Extensive prediction of drug response in mutation-subtype-specific LUAD with machine learning approach
KEGANG JIA,
YAWEI WANG,
QI CAO
et al.
Abstract:Background
Lung cancer is the most prevalent cancer diagnosis and the leading cause of cancer death worldwide. Therapeutic failure in lung cancer (LUAD) is heavily influenced by drug resistance. This challenge stems from the diverse cell populations within the tumor, each having unique genetic, epigenetic, and phenotypic profiles. Such variations lead to varied therapeutic responses, thereby contributing to tumor relapse and disease progression.
Methods
The Genomics of … Show more
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