Ovarian Cancer: A Clinical Challenge That Needs Some Basic Answers

Kate Lawrenson and Simon Gayther discuss two studies of ovarian cancer inPLoS Medicine, one on clinico-pathological heterogeneity and one on gene expression profiling

Cancer Stem Cells and Epithelial Ovarian Cancer

The cancer stem cell hypothesis is becoming more widely accepted as a model for carcinogenesis. Tumours are heterogeneous both at the molecular and cellular level, containing a small population of cells that possess highly tumourigenic “stem-cell” properties. Cancer stem cells (CSCs), or tumour-initiating cells, have the ability to self-renew, generate xenografts reminiscent of the primary tumour that they were derived from, and are chemoresistant. The characterisation of the CSC population within a tumour that drives its growth could provide novel target therapeutics against these cells specifically, eradicating the cancer completely. There have been several reports describing the isolation of putative cancer stem cell populations in several cancers; however, no defined set of markers has been identified that conclusively characterises “stem-like” cancer cells. This paper highlights the current experimental approaches that have been used in the field and discusses their limitations, with specific emphasis on the identification and characterisation of the CSC population in epithelial ovarian cancer

A Perl toolkit for LIMS development

BACKGROUND: High throughput laboratory techniques generate huge quantities of scientific data. Laboratory Information Management Systems (LIMS) are a necessary requirement, dealing with sample tracking, data storage and data reporting. Commercial LIMS solutions are available, but these can be both costly and overly complex for the task. The development of bespoke LIMS solutions offers a number of advantages, including the flexibility to fulfil all a laboratory's requirements at a fraction of the price of a commercial system. The programming language Perl is a perfect development solution for LIMS applications because of Perl's powerful but simple to use database and web interaction, it is also well known for enabling rapid application development and deployment, and boasts a very active and helpful developer community. The development of an in house LIMS from scratch however can take considerable time and resources, so programming tools that enable the rapid development of LIMS applications are essential but there are currently no LIMS development tools for Perl. RESULTS: We have developed ArrayPipeline, a Perl toolkit providing object oriented methods that facilitate the rapid development of bespoke LIMS applications. The toolkit includes Perl objects that encapsulate key components of a LIMS, providing methods for creating interactive web pages, interacting with databases, error tracking and reporting, and user and session management. The MT_Plate object provides methods for manipulation and management of microtitre plates, while a given LIMS can be encapsulated by extension of the core modules, providing system specific methods for database interaction and web page management. CONCLUSION: This important addition to the Perl developer's library will make the development of in house LIMS applications quicker and easier encouraging laboratories to create bespoke LIMS applications to meet their specific data management requirements

Rare Germline Genetic Variants and the Risks of Epithelial Ovarian Cancer.

A family history of ovarian or breast cancer is the strongest risk factor for epithelial ovarian cancer (EOC). Germline deleterious variants in the BRCA1 and BRCA2 genes confer EOC risks by age 80, of 44% and 17% respectively. The mismatch repair genes, particularly MSH2 and MSH6, are also EOC susceptibility genes. Several other DNA repair genes, BRIP1, RAD51C, RAD51D, and PALB2, have been identified as moderate risk EOC genes. EOC has five main histotypes; high-grade serous (HGS), low-grade serous (LGS), clear cell (CCC), endometrioid (END), and mucinous (MUC). This review examines the current understanding of the contribution of rare genetic variants to EOC, focussing on providing frequency data for each histotype. We provide an overview of frequency and risk for pathogenic variants in the known susceptibility genes as well as other proposed genes. We also describe the progress to-date to understand the role of missense variants and the different breast and ovarian cancer risks for each gene. Identification of susceptibility genes have clinical impact by reducing disease-associated mortality through improving risk prediction, with the possibility of prevention strategies, and developing new targeted treatments and these clinical implications are also discussed

Principles for the post-GWAS functional characterisation of risk loci

Several challenges lie ahead in assigning functionality to susceptibility SNPs. For example, most effect sizes are small relative to effects seen in monogenic diseases, with per allele odds ratios usually ranging from 1.15 to 1.3. It is unclear whether current molecular biology methods have enough resolution to differentiate such small effects. Our objective here is therefore to provide a set of recommendations to optimize the allocation of effort and resources in order maximize the chances of elucidating the functional contribution of specific loci to the disease phenotype. It has been estimated that 88% of currently identified disease-associated SNP are intronic or intergenic. Thus, in this paper we will focus our attention on the analysis of non-coding variants and outline a hierarchical approach for post-GWAS functional studies

