ArticleTranslational cancer research2026
A three-gene radioresistance signature predicts tumor progression in cervical cancer.
Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: As a primary curative treatment for locally advanced cervical cancer, radiotherapy is frequently undermined by radioresistant tumor cells that evade cell death and subsequently drive post-treatment tumor progression. This study aimed to identify candidate genes associated with radioresistance in cervical cancer and to explore their potential in predicting unfavorable outcomes among radioresistant patients, thereby providing a reference for future research. Methods: We screened for co-expressed genes using transcriptomic data from radiation non-complete response (NCR) cervical cancer patients in Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Cox regression analyses were conducted to identify the most significant radioresistance-associated genes for constructing a prognostic model. The predictive performance of this model was further validated through logistic regression, weighted gene co-expression network analysis (WGCNA), and pan-cancer analyses. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) was performed to quantify the expression levels of key genes in cervical cancer tissue samples from radiosensitive and radioresistant patients. Results: The resulting prognostic model comprised three genes: Conclusions: Our findings indicate that
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