Deep learning based analysis of G3BP1 protein expression to predict the prognosis of nasopharyngeal carcinoma.

ABSTRACT:

Background

Ras-GTPase-activating protein (GAP)-binding protein 1 (G3BP1) emerges as a pivotal oncogenic gene across various malignancies, notably including nasopharyngeal carcinoma (NPC). The use of automated image analysis tools for immunohistochemical (IHC) staining of particular proteins is highly beneficial, as it could reduce the burden on pathologists. Interestingly, there have been no prior studies that have examined G3BP1 IHC staining using digital pathology.

Methods

Whole-slide images (WSIs) were meticulously collected and annotated by experienced pathologists. A model was intricately designed and rigorously tested to yield the quantitative data regarding staining intensity and extent. The collective output data was subjected multiplicative analysis, exploring its c

SUBMITTER: Zhou L 

PROVIDER: S-EPMC11771904 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature