How can clinicians use spatial transcriptomics data to interpret the complexity of tumor...
Автор: Labroots
Загружено: 2025-01-08
Просмотров: 113
Presented By: Kwon Joong Na
Speaker Biography:
Internship (2010.3. – 2011.2) - Seoul National University Hospital
Resident (2011.3. – 2015.2.) - Department of Thoracic and Cardiovascular Surgery | Seoul National University Hospital
Public health doctor as military service (2015.4. – 2018.4.)
Fellowship (2018.3. – 2019.2.) - Division of General Thoracic Surgery, Department of Thoracic and Cardiovascular Surgery | Seoul National University Hospital Clinical
Clinical Assistant Professor (2019.3. – 2024.2.) - Division of General Thoracic Surgery, Department of Thoracic and Cardiovascular Surgery | Seoul National University Hospital Clinical Associate
Professor (2024.3. – Present) - Division of General Thoracic Surgery, Department of Thoracic and Cardiovascular Surgery Seoul National University Hospital
Chief Medical Officer, Portrai (2021.7. – Present)
Webinar: How can clinicians use spatial transcriptomics data to interpret the complexity of tumor microenvironment?
Webinar Abstract:
Spatial transcriptomics offers a revolutionary approach to understanding the tumor microenvironment (TME) in solid tumors by preserving the spatial context of gene expression, which is crucial for comprehending the interactions between various cell types, such as cancer cells, immune cells, fibroblasts, and endothelial cells. By integrating high-throughput sequencing and imaging technologies, spatial transcriptomics maps gene expression patterns within tissue sections, providing a high-resolution view of gene activity across the TME. This technique enables clinicians to study tumor heterogeneity, trace the lineage of cancer cells, and identify spatially resolved biomarkers essential for developing effective immunotherapies. By offering insights into tumor evolution, immune evasion, and therapeutic resistance, spatial transcriptomics holds great promise for improving the diagnosis, treatment, and prognosis of solid tumors, ultimately leading to better patient outcomes.
Learning Objectives
Infer the interactions between various cell types, such as cancer cells, immune cells, fibroblasts, and endothelial cells using Spatial Transcriptomics.
Uncover how Spatial Transcriptomics maps gene expression patterns within tissue sections, providing a high-resolution view of gene activity across the TME.
Examine how spatial transcriptomics contributes to understanding tumor evolution, immune evasion, and therapeutic resistance.
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2. Watch the webinar on YouTube or on the Labroots Website (https://www.labroots.com/ms/webinar/c...)
3. Click Here to get your PACE credits (Expiration date – July 25, 2026): https://www.labroots.com/credit/pace-...
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