Association of KLK3, VAMP8 and MDM4 Genetic Variants within microRNA Binding Sites with Prostate Cancer: Evidence from Serbian Population

Kotarac, Nevena; Dobrijević, Zorana; Matijasević, S; Savić‐Pavićević, Dušanka; Brajušković, Goran

doi:10.1007/s12253-020-00839-7

Cited by 9 publications

(5 citation statements)

References 50 publications

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“…Nevertheless, the findings of molecular genetic studies focusing on microRNA-related genes, as well as of studies analyzing the biomarker properties of circulatory microRNA in PCa, remain inconclusive. Since our previous case–control studies on microRNA-related genetic variants and PCa provided promising results [ 12 , 13 , 14 , 15 , 16 ], we further expanded our research topic by analyzing the expression of selected candidate microRNAs in plasma and EVs extracted from whole plasma samples obtained from Serbian patients diagnosed with PCa.…”

Section: Discussionmentioning

confidence: 99%

MiR-375 and miR-21 as Potential Biomarkers of Prostate Cancer: Comparison of Matching Samples of Plasma and Exosomes

Joković

Dobrijević

Kotarac

et al. 2022

Genes

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MiR-21 and miR-375 have been reported as dysregulated in prostate cancer (PCa) in multiple previous studies. Still, variable or even opposing data for the expression of these microRNAs in PCa were found, and their potential biomarker properties remain elusive. In an attempt to clarify their significance as PCa biomarkers, as well as to compare different types of specimens as a source of relevant microRNAs, we used plasma and matching plasma-derived exosomes from patients with PCa and patients with benign prostatic hyperplasia (BPH). Plasma and exosomes were obtained from 34 patients with PCa and 34 patients with BPH, and their levels of expression of miR-21 and miR-375 were determined by RT-qPCR. We found no significant difference in the level of expression of these microRNAs in plasma and exosomes between patients with PCa and BPH. The level of exosomal miR-21 was elevated in PCa patients with high serum PSA values, as well as in patients with aggressive PCa, while for plasma samples, the results remained insignificant. For miR-375, we did not find an association with the values of standard prognostic parameters of PCa, nor with cancer aggressiveness. Therefore, our results support the potential prognostic role of exosomal miR-21 expression levels in PCa.

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Section: Discussionmentioning

confidence: 99%

MiR-375 and miR-21 as Potential Biomarkers of Prostate Cancer: Comparison of Matching Samples of Plasma and Exosomes

Joković

Dobrijević

Kotarac

et al. 2022

Genes

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“…Gao et al discovered that the rs4245739 polymorphism decreased lung cancer incidence [ 13 ], while Gansmo et al concluded that it was not associated with lung cancer [ 12 ]. Kotarac et al and Gansmo et al both discovered that this SNP was not associated with prostate cancer [ 12 , 17 ]. Ovarian cancer, endometrial cancer, thyroid cancer, and non-Hodgkin lymphoma have been less studied [ 10 , 11 , 19 ].…”

Section: Discussionmentioning

confidence: 99%

The Correlation of Mouse Double Minute 4 (MDM4) Polymorphisms (rs4245739, rs1563828, rs11801299, rs10900598, and rs1380576) with Cancer Susceptibility: A Meta-Analysis

