Artificial neural network systems to predict the response to sintilimab in squamous-cell non-small-cell lung cancer based on data of ORIENT-3 study.

ABSTRACT:

Background

Existing biomarkers and models for predicting response to programmed cell death protein 1 monoclonal antibody in advanced squamous-cell non-small cell lung cancer (sqNSCLC) did not have enough accuracy. We used data from the ORIENT-3 study to construct artificial neural network (ANN) systems to predict the response to sintilimab for sqNSCLC.

Methods

Four ANN systems based on bulk RNA data to predict disease control (DC), immune DC (iDC), objective response (OR) and immune OR (iOR) were constructed and tested for patients with sqNSCLC treated with sintilimab. The mechanism exploration on the bulk and the spatial level were performed in patients from the ORIENT-3 study and the real world, respectively.

Findings

sqNSCLC patients with different responses to sin

SUBMITTER: Xie T 

PROVIDER: S-EPMC11663205 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature