| Autor: |
Subarnarekha Chatterji, Jan Moritz Niehues, Marko van Treeck, Chiara Maria Lavinia Loeffler, Oliver Lester Saldanha, Gregory Patrick Veldhuizen, Didem Cifci, Zunamys Itzell Carrero, Rasha Abu-Eid, Valerie Speirs, Jakob Nikolas Kather |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
npj Breast Cancer, Vol 9, Iss 1, Pp 1-10 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2374-4677 |
| DOI: |
10.1038/s41523-023-00599-y |
| Popis: |
Abstract Breast cancer prognosis and management for both men and women are reliant upon estrogen receptor alpha (ERα) and progesterone receptor (PR) expression to inform therapy. Previous studies have shown that there are sex-specific binding characteristics of ERα and PR in breast cancer and, counterintuitively, ERα expression is more common in male than female breast cancer. We hypothesized that these differences could have morphological manifestations that are undetectable to human observers but could be elucidated computationally. To investigate this, we trained attention-based multiple instance learning prediction models for ERα and PR using H&E-stained images of female breast cancer from the Cancer Genome Atlas (TCGA) (n = 1085) and deployed them on external female (n = 192) and male breast cancer images (n = 245). Both targets were predicted in the internal (AUROC for ERα prediction: 0.86 ± 0.02, p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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