ArticleTranslational oncology2025
Ferroptosis and cellular senescence -Related Genes in Cervical Cancer: Mechanistic Insights from Multi-Omics and Clinical Sample Analysis.
Article in Translational oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Single-cell transcriptomics uncovers HPV-driven immune evasion and establishes a TAB2-based prognostic signature in cervical cancer.Translational oncology · 2026Article
- Reading the tumour at single-cell resolution: Original research in the Precision Therapeutics special issue.Translational oncology · 2026Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mortality and treatment failure in cervical cancer (CC) patients are primarily due to extensive metastasis and chemoresistance. Immunotherapy has emerged as a crucial clinical treatment strategy for CC patients; however, the current methods and biomarkers are inadequate for accurately predicting immunotherapy responses and patient prognosis. This study comprehensively analyzed ferroptosis and cellular senescence, two processes intricately linked to tumorigenesis, progression, and therapy, utilizing multi-omics data from TCGA-CESC, GEO cohorts, and clinical data from CC patients. Based on ferroptosis- and cellular senescence -related patterns, two distinct clusters with divergent prognoses and tumor microenvironment (TME) characteristics were identified. A prognostic model was subsequntly constructed, demonstrating robust reliability in predicting CC prognosis and response to immunotherapy. Patients in the low-risk group exhibited enriched immune cell infiltration, lower TIDE scores, higher IPS scores, and higher expression levels of immune checkpoint inhibitor-related genes, such as PDCD1 and CTLA4, which were associated with improved overall outcomes. Validation with clinical samples confirmed the differential expression of model-associated genes in CC, further supporting the model's accuracy. This prognostic model provides valuable insights into predicting CC prognosis and optimizing immunotherapy, offering potential benefits for personalized treatment strategies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.