Prognostic Model for Ovarian Cancer Based on Lysosome-Related Genes
Author Information
Author(s): Sun Ran, Li Siyi, Ye Wanlu, Lu Yanming
Primary Institution: Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
Hypothesis
Can lysosome-related genes serve as effective prognostic markers for ovarian cancer?
Conclusion
A 10-gene prognostic model linked to the tumor microenvironment was developed, providing insights for personalized treatment strategies in ovarian cancer.
Supporting Evidence
- A 10-gene prognostic risk signature was established and validated across multiple cohorts.
- The high-risk and low-risk groups showed significant differences in immune infiltration patterns and drug sensitivity.
- Survival analysis confirmed the predictive accuracy of the model.
Takeaway
Researchers created a new way to predict how ovarian cancer will progress by looking at specific genes related to lysosomes, which are important for cell health.
Methodology
The study involved differential expression analysis, multiple regression analyses, and survival analysis using gene expression profiles from ovarian cancer patients.
Limitations
The study is retrospective and relies on publicly available databases, necessitating further validation through prospective multicenter studies.
Participant Demographics
The study included 367 ovarian cancer patients from the TCGA cohort.
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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