Prognostic Values for the mRNA Expression of the ADAMTS Family of Genes in Gastric Cancer.
Liang LiangJin-Hui ZhuGang ChenXin-Gan QinJun-Qiang ChenPublished in: Journal of oncology (2020)
The "A Disintegrin and Metalloproteinase with Thrombospondin Motif" (ADAMTS) family of genes is involved in the occurrence and development of different cancers. However, the prognostic value of these genes in gastric cancer (GC) has not been revealed. The present study was thus conducted to determine the prognostic value for the ADAMTS family of genes in GC. First, we evaluated the mRNA expression levels of the ADAMTS family in GC patients using a GEPIA dataset. Thereafter, we determined the prognostic value of these genes by analyzing their mRNA level using the Kaplan-Meier Plotter database. The mRNA expression level of ADAMTS12 was randomly validated by qRT-PCR and meta-analysis while its coexpression genes were derived using Coexpedia. Finally, we performed Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses using the OmicShare Tools. Compared to normal tissues, expression of ADAMTS2 and 12 was significantly higher while that of ADAMTS1, 13, and 15 was significantly lower in GC tissues. According to the RNA-seq and gene chip data, the ADAMTS family (6, 7, 12, 15, and 18) of genes was closely related to the prognosis of GC, and their high expression levels were associated with poor prognosis and survival time. In addition, ADAMTS12 was highly expressed in 20 pairs of GC tissues based on RT-PCR (P=0.016) and meta-analysis (SMD: 0.73, 95% CI: 0.32-1.14, P < 0.001). GO and KEGG pathway analyses indicated that the ADAMTS12 coexpressed genes were enriched in the pathways of extracellular matrix organization, extracellular matrix structural constituent, extracellular matrix, and protein digestion and absorption. Herein, we discovered the prognostic values and biological roles of the ADAMTS genes in GC.
Keyphrases
- extracellular matrix
- genome wide
- poor prognosis
- genome wide identification
- bioinformatics analysis
- genome wide analysis
- rna seq
- gene expression
- long non coding rna
- dna methylation
- high throughput
- copy number
- gas chromatography
- single cell
- risk assessment
- emergency department
- end stage renal disease
- machine learning
- deep learning
- binding protein
- big data
- simultaneous determination