DEPD®, A HIGH RESOLUTION GENE EXPRESSION PROFILING TECHNIQUE CAPABLE OF IDENTIFYING NEW DRUG TARGETS IN THE CENTRAL NERVOUS SYSTEM

2002 ◽  
Vol 22 (1-4) ◽  
pp. 283-295 ◽  
Author(s):  
Alfred Maelicke ◽  
Hermann Lübbert
Keyword(s):  
Gene Expression ◽  
Central Nervous System ◽  
Nervous System ◽  
High Resolution ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Drug Targets ◽  
New Drug ◽  
The Central Nervous System

New cancer drug targets identified in adrenocortical carcinoma through gene expression profiling

2018 ◽  
Author(s):  
Raimunde Liang ◽  
Isabel Weigand ◽  
Barbara Altieri ◽  
Stefan Kircher ◽  
Sonja Steinhauer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Adrenocortical Carcinoma ◽  
Expression Profiling ◽  
Drug Targets ◽  
Cancer Drug

Negative and positive effects of an IAP-LTR on nearby Pcdaα gene expression in the central nervous system and neuroblastoma cell lines

Gene ◽  
2004 ◽  
Vol 337 ◽  
pp. 91-103 ◽  
Author(s):  
Hidehiko Sugino ◽  
Tomoko Toyama ◽  
Yusuke Taguchi ◽  
Shigeyuki Esumi ◽  
Mitsuhiro Miyazaki ◽  
...  
Keyword(s):  
Gene Expression ◽  
Central Nervous System ◽  
Nervous System ◽  
Cell Lines ◽  
Neuroblastoma Cell ◽  
Positive Effects ◽  
The Central Nervous System ◽  
Neuroblastoma Cell Lines

scholarly journals A novel gene signature based on five immune checkpoint genes predicts the survival of glioma

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Wei Zhang ◽  
You Zhai ◽  
Guanzhang Li ◽  
Tao Jiang
Keyword(s):  
Gene Expression ◽  
Central Nervous System ◽  
Immune Response ◽  
Nervous System ◽  
Cox Regression ◽  
Gene Signature ◽  
Immune Checkpoints ◽  
The Novel ◽  
The Central Nervous System ◽  
Checkpoint Genes

Abstract Background Glioma is the most common and fatal type of nerve neoplasm in the central nervous system. Several biomarkers have been considered for prognosis prediction, which is not accurate enough. We aimed to carry out a gene signature related to the expression of immune checkpoints which was enough for its performance in prediction. Methods Gene expression of immune checkpoints in TGGA database was filtrated. The 5 selected genes underwent verification by COX and Lasso-COX regression. Next, the selected genes were included to build a novel signature for further analysis. Results Patients were sub-grouped into high and low risk according to the novel signature. Immune response, clinicopathologic characters, and survival showed significant differences between those 2 groups. Terms including “naive,” “effector,” and “IL-4” were screened out by GSEA. The results showed strong relevance between the signature and immune response. Conclusions We constructed a gene signature with 5 immune checkpoints. The signature predicted survival effectively. The novel signature performed more functional than previous biomarkers.

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