Identification of novel hub genes associated with gastric cancer using integrated bioinformatics analysis.
Identification of novel hub genes associated with gastric cancer using integrated bioinformatics analysis.
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DOI：
10.1186/s12885-021-08358-7
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发表时间：
2021-06-14
期刊：
影响因子：
3.8
通讯作者：
Zhang HH
中科院分区：
文献类型：
--
作者：
Lu XQ;Zhang JQ;Zhang SX;Qiao J;Qiu MT;Liu XR;Chen XX;Gao C;Zhang HH
Gastric cancer (GC) is one of the most common solid malignant tumors worldwide with a high-recurrence-rate. Identifying the molecular signatures and specific biomarkers of GC might provide novel clues for GC prognosis and targeted therapy. Gene expression profiles were obtained from the ArrayExpress and Gene Expression Omnibus database. Differentially expressed genes (DEGs) were picked out by R software. The hub genes were screened by cytohubba plugin. Their prognostic values were assessed by Kaplan–Meier survival analyses and the gene expression profiling interactive analysis (GEPIA). Finally, qRT-PCR in GC tissue samples was established to validate these DEGs. Total of 295 DEGs were identified between GC and their corresponding normal adjacent tissue samples in E-MTAB-1440, GSE79973, GSE19826, GSE13911, GSE27342, GSE33335 and GSE56807 datasets, including 117 up-regulated and 178 down-regulated genes. Among them, 7 vital upregulated genes (HMMR, SPP1, FN1, CCNB1, CXCL8, MAD2L1 and CCNA2) were selected. Most of them had a significantly worse prognosis except SPP1. Using qRT-PCR, we validated that their transcriptions in our GC tumor tissue were upregulated except SPP1 and FN1, which correlated with tumor relapse and predicts poorer prognosis in GC patients. We have identified 5 upregulated DEGs (HMMR, CCNB1, CXCL8, MAD2L1, and CCNA2) in GC patients with poor prognosis using integrated bioinformatical methods, which could be potential biomarkers and therapeutic targets for GC treatment. The online version contains supplementary material available at 10.1186/s12885-021-08358-7.
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影响因子：
3.7
作者：
Higashiyama, Motoshige;Ito, Tetsuo;Shimada, Yutaka
通讯作者：
Shimada, Yutaka
DOI：
10.1083/jcb.201102085
发表时间：
2012-01-09
期刊：
The Journal of cell biology
影响因子：
--
作者：
Arsic N;Bendris N;Peter M;Begon-Pescia C;Rebouissou C;Gadéa G;Bouquier N;Bibeau F;Lemmers B;Blanchard JM
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Blanchard JM
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He, Yuting
影响因子：
3.7
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Ji J
影响因子：
3
作者：
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通讯作者：
Hogue, CW