Comprehensive analysis of mitophagy-related genes in NSCLC diagnosis and immune scenery: based on bulk and single-cell RNA sequencing data

Abstract

Lung cancer is the main cause of cancer-related deaths, and non-small cell lung cancer (NSCLC) is the most common type. Understanding the potential mechanisms, prognosis, and treatment aspects of NSCLC is essential. This study systematically analyzed the correlation between mitophagy and NSCLC. Six mitophagy-related feature genes (SRC, UBB, PINK1, FUNDC1, MAP1LC3B, and CSNK2A1) were selected through machine learning and used to construct a diagnostic model for NSCLC. These feature genes are closely associated with the occurrence and development of NSCLC. Additionally, NSCLC was divided into two subtypes using unsupervised consensus clustering, and their differences in clinical characteristics, immune infiltration, and immunotherapy were systematically analyzed. Furthermore, the interaction between mitophagy-related genes (MRGs) and immune cells was analyzed using single-cell sequencing data. The findings of this study will contribute to the development of potential diagnostic biomarkers for NSCLC and the advancement of personalized treatment strategies.