Background
Cervical cancer, as one of the most common malignancies in women, is closely related to the mechanism of angiogenesis, which needs further exploration.
Conclusion
This research provides fresh insights and a valuable tool to guide therapeutic decision-making for CESC.
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 in vitro analysis, the expressions of these key genes were additionally tested via reverse-transcription quantitative PCR, and the migration and invasion of Hela cells were determined in scratch and transwell assays, respectively.
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 in vitro.