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Status |
Public on Jul 19, 2022 |
Title |
A novel prognostic risk model for cervical cancer based on immune checkpoint HLA-G-driven differentially expressed genes [HeLa] |
Organism |
Homo sapiens |
Experiment type |
Expression profiling by high throughput sequencing
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Summary |
The aim of this study was to construct and validate a prognostic risk model to predict the overall survival (OS) of patients with cervical cancer, providing a reference for individualized clinical treatment that may lead to better clinical outcomes. HLA-G-driven DEG signature consisting of the eight most important prognostic genes CD46, LGALS9, PGM1, SPRY4, CACNB3, PLIN2, MSMO1, and DAGLB was identified as a key predictor of cervical cancer. To summarize, we developed and validated a novel prognostic risk model for cervical cancer based on HLA-G-driven DEGs, and the prognostic signature showed great ability in predicting the overall survival of patients with cervical cancer.
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Overall design |
HLA-G-driven differentially expressed genes (DEGs) were obtained from two cervical carcinoma cell lines, namely, SiHa and HeLa, with stable overexpression of HLA-G by RNA sequencing (RNA-seq).
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Contributor(s) |
Xu H |
Citation missing |
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Submission date |
Jul 13, 2022 |
Last update date |
Jul 19, 2022 |
Contact name |
Hui-Hui Xu |
E-mail(s) |
[email protected]
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Phone |
+86-13757609637
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Organization name |
Taizhou Hospital
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Street address |
150
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City |
Linhai |
State/province |
Zhejiang province |
ZIP/Postal code |
317000 |
Country |
China |
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Platforms (1) |
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Samples (6)
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This SubSeries is part of SuperSeries: |
GSE208119 |
A novel prognostic risk model for cervical cancer based on immune checkpoint HLA-G-driven differentially expressed genes |
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Relations |
BioProject |
PRJNA858423 |
Supplementary file |
Size |
Download |
File type/resource |
GSE208117_Processed_data_files_HeLa-HLA-G_VS._HeLa_FPKM.csv.gz |
335.0 Kb |
(ftp)(http) |
CSV |
SRA Run Selector |
Raw data are available in SRA |
Processed data are available on Series record |
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