Content area
Background
Predictive, preventive, and personalized medicine (PPPM/3PM) is a strategy aimed at improving the prognosis of cancer, and programmed cell death (PCD) is increasingly recognized as a potential target in cancer therapy and prognosis. However, a PCD-based predictive model for serous ovarian carcinoma (SOC) is lacking. In the present study, we aimed to establish a cell death index (CDI)–based model using PCD-related genes.
Methods
We included 1254 genes from 12 PCD patterns in our analysis. Differentially expressed genes (DEGs) from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) were screened. Subsequently, 14 PCD-related genes were included in the PCD-gene-based CDI model. Genomics, single-cell transcriptomes, bulk transcriptomes, spatial transcriptomes, and clinical information from TCGA-OV, GSE26193, GSE63885, and GSE140082 were collected and analyzed to verify the prediction model.
Results
The CDI was recognized as an independent prognostic risk factor for patients with SOC. Patients with SOC and a high CDI had lower survival rates and poorer prognoses than those with a low CDI. Specific clinical parameters and the CDI were combined to establish a nomogram that accurately assessed patient survival. We used the PCD-genes model to observe differences between high and low CDI groups. The results showed that patients with SOC and a high CDI showed immunosuppression and hardly benefited from immunotherapy; therefore, trametinib_1372 and BMS-754807 may be potential therapeutic agents for these patients.
Conclusions
The CDI-based model, which was established using 14 PCD-related genes, accurately predicted the tumor microenvironment, immunotherapy response, and drug sensitivity of patients with SOC. Thus this model may help improve the diagnostic and therapeutic efficacy of PPPM.
Details
; Long, Chunhao 2 ; Xu, Binbing 3 ; Yao, Xuyang 3 ; Yu, Jiaye 4 ; Luo, Yunhui 4 ; Xu, Yuan 4 ; Jiang, Zhuofeng 2 ; Nian, Zekai 5 ; Zheng, Yawen 6 ; Cai, Yaoyao 7 ; Xue, Xiangyang 4
; Guo, Gangqiang 8
1 The First Affiliated Hospital, Wenzhou Medical University, Department of Gynecology, Wenzhou, China (GRID:grid.268099.c) (ISNI:0000 0001 0348 3990)
2 Southern University of Science and Technology, School of Medicine, Shenzhen, China (GRID:grid.263817.9) (ISNI:0000 0004 1773 1790)
3 Wenzhou Medical University, First Clinical College, Wenzhou, China (GRID:grid.268099.c) (ISNI:0000 0001 0348 3990)
4 Wenzhou Medical University, Wenzhou Collaborative Innovation Center of Gastrointestinal Cancer in Basic Research and Precision Medicine, Wenzhou Key Laboratory of Cancer-Related Pathogens and Immunity, Department of Microbiology and Immunology, Institute of Molecular Virology and Immunology, Institute of Tropical Medicine, School of Basic Medical Sciences, Wenzhou, China (GRID:grid.268099.c) (ISNI:0000 0001 0348 3990)
5 Second Clinical College, Wenzhou Medical University, Wenzhou, China (GRID:grid.268099.c) (ISNI:0000 0001 0348 3990)
6 Zhejiang University School of Medicine, Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education) of the Second Affiliated Hospital and Institute of Translational Medicine, Hangzhou, China (GRID:grid.13402.34) (ISNI:0000 0004 1759 700X)
7 The First Affiliated Hospital, Wenzhou Medical University, Department of Obstetrics, Wenzhou, China (GRID:grid.268099.c) (ISNI:0000 0001 0348 3990)
8 The First Affiliated Hospital, Wenzhou Medical University, Department of Gynecology, Wenzhou, China (GRID:grid.268099.c) (ISNI:0000 0001 0348 3990); Wenzhou Medical University, Wenzhou Collaborative Innovation Center of Gastrointestinal Cancer in Basic Research and Precision Medicine, Wenzhou Key Laboratory of Cancer-Related Pathogens and Immunity, Department of Microbiology and Immunology, Institute of Molecular Virology and Immunology, Institute of Tropical Medicine, School of Basic Medical Sciences, Wenzhou, China (GRID:grid.268099.c) (ISNI:0000 0001 0348 3990)