AI Article Synopsis
- Cancer is a complex environment where cancerous and non-cancerous cells interact, necessitating advanced tools to analyze this intricate landscape using new imaging technologies.* -
- The study presents SpatialCells, an open-source software that allows researchers to analyze and characterize tumor microenvironments using detailed single-cell data.* -
- SpatialCells automates the extraction of important features from large datasets and assists in further analyses, enhancing our understanding of how tumors grow and spread.*
Article Abstract
Background: Cancer is a complex cellular ecosystem where malignant cells coexist and interact with immune, stromal, and other cells within the tumor microenvironment. Recent technological advancements in spatially resolved multiplexed imaging at single-cell resolution have led to the generation of large-scale and high-dimensional datasets from biological specimens. This underscores the necessity for automated methodologies that can effectively characterize the molecular, cellular, and spatial properties of tumor microenvironments for various malignancies.
Results: This study introduces SpatialCells, an open-source software package designed for region-based exploratory analysis and comprehensive characterization of tumor microenvironments using multiplexed single-cell data.
Conclusions: SpatialCells efficiently streamlines the automated extraction of features from multiplexed single-cell data and can process samples containing millions of cells. Thus, SpatialCells facilitates subsequent association analyses and machine learning predictions, making it an essential tool in advancing our understanding of tumor growth, invasion, and metastasis.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10680639 | PMC |
| http://dx.doi.org/10.1101/2023.11.10.566378 | DOI Listing |
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