AUTHOR=Liu Chen , Zhang Xuhui , Hu Caoyang , Liang Xuezhi , Cao Xiaoming , Wang Dongwen 

TITLE=Systematic Construction and Validation of a Novel Macrophage Differentiation–Associated Prognostic Model for Clear Cell Renal Cell Carcinoma

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.877656

DOI=10.3389/fgene.2022.877656

ISSN=1664-8021

ABSTRACT=Background: Clear cell renal cell carcinoma (ccRCC) is a malignant tumor of the human urinary system. Macrophage differentiation is associated with tumorigenesis. Therefore, exploring the prognostic value of macrophage differentiation-associated genes (MDGs) may contribute to better clinical management of ccRCC patients. 
Methods: The RNA sequence data of ccRCC was obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed of MDGs were unveiled in ccRCC and normal samples. The prognostic model was established according to the univariate and multivariate Cox regression analyses. By combining clinic- pathological features and prognostic genes, a nomogram was established to predict individual survival probability. The Tumor Immune Estimation Resource (TIMER) database was utilized to analyze the correlation between prognostic genes and immune infiltrating cells. Eventually, the mRNA and protein expression levels of prognostic genes were verified.
Results: A total of 52 differentially expressed prognosis-related MDGs were identified in ccRCC. After, a six-gene prognostic model (ABCG1, KDF1, KITLG, TGFA, HAVCR2, CD14) was constructed through Cox analysis. The overall survival in the high-risk group was relatively poor. Moreover, riskscore was identified as an independent prognostic factor. We constructed a prognostic nomogram with well fitted calibration curve based on risk score and clinical data. Furthermore, the prognostic genes were significantly related to the level of immune cells infiltration including B cells, CD8+T cells, CD4+T cells, macrophages, neutrophils, and dendritic cells. Finally, the mRNA expression of prognostic genes in clinical ccRCC tissues showed the ABCG1, HAVCR2, CD14 and TGFA mRNA in tumor samples were increased compared with the adjacent control tissue samples, while KDF1 and KITLG were decreased, which was consistent with the verification results in the GSE53757.
Conclusion: In conclusion, this study identified and validated a macrophage differentiation-associated prognostic model for ccRCC that could be employed to predict the outcomes of the ccRCC patients.