BRCA1 and BRCA2 mutations in a population-based study of male breast cancer

Background: The contribution of BRCA1 and BRCA2 to the incidence of male breast cancer (MBC) in the United Kingdom is not known, and the importance of these genes in the increased risk of female breast cancer associated with a family history of breast cancer in a male first-degree relative is unclear. Methods: We have carried out a population-based study of 94 MBC cases collected in the UK. We screened genomic DNA for mutations in BRCA1 and BRCA2 and used family history data from these cases to calculate the risk of breast cancer to female relatives of MBC cases. We also estimated the contribution of BRCA1 and BRCA2 to this risk. Results: Nineteen cases (20%) reported a first-degree relative with breast cancer, of whom seven also had an affected second-degree relative. The breast cancer risk in female first-degree relatives was 2.4 times (95% confidence interval [CI] = 1.4–4.0) the risk in the general population. No BRCA1 mutation carriers were identified and five cases were found to carry a mutation in BRCA2. Allowing for a mutation detection sensitivity frequency of 70%, the carrier frequency for BRCA2 mutations was 8% (95% CI = 3–19). All the mutation carriers had a family history of breast, ovarian, prostate or pancreatic cancer. However, BRCA2 accounted for only 15% of the excess familial risk of breast cancer in female first-degree relatives. Conclusion: These data suggest that other genes that confer an increased risk for both female and male breast cancer have yet to be found

Genetic epidemiology of ovarian cancer and prospects for polygenic risk prediction.

Epithelial ovarian cancer (EOC) is a heterogeneous disease with a major heritable component. The different histotypes of invasive disease - high grade serous, clear cell, endometrioid and mucinous - are associated with different underlying genetic susceptibility and epidemiological and lifestyle risk factors, all of which contribute to the different biology and clinical characteristics of each histotype. A combination of familial and population based sequencing studies, and genome wide association studies (GWAS) have identified a range of genetic susceptibility alleles for EOC comprising rare but highly penetrant genes (e.g. BRCA1, BRCA2) that are responsible for familial clustering of ovarian cancer cases; more moderate penetrance susceptibility genes (e.g. BRIP1, RAD51C/D, MSH6); and multiple common but low penetrance susceptibility alleles identified by GWAS. Identifying genetic risk alleles for ovarian cancer has had a significant impact on disease prevention strategies; for example it is now routine clinical practice for individuals with germline BRCA1 and BRCA2 mutations to undergo risk reducing salpingo-oophorectomy. Because ovarian cancers are commonly diagnosed at a late clinical stage when the prognosis is poor, the continued development of genetic risk prediction and prevention strategies will represent an important approach to reduce mortality due to ovarian cancer. Advances in genomics technologies that enable more high-throughput genetic testing, combined with research studies that identify additional EOC risk alleles will likely provide further opportunities to establish polygenic risk prediction approaches, based on combinations of rare high/moderate penetrance susceptibility genes and common, low penetrance susceptibility alleles. This article reviews the current literature describing the genetic and epidemiological components of ovarian cancer risk, and discusses both the opportunities and challenges in using this information for clinical risk prediction and prevention

Super-Enhancer-Associated LncRNA UCA1 Interacts Directly with AMOT to Activate YAP Target Genes in Epithelial Ovarian Cancer

Long noncoding RNAs (lncRNAs) have emerged as critical regulators of tumorigenesis, and yet their mechanistic roles remain challenging to characterize. Here, we integrate functional proteomics with lncRNA-interactome profiling to characterize Urothelial Cancer Associated 1 (UCA1), a candidate driver of ovarian cancer development. Reverse phase protein array (RPPA) analysis indicates that UCA1 activates transcription coactivator YAP and its target genes. In vivo RNA antisense purification (iRAP) of UCA1 interacting proteins identified angiomotin (AMOT), a known YAP regulator, as a direct binding partner. Loss-of-function experiments show that AMOT mediates YAP activation by UCA1, as UCA1 enhances the AMOT-YAP interaction to promote YAP dephosphorylation and nuclear translocation. Together, we characterize UCA1 as a lncRNA regulator of Hippo-YAP signaling and highlight the UCA1-AMOT-YAP signaling axis in ovarian cancer development