Back to search

Article

Spatial biomarker-driven deep learning model via digital pathology predicts response to PI3K inhibitor buparlisib in head and neck squamous cell carcinoma

2025-10-10

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Purpose</h4> Buparlisib, a pan-class I PI3K inhibitor, combined with paclitaxel, demonstrated improved survival in the BERIL-1 trial for patients with recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC). However, predictive biomarkers of benefit remain undefined. We evaluated spatial biomarkers derived from hematoxylin and eosin (H&E) images using artificial intelligenc...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
7f8b1a92-94ef-57c9-aace-e516225bae58
DOI
10.1101/2025.10.09.25337502
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Spatial biomarker-driven deep learning model via digital pathology predicts response to PI3K inhibitor buparlisib in head and neck squamous cell carcinomaDOI 10.1101/2025.10.09.25337502
Select a neighboring publication to make it the new centre.