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. 2008 Jan 22:7:8.
doi: 10.1186/1476-4598-7-8.

An integrative model for recurrence in ovarian cancer

Alexandros Laios  1 , Sharon A O'Toole, Richard Flavin, Cara Martin, Martina Ring, Noreen Gleeson, Tom D'Arcy, Eamonn P J McGuinness, Orla Sheils, Brian L Sheppard, John J O' Leary
Affiliations

An integrative model for recurrence in ovarian cancer

Alexandros Laios et al. Mol Cancer. .
No abstract available

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Figures

Figure 1
Figure 1
Flow chart of our study design. 2 cohorts were used in this study: In the first one, we selected a homogeneous series of primary and recurrent serous papillary adenocarcinomas from different patients(Between patient cohort). The second cohort consisted of 3 paired ovarian cancers (primary and recurrent samples coming from the same patient) but of different histology (Within patient cohort). Selected genes identified from microarray experiments were validated for both cohorts and a subset of these genes (n = 12) were validated in an independent set (test set) of 13 serous papillary adenocarcinomas using TaqMan® PCR.
Figure 2
Figure 2
Hierarchical cluster heatmaps demonstrating distinct patterns of gene expression between primary and recurrent ovarian tumors. (a) Heatmap of the ovarian tumors in cohort 1 based on the FDR0.1 list with the primary clustering on the left and the recurrent samples on the right. Vertical bars represent the samples and the horizontal bars represent the genes. Green bars reflect downregulated genes and red bars upregulated genes. (b) Heat map discriminating recurrent (left) and primary (right) ovarian tumours in cohort 2 based on the p0.01 list. P, primary tumours; R, recurrent tumors.
Figure 3
Figure 3
Gene families involved in the molecular regulation of recurrence in ovarian cancer. Some of the upregulated genes in recurrent compared to primary ovarian carcinomas that we validated in cohort 2 belong in the same gene families with some of the upregulated genes validated in cohort 1. Upregulation of tight junction proteins and EGFR ligands, development of a cytokine response via interleukin receptors and intracellular signaling via calcium binding S100 proteins seem to contribute to the "recurrent" signature and possibly have a role in drug resistance.
Figure 4
Figure 4
TaqMan® PCR validation of target genes identified in both training and test sets. Gene selection for TaqMan® validation was based on the most differentially expressed genes from the p and FDR value list with a fold change > 4 but also included genes that had a 2–4 fold change and also some genes involved in the most differentially expressed pathways. Priority was given to selection of genes upregulated in recurrent compared to primary samples, which might provide "recurrence" signatures in ovarian cancer. Upregulated genes validated in both cohorts were alternatively interrogated (external validation) and further advanced for validation in the test set. Independent validation on a test set refers to completely distinct samples of serous histology that were not previously employed in marker development (n = number of gene targets selected for validation).
Figure 5
Figure 5
TaqMan® PCR validation of microarray experiments in cohort 1. The fold changes in the arrays were plotted against the relative quantitation from TaqMan® in recurrent vs primary tumours. The TaqMan® values are displayed in blue and the array results in red. Spearman correlation r showed high concordance between the 2 experiments.
Figure 6
Figure 6
TaqMan® PCR validation of microarray experiments in cohort 2. A similar concordance was observed as in cohort 1.
Figure 7
Figure 7
External validation of a subset of upregulated genes in cohort 2 that validated in cohort 1. Bars indicate the relative overexpression of target genes in recurrent vs primary tumors. IL1R2 and ZNF218 gave the best distinction between recurrent and primary tumors with greater than twofold changes.
Figure 8
Figure 8
Independent TaqMan® PCR validation of a set of selected genes from both cohorts in a test set of serous papillary adenocarcinomas of varying grade and stage. BTC and FGF2 provided the best distinction between recurrent and primary tumours with fold changes of 2.8 and 2.71 respectively.
Figure 9
Figure 9
An integrative model for recurrence in ovarian cancer. Schematic representation of putative genes and gene families involved in the recurrence of ovarian carcinomas. According to our current working concept, tumour cells during relapse produce adhesion molecules to mediate attachment and invasion via co-overexpression of matrix metalloproteinases, cytokines and inflammatory mediators to stimulate survival and a variety of growth factors bound to their cognate receptors to fully proliferate in order to confront and modulate their immediate environment, which they must eventually overtake.
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