Rebecca Sutphen

Determination of cancer risk associated with germ line BRCA1 missense variants by functional analysis

Germ line inactivating mutations in BRCA1 confer susceptibility for breast and ovarian cancer. However, the relevance of the many missense changes in the gene for which the effect on protein function is unknown remains unclear. Determination of which variants are causally associated with cancer is important for assessment of individual risk. We used a functional assay that measures the transactivation activity of BRCA1 in combination with analysis of protein modeling based on the structure of BRCA1 BRCT domains. In addition, the information generated was interpreted in light of genetic data. We determined the predicted cancer association of 22 BRCA1 variants and verified that the common polymorphism S1613G has no effect on BRCA1 function, even when combined with other rare variants. We estimated the specificity and sensitivity of the assay, and by meta-analysis of 47 variants, we show that variants with <45% of wild-type activity can be classified as deleterious whereas variants with >50% can be classified as neutral. In conclusion, we did functional and structure-based analyses on a large series of BRCA1 missense variants and defined a tentative threshold activity for the classification missense variants. By interpreting the validated functional data in light of additional clinical and structural evidence, we conclude that it is possible to classify all missense variants in the BRCA1 COOH-terminal region. These results bring functional assays for BRCA1 closer to clinical applicability.

Study of the molecular recognition of aptamers selected through ovarian cancer cell-SELEX.

Background Ovarian cancer is the most lethal gynecological malignancy, and the ovarian clear cell carcinoma subtype (OCCA) demonstrates a particularly poor response to standard treatment. Improvements in ovarian cancer outcomes, especially for OCCA, could be expected from a clearer understanding of the molecular pathology that might guide strategies for earlier diagnosis and more effective treatment. Methodology/Principal Findings Cell-SELEX technology was employed to develop new molecular probes for ovarian cancer cell surface markers. A total of thirteen aptamers with Kds to ovarian cancer cells in the pico- to nanomolar range were obtained. Preliminary investigation of the targets of these aptamers and their binding characteristics was also performed. Conclusions/Significance We have selected a series of aptamers that bind to different types of ovarian cancer, but not cervical cancer. Though binding to other cancer cell lines was observed, these aptamers could lead to identification of biomarkers that are related to cancer.

Proteomic Contributions to Personalized Cancer Care

Cancer impacts each patient and family differently. Our current understanding of the disease is primarily limited to clinical hallmarks of cancer, but many specific molecular mechanisms remain elusive. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies that improve patient prognosis are not widely available for most cancers. Individualized care plans, also described as personalized medicine, still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics holds great promise in contributing to the prevention and cure of cancer because it provides unique tools for discovery of biomarkers and therapeutic targets. As such, proteomics can help translate basic science discoveries into the clinical practice of personalized medicine. Here we describe how biological mass spectrometry and proteome analysis interact with other major patient care and research initiatives and present vignettes illustrating efforts in discovery of diagnostic biomarkers for ovarian cancer, development of treatment strategies in lung cancer, and monitoring prognosis and relapse in multiple myeloma patients.

LIN28B Polymorphisms Influence Susceptibility to Epithelial Ovarian Cancer

Defective microRNA (miRNA) biogenesis contributes to the development and progression of epithelial ovarian cancer (EOC). In this study, we examined the hypothesis that single nucleotide polymorphisms (SNP) in miRNA biogenesis genes may influence EOC risk. In an initial investigation, 318 SNPs in 18 genes were evaluated among 1,815 EOC cases and 1,900 controls, followed up by a replicative joint meta-analysis of data from an additional 2,172 cases and 3,052 controls. Of 23 SNPs from 9 genes associated with risk (empirical P < 0.05) in the initial investigation, the meta-analysis replicated 6 SNPs from the DROSHA, FMR1, LIN28, and LIN28B genes, including rs12194974 (G>A), an SNP in a putative transcription factor binding site in the LIN28B promoter region (summary OR = 0.90, 95% CI: 0.82-0.98; P = 0.015) which has been recently implicated in age of menarche and other phenotypes. Consistent with reports that LIN28B overexpression in EOC contributes to tumorigenesis by repressing tumor suppressor let-7 expression, we provide data from luciferase reporter assays and quantitative RT-PCR to suggest that the inverse association among rs12194974 A allele carriers may be because of reduced LIN28B expression. Our findings suggest that variants in LIN28B and possibly other miRNA biogenesis genes may influence EOC susceptibility.

Urine Collection and Processing for Protein Biomarker Discovery and Quantification

Background: Urine is a useful source of protein for biomarker discovery and assessment because it is readily available, can be obtained by noninvasive collection methods, and enables monitoring of a wide range of physiologic processes and diseases. Urine aliquots provide enough protein for multiple analyses, combining current protocols with new techniques. Conclusions: Standardized collection and processing protocols are now being established and new methods for protein detection and quantification are emerging to complement traditional immunoassays. The current state of urine collection, specimen processing, and storage is reviewed with regard to discovery and quantification of protein biomarkers for cancer. Cancer Epidemiol Biomarkers Prev; 19(4); 953–9. ©2010 AACR.

