Abstract
BACKGROUND: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) pose significant global health challenges. While the mitochondrial unfolded protein response (UPR(mt)) is known to influence cancer biology, its specific role in CESC remains unclear. METHODS: We employed machine learning to analyze UPR(mt) genes in CESC using TCGA multi-omics data. Our comprehensive analysis included genetic alterations, prognostic significance, tumor-immune interactions, single-cell transcriptomics, pathway enrichment, and drug sensitivity assessments. RESULTS: ATF5 emerged as the most significant prognostic factor among UPR(mt) genes, with high expression correlating with better overall survival. High ATF5 expression was associated with an immunologically active tumor microenvironment, characterized by enhanced immune cell infiltration, increased immune checkpoint expression, and higher tumor mutational burden. Single-cell RNA sequencing revealed ATF5's distinct expression patterns in stromal cells, particularly in endometrial stromal and smooth muscle cells. Gene set enrichment analysis provided mechanistic insight, revealing ATF5's connection to the immune response via the regulation of P-stalk ribosome functions, a finding that underscores a novel aspect of UPR(mt)'s role in shaping the tumor immune landscape. Drug sensitivity analysis showed that low ATF5 expression correlated with resistance to conventional chemotherapeutics (cisplatin, paclitaxel, and etoposide) but increased sensitivity to imatinib, potentially through EP300-dependent mechanisms. CONCLUSIONS: Our findings establish ATF5 as both a favorable prognostic marker and a key immune response regulator in CESC. Its influence on the tumor microenvironment and treatment response suggests potential therapeutic applications. These insights into UPR(mt)'s role in CESC provide new directions for developing personalized treatment strategies.