Related Experiment Video
Updated: Oct 11, 2025
10:41
An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues
Published on: April 5, 2018
10.6K
Single cell imaging-based chromatin biomarkers for tumor progression
Saradha Venkatachalapathy1,2,3, Doorgesh S Jokhun1, Madhavi Andhari1,4
1Mechanobiology Institute and Department of Biological Sciences, National University of Singapore, Singapore, 117411, Singapore.
Scientific Reports
|November 30, 2021
Summary
Researchers developed a new method to analyze cell nuclei in breast cancer biopsies. This approach uses chromatin organization and nuclear morphology to create a single-cell score, improving tumor progression assessment.
Area of Science:
- Biomedical Engineering
- Computational Biology
- Cancer Research
Background:
- Tumor progression involves complex biomechanical changes in the tissue microenvironment.
- Current histopathology relies on biochemical markers, lacking quantitative single-cell mechanical and genomic integration.
- A need exists for a single-cell score integrating nuclear morphology, chromatin organization, and mechanical coupling.
Purpose of the Study:
- To develop and validate an image analysis pipeline for classifying nuclei based on morphology and chromatin organization.
- To establish a pseudo-time model for identifying chromatin state changes during tumor progression.
- To create a single-cell mechano-genomic score for characterizing cell states from normal to metastatic.
Main Methods:
- Developed an image analysis pipeline to classify nuclei from patient-derived breast tissue biopsies.
- Utilized DNA binding dyes (e.g., Hoechst) for improved classification accuracy over H&E staining.
- Constructed a pseudo-time model using nuclear morphology and chromatin organization features.
- Incorporated nuclear orientation analysis to identify tumor-promoting spatial neighborhoods.
Main Results:
- Successfully classified nuclei based on distinct nuclear and chromatin features across various cancer stages.
- Identified key chromatin state changes during tumor progression via the pseudo-time model.
- Developed a single-cell mechano-genomic score correlating with tumor progression from normal to metastatic states.
- Nuclear orientation analysis revealed spatial neighborhoods associated with tumor progression.
Conclusions:
- Image-based single-cell chromatin and nuclear features serve as crucial biomarkers for phenotypic mapping of tumor progression.
- The developed mechano-genomic score offers a quantitative method to assess cell states during cancer development.
- Integrating nuclear morphology, chromatin organization, and spatial information provides deeper insights into tumor microenvironment dynamics.
