scholarly journals Systematical Analysis of the Cancer Genome Atlas Database Reveals EMCN/MUC15 Combination as a Prognostic Signature for Gastric Cancer

2020 ◽  
Vol 7 ◽  
Author(s):  
Wentao Dai ◽  
Jixiang Liu ◽  
Bingya Liu ◽  
Quanxue Li ◽  
Qingqing Sang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Prognostic Signature ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals Why MUC16 mutations lead to a better prognosis: A study based on The Cancer Genome Atlas gastric cancer cohort

2021 ◽  
Vol 9 (17) ◽  
pp. 4143-4158
Author(s):  
Yu-Jie Huang ◽  
Zhi-Fei Cao ◽  
Jie Wang ◽  
Jian Yang ◽  
Yi-Jun Wei ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals Candidate genes for predicting the survival of patients with gastric cancer: a study based on The Cancer Genome Atlas (TCGA) database

2020 ◽  
Vol 9 (4) ◽  
pp. 2599-2608
Author(s):  
Xiqiao Liu ◽  
Liying Gao ◽  
Dongqiong Ni ◽  
Chengao Ma ◽  
Yuping Lu ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Candidate Genes ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Genome Atlas

scholarly journals Potential prognostic impact of EBV RNA‐seq reads in gastric cancer: a reanalysis of The Cancer Genome Atlas cohort

FEBS Open Bio ◽  
2020 ◽  
Vol 10 (3) ◽  
pp. 455-467 ◽  
Author(s):  
Daichi Sadato ◽  
Mina Ogawa ◽  
Chizuko Hirama ◽  
Tsunekazu Hishima ◽  
Shin‐Ichiro Horiguchi ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Prognostic Impact ◽  
Rna Seq ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Eight-gene prognostic signature associated with hypoxia and ferroptosis for gastric cancer with general applicability

Epigenomics ◽  
2021 ◽  
Author(s):  
Junyu Huo ◽  
Liqun Wu ◽  
Yunjin Zang
Keyword(s):  
Gastric Cancer ◽  
Regression Analysis ◽  
Risk Score ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cox Regression Analysis ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Aims: To investigate the prognostic significance of hypoxia- and ferroptosis-related genes for gastric cancer (GC). Materials & methods: We extracted data on 259 hypoxia- and ferroptosis-related genes from The Cancer Genome Atlas and identified the differentially expressed genes between normal (n = 32) and tumor (n = 375) tissues. A risk score was established by univariate Cox regression analysis and LASSO penalized Cox regression analysis. Results: The risk score contained eight genes showed good performance in predicting overall survival and relapse-free survival in GC patients in both the training cohort (The Cancer Genome Atlas, n = 350) and the testing cohorts (GSE84437, n = 431; GSE62254, n = 300; GSE15459, n = 191; GSE26253, n = 432). Conclusion: The eight-gene signature may help to the improve the prognostic risk classification of GC.

scholarly journals Validation and calibration of next-generation sequencing to identify Epstein-Barr virus-positive gastric cancer in The Cancer Genome Atlas

2015 ◽  
Vol 19 (2) ◽  
pp. 676-681 ◽  
Author(s):  
M. Constanza Camargo ◽  
Reanne Bowlby ◽  
Andy Chu ◽  
Chandra Sekhar Pedamallu ◽  
Vesteinn Thorsson ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Next Generation Sequencing ◽  
Epstein Barr Virus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Barr Virus ◽  
Cancer Genome Atlas ◽  
Epstein Barr ◽  
Generation Sequencing ◽  
Genome Atlas

Aberrantly methylated-differentially expressed genes and pathways in Epstein–Barr virus-associated gastric cancer

2020 ◽  
Vol 16 (6) ◽  
pp. 187-197
Author(s):  
Jing-jing Jing ◽  
Hao Li ◽  
Ze-yang Wang ◽  
Heng Zhou ◽  
Li-ping Sun ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Differentially Expressed Genes ◽  
Epstein Barr Virus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Hub Genes ◽  
Barr Virus ◽  
Cancer Genome Atlas ◽  
Epstein Barr ◽  
Genome Atlas

Aim: To identify the methylated-differentially expressed genes (MDEGs) that may serve as diagnostic markers and therapeutic targets in Epstein–Barr virus-associated gastric cancer (EBVaGC) and to explore the methylation-based pathways for elucidating biological mechanisms of EBVaGC. Materials & methods: Gene expression and methylation profiles were downloaded from GEO database. MDEGs were identified by GEO2R. Pathway enrichment analyses were conducted based on DAVID database. Hub genes were identified by Cytoscape, which were further verified by The Cancer Genome Atlas database. Results: A total of 367 hypermethylated, lowly expressed genes were enriched in specific patterns of cell differentiation. 31 hypomethylated, highly expressed genes demonstrated enrichment in regulation of immune system process. After validation using The Cancer Genome Atlas database, seven genes were confirmed to be significantly different hub genes in EBVaGC. Conclusion: EBVaGC-specific MDEGs and pathways can be served as potential biomarkers for precise diagnosis and treatment of EBVaGC and provide novel insights into the mechanisms involved.

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