Chen

Liu

et al. 2022

Med Sci Monit

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Background Mouse double minute 4 (MDM4) has been extensively investigated as a negative regulator of P53, its negative feedback loop, and the effect of its genetic polymorphisms on cancers. However, many studies showed varying and even conflicting results. Therefore, we employed meta-analysis to further assess the intensity of the connection between MDM4 polymorphisms and malignancies. Material/Methods We searched eligible articles in 5 databases (Cochrane Library, PubMed, Web of Science, Wan Fang Database, and China National Knowledge Infrastructure) up to August 2021. Odds ratios (ORs) and 95% confidence intervals (CIs) were utilized to probe the correlation of 5 MDM4 polymorphisms (rs4245739, rs1563828, rs11801299, rs10900598, and rs1380576) with carcinomas. We employed meta-regression and subgroup analysis to probe for sources of heterogeneity; Funnel plots, Begg’s test, and Egger’s test were used to evaluate publication bias. Sensitivity analysis was applied to assess the stability of the study. Results Twenty-two studies, comprising 77 reports with 29 853 cases and 72 045 controls, were included in our meta-analysis. We found that rs4245739 polymorphism was a factor in reducing overall cancer susceptibility (dominant model, OR=0.85, 95% CI=0.76–0.95; heterozygous model, OR=0.86, 95% CI=0.78–0.96; additive model, OR=0.87, 95% CI=0.79–0.95), especially in Asian populations, and it also reduces the risk for esophageal squamous cell carcinoma (ESCC). The remaining 4 SNPs were not associated with cancers. Conclusions The rs4245739 polymorphism might reduce the risk of malignancies, especially in Asian populations, and it is a risk-reducing factor for ESCC incidence. However, rs1563828, rs11801299, rs10900598, and rs1380576 are not relevant to cancer susceptibility.

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“…The prostate is an androgen-dependent organ, and SNPs in genes involved in the androgen metabolism pathway, such as KLK3, have been previously implicated in PCa risk and progression 22,25 . KLK3 is a proteincoding gene on chromosome 19q13.4, and its protein product, PSA, is a serine protease exclusively secreted by the prostate gland into the seminal fluid, where it plays an important functional role in the normal physiology www.nature.com/scientificreports/ of the prostate 26 .…”

Section: Discussionmentioning

confidence: 99%

KLK3 SNP–SNP interactions for prediction of prostate cancer aggressiveness

Lin

Huang

Cheng

et al. 2021

Sci Rep

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Risk classification for prostate cancer (PCa) aggressiveness and underlying mechanisms remain inadequate. Interactions between single nucleotide polymorphisms (SNPs) may provide a solution to fill these gaps. To identify SNP–SNP interactions in the four pathways (the angiogenesis-, mitochondria-, miRNA-, and androgen metabolism-related pathways) associated with PCa aggressiveness, we tested 8587 SNPs for 20,729 cases from the PCa consortium. We identified 3 KLK3 SNPs, and 1083 (P < 3.5 × 10–9) and 3145 (P < 1 × 10–5) SNP–SNP interaction pairs significantly associated with PCa aggressiveness. These SNP pairs associated with PCa aggressiveness were more significant than each of their constituent SNP individual effects. The majority (98.6%) of the 3145 pairs involved KLK3. The 3 most common gene–gene interactions were KLK3-COL4A1:COL4A2, KLK3-CDH13, and KLK3-TGFBR3. Predictions from the SNP interaction-based polygenic risk score based on 24 SNP pairs are promising. The prevalence of PCa aggressiveness was 49.8%, 21.9%, and 7.0% for the PCa cases from our cohort with the top 1%, middle 50%, and bottom 1% risk profiles. Potential biological functions of the identified KLK3 SNP–SNP interactions were supported by gene expression and protein–protein interaction results. Our findings suggest KLK3 SNP interactions may play an important role in PCa aggressiveness.

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Association of KLK3, VAMP8 and MDM4 Genetic Variants within microRNA Binding Sites with Prostate Cancer: Evidence from Serbian Population

Cited by 9 publications

References 50 publications

MiR-375 and miR-21 as Potential Biomarkers of Prostate Cancer: Comparison of Matching Samples of Plasma and Exosomes

MiR-375 and miR-21 as Potential Biomarkers of Prostate Cancer: Comparison of Matching Samples of Plasma and Exosomes

The Correlation of Mouse Double Minute 4 (MDM4) Polymorphisms (rs4245739, rs1563828, rs11801299, rs10900598, and rs1380576) with Cancer Susceptibility: A Meta-Analysis

KLK3 SNP–SNP interactions for prediction of prostate cancer aggressiveness

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