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Uncoupling protein 2 and signal transducer and activator of transcription 1 are targets of human papillomavirus oncoproteins and may be prognostic markers for cervical cancer development

Year: 2025
Type: article
Abstract: Introduction: Cervical cancer, predominantly caused by persistent high-risk Human Papillomavirus (HPV) infection, remains a significant public health issue in developing countries. Identifying prognostic markers for patients with precursor lesions could improve clinical management and outcomes. Methods: We performed a comparative gene expression analysis between low- and high-grade cervical intraepithelial lesions, focusing on genes associated with inflammation and oxidative stress. STAT1 (Signal Transducer and Activator of Transcription 1) and UCP2 (Uncoupling Protein 2), known for their roles in other cancers, were selected for further validation. Immunodetection techniques were applied in both monolayer and organotypic cultures to assess the regulation of these proteins by HPV oncoproteins. Additionally, immunohistochemistry was conducted on two patient groups: those with precursor lesions plus cancer, and those with cervical cancer only. Results: In cultured HaCaT cells transduced with E6/E7 HPV oncogenes, expression levels of STAT1 and UCP2 changed, especially in organotypic cultures. In patient samples, both UCP2 and STAT1 levels increased with the severity of cervical precursor lesions, and their expressions showed a strong correlation. Notably, nuclear STAT1 expression, indicative of protein activation, was rare in cancer samples but correlated with poor prognosis. In contrast, positive UCP2 expression was linked to improved survival rates and reduced recurrence. Discussion: Our findings demonstrate that HPV oncoproteins modulate the expression of UCP2 and STAT1. These proteins may serve as valuable prognostic markers for patients with precursor cervical lesions, and UCP2 expression, in particular, could be beneficial for predicting outcomes in cervical cancer patients.
Language: English
Subfield: Epidemiology
Field: Medicine
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W4416598877
FWCI:
Cites: 49
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