In order to develop possible medications for patients with high-risk ccRCC, the “pRRophetic” package is employed. In addition, the enrichment scores of 28 immune cells in the tumor microenvironment (TME) were calculated using the “ssGSEA” algorithm. The Gene Expression Omnibus (GEO) database provided the single cell RNA sequencing (scRNA-seq) data, and the R package “Seurat” was applied to analyze the scRNA-seq data. Utilizing the LASSO algorithm in conjunction with univariate Cox analysis, the gene signature was constructed. Methods: mRNA sequencing data and clinicopathological data on 526 individuals with ccRCC were gathered from the The Cancer Genome Atlas database for this investigation (263 training group samples and 263 validation group samples). Establishing a chemokine genes signature to assess prognosis and therapy responsiveness in ccRCC is the goal of this effort. Chemokines can form a local network to regulate the movement of immune cells and are essential for tumor proliferation and metastasis as well as for the interaction between tumor cells and mesenchymal cells. 5Department of Urology, Jiangmen Central Hospital, Jiangmen, Guangdong, Chinaīackground: Renal clear cell carcinoma (ccRCC) is one of the most prevailing type of malignancies, which is affected by chemokines.4Institute of Precision Medicine, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.3Department of Urology, Affiliated Longhua People’s Hospital, Southern Medical University, Shenzhen, China.2Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.1Department of Urology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.Ming-Jie Lin 1 †, Xiu-Xiao Tang 2 †, Gao-Sheng Yao 1 †, Zhi-Ping Tan 1 †, Lei Dai 1 †, Ying-Han Wang 1, Jiang-Quan Zhu 1, Quan-Hui Xu 1, Mukhtar Adan Mumin 1, Hui Liang 3, Zhu Wang 3, Qiong Deng 3, Jun-Hang Luo 1,4*, Jin-Huan Wei 1* and Jia-Zheng Cao 5*
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