rs10993994 in MSMB promoter affects serum MSMB expression, contributes to the genetic predisposition to prostate cancer in southern Chinese Han population.
A peak at m/z 10,760 was identified as β-microseminoprotein (β-MSMB) and found to be statistically lower in urine from PCa participants using the peak's average areas.
A plausible functional basis for a few loci, such as FGFR2 for breast cancer and MSMB for prostate cancer, has been elucidated, but the majority are not understood and suggest new mechanisms of carcinogenesis.
A total of 31 proteins were associated with prostate cancer risk including proteins encoded by <i>GSTP1</i>, whose methylation level was shown previously to be associated with prostate cancer risk, and <i>MSMB, SPINT2, IGF2R</i>, and <i>CTSS</i>, which were previously implicated as potential target genes of prostate cancer risk variants identified in genome-wide association studies.
Across 66 meta-analyses, a total of 20 genetic variants involving 584,100 subjects in 19 different genes (KLK3, IGFBP3, ESR1, SOD2, CAT, CYP1B1, VDR, RFX6, HNF1B, SRD5A2, FGFR4, LEP, HOXB13, FAS, FOXP4, SLC22A3, LMTK2, EHBP1 and MSMB) exhibited significant association with prostate cancer.
Additional copies of the prostate cancer risk allele resulted in lower beta-MSP but higher PSA levels, and singly explained 23% and 5% of the variation seen in semen beta-MSP and PSA, respectively.
Additionally, 6 pathways were identified based on identified variants and genes, including estrogen signaling pathway, signaling by MST1, IL-15 production, MSP-RON signaling pathway, and IL-12 signaling and production in macrophages, which are known to be associated with prostate cancer.
Another novel mechanism, which we propose in this review article, is that PSP94 may protect against prostate cancer by preventing or limiting an intracellular fungal infection in the prostate.
For the two SNPs that had significant differences between more and less aggressive disease rs2735839 in KLK3 (P = 8.4 x 10(-7)) and rs10993994 in MSMB (P = 0.046), the alleles that are associated with increased risk for PCa were more frequent in patients with less aggressive disease.
Further improvement was achieved by multivariate logistic regression analysis, which identified novel duplex (TRPM8 and MSMB), triplex (plus AMACR) and quadriplex (plus PCA3) models for the detection of early CaPs (AUC=0.665, 0.726 and 0.741, respectively).
Genome-wide significant associations were observed with 84 variants all located at the known PrCa risk regions at 8q24 (128.484-128.548) and 10q11.22 (MSMB gene).
Identification of genes potentially involved in the acquisition of androgen-independent and metastatic tumor growth in an autochthonous genetically engineered mouse prostate cancer model.