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A Syngeneic Mouse Model of Metastatic Renal Cell Carcinoma for Quantitative and Longitudinal Assessment of Preclinical Therapies
Published on: April 12, 2017
A Novel KIF4A-related Model for Predicting Immunotherapy Response and Prognosis in Kidney Renal Clear Cell Carcinoma
Guang Hua Yang1,2, Xu Dong Ma3, Xi Feng Wei4
1Department of Urology, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, People's Republic of China.
Background:
The efficacy of chemotherapy in treating Kidney Renal Clear Cell Carcinoma (KIRC) is limited, whereas immunotherapy has shown some promising clinical outcomes. In this context, KIF4A is considered a potential therapeutic target for various cancers. Therefore, identifying the mechanism of KIF4A that can predict the prognosis and immunotherapy response of KIRC would be of significant importance.
Methods:
Based on the TCGA Pan-Cancer dataset, the prognostic significance of the KIF4A expression across 33 cancer types was analyzed by univariate Cox algorithm. Furthermore, overlapping differentially expressed genes (DEGs1) between the KIF4A high- and lowexpression groups and DEGs2 between the KIRC and normal groups were also analyzed. Machine learning and Cox regression algorithms were performed to obtain biomarkers and construct a prognostic model. Finally, the role of KIF4A in KIRC was analyzed using quantitative real-time PCR, transwell assay, and EdU experiment.
Results:
Our analysis revealed that KIF4A was significant for the prognosis of 13 cancer types. The highest correlation with KIF4A was found for KICH among the tumour mutation burden (TMB) indicators. Subsequently, a prognostic model developed with UBE2C, OTX1, PPP2R2C, and RFLNA was obtained and verified with the Renal Cell Cancer-EU/FR dataset. There was a positive correlation between risk score and immunotherapy. Furthermore, the experiment results indicated that KIF4A expression was considerably increased in the KIRC group. Besides, the proliferation, migration, and invasion abilities of KIRC tumor cells were significantly weakened after KIF4A was knocked out.
Conclusion:
We identified four KIF4A-related biomarkers that hold potential for prognostic assessment in KIRC. Specifically, early implementation of immunotherapy targeting these biomarkers may yield improved outcomes for patients with KIRC.
Insights
This study identifies KIF4A as a prognostic biomarker for Kidney Renal Clear Cell Carcinoma (KIRC). Targeting KIF4A and its related biomarkers may improve immunotherapy response and patient outcomes in KIRC.
Area of Science:
- Oncology
- Genetics
- Immunotherapy
Background:
- Chemotherapy for Kidney Renal Clear Cell Carcinoma (KIRC) has limited efficacy.
- Immunotherapy shows promise for KIRC treatment.
- KIF4A is a potential therapeutic target in cancer.
Purpose of the Study:
- To investigate the prognostic significance of KIF4A in KIRC.
- To identify KIF4A-related biomarkers for predicting prognosis and immunotherapy response in KIRC.
Main Methods:
- Analysis of TCGA Pan-Cancer dataset for KIF4A prognostic significance.
- Differential gene expression analysis between high/low KIF4A groups and KIRC/normal groups.
- Machine learning and Cox regression to build a prognostic model.
- Experimental validation of KIF4A's role in KIRC using qPCR, transwell, and EdU assays.
Main Results:
- KIF4A expression is significant for prognosis in 13 cancer types.
- A prognostic model comprising UBE2C, OTX1, PPP2R2C, and RFLNA was developed and validated.
- Higher risk scores correlated positively with immunotherapy response.
- KIF4A expression was elevated in KIRC, and its knockout reduced tumor cell proliferation, migration, and invasion.
Conclusions:
- Four KIF4A-related biomarkers were identified for KIRC prognostic assessment.
- Targeting these biomarkers with immunotherapy could enhance patient outcomes in KIRC.
