scholarly journals Discovery and construction of prognostic model for clear cell renal cell carcinoma based on single-cell and bulk transcriptome analysis

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Fangyuan Zhang ◽  
Shicheng Yu ◽  
Pengjie Wu ◽  
Liansheng Liu ◽  
Dong Wei ◽  
...  
Oncotarget ◽  
2018 ◽  
Vol 9 (28) ◽  
pp. 20058-20074 ◽  
Author(s):  
Lucile Broncy ◽  
Basma Ben Njima ◽  
Arnaud Méjean ◽  
Christophe Béroud ◽  
Khaled Ben Romdhane ◽  
...  

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Guangzhen Wu ◽  
Jianyi Li ◽  
Yingkun Xu ◽  
Xiangyu Che ◽  
Feng Chen ◽  
...  

The main purpose of this study was to explore the genetic variation, gene expression, and clinical significance of ADAMTSs (a disintegrin and metalloprotease domains with thrombospondin motifs) across cancer types. Analysis of data from the TCGA (The Cancer Genome Atlas) database showed that the ADAMTSs have extensive CNV (copy number variation) and SNV (single nucleotide variation) across cancer types. Compared with normal tissues, the methylation of ADAMTSs in cancer tissues is also significantly different, which affects the expression of ADAMTS gene and the prognosis of cancer patients. Through gene expression analysis, we found that ADAMTS family has significant changes in gene expression across cancer types and is closely related to the prognosis of carcinoma, especially in ccRCC (clear cell renal cell carcinoma). LASSO regression analysis was used to establish a prognostic model based on the ADAMTSs to judge the prognosis of patients with ccRCC. Multiple Cox regression analysis suggested that age, grade, stage, and risk score of the prognostic model of ccRCC were independent prognostic factors in patients with renal clear cell carcinoma. These findings indicate that the ADAMTSs-based survival model can accurately predict the prognosis of patients with ccRCC and suggest that ADAMTSs are a potential prognostic biomarker and therapeutic target in ccRCC.


2020 ◽  
Author(s):  
Haosheng Liu ◽  
Jianxiong Fang ◽  
Tianqi Liu ◽  
Zhenhui Zhang ◽  
Chao Zhao ◽  
...  

Abstract Background: Renal cell cacinoma (RCC) accounts for 3% of human cancers, and clear cell renal cell carcinoma (ccRCC) is the most common pathological type of RCC. Cell surface proteins have been shown to play an important role in the occurrence and progression of various cancers. In this study, we focused on plasma membrane proteins (PMPs), to explore their potential value in ccRCC. Methods: The PMPs expression profiles and ccRCC patients’ clinical information were downloaded from TCGA database. Through a series of bioinformatic methods, we established a plasma membrane proteins prognostic model and verify its value in multiple ways. Results: Multivariate cox regression analysis and area under receiver operating characteristic curve indicated that this model was an effective independent predictor of ccRCC clinical outcomes. It has good prognostic value in different groups of clinical features. Combined with other two clinical characteristics, a nomogram was constructed to predict patient survival at 1, 3, and 5 years. Conclusions: Our study is the first to explore the prognostic value of plasma membrane proteins in clear cell renal cell carcinoma. We hope our work could provide a new viewpoint for ccRCC prognosis and drawn people’s attention to plasma membrane proteins in clear cell renal cell carcinoma.


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