Expression profiling and individualisation of treatment for ovarian cancer

Ovarian cancer is the commonest cause of gynaecological cancer-related mortality. Patients with this disease generally undergo surgery followed by platinum-taxane chemotherapy, with additional chemotherapy at relapse. Although the prognosis for patients with advanced cancer is poor — a five-year survival of only 30–40% — there is a wide range of outcomes for individual patients. To date, clinico-pathological variables such as age, stage, grade, histology, debulking status and response to chemotherapy continue to provide the basis on which treatment decisions are made for individual patients. Immunohistochemical markers and information on p53 mutation status have been extensively evaluated in ovarian cancer, but have not yet been shown to be sufficiently informative to influence clinical decisions on a routine basis. The recent advent of expression profiling has provided a new impetus to identifying clinically useful prognostic markers. The ambition of personalised medicine through microarray-based profiling appears to be realistic, but further studies on large uniform cohorts are needed before this potential is fully realised.

Introduction

Ovarian cancer is the fourth commonest cause of cancer-related death in women. The majority of patients present with advanced disease, with an overall five-year survival rate of approximately 30–40% following debulking surgery, initial platinum-based chemotherapy and further chemotherapy at relapse [1, 2]. However, individual patients within this group demonstrate wide variations in response to treatment and in their overall survival (OS), which can range from a few months to several years.

One challenge in the management of these patients is, therefore, to accurately identify those most likely to benefit from particular therapies, so that patients unlikely to benefit can be spared the toxicity and cost of those interventions. Until recently, such attempts at individualising therapy were based on the measurement of, at most, a handful of molecular markers, none of which has yet achieved sufficient significance to be adopted into clinical practice [3].

The recent advent of microarray-based profiling technologies, however, has provided an opportunity to simultaneously examine the relationship between thousands of genes and clinical phenotypes. Using this approach, several groups have reported the ability to identify biologically and prognostically distinct tumour subgroups in a number of cancers. In the case of early breast cancer, a signature associated with metastasis-free survival has been identified, validated in an independent dataset, and is currently the subject of a multi-centre randomised clinical trial (MINDACT) to establish its utility in selecting patients for adjuvant chemotherapy in clinical practice [4, 5].

In this review, we examine attempts to apply microarray-based expression profiling to individualisation of therapy in ovarian cancer, focusing on the identification of signatures associated with the outcome of debulking surgery, response to chemotherapy and survival.