Association and in silico investigations of miR-302c insertion/deletion variant as a novel biomarker with susceptibility to gastric cancer.
Mohammad RaadAmir BayatAlireza SharafshahAli Zahedi AmiriMostafa Montazer ZohourMohammad AhmadvandPublished in: Journal of cellular biochemistry (2019)
Gastric cancer (GC) is the fifth most prevalent malignant tumor and the third most frequent cause of cancer mortality worldwide. rs199971565 is an insertion/deletion (INDEL) located in microRNA-302c (miR-302c) seed site, which may affect its function and biogenesis. There is no genetic association study investigating this INDEL with any disease till now. Thus, the current study was conducted to investigate the association of rs199971565 with susceptibility to GC in an Iranian population. In addition, in silico studies were performed to reveal the possible functional significance of this INDEL. A total of 378 subjects were genotyped through amplification refractory mutation system PCR (ARMS-PCR) after DNA extraction from peripheral blood by the salting out procedure. Also, in silico analyses were performed through databases and web tools including MiRNASNP V2.0, miRWalk V2.0, miRTarBase, DAVID V6.8, RNAfold, PHDcleave, miRmap, and STarMir. Results revealed that there was an association between rs199971565 and the incidence risk of GC under a recessive (P = .04, odds ratio [OR] = 18.73; 95% confidence interval [CI] = 1.07-326.95) model of inheritance. Also, compared to the Ins allele, the Del allele significantly increased the risk of GC (P = .01, OR = 2.02; 95% CI = 1.11-3.66). Further analyses showed no significant association in age and sex between two study groups (P = .216 and P = .798, respectively). In conclusion, for the first time, this study indicated the association and in silico investigations of rs199971565 and suggested it as a novel INDEL biomarker located in the seed site of miR-302c, which may have crucial roles in the susceptibility to GC and its incidence risk.
Keyphrases
- cell proliferation
- long non coding rna
- type diabetes
- gene expression
- cardiovascular disease
- squamous cell carcinoma
- single cell
- dna methylation
- machine learning
- mitochondrial dna
- high resolution
- coronary artery disease
- minimally invasive
- single molecule
- big data
- artificial intelligence
- circulating tumor
- squamous cell