Machine learning explores the prognostic and immuno-oncological impact of mitochondrial unfolded protein response in CESC
Abstract Background Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) pose significant global health challenges. While the mitochondrial unfolded protein response (UPRmt) is known to influence cancer biology, its specific role in CESC remains unclear. Methods We employed machin...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-05-01
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| Series: | Discover Oncology |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s12672-025-02723-9 |
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| Summary: | Abstract Background Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) pose significant global health challenges. While the mitochondrial unfolded protein response (UPRmt) is known to influence cancer biology, its specific role in CESC remains unclear. Methods We employed machine learning to analyze UPRmt 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 UPRmt 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 UPRmt’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 UPRmt’s role in CESC provide new directions for developing personalized treatment strategies. |
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| ISSN: | 2730-6011 |