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Comparing Metastatic Clear Cell Renal Cell Carcinoma Model Established in Mouse Kidney and on Chicken Chorioallantoic Membrane
Published on: February 8, 2020
Angiogenesis Pathway in Kidney Renal Clear Cell Carcinoma and Its Prognostic Value for Cancer Risk Prediction
Xiangyu Che1, Wenyan Su2, Xiaowei Li1
1Department of Urology, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
Abstract:
Angiogenesis, a process highly regulated by pro-angiogenic and anti-angiogenic factors, is disrupted and dysregulated in cancer. Despite the increased clinical use of angiogenesis inhibitors in cancer therapy, most molecularly targeted drugs have been less effective than expected. Therefore, an in-depth exploration of the angiogenesis pathway is warranted. In this study, the expression of angiogenesis-related genes in various cancers was explored using The Cancer Genome Atlas datasets, whereupon it was found that most of them were protective genes in the patients with kidney renal clear cell carcinoma (KIRC). We divided the samples from the KIRC dataset into three clusters according to the mRNA expression levels of these genes, with the enrichment scores being in the order of Cluster 2 (upregulated expression) > Cluster 3 (normal expression) > Cluster 1 (downregulated expression). The survival curves plotted for the three clusters revealed that the patients in Cluster 2 had the highest overall survival rates. Via a sensitivity analysis of the drugs listed on the Genomics of Drug Sensitivity in Cancer database, we generated IC50 estimates for 12 commonly used molecularly targeted drugs for KIRC in the three clusters, which can provide a more personalized treatment plan for the patients according to angiogenesis-related gene expression. Subsequently, we investigated the correlation between the angiogenesis pathway and classical cancer-related genes as well as that between the angiogenesis score and immune cell infiltration. Finally, we used the least absolute shrinkage and selection operator (LASSO)-Cox regression analysis to construct a risk score model for predicting the survival of patients with KIRC. According to the areas under the receiver operating characteristic (ROC) curves, this new survival model based on the angiogenesis-related genes had high prognostic prediction value. Our results should provide new avenues for the clinical diagnosis and treatment of patients with KIRC.
Insights
Investigating angiogenesis-related genes in kidney renal clear cell carcinoma (KIRC) revealed protective roles and identified patient clusters with distinct survival outcomes. This work supports personalized KIRC treatment strategies based on gene expression.
Area of Science:
- Oncology
- Molecular Biology
- Genomics
Background:
- Angiogenesis is crucial in cancer, but its dysregulation and the efficacy of inhibitors remain challenging.
- Understanding the role of angiogenesis-related genes is vital for improving targeted cancer therapies.
- Kidney renal clear cell carcinoma (KIRC) presents a significant need for novel therapeutic strategies.
Purpose of the Study:
- To explore the expression patterns of angiogenesis-related genes in KIRC using The Cancer Genome Atlas (TCGA) datasets.
- To correlate gene expression clusters with patient survival and drug sensitivity.
- To develop a prognostic model for KIRC survival prediction based on angiogenesis pathways.
Main Methods:
- Analysis of TCGA datasets to identify angiogenesis-related gene expression in KIRC.
- Clustering of KIRC samples based on mRNA expression levels.
- Drug sensitivity analysis using the Genomics of Drug Sensitivity in Cancer (GDSC) database.
- Correlation analysis with cancer-related genes and immune cell infiltration.
- Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression for prognostic model construction.
Main Results:
- Most angiogenesis-related genes were found to be protective in KIRC patients.
- Three distinct patient clusters were identified, with Cluster 2 (upregulated expression) showing the highest overall survival.
- IC50 estimates for 12 targeted drugs varied across clusters, suggesting personalized treatment potential.
- A novel risk score model based on angiogenesis-related genes demonstrated high prognostic value (ROC analysis).
Conclusions:
- Angiogenesis-related genes play a protective role in KIRC and can stratify patients by survival.
- Gene expression profiling offers a pathway to personalized drug selection for KIRC.
- The developed risk score model provides a valuable tool for predicting KIRC patient survival.
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