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

Abstract

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.

Lyapunov–Schmidt and Centre Manifold Reduction Methods for Nonlocal PDEs Modelling Animal Aggregations

“…However, if the DNA is damaged or not copied correctly, the new damaged cells will either die or start to proliferate in an uncontrolled manner, creating a signalling of oncogenes that act by mimicking growth signalling (Hanahan & Weinberg, 2000), eventually leading to an abnormal mass of tissues from cells that differ in clinically important phenotypic features (Marusyk et al, 2012). More precisely, tumour formation is a result of clonal expansion driven by somatic mutation, developed by a single precursor (monoclonal) that undergoes genetic and biological changes (Khalique et al, 2007;Nowell, 1976). This transformation of normal cells to cancer cells is a multistep process described via the steps of hyperplasia, premalignant change and dysplasia (Beckmann et al, 1997).…”

“…This transformation of normal cells to cancer cells is a multistep process described via the steps of hyperplasia, premalignant change and dysplasia (Beckmann et al, 1997). Cancer cells lose their ability to regulate genome stability which leads to further genetic changes and tumour development (Khalique et al, 2007). Over the last three decades it has been shown experimentally that tumours consist of heterogeneous populations of cells, which are the result of genetic instability (Stackpole, 1983; 3 of 36 new mathematical models of parabolic type have been derived to describe these cell-cell and cell-matrix adhesion processes (Armstrong et al, 2006;Dyson et al, 2016;Gerisch & Chaplain, 2008;Gerisch & Painter, 2010;Green et al, 2010;Painter et al, 2015).…”

Mathematical modelling of cancer invasion: The multiple roles of TGF-β pathway on tumour proliferation and cell adhesion

“…Through these processes, cancer cells become metastatic and form new colonies at distant sites. Experimental studies 33,41 have shown that tumours consist of heterogeneous populations of cells, which are the result of genetic instability. Intra-tumour heterogeneity appears in almost all phenotypic cell features: from cell morphology, to gene expression, motility, proliferation, immunogenicity and metastatic potential.…”

The clonal evolution of metastases from primary serous epithelial ovarian cancers

“…Recent studies have also suggested that there is extensive genetic heterogeneity within ovarian tumors, which may hinder a better understanding of cancer development. 4 Primary ovarian cancers tend to spread, at first, within the peritoneal cavity and the omentum, and are frequently associated with ascites, a fluid rich in growth factors and tumor cells disseminated from the primary cancer that fills the peritoneum. Tumor spread to more distant sites, including the contralateral ovary might also occur; bilateral ovarian cancers almost always represents a primary tumor and its metastasis rather than dual primary cancers.…”