Back to Search
Start Over
Single cell imaging-based chromatin biomarkers for tumor progression.
- Source :
-
Scientific reports [Sci Rep] 2021 Nov 29; Vol. 11 (1), pp. 23041. Date of Electronic Publication: 2021 Nov 29. - Publication Year :
- 2021
-
Abstract
- Tumour progression within the tissue microenvironment is accompanied by complex biomechanical alterations of the extracellular environment. While histopathology images provide robust biochemical markers for tumor progression in clinical settings, a quantitative single cell score using nuclear morphology and chromatin organization integrated with the long range mechanical coupling within the tumor microenvironment is missing. We propose that the spatial chromatin organization in individual nuclei characterises the cell state and their alterations during tumor progression. In this paper, we first built an image analysis pipeline and implemented it to classify nuclei from patient derived breast tissue biopsies of various cancer stages based on their nuclear and chromatin features. Replacing H&E with DNA binding dyes such as Hoescht stained tissue biopsies, we improved the classification accuracy. Using the nuclear morphology and chromatin organization features, we constructed a pseudo-time model to identify the chromatin state changes that occur during tumour progression. This enabled us to build a single-cell mechano-genomic score that characterises the cell state during tumor progression from a normal to a metastatic state. To gain further insights into the alterations in the local tissue microenvironments, we also used the nuclear orientations to identify spatial neighbourhoods that have been posited to drive tumor progression. Collectively, we demonstrate that image-based single cell chromatin and nuclear features are important single cell biomarkers for phenotypic mapping of tumor progression.<br /> (© 2021. The Author(s).)
- Subjects :
- Biomarkers, Tumor
Biophysics
Biopsy
Breast Neoplasms metabolism
Collagen chemistry
Computational Biology
DNA chemistry
Disease Progression
Fibroblasts metabolism
Genomics
Humans
Image Processing, Computer-Assisted
In Vitro Techniques
Machine Learning
Neoplasm Metastasis
Phenotype
Probability
Protein Binding
Tumor Microenvironment
Biomarkers metabolism
Cell Nucleus metabolism
Chromatin chemistry
Neoplasms metabolism
Subjects
Details
- Language :
- English
- ISSN :
- 2045-2322
- Volume :
- 11
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Scientific reports
- Publication Type :
- Academic Journal
- Accession number :
- 34845273
- Full Text :
- https://doi.org/10.1038/s41598-021-02441-6