Spatiotemporal Architecture of High-Grade Serous Ovarian Carcinoma (Q6718144)
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Dataset published at Zenodo repository.
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Spatiotemporal Architecture of High-Grade Serous Ovarian Carcinoma |
Dataset published at Zenodo repository. |
Statements
High-grade serous ovarian carcinoma (HGSOC), the deadliest form of ovarian cancer, is typically first diagnosed after it has metastasized and almost always relapses after standard-of-care platinum-based chemotherapy. Targeted therapies and immunotherapies are effective in only a small subset of patients, likely due to advanced tumor stage, inherent heterogeneity, and immune suppression and/or tumor-promoting signaling from the tumor microenvironment. There is a large gap in understanding how spatial heterogeneity and intercellular signaling contribute to HGSOC progression and early relapse. We used Imaging Mass Cytometry (IMC) and a HGSOC tissue microarray of patient-matched pre-chemotherapy primary tumors, synchronous metastases, and metachronous post-chemotherapy recurrent metastases from 42 patients to determine the spatiotemporal arrangement of different cell types during HGSOC progression. We found that tumors from patients with early relapse exhibit distinct patterns of immune cells, fibroblasts, and epithelial cells, including malformed tertiary lymphoid structures and increased presence of podoplanin-expressing fibroblasts. Changes in T cell localization between primary and synchronous metastatic tumors were also associated with early relapse, independent of the concentration of total T cells. Our highly multiplexed IMC data was consistent with data obtained by standard histology and immunohistochemistry and also demonstrated the additive value of highly multiplexed analyses.
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18 March 2023
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MCD IMC Files, GeoMx Files
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