The genesis and evolution of high-grade serous ovarian cancer

RC, Berchuck A, Berek JS, Brenton JD, Coukos G, Crum CC, Drapkin R, Etemadmoghadam D, Friedlander M, Gabra H, Kaye SB, Lord CJ, Lengyel E, Levine DA, McNeish IA, Menon U, Mills GB, Nephew KP, Oza AM, Sood AK, Stronach EA, Walczak H, Bowtell DD, Balkwill FR. Rethinking ovarian cancer: recommendations for improving outcomes

There have been major advances in our understanding of the cellular and molecular biology of the human malignancies that are collectively referred to as ovarian cancer. At a recent Helene Harris Memorial Trust meeting, an international group of researchers considered actions that should be taken to improve the outcome for women with ovarian cancer. Nine major recommendations are outlined in this Opinion article.

High throughput interrogation of somatic mutations in high grade serous cancer of the ovary

Background

Epithelial ovarian cancer is the most lethal of all gynecologic malignancies, and high grade serous ovarian cancer (HGSC) is the most common subtype of ovarian cancer. The objective of this study was to determine the frequency and types of point somatic mutations in HGSC using a mutation detection protocol called OncoMap that employs mass spectrometric-based genotyping technology.

Methodology/Principal Findings

The Center for Cancer Genome Discovery (CCGD) Program at the Dana-Farber Cancer Institute (DFCI) has adapted a high-throughput genotyping platform to determine the mutation status of a large panel of known cancer genes. The mutation detection protocol, termed OncoMap has been expanded to detect more than 1000 mutations in 112 oncogenes in formalin-fixed paraffin-embedded (FFPE) tissue samples. We performed OncoMap on a set of 203 FFPE advanced staged HGSC specimens. We isolated genomic DNA from these samples, and after a battery of quality assurance tests, ran each of these samples on the OncoMap v3 platform. 56% (113/203) tumor samples harbored candidate mutations. Sixty-five samples had single mutations (32%) while the remaining samples had ≥2 mutations (24%). 196 candidate mutation calls were made in 50 genes. The most common somatic oncogene mutations were found in EGFR, KRAS, PDGRFα, KIT, and PIK3CA. Other mutations found in additional genes were found at lower frequencies (<3%).

Conclusions/Significance

Sequenom analysis using OncoMap on DNA extracted from FFPE ovarian cancer samples is feasible and leads to the detection of potentially druggable mutations. Screening HGSC for somatic mutations in oncogenes may lead to additional therapies for this patient population.

Clear cell carcinoma of the ovary: a report from the first Ovarian Clear Cell Symposium, June 24th, 2010

OBJECTIVES

Recent literature has highlighted histological types of ovarian carcinoma as distinct diseases, each with unique clinical and molecular features. Historically, the diagnosis of ovarian clear cell carcinoma (CCC) has been of concern to both patients and physicians due to reports that CCC is associated with a worse prognosis than the more common serous type of ovarian carcinoma (HGSC). This review discusses the unique features of ovarian CCC.

METHODS

In June of 2010, a group of researchers and clinicians convened in Vancouver to review and discuss the clinical, pathological, molecular, and treatment-related features of CCC.

RESULTS

CCC is the second most common type of ovarian epithelial cancer, representing 5-25% of ovarian carcinomas. It is characterised by its association with endometriosis, and frequent mutations of ARID1A and PIK3CA. Low-stage CCC appears to have a better outcome than stage matched HGSC, while the opposite is true for high-stage disease, suggesting that the current standard treatments applied to HGSC are ineffective for CCC.

CONCLUSIONS

Ovarian CCC is highly distinct from HGSC, and a clearer understanding of the basic biology of this disease is needed. Alternative therapies should be explored: irradiation and targeting disease-specific molecular markers should be examined in greater detail. Finally, novel approaches to clinical trial design are needed due to the smaller numbers of patients affected.