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Mining bone metastasis related key genes of prostate cancer from the STING pathway based on machine learning
Guiqiang Li1,2, Runhan Zhao3, Zhou Xie3
1Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Frontiers in Medicine
|June 5, 2024
Summary
This study identifies key genes in the STING pathway involved in prostate cancer bone metastasis. RELA was found to inhibit cancer cell migration and is downregulated in bone metastasis, suggesting it as a therapeutic target.
Area of Science:
- Oncology
- Immunology
- Genetics
Background:
- Prostate cancer (PCa) is a leading male malignancy with high rates of bone metastasis.
- The STING pathway is crucial in cancer development, metastasis, and bone pain.
- Understanding STING's role in PCa bone metastasis offers new treatment avenues.
Purpose of the Study:
- Identify key STING-related genes (SRGs) predicting PCa bone metastasis.
- Investigate the function of identified genes in PCa progression and immunity.
- Develop a predictive model and identify potential drug targets for PCa bone metastasis.
Main Methods:
- Random forest algorithm to screen key SRGs.
- Comprehensive analysis of gene roles in PCa carcinogenesis, metastasis, and immunity.
- In vitro cell experiments and immunohistochemistry to validate RELA function and expression.
- Nomogram construction for predictive performance evaluation and drug target mining.
Main Results:
- Three key SRGs were identified with high predictive performance for bone metastasis.
- RELA overexpression inhibited PCa cell proliferation and migration.
- RELA showed significantly lower expression in bone metastatic tissues compared to primary tumors.
- The constructed nomogram demonstrated excellent predictive accuracy (AUC=0.99).
Conclusions:
- Identified key genes and mechanisms underlying PCa bone metastasis.
- RELA emerges as a potential therapeutic target for advanced PCa.
- Developed a novel diagnostic tool (nomogram) for PCa bone metastasis.
