Current state and future prospects of spatial biology in colorectal cancer

Frontiers in Oncology, Journal Year: 2024, Volume and Issue: 14

Published: Dec. 3, 2024

Over the past century, colorectal cancer (CRC) has become one of most devastating cancers impacting human population. To gain a deeper understanding molecular mechanisms driving this solid tumor, researchers have increasingly turned their attention to tumor microenvironment (TME). Spatial transcriptomics and proteomics emerged as particularly powerful technology for deciphering complexity CRC tumors, given that TME its spatial organization are critical determinants disease progression treatment response. enables high-resolution mapping whole transcriptome. While maps protein expression function across tissue sections. Together, they provide detailed view landscape cellular interactions within TME. In review, we delve into recent advances in biology technologies applied research, highlighting both methodologies challenges associated with use, such substantial heterogeneity characteristic CRC. We also discuss limitations current approaches need novel computational tools manage interpret these complex datasets. conclude, emphasize importance further developing integrating precision medicine strategies enhance therapeutic targeting improve patient outcomes.

Language: Английский

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Analysis of single-cell and spatial transcriptomics in TNBC cell-cell interactions

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

Published: Feb. 26, 2025

Triple-negative breast cancer (TNBC) is a highly malignant tumor in women, characterized by high morbidity, mortality, and recurrence rates. Although surgical treatment, radiotherapy, chemotherapy are the mainstays of current treatment methods, heterogeneity TNBC results unsatisfactory outcomes with low 5-year survival Rapid advancements omics technology have propelled understanding molecular biology. The emergence single-cell RNA sequencing (scRNA-seq) spatial transcriptomics (ST) has significantly enhanced knowledge distribution, functionality, intercellular interactions various cell types within microenvironment, including cells, T B macrophages, fibroblasts. present study provides an overview technical characteristics scRNA-seq ST, highlighting their applications exploring heterogeneity, distribution patterns, interactions. This review aims to enhance comprehension at cellular level for development effective therapeutic targets.

Language: Английский

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Small Fish, Big Answers: Zebrafish and the Molecular Drivers of Metastasis

International Journal of Molecular Sciences, Journal Year: 2025, Volume and Issue: 26(3), P. 871 - 871

Published: Jan. 21, 2025

Cancer metastasis is a leading cause of cancer-related deaths and represents one the most challenging processes to study due its complexity dynamic nature. Zebrafish (Danio rerio) have become an invaluable model in research, offering unique advantages such as optical transparency, rapid development, ability visualize tumor interactions with microenvironment real time. This review explores how zebrafish models elucidated critical steps metastasis, including invasion, vascular remodeling, immune evasion, while also serving platforms for drug testing personalized medicine. Advances patient-derived xenografts innovative genetic tools further established cornerstone cancer particularly understanding molecular drivers identifying therapeutic targets. By bridging experimental findings clinical relevance, continue transforming our biology therapy.

Language: Английский

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Artificial intelligence-driven integration of multi-omics and radiomics: A new hope for precision cancer diagnosis and prognosis

Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease, Journal Year: 2025, Volume and Issue: unknown, P. 167841 - 167841

Published: April 1, 2025

Language: Английский

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Easydecon: A Lightweight Workflow for Cell Type Analysis in High-Definition Spatial Transcriptomics Assays

Published: April 14, 2025

Abstract Spatial transcriptomics enables mapping gene expression within tissue structures. VisiumHD by 10x Genomics advances this further, offering near-single-cell resolution across sections. Here we introduce Easydecon, a lightweight bioinformatics workflow leveraging similarity algorithms and regression-based cell type proportion estimation to transfer types deconvolute spatial bins. Easydecon streamlines visualization deconvolution utilizing differentially expressed genes identified from single-cell RNA sequencing datasets.

Language: Английский

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Biomarkers in high grade serous ovarian cancer

Biochimica et Biophysica Acta (BBA) - Reviews on Cancer, Journal Year: 2024, Volume and Issue: unknown, P. 189224 - 189224

Published: Nov. 1, 2024

Language: Английский

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