Identification of key gene signatures for predicting chemo-immunotherapy efficacy in extensive-stage small-cell lung cancer using machine learning.
Journal:
Lung cancer (Amsterdam, Netherlands)
PMID:
39787635
Abstract
OBJECTIVES: The lack of definitive biomarkers presents a significant challenge for chemo-immunotherapy in extensive-stage small-cell lung cancer (ES-SCLC). We aimed to identify key genes associated with chemo-immunotherapy efficacy in ES-SCLC through comprehensive gene expression analysis using machine learning (ML).
Authors
Keywords
Aged
Antineoplastic Combined Chemotherapy Protocols
Biomarkers, Tumor
Female
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Humans
Immunotherapy
Lung Neoplasms
Machine Learning
Male
Middle Aged
Neoplasm Staging
Prognosis
Prospective Studies
Small Cell Lung Carcinoma
Transcriptome
Treatment Outcome