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Research Paper|Volume 13, Issue 4|pp 5461—5474

Identification of prognostic immune-related genes in rhabdoid tumor of kidney based on TARGET database analysis

Huimou Chen1,2, Suying Lu1,2, Jinqiu Guan1,2, Xiaoqin Zhu1,2, Feifei Sun1,2, Junting Huang1,2, Jia Zhu1,2, Juan Wang1,2, Zijun Zhen1,2, Yi Que1,2, Xiaofei Sun1,2, Yizhuo Zhang1,2
  • 1State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong 510060, P.R. China
  • 2Department of Pediatric Oncology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong 510060, P.R. China
* Equal contribution
Received: August 3, 2020Accepted: December 9, 2020Published: February 11, 2021
https://doi.org/10.18632/aging.202475

Copyright: © 2021 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Background: Malignant rhabdoid tumor of the kidney (RTK) is a rare and highly aggressive pediatric malignancy. Immune system dysfunction is significantly correlated with tumor initiation and progression.

Methods: We integrated and analyzed the expression profiles of immune-related genes (IRGs) in 65 RTK patients based on the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Prognostic related IRGs in RTK patients were analyzed using univariate and multivariate analysis, based on which a prognostic model with IRGs was constructed. Correlation analysis between the risk score of our model and tumor-infiltrating cell were also investigated.

Results: Twenty two IRGs were significantly associated with the clinical outcomes of RTK patients. Gene ontology (GO) analysis revealed that inflammatory pathways were most frequently implicated in RTK. A prognostic model was constructed using 7 IRGs (MMP9, SERPINA3, FAM19A5, CCR9, PLAUR, IL1R2, PRKCG), which were independent prognostic indices that could differentiate patients based on their survival outcomes. Furthermore, the risk scores from our prognostic model was positively associated with cancer-associated fibroblasts (CAFs).

Conclusions: We screened seven IRGs of clinical significance to distinguish patients with different survival outcomes. This may enhance our understanding of the immune microenvironment of RTK, and could use to design individualized treatments for RTK patients.

Background: Malignant rhabdoid tumor of the kidney (RTK) is a rare and highly aggressive pediatric malignancy. Immune system dysfunction is significantly correlated with tumor initiation and progression.

Methods: We integrated and analyzed the expression profiles of immune-related genes (IRGs) in 65 RTK patients based on the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Prognostic related IRGs in RTK patients were analyzed using univariate and multivariate analysis, based on which a prognostic model with IRGs was constructed. Correlation analysis between the risk score of our model and tumor-infiltrating cell were also investigated.

Results: Twenty two IRGs were significantly associated with the clinical outcomes of RTK patients. Gene ontology (GO) analysis revealed that inflammatory pathways were most frequently implicated in RTK. A prognostic model was constructed using 7 IRGs (MMP9, SERPINA3, FAM19A5, CCR9, PLAUR, IL1R2, PRKCG), which were independent prognostic indices that could differentiate patients based on their survival outcomes. Furthermore, the risk scores from our prognostic model was positively associated with cancer-associated fibroblasts (CAFs).

Conclusions: We screened seven IRGs of clinical significance to distinguish patients with different survival outcomes. This may enhance our understanding of the immune microenvironment of RTK and could use to design individualized treatments for RTK patients.