Identification of novel hub genes associated with gastric cancer using integrated bioinformatics analysis.

Autor: Lu XQ; Department of Breast Surgery, Shanxi Cancer Hospital, Taiyuan, Shanxi, China., Zhang JQ; Department of Rheumatology, the Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China., Zhang SX; Department of Rheumatology, the Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China., Qiao J; Department of Rheumatology, the Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China., Qiu MT; Department of Rheumatology, the Second Hospital of Shanxi Medical University, Taiyuan, Shanxi, China., Liu XR; Department of Breast Surgery, Shanxi Cancer Hospital, Taiyuan, Shanxi, China., Chen XX; Department of Breast Surgery, Shanxi Cancer Hospital, Taiyuan, Shanxi, China., Gao C; Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA., Zhang HH; Department of Gastroenterology, Shanxi Cancer Hospital, Taiyuan, 030001, Shanxi, China. zhhh31@163.com.
Jazyk: angličtina
Zdroj: BMC cancer [BMC Cancer] 2021 Jun 14; Vol. 21 (1), pp. 697. Date of Electronic Publication: 2021 Jun 14.
DOI: 10.1186/s12885-021-08358-7
Abstrakt: Background: 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.
Methods: 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.
Results: 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.
Conclusions: 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.
Databáze: MEDLINE
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