Single Nucleotide Polymorphisms in the TP53 Region and Susceptibility to Invasive Epithelial Ovarian Cancer

The p53 protein is critical for multiple cellular functions including cell growth and DNA repair. We assessed whether polymorphisms in the region encoding TP53 were associated with risk of invasive ovarian cancer. The study population includes a total of 5,206 invasive ovarian cancer cases (2,829 of which were serous) and 8,790 controls from 13 case-control or nested case-control studies participating in the Ovarian Cancer Association Consortium (OCAC). Three of the studies performed independent discovery investigations involving genotyping of up to 23 single nucleotide polymorphisms (SNP) in the TP53 region. Significant findings from this discovery phase were followed up for replication in the other OCAC studies. Mixed effects logistic regression was used to generate posterior median per allele odds ratios (OR), 95% probability intervals (PI), and Bayes factors (BF) for genotype associations. Five SNPs showed significant associations with risk in one or more of the discovery investigations and were followed up by OCAC. Mixed effects analysis confirmed associations with serous invasive cancers for two correlated (r(2) = 0.62) SNPs: rs2287498 (median per allele OR, 1.30; 95% PI, 1.07-1.57) and rs12951053 (median per allele OR, 1.19; 95% PI, 1.01-1.38). Analyses of other histologic subtypes suggested similar associations with endometrioid but not with mucinous or clear cell cancers. This large study provides statistical evidence for a small increase in risk of ovarian cancer associated with common variants in the TP53 region.

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 ≥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. (Cancer Epidemiol Biomarkers Prev 2008;17(2):397–404)

Identification of cell membrane protein stress-induced phosphoprotein 1 as a potential ovarian cancer biomarker using aptamers selected by cell systematic evolution of ligands by exponential enrichment.

In this paper, we describe the elucidation of the target of an aptamer against ovarian cancer previously obtained by cell-SELEX (SELEX = systematic evolution of ligands by exponential enrichment). The target’s identity, stress-induced phosphoprotein 1 (STIP1), was determined by mass spectrometry and validated by flow cytometry, using siRNA silencing and protein blotting. Initial oncologic studies show that the aptamer inhibits cell invasion, indicating that STIP1, which is currently under investigation as a potential biomarker for ovarian cancer, plays a critical role in this process. These results serve as an excellent example of how protein target identification of aptamers obtained by cell-SELEX can serve as a means to identify promising biomarker candidates and can promote the development of aptamers as a new drug class to block important oncological processes.

The genetic basis of Cowden’s syndrome: three novel mutations in PTEN/MMAC1/TEP1

Cowden’s syndrome (CS) is an autosomal dominant disorder associated with an increased risk of developing benign and malignant tumors in a variety of tissues, including the skin, thyroid, breast and brain. Women with CS are felt to have an increased risk of developing breast cancer, and virtually all women with CS develop bilateral fibrocystic disease of the breast. Recently, a series of germline mutations have been identified from CS families in a gene known as PTEN/MMAC1/TEP1. In this study, we used heteroduplex analysis and direct sequencing analysis and identified three novel germline mutations in the PTEN/MMAC1/TEP1 coding sequence from unrelated individuals with CS. We report a de novo transition (T→C) at nucleotide 335 in exon 5. This missense mutation resulted in a leucine to proline (CTA to CCA) change at codon 112. We also describe a novel splice site mutation (801+2T→G) in intron 7 that caused exon skipping in PTEN/MMAC1/TEP1 mRNA. The third mutation we report is a missense mutation, consisting of a transition (T→C) at nucleotide 202 in exon 3, resulting in a tyrosine to histidine (TAC to CAC) change at codon 68. Finally, we also detected a rare polymorphism in exon 7 of the PTEN/MMAC1/TEP1 coding sequence. These data confirm the observation that mutations of the PTEN/MMAC1/ TEP1 coding sequence are responsible for at least some cases of CS, and further define the spectrum of mutations in this autosomal dominant disorder.

Ovarian Cancer Risk Associated with Inherited Inflammation-Related Variants

The importance of inflammation pathways to the development of many human cancers prompted us to examine the associations between single-nucleotide polymorphisms (SNP) in inflammation-related genes and risk of ovarian cancer. In a multisite case-control study, we genotyped SNPs in a large panel of inflammatory genes in 930 epithelial ovarian cancer cases and 1,037 controls using a custom array and analyzed by logistic regression. SNPs with P < 0.10 were evaluated among 3,143 cases and 2,102 controls from the Follow-up of Ovarian Cancer Genetic Association and Interaction Studies (FOCI) post-GWAS collaboration. Combined analysis revealed association with SNPs rs17561 and rs4848300 in the interleukin gene IL1A which varied by histologic subtype (P(heterogeneity) = 0.03). For example, IL1A rs17561, which correlates with numerous inflammatory phenotypes, was associated with decreased risk of clear cell, mucinous, and endometrioid subtype, but not with the most common serous subtype. Genotype at rs1864414 in the arachidonate 5-lipoxygenase ALOX5 was also associated with decreased risk. Thus, inherited variation in IL1A and ALOX5 seems to affect ovarian cancer risk which, for IL1A, is limited to rarer subtypes. Given the importance of inflammation in tumorigenesis and growing evidence of subtype-specific features in ovarian cancer, functional investigations will be important to help clarify the importance of inherited variation related to inflammation in ovarian carcinogenesis.