Expression of miR-148b-3p is correlated with overexpression of biomarkers in prostate cancer.
Eliakym Arámbula-MerazFernando Bergez-HernándezEmir Leal-LeónEnrique Romo-MartínezVerónica Picos-CárdenasFred Luque-OrtegaJose Romero-QuintanaMarco Alvarez-ArrazolaNoemí García-MagallanesPublished in: Genetics and molecular biology (2020)
Prostate cancer (PCa) is one of the leading causes of death among men. Genes such as PCA3, PSA, and Fra-1 are suggested to serve as potential tools for the detection of PCa, as they are deregulated during this pathology. A similar event occurs with small non-coding RNAs, called miRNAs, specifically miR-195-5p, miR-133a-3p, and miR-148b-3p, which were analyzed in a Chinese population and suggested to be possible candidates for PCa diagnosis. We evaluated the expression levels of three miRNAs and three genes in tissue samples of PCa and benign prostate disease, such as benign prostatic hyperplasia, or prostatitis, in order to determine their potential as candidates for PCa detection. Our results showed a statistically significant overexpression of 279-fold increase in PSA levels and a 1,012-fold increase in PCA3 levels in PCa patients compared to benign prostate disease patients (p = 0.001 and p = 0.002, respectively). We observed a positive correlation between the expression of miR-148b-3p and the expression of PSA and PCA3 genes, two established biomarkers in PCa. The expression of miR-148b-3p was not related to clinical characteristics, such as age and weight, as observed for the other miRNAs analyzed, suggesting its potential as a biomarker for detection of this pathology.
Keyphrases
- prostate cancer
- poor prognosis
- radical prostatectomy
- benign prostatic hyperplasia
- end stage renal disease
- ejection fraction
- genome wide
- newly diagnosed
- binding protein
- chronic kidney disease
- long non coding rna
- peritoneal dialysis
- prognostic factors
- dna methylation
- weight loss
- physical activity
- transcription factor
- real time pcr
- middle aged
- climate change
- bioinformatics analysis