Impact of Mitophagy-Related Genes on the Diagnosis and Development of Esophageal Squamous Cell Carcinoma via Single-Cell RNA-seq Analysis and Machine Learning Algorithms.

Abstract

As a treatment for esophageal squamous cell carcinoma (ESCC), which is common and fatal, mitophagy is a conserved cellular mechanism that selectively removes damaged mitochondria and is crucial for cellular homeostasis. While tumor development and resistance to anticancer therapies are related to ESCC, their role in ESCC remains unclear. Here, we investigated the relationship between mitophagy-related genes (MRGs) and ESCC to provide novel insights into the role of mitophagy in ESCC prognosis and diagnosis prediction. First, we identified MRGs from the GeneCards database and examined them at both the single-cell and transcriptome levels. Key genes were selected and a prognostic model was constructed using least absolute shrinkage and selection operator analysis. External validation was performed using the GSE53624 dataset and Kaplan-Meier survival analysis was performed to identify PYCARD as a gene significantly associated with survival in ESCC. We then examined the effect of PYCARD on ESCC cell proliferation and migration and identified 169 MRGs at the single-cell and transcriptome levels, as well as the high-risk groups associated with cancer-related pathways. Thirteen key genes were selected for model construction via multiple machine learning algorithms. PYCARD, which is upregulated in patients with ESCC, was negatively correlated with prognosis and its knockdown inhibited ESCC cell proliferation and migration. Our ESCC prediction model based on mitophagy-related genes demonstrated promising results and provides more options for the management and clinical treatment of ESCC patients. Moreover, targeting or regulating PYCARD levels might offer new therapeutic strategies for ESCC patients in clinical settings.