Abstract
Ovarian cancer (OC) is a highly malignant gynaecological tumour that has a very poor prognosis. Pyroptosis has been demonstrated in recent years to be an inflammatory form of programmed cell death. However, the expression of pyroptosis-related genes in OC and their correlations with prognosis remain unclear. In this study, we identified 31 pyroptosis regulators that were differentially expressed between OC and normal ovarian tissues. Based on these differentially expressed genes (DEGs), all OC cases could be divided into two subtypes. The prognostic value of each pyroptosis-related gene for survival was evaluated to construct a multigene signature using The Cancer Genome Atlas (TCGA) cohort. By applying the least absolute shrinkage and selection operator (LASSO) Cox regression method, a 7-gene signature was built and classified all OC patients in the TCGA cohort into a low- or high-risk group. OC patients in the low-risk group showed significantly higher survival possibilities than those in the high-risk group (P < 0.001). Utilizing the median risk score from the TCGA cohort, OC patients from a Gene Expression Omnibus (GEO) cohort were divided into two risk subgroups, and the low-risk group had increased overall survival (OS) time (P = 0.014). Combined with the clinical characteristics, the risk score was found to be an independent factor for predicting the OS of OC patients. Gene ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) analyses indicated that immune-related genes were enriched and that the immune status was decreased in the high-risk group. In conclusion, pyroptosis-related genes play important roles in tumour immunity and can be used to predict the prognosis of OCs.
Highlights
Ovarian cancer (OC) is a common malignancy of the female reproductive system, second only to cervical cancer and uterine corpus cancer in terms of incidence
Identification of DEGs between normal and tumour tissues The 33 pyroptosis-related gene expression levels were compared in the pooled Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) data from 88 normal and 379 tumour tissues, and we identified 31 differentially expressed genes (DEGs)
The two clusters produced by the consensus clustering analysis based on the DEGs did not show any significant differences in clinical characteristics
Summary
Ovarian cancer (OC) is a common malignancy of the female reproductive system, second only to cervical cancer and uterine corpus cancer in terms of incidence. OC has extremely high recurrence and mortality rates, which seriously threaten women’s health. In the United States, ~22,530 new OC cases were diagnosed, and OC caused 13,980 deaths in 20191. Due to the lack of effective screening tools and difficulties in early diagnosis, 80% of OC patients are already at an advanced stage when diagnosed, and 50–70% of patients will experience recurrence within 2 years after treatment, with a poor 5-year survival rate of 30%2,3. The current main treatments for OC are surgery and platinum-based chemotherapies. Despite recent improvements in treatments, the 5-year survival rate has been slow to improve[4]. Considering the limitations of OC treatments, new therapeutic targets are needed to improve the clinical outcome of OC; reliable novel prognostic models are urgently required to make targeted therapies more feasible
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