Genetic intra‐tumour heterogeneity in epithelial ovarian cancer and its implications for molecular diagnosis of tumours

Genetic analysis of solid tumours using DNA or cDNA expression microarrays may enable individualized treatment based on the profiles of genetic changes that are identified from each patient. This could result in better response to adjuvant chemotherapy and, consequently, improved clinical outcome. So far, most research studies that have tested the efficacy of such an approach have sampled only single areas of neoplastic tissue from tumours; this assumes that the genetic profile within solid tumours is homogeneous throughout. The aim of this study was to evaluate the extent of genetic intra-tumour heterogeneity (ITH) within a series of epithelial ovarian cancers. Several different regions (five to eight regions) of tumour tissue from 16 grade 3, serous epithelial ovarian cancers were analysed for genetic alterations using a combination of microsatellite analysis and single nucleotide polymorphism (SNP) analysis, in order to establish the extent of ITH. Maximum parsimony tree analysis was applied to the genetic data from each tumour to evaluate the clonal relationship between different regions within tumours. Extensive ITH was identified within all ovarian cancers using both microsatellite and SNP analysis. Evolutionary analysis of microsatellite data suggested that the origin of all tumours was monoclonal, but that subsequent clonal divergence created mixed populations of genetically distinct cells within the tumour. SNP analysis suggested that ITH was not restricted to random genetic changes, but affected genes that have an important functional role in ovarian cancer development. The frequent occurrence of ITH within epithelial ovarian cancers may have implications for the interpretation of genetic data generated from emerging technologies such as DNA and mRNA expression microarrays, and their use in the clinical management of patients with ovarian cancer. The basis of genetic ITH and the possible implications for molecular approaches to clinical diagnosis of ovarian cancers may apply to other tumour types.