ArticleAnalytical cellular pathology (Amsterdam)2023
Machine Learning Developed a Programmed Cell Death Signature for Predicting Prognosis, Ecosystem, and Drug Sensitivity in Ovarian Cancer.
Article in Analytical cellular pathology (Amsterdam), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 2 citations in OpenAlex.
- xNNPCD identifies regulators of programmed cell death by integrating perturbation transcriptomes with cancer dependency profiles.bioRxiv : the preprint server for biology · 2026Article
- Identification of Key Genes in Acute Liver Failure via Analysis of Programmed Cell Death Patterns.International journal of genomics · 2026Article
- The development and validation of a novel programmed cell death-related signature based on machine learning analysis of 15 programmed cell death patterns for predicting prognosis and therapeutic response in high-grade serous ovarian carcinoma.Translational cancer research · 2025Article
- Establishment of a Prognostic Model for Pancreatic Cancer Based on Hypoxia-Related Genes.Technology in cancer research & treatmentArticle
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Ovarian cancer (OC) is the leading cause of gynecological cancer death and the fifth most common cause of cancer-related death in women in America. Programmed cell death played a vital role in tumor progression and immunotherapy response in cancer. Methods: The prognostic cell death signature (CDS) was constructed with an integrative machine learning procedure, including 10 methods, using TCGA, GSE14764, GSE26193, GSE26712, GSE63885, and GSE140082 datasets. Several methods and single-cell analysis were used to explore the correlation between CDS and the ecosystem and therapy response of OC patients. Results: The prognostic CDS constructed by the combination of StepCox ( Conclusion: The current study constructed a novel CDS for OC, which could serve as an indicator for predicting the prognosis, ecosystem, and immunotherapy benefits of OC patients.
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