William Isaacs and colleagues report evidence for a second prostate cancer risk locus in the HNF1B gene at 17q12, ∼26 kb from the previously reported risk locus in this region. The two loci are separated by a recombination hot spot and contribute independently to prostate cancer risk. We carried out a fine-mapping study in the HNF1B gene at 17q12 in two study populations and identified a second locus associated with prostate cancer risk, ∼26 kb centromeric to the first known locus (rs4430796); these loci are separated by a recombination hot spot. We confirmed the association with a SNP in the second locus (rs11649743) in five additional populations, with P = 1.7 × 10−9 for an allelic test of the seven studies combined. The association at each SNP remained significant after adjustment for the other SNP.

Long non-coding RNAs (lncRNAs), representing a large proportion of non-coding transcripts across the human genome, are evolutionally conserved and biologically functional. At least one-third of the phenotype-related loci identified by genome-wide association studies (GWAS) are mapped to non-coding intervals. However, the relationships between phenotype-related loci and lncRNAs are largely unknown. Utilizing the 1000 Genomes data, we compared single-nucleotide polymorphisms (SNPs) within the sequences of lncRNA and protein-coding genes as defined in the Ensembl database. We further annotated the phenotype-related SNPs reported by GWAS at lncRNA intervals. Because prostate cancer (PCa) risk-related loci were enriched in lncRNAs, we then performed meta-analysis of two existing GWAS for discovery and an additional sample set for replication, revealing PCa risk-related loci at lncRNA regions. The SNP density in regions of lncRNA was similar to that in protein-coding regions, but they were less polymorphic than surrounding regions. Among the 1998 phenotype-related SNPs identified by GWAS, 52 loci were located directly in lncRNA intervals with a 1.5-fold enrichment compared with the entire genome. More than a 5-fold enrichment was observed for eight PCa risk-related loci in lncRNA genes. We also identified a new PCa risk-related SNP rs3787016 in an lncRNA region at 19q13 (per allele odds ratio = 1.19; 95% confidence interval: 1.11–1.27) with P value of 7.22 × 10 ⁻⁷ . lncRNAs may be important for interpreting and mining GWAS data. However, the catalog of lncRNAs needs to be better characterized in order to fully evaluate the relationship of phenotype-related loci with lncRNAs.

To search for genetic variants that are associated with prostate cancer risk in the genome, we combined the data from our genome-wide association study (GWAS) in a population-based case-control study in Sweden with publicly available GWAS data from the Cancer Genetic Markers of Susceptibility (CGEMS) study. We limited the cases to those with aggressive disease in an attempt to identify risk variants that are associated with this most clinically relevant form of the disease. Among the most likely candidate single nucleotide polymorphisms (SNP) identified from the two GWAS, we sequentially confirmed one SNP at 22q13 in two independent study populations: the remaining subjects in Cancer of the Prostate in Sweden and a hospital-based case-control study at Johns Hopkins Hospital. Association of aggressive prostate cancer with the SNP at 22q13 was also observed in the publicly available data of four additional study populations from the second stage of the CGEMS study. In all seven study populations examined, the frequency of allele “C” of rs9623117 at 22q13 was consistently higher in aggressive cases than in controls. The combined allelic test was highly significant, with P = 5.0 × 10⁻⁷. The odds ratio (OR) of allele C for aggressive prostate cancer was estimated to be 1.18 [95% confidence interval (95% CI), 1.11-1.26]. However, the SNP was also associated with nonaggressive prostate cancer, with an estimated OR of 1.11 (95% CI, 1.04-1.19; P = 0.004). The risk-associated variants are located within the genomic region of TNRC6B, a gene involved in miRNA-mediated mRNA degradation. Additional studies are warranted to further confirm the association. [Cancer Res 2009;69(1):10–5]

Objective: Tumour biomarkers are used as indicators for cancer screening and as predictors for therapeutic responses and prognoses in cancer patients. We aimed to identify genetic loci that influence concentrations of cancer antigen 19-9 (CA19-9), carcinoembryonic antigen (CEA) and α fetoprotein (AFP), and investigated the associations between the significant single nucleotide polymorphisms (SNPs) with risks of oesophageal squamous cell (OSCC), pancreatic and hepatocellular cancers. Design: We carried out a genome wide association study on plasma CA19-9, CEA and AFP concentrations in 3451 healthy Han Chinese and validated the results in 10 326 individuals. Significant SNPs were further investigated in three case control studies (2031 OSCC cases and 2044 controls; 981 pancreatic cancer cases and 1991 controls; and 348 hepatocellular cancer cases and 359 controls). Results: The analyses showed association peaks on three genetic loci for CA19-9 (FUT6-FUT3 at 19p13.3, FUT2-CA11 at 19q13.3 and B3GNT3 at 19p13.1; p=1.16×10⁻¹³–3.30×10⁻²⁹⁰); four for CEA (ABO at 9q34.2, FUT6 at 19p13.3, FUT2 at 19q13.3 and FAM3B at 21q22.3; p=3.33×10⁻²²–5.81×10⁻²⁰⁹); and two for AFP (AFP at 4q11-q13 and HISPPD2A at 15q15.3; p=3.27×10⁻¹⁸ and 1.28×10⁻¹⁴). These explained 17.14% of the variations in CA19-9, 8.95% in CEA and 0.57% in AFP concentrations. Significant ABO variants were also associated with risk of OSCC and pancreatic cancers, and AFP variants with risk of hepatocellular cancer (p<0.05). Conclusions: This study identified several loci associated with CA19-9, CEA and AFP concentrations. The ABO variants were associated with risk of OSCC and pancreatic cancers and AFP variants with risk of hepatocellular cancer.

Circulating androgen levels are often used as indicators of physiological or pathological conditions. More than half of the variance for circulating androgen levels is thought to be genetically influenced. A genome-wide association study (GWAS) has identified two loci, SHBG at 17p13 and FAM9B at Xp22, for serum testosterone (T) levels; however, these explain only a small fraction of inter-individual variability. To identify additional genetic determinants of androgen levels, a GWAS of baseline serum T and dihydrotestosterone (DHT) levels was conducted in 3225 men of European ancestry from the REduction by DUtasteride of Prostate Cancer Events (REDUCE) study. Cross-validation was used to confirm the observed associations between the drug (n = 1581) and placebo (n = 1644) groups of REDUCE. In addition to confirming the associations of two known loci with serum T levels (rs727428 in SHBG: P = 1.26 × 10⁻¹²; rs5934505 in FAM9B: P = 1.61 × 10⁻⁸), we identified a new locus, JMJD1C at 10q21 that was associated with serum T levels at a genome-wide significance level (rs10822184: P = 1.12 × 10⁻⁸). We also observed that the SHBG locus was associated with serum DHT levels (rs727428: P = 1.47 × 10⁻¹¹). Moreover, two additional variants in SHBG [rs72829446, in strong linkage equilibrium with the missense variant D356N (rs6259), and rs1799941] were also independently associated with circulating androgen levels in a statistical scale. These three loci (JMJD1C, SHBG and FAM9B) were estimated to account for ∼5.3 and 4.1% of the variance of serum T and DHT levels. Our findings may provide new insights into the regulation of circulating androgens and potential targets for androgen-based therapy.