, quantified by conventional methods do not predict response highlights heterogeneity complexity network composed diverse cell populations, including cytotoxic CD8-positive T B myeloid cells. Traditionally, stroma been evaluated histology. However, standardization this approach is limited, necessitating use various novel technologies elucidate This review outlines evaluation from pathological approaches that evaluate intratumoral stromal such as immunohistochemistry, more recent advancements computer tissue imaging using artificial intelligence, flow cytometry sorting multi-omics analyses high-throughput assays estimate bulk signatures deconvolution tools. We also discuss higher resolution enable analysis single-cell spatial transcriptomics. As we era personalized medicine, it important clinicians understand these technologies.

Language: Английский

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