Tertiary lymphoid structures in cancer: maturation and induction

Frontiers in Immunology, Год журнала: 2024, Номер 15

Опубликована: Апрель 16, 2024

Tertiary lymphoid structure (TLS) is an ectopic lymphocyte aggregate formed in peripheral non-lymphoid tissues, including inflamed or cancerous tissue. Tumor-associated TLS serves as a prominent center of antigen presentation and adaptive immune activation within the periphery, which has exhibited positive prognostic value various cancers. In recent years, concept maturity regarding been proposed mature TLS, characterized by well-developed germinal centers, exhibits more potent tumor-suppressive capacity with stronger significance. Meanwhile, evidence showed that can be induced therapeutic interventions during cancer treatments. Thus, evaluation induce its formation are critical issues current research. this review, we aim to provide comprehensive summary existing classifications for strategies capable inducing tumors.

Язык: Английский

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AI-driven multi-omics integration for multi-scale predictive modeling of genotype-environment-phenotype relationships

Computational and Structural Biotechnology Journal, Год журнала: 2025, Номер 27, С. 265 - 277

Опубликована: Янв. 1, 2025

Despite the wealth of single-cell multi-omics data, it remains challenging to predict consequences novel genetic and chemical perturbations in human body. It requires knowledge molecular interactions at all biological levels, encompassing disease models humans. Current machine learning methods primarily establish statistical correlations between genotypes phenotypes but struggle identify physiologically significant causal factors, limiting their predictive power. Key challenges modeling include scarcity labeled generalization across different domains, disentangling causation from correlation. In light recent advances data integration, we propose a new artificial intelligence (AI)-powered biology-inspired multi-scale framework tackle these issues. This will integrate organism hierarchies, species genotype-environment-phenotype relationships under various conditions. AI inspired by biology may targets, biomarkers, pharmaceutical agents, personalized medicines for presently unmet medical needs.

Язык: Английский

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Role of tertiary lymphoid structures and B cells in clinical immunotherapy of gastric cancer

Frontiers in Immunology, Год журнала: 2025, Номер 15

Опубликована: Янв. 7, 2025

Gastric cancer is a common malignant tumor of the digestive tract, and its treatment remains significant challenge. In recent years, role various immune cells in microenvironment progression has gained increasing attention. Immunotherapy, primarily based on checkpoint inhibitors, notably improved prognosis patients with gastric cancer; however, challenges regarding therapeutic efficacy persist. Histological features within microenvironment, such as tertiary lymphoid structures (TLSs), tumor-infiltrating lymphocytes, proportion intratumoral stroma, are emerging potentially effective prognostic factors. cancer, TLSs may serve local hubs, enhancing ability to interact recognize antigens, which closely linked effectiveness immunotherapy survival rates patients. However, specific cell type driving TLS formation tumors not yet been elucidated. Mature B-cell regions containing germinal centers. During center formation, B undergo transformations become mature function, exerting anti-tumor effects. Therefore, targeting could provide new avenues for immunotherapy. This review, combined current research elaborates relationship between aiming guidance precise

Язык: Английский

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Quantitative characterization of cell niches in spatially resolved omics data

Nature Genetics, Год журнала: 2025, Номер unknown

Опубликована: Март 18, 2025

Abstract Spatial omics enable the characterization of colocalized cell communities that coordinate specific functions within tissues. These communities, or niches, are shaped by interactions between neighboring cells, yet existing computational methods rarely leverage such for their identification and characterization. To address this gap, here we introduce NicheCompass, a graph deep-learning method models cellular communication to learn interpretable embeddings encode signaling events, enabling niches underlying processes. Unlike methods, NicheCompass quantitatively characterizes based on pathways consistently outperforms alternatives. We show its versatility mapping tissue architecture during mouse embryonic development delineating tumor in human cancers, including spatial reference application. Finally, extend capabilities multi-omics, demonstrate cross-technology integration with datasets from different sequencing platforms construct whole brain atlas comprising 8.4 million highlighting NicheCompass’ scalability. Overall, provides scalable framework identifying analyzing through events.

