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Unsupervised representation learning of chromatin images identifies changes in cell state and tissue organization in DCIS.
- Source :
-
Nature communications [Nat Commun] 2024 Jul 20; Vol. 15 (1), pp. 6112. Date of Electronic Publication: 2024 Jul 20. - Publication Year :
- 2024
-
Abstract
- Ductal carcinoma in situ (DCIS) is a pre-invasive tumor that can progress to invasive breast cancer, a leading cause of cancer death. We generate a large-scale tissue microarray dataset of chromatin images, from 560 samples from 122 female patients in 3 disease stages and 11 phenotypic categories. Using representation learning on chromatin images alone, without multiplexed staining or high-throughput sequencing, we identify eight morphological cell states and tissue features marking DCIS. All cell states are observed in all disease stages with different proportions, indicating that cell states enriched in invasive cancer exist in small fractions in normal breast tissue. Tissue-level analysis reveals significant changes in the spatial organization of cell states across disease stages, which is predictive of disease stage and phenotypic category. Taken together, we show that chromatin imaging represents a powerful measure of cell state and disease stage of DCIS, providing a simple and effective tumor biomarker.<br /> (© 2024. The Author(s).)
- Subjects :
- Humans
Female
Biomarkers, Tumor metabolism
Biomarkers, Tumor genetics
Unsupervised Machine Learning
Image Processing, Computer-Assisted methods
Tissue Array Analysis
Neoplasm Staging
Carcinoma, Intraductal, Noninfiltrating pathology
Carcinoma, Intraductal, Noninfiltrating genetics
Carcinoma, Intraductal, Noninfiltrating metabolism
Chromatin metabolism
Breast Neoplasms pathology
Breast Neoplasms genetics
Breast Neoplasms metabolism
Subjects
Details
- Language :
- English
- ISSN :
- 2041-1723
- Volume :
- 15
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Nature communications
- Publication Type :
- Academic Journal
- Accession number :
- 39030176
- Full Text :
- https://doi.org/10.1038/s41467-024-50285-1