ArticleHeliyon2024
Identification of molecular subtypes, prognostic status and immunotherapy response in cervical cancer based on angiogenic signature genes.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Lymphangiogenesis-related gene signature-based risk model for prognostic assessment of cervical cancer: immune-metabolic characterization and molecular subtype analysis.Frontiers in genetics · 2026Article
- Immunogenic cell death genes in single-cell and transcriptome analyses perspectives from a prognostic model of cervical cancer.Frontiers in genetics · 2025Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Cervical cancer, as one of the most common malignancies in women, is closely related to the mechanism of angiogenesis, which needs further exploration. Methods: The squamous cell carcinoma of the cervix and cervical adenocarcinoma (CESC) data from The Cancer Genome Atlas (TCGA) database. CESC subtypes based on 48 angiogenesis-related genes were identified using consistent cluster analysis, and the limma package were adopted to screen the differentially expressed genes (DEGs) associated with prognosis. Further compress the DEGs through univariate and Least Absolute Shrinkage and Selection Operator (LASSO) COX analysis to identify the key genes. Calculate immune scores using the GSVA package and predict immunotherapy response with TIDE. For Results: 3 CESC subtypes were identified, with the best survival advantage in the C2 subtype and the worst in C1 subtype. A risk model was established utilizing seven key genes (MMP3, DLL4, CAP2, PDIA6, TCN2, PAPSS2, and VCAM1), showcases an Area Under the Curve (AUC) exceeding 0.7, underlining its robust performance. The risk score model showed a trend of poorer survival for patients in the high-risk score group and good agreement across different datasets. A nomogram was constructed, and calibration curves indicated robust predictive performance. Immunological analysis revealed heightened sensitivity to immunotherapy in the low-risk group. Besides, the elevated expressions of all 7 genes were seen in Hela cells, and the specific target-mediated DLL4 knockdown diminished the migration and invasion of Hela cells Conclusion: This research provides fresh insights and a valuable tool to guide therapeutic decision-making for CESC.
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