Abstract
Cervical cancer (CC) is among the most prevalent gynaecological malignancy. The rate of mortality and morbidity of patients with CC is high. Cellular senescence is involved in tumorigenesis as well as cancer progression. However, the involvement of cellular senescence in CC development is still unclear and requires further investigation. We retrieved data on cellular senescence-related genes (CSRGs) from the "CellAge" Database. We used TCGA-CESC and the CGCI-HTMCP-CC datasets as the training and validation sets, respectively. Eight CSRGs signatures based on the data extracted from these sets were constructed using "univariate" and "Least Absolute Shrinkage and Selection Operator Cox regression analyses". Using this model, we calculated the risk scores of all patients in the training and validation cohort and categorised these patients into the low-risk group (LR-G) and the high-risk group (HR-G). Finally, compared to patients in the HR-G, CC patients in the LR-G demonstrated a more positive clinical prognosis; the expression of senescence-associated secretory phenotype (SASP) markers and immune cell infiltration was higher, and these patients had more active immune responses. In vitro studies showed increased SERPINE1 and IL-1α ((genes included in the signature) expression in CC cells and tissues. The eight-gene prognostic signatures could modulate the expression of SASP factors and the tumour immune micro-environment (TIME). It could be used as a reliable biomarker for predicting the patient's prognosis and response to immunotherapy in CC.