Язык: Английский

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Liver endothelial cells in NAFLD and transition to NASH and HCC

Cellular and Molecular Life Sciences, Год журнала: 2023, Номер 80(11)

Опубликована: Окт. 5, 2023

Язык: Английский

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Cancer cell states: Lessons from ten years of single-cell RNA-sequencing of human tumors

Cancer Cell, Год журнала: 2024, Номер 42(9), С. 1497 - 1506

Опубликована: Авг. 29, 2024

Язык: Английский

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Advances in Integrated Multi-omics Analysis for Drug-Target Identification

Biomolecules, Год журнала: 2024, Номер 14(6), С. 692 - 692

Опубликована: Июнь 14, 2024

As an essential component of modern drug discovery, the role drug-target identification is growing increasingly prominent. Additionally, single-omics technologies have been widely utilized in process discovering targets. However, it difficult for any level to clearly expound causal connection between drugs and how they give rise emergence complex phenotypes. With progress large-scale sequencing development high-throughput technologies, tendency has shifted towards integrated multi-omics techniques, gradually replacing traditional techniques. Herein, this review centers on recent advancements domain techniques target identification, highlights common analysis strategies, briefly summarizes selection tools, explores challenges existing analyses, as well applications technology identification.

Язык: Английский

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A revised conceptual framework for mouse vomeronasal pumping and stimulus sampling

Current Biology, Год журнала: 2024, Номер 34(6), С. 1206 - 1221.e6

Опубликована: Фев. 5, 2024

The physiological performance of any sensory organ is determined by its anatomy and physical properties. Consequently, complex structures with elaborate features have evolved to optimize stimulus detection. Understanding these their nature forms the basis for mechanistic insights into function. Despite crucial role as a sensor pheromones other behaviorally instructive chemical cues, vomeronasal (VNO) remains poorly characterized mammalian structure. Fundamental principles physico-mechanical function, including basic aspects sampling, remain explored. Here, we revisit classical vasomotor pump hypothesis uptake. Using advanced anatomical, histological, methods, demonstrate that large parts lateral mouse VNO are composed smooth muscle. Vomeronasal muscle tissue comprises two subsets fibers distinct topography, structure, excitation-contraction coupling, and, ultimately, contractile Specifically, contractions population noradrenaline-sensitive cells mediate both transverse longitudinal lumen expansion, whereas cholinergic stimulation targets an adluminal group fibers. latter run parallel VNO's rostro-caudal axis ideally situated antagonistic constriction lumen. This newly discovered arrangement implies novel mode Single-cell transcriptomics pharmacological profiling reveal receptor subtypes involved. Finally, 2D/3D tomography provides non-invasive insight intact mechanics, enables measurement luminal fluid volume, allows assessment relative volume change upon noradrenergic stimulation. Together, propose revised conceptual framework pumping thus, sampling.

Язык: Английский

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Integrating Machine Learning with Multi-Omics Technologies in Geroscience: Towards Personalized Medicine

Journal of Personalized Medicine, Год журнала: 2024, Номер 14(9), С. 931 - 931

Опубликована: Авг. 31, 2024

Aging is a fundamental biological process characterized by progressive decline in physiological functions and an increased susceptibility to diseases. Understanding aging at the molecular level crucial for developing interventions that could delay or reverse its effects. This review explores integration of machine learning (ML) with multi-omics technologies-including genomics, transcriptomics, epigenomics, proteomics, metabolomics-in studying hallmarks develop personalized medicine interventions. These include genomic instability, telomere attrition, epigenetic alterations, loss proteostasis, disabled macroautophagy, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, altered intercellular communication, chronic inflammation, dysbiosis. Using ML analyze big complex datasets helps uncover detailed interactions pathways play role aging. The advances can facilitate discovery biomarkers therapeutic targets, offering insights into anti-aging strategies. With these developments, future points toward better understanding process, aiming ultimately promote healthy extend life expectancy.

Язык: Английский

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Multimodal bioimaging across disciplines and scales: challenges, opportunities and breaking down barriers

npj Imaging, Год журнала: 2024, Номер 2(1)

Опубликована: Март 1, 2024

Abstract Multimodal bioimaging is a broad term used to describe experimental workflows that employ two or more different imaging modalities. Such approaches have been in use across life science domains for several years but these remain relatively limited scope, part due the complexity of undertaking types analysis. Expanding encompass diverse, emerging technology holds potential revolutionize our understanding spatial biology. In this perspective we reflect on instrument and current use, areas consider experience barriers broader adoption progress. We propose enabling solutions challenge areas, opportunities consideration highlight some key community activities help move field forward.

Язык: Английский

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