Materials and Methods: Sixty-nine men underwent mpMRI of the prostate followed by TRUS biopsy. In addition to 12-core biopsy, CFB was performed on abnormal lesions detected on MRI.
Results: Abnormal lesions were identified in 98.6% of the patients, and 59.4% had the highest PI-RADS score of 3 or more. With the use of PI-RADS 3 as cutoff, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of MRI for the detection of PCa were 91.7%, 57.8%, 53.7%, and 92.8%, respectively. With the use of PI-RADS 4 as cutoff, the sensitivity, specificity, PPV, and NPV of mpMRI were 66.7%, 91.1%, 80%, and 83.7%, respectively. Systematic biopsy detected more PCa compared to CFB (29% vs. 26.1%), but CFB detected more significant (Gleason grade ≥7) PCa (17.4% vs. 14.5%) (P < 0.01). CFB cores have a higher PCa detection rate as compared to systematic cores (P < 0.01).
Conclusions: mpMRI has a good predictive ability for PCa. CFB is superior to systematic biopsy in the detection of the significant PCa.
METHODS: DNA samples from 92 patients and 156 healthy controls collected from two medical centers in Riyadh, Saudi Arabia were analyzed for four regions located at X-chromosome using the Investigator® Argus X-12 QS Kit.
RESULTS: The results demonstrated that microvariant alleles of (DXS7132, DXS10146, HPRTB, DXS10134, and DXS10135) are overrepresented in the BPH group (p < 0.00001). Allele 28 of DXS10135 and allele 15 of DXS7423 could have a protective effect, OR 0.229 (95%CI, 0.066-0.79); and OR 0.439 (95%CI, 0.208-0.925). On the other hand, patients carrying allele 23 of DXS10079 and allele 26 of DXS10148 presented an increased risk to PrCa OR 4.714 (95%CI, 3.604-6.166).
CONCLUSION: The results are in concordance with the involvement of the X chromosome in PrCa and BPH development. STR allele studies may add further information from the definition of a genetic profile of PrCa resistance or susceptibility. As TBL1, AR, LDOC1, and RPL10 genes are located at regions Xp22.31, Xq11.2-12, Xq26.2, and Xq28, respectively, these genes could play an essential role in PrCa or BPH.
DISCUSSION: Several treatment options are available for different stages of prostate cancer. Hormone therapy known as androgen deprivation therapy (ADT) is the first line treatment used to treat advanced prostate cancer. Chemical castration by gonadotropin-releasing hormone agonists suppresses lutenizing hormone production, which in turn inhibits the production of testosterone and dihydrotestosterone. This will prevent the growth of prostate cancer cells. However, ADT causes deleterious effects on bone health because the androgens are essential in preserving optimal bone health in men.
CONCLUSION: Various observational studies showed that long-term ADT for advanced or metastatic prostate cancer was associated with decreased bone mineral density, as well as altered body composition that might affect bone health. Considering the potential impact of osteoporotic fracture, interventions to mitigate these skeletal adverse effects should be considered by physicians when initiating ADT on their patients.
OBJECTIVE: To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer.
DESIGN, SETTING, AND PARTICIPANTS: SNPs implicated in any phenotype other than prostate cancer (p≤10(-7)) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24,534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated.
RESULTS AND LIMITATIONS: A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p=1.6×10(-6)), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95% CI 1.16-1.27; p=3.22×10(-18)). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86-0.94; p=2.5×10(-6)). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12, 95% CI 1.06-1.19; p=4.67×10(-5)); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL.
CONCLUSIONS: We did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in prostate cancer etiology.
PATIENT SUMMARY: We evaluated whether genetic variants associated with several traits are linked to the risk of aggressive prostate cancer. No new such variants were identified.