Hereditary gynecologic cancer

Mucins in ovarian cancer diagnosis and therapy

Ovarian cancer is the most lethal gynecologic malignancy and the five-year survival rate is only 35% after diagnosis. Epithelial ovarian cancer is a highly metastatic disease characterized by widespread peritoneal dissemination and ascites. The death incidences from ovarian cancer could be significantly lowered by developing new methods for the early diagnosis and treatment of this fatal disease. Several potential markers have been identified recently. However, mucins are the most promising markers for ovarian cancer diagnosis. Mucins are large extracellular, heavily glycosylated proteins and their aberrant expression has been implicated in the pathogenesis of a variety of cancers, including ovarian cancer. This review will summarize known facts about the pathological and molecular characteristics of ovarian cancer, the current status of ovarian cancer markers, as well as general information about mucins, the putative role of mucins in the progression of ovarian cancer and their potential use for the early diagnosis and treatment of this disease.

Association of single nucleotide polymorphisms in glycosylation genes with risk of epithelial ovarian cancer

Studies suggest that underglycosylation of the cell membrane mucin MUC1 may be associated with epithelial ovarian cancer. We identified 26 genes involved in glycosylation and examined 93 single nucleotide polymorphisms (SNP) with a minor allele frequency of > or =0.05 in relation to incident ovarian cancer. Cases were ascertained at the Mayo Clinic, Rochester, MN (n = 396) or a 48-county region in North Carolina (Duke University; n = 534). Ovarian cancer-free controls (n = 1,037) were frequency matched to the cases on age, race, and residence. Subjects were interviewed to obtain data on risk factors and a sample of blood for DNA and genotyped using the Illumina GoldenGate assay. We excluded subjects and individual SNPs with genotype call rates of <90%. Data were analyzed using logistic regression, with adjustment for age and residence. We fitted dominant, log additive, and recessive genetic models. Among Caucasians, nine SNPs in eight genes were associated with risk at P < 0.05 under at least one genetic model before adjusting for multiple testing. A SNP in GALNT1 (rs17647532) was the only one that remained statistically significant after Bonferroni adjustment for multiple testing but was not statistically significant in Hardy-Weinberg equilibrium among controls. Haplotype analyses revealed a global association of GALNT1 with risk (P = 0.038, under a recessive genetic model), which largely reflected a decreased risk of one haplotype (0.10 frequency; odds ratio, 0.07; P = 0.01) compared with the most common haplotype (0.39 frequency). These results suggest that genetic polymorphisms in the glycoslyation process may be novel risk factors for ovarian cancer.