Automated Prognosis Marker Assessment in Breast Cancers Using BLEACH&STAIN Multiplexed Immunohistochemistry.
artificial intelligence
breast cancer
multiplex fluorescence immunohistochemistry
prognosis markers
Journal
Biomedicines
ISSN: 2227-9059
Titre abrégé: Biomedicines
Pays: Switzerland
ID NLM: 101691304
Informations de publication
Date de publication:
29 Nov 2023
29 Nov 2023
Historique:
received:
22
10
2023
revised:
12
11
2023
accepted:
18
11
2023
medline:
23
12
2023
pubmed:
23
12
2023
entrez:
23
12
2023
Statut:
epublish
Résumé
Prognostic markers in routine clinical management of breast cancer are often assessed using RNA-based multi-gene panels that depend on fluctuating tumor purity. Multiplex fluorescence immunohistochemistry (mfIHC) holds the potential for an improved risk assessment. To enable automated prognosis marker detection (i.e., progesterone receptor [PR], estrogen receptor [ER], androgen receptor [AR], GATA3, TROP2, HER2, PD-L1, Ki67, TOP2A), a framework for automated breast cancer identification was developed and validated involving thirteen different artificial intelligence analysis steps and an algorithm for cell distance analysis using 11+1-marker-BLEACH&STAIN-mfIHC staining in 1404 invasive breast cancers of no special type (NST). The framework for automated breast cancer detection discriminated normal glands from malignant glands with an accuracy of 98.4%. This approach identified that five (PR, ER, AR, GATA3, PD-L1) of nine biomarkers were associated with prolonged overall survival (
Identifiants
pubmed: 38137396
pii: biomedicines11123175
doi: 10.3390/biomedicines11123175
pii:
doi:
Types de publication
Journal Article
Langues
eng