Multi‑omics Identification of a Novel Signature for Serous Ovarian Carcinoma in the Context of 3P Medicine and Based on Twelve Programmed Cell Death Patterns: a Multi-cohort Machine Learning Study

Overview

Journal Mol Med

Publisher Biomed Central

Specialties General Medicine
Molecular Biology

Date 2025 Jan 8

PMID 39773329

Authors

Lele Ye

Chunhao Long

Binbing Xu

Xuyang Yao

Jiaye Yu

Yunhui Luo

Yuan Xu

Zhuofeng Jiang

Zekai Nian

Yawen Zheng

Yaoyao Cai

Xiangyang Xue

Gangqiang Guo

Affiliations

Soon will be listed here.

Abstract

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.

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