854 – Rna Binding Protein Imp1 Promotes Exosome Production in Colon Cancer

2019 ◽  
Vol 156 (6) ◽  
pp. S-188
Author(s):  
Sarah F. Andres ◽  
Ranjan Preet ◽  
Sukanya Das ◽  
Jiegang Yang ◽  
Priya Chatterji ◽  
...  
2012 ◽  
Vol 8 (4) ◽  
pp. 290-297 ◽  
Author(s):  
Michelina Plateroti ◽  
Patricia Rosa de Araujo ◽  
Acarizia Eduardo da Silva ◽  
Luiz O. F. Penalva

2020 ◽  
Vol 158 (6) ◽  
pp. S-531
Author(s):  
Sarah F. Andres ◽  
Ranjan Preet ◽  
Wei Zhang ◽  
Jiegang Yang ◽  
Sukanya Das ◽  
...  

2015 ◽  
Vol 9 (7) ◽  
pp. 1406-1420 ◽  
Author(s):  
Lan Lan ◽  
Carl Appelman ◽  
Amber R. Smith ◽  
Jia Yu ◽  
Sarah Larsen ◽  
...  

2007 ◽  
Vol 121 (3) ◽  
pp. 486-494 ◽  
Author(s):  
Euthymios Dimitriadis ◽  
Theoni Trangas ◽  
Stavros Milatos ◽  
Periklis G. Foukas ◽  
Ioannis Gioulbasanis ◽  
...  

2020 ◽  
Author(s):  
Haoling Liu ◽  
Qingquan Bai ◽  
Zhaoyang Lu ◽  
Xuan Song ◽  
Yao Liu ◽  
...  

Abstract Background: Dysregulation of RNA binding protein (RBP) expression has been reported in various malignant tumors, and it is related to the occurrence and development of cancer. However, the role of RBPs in colon cancer remains unclear. Methods: We downloaded the RNA sequencing data of colon cancer from The Cancer Genome Atlas (TCGA) database, and determined the differently expressed RBPs between normal and cancer tissues. Then, through a series of bioinformatics analysis, we systematically studied the expression and prognostic value of these RBPs.Result: A total of 490 different expression differently expressed RBPs were identified, including 323 up-regulated and 167 down regulated RBPs. Five RBPs (PNLDC1, NSUN6, NOL3, PPARGC1A, LRRFIP2) were identified as prognosis related genes for the construction of prognostic model. Further analysis showed that the overall survival rate (OS) of patients in the high-risk subgroup was worse than that in the low-risk subgroup based on this model. The area under the characteristic curve of time-dependent receiver was 0.691 in TCGA and 0.624 in GEO, which confirmed the prognostic model to be a good one. We also established a nominal map based on the internal validation in 5 RBPs mRNAs and TCGA sequeues, showing a good ability to differentiate colon cancer.Conclusions: We screened RBPs expression differences between colon cancer and adjacent non tumor colon tissues using the TCGA database to identify potential gene biomarkers.Besides,a very effective prediction model was constructed and tested based on the differential expression of RBPs using the TCGA and Gene Expression Omnibus (GEO) database.We also Validated of the relationship between the expression of five RBPs and prognosis


2020 ◽  
Vol 34 (S1) ◽  
pp. 1-1
Author(s):  
Afreen Sayed ◽  
Sonali Choudhury ◽  
Dharmalingam Subramaniam ◽  
Sumedha Gunewardena ◽  
Sivapriya Ponnurangam ◽  
...  

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