The role of immunogenic cell death in the prognosis and development of treatment strategies for non-small cell lung cancer: a multiomics and machine learning approach for predictive and personalized treatment.

ABSTRACT:

Background

Non-small cell lung cancer (NSCLC) is the predominant histological subtype of lung cancer, whose diverse genomic landscape complicates prognosis and outcome prediction. In this context, immunogenic cell death (ICD), a distinct mechanism of cell death, may exert important antitumor effects. However, the specific role of ICD in NSCLC has not been clarified, and there is no suitable method for using ICD to achieve the treatment and prognosis assessment of NSCLC. The purpose of the current research is to develop a new approach to predict the survival prognosis and response to chemotherapy and targeted therapy in patients with NSCLC.

Methods

We used 101 combinations of 10 machine learning algorithms to construct an ICD-related signature (ICDRS). The predictive potentia

SUBMITTER: Sun Y 

PROVIDER: S-EPMC12432684 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature