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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
Construction and Validation of a Novel Immune Checkpoint-Related Model in Clear Cell Renal Cell Carcinoma
ZhiXiang Fan1, XinXin Sun1, Kun Li2
1The Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Zhengzhou University, Henan, Zhengzhou 450014, China.
Background:
With the highest mortality and metastasis rate, kidney renal clear cell carcinoma (KIRC) is one of the most common urological malignant tumors and not sensitive to chemotherapy and radiotherapy. Immunotherapy, which proves to be effective and a big progression, such as PD-1/PD-L1 inhibitors, is not sensitive to all KIRC patients. To predict prognosis and immunotherapy response, a novel immune checkpoint gene- (ICG-) related model is essential in clinics.
Methods:
From the public database-downloaded dataset, a novel ICG-related model for predicting prognosis and immunotherapy response in KIRC patients was built up and verified with R packages and Cox regression analysis. The Kaplan-Meier curve was plotted.
Results:
39 ICGs were identified to have different expression in KIRC patients and enriched in immune-related biological pathways and activities. Three ICGs (CTLA4, TNFSF14, and HHLA2) were screened to generate KIRC-ICG model. The KIRC-ICG model was verified to be effective. With conducting KIRC-SYS model, KIRC-ICGscore was verified to be an independent factor regardless of age, gender, stage, grade, and TNM stage. Compared to the ICG-low subgroup, the ICG-high subgroup had more immune activities. KIRC-ICGscore was significantly positively correlated with the expression of Treg markers. KIRC-ICG model could also be reliable to predict immunotherapy response.
Conclusion:
The KIRC-ICG model was reliable to predict prognosis and immunotherapy response for KIRC patients and could be an independent factor regardless of clinical characteristics.
Insights
A new model using immune checkpoint genes (ICGs) can predict prognosis and immunotherapy response in kidney renal clear cell carcinoma (KIRC) patients. This KIRC-ICG model is an independent factor, improving clinical decision-making.
Area of Science:
- Oncology
- Immunology
- Genetics
Background:
- Kidney renal clear cell carcinoma (KIRC) has high mortality and metastasis rates, with limited sensitivity to traditional therapies.
- Immunotherapy, including PD-1/PD-L1 inhibitors, shows promise but is not universally effective for KIRC patients.
- Predictive models for prognosis and immunotherapy response are crucial for personalized KIRC treatment.
Purpose of the Study:
- To develop and validate a novel immune checkpoint gene (ICG)-related model for predicting prognosis in KIRC.
- To assess the model's ability to predict immunotherapy response in KIRC patients.
- To determine if the model serves as an independent prognostic factor.
Main Methods:
- Utilized a public database to identify differentially expressed ICGs in KIRC.
- Employed R packages and Cox regression analysis to build and validate the KIRC-ICG model.
- Analyzed ICG expression, immune activities, and correlation with Treg markers.
Main Results:
- Identified 39 differentially expressed ICGs, enriched in immune pathways.
- Developed a KIRC-ICG model using CTLA4, TNFSF14, and HHLA2, which proved effective.
- The KIRC-ICG score was an independent prognostic factor and correlated with immune activity and Treg markers, predicting immunotherapy response.
Conclusions:
- The KIRC-ICG model reliably predicts prognosis and immunotherapy response in KIRC patients.
- The model is an independent prognostic factor, irrespective of clinical characteristics.
- This ICG-based model offers a valuable tool for clinical decision-making in KIRC management.
