Global gene expression analysis of early response to chemotherapy treatment in ovarian cancer spheroids - PubMed (original) (raw)
Global gene expression analysis of early response to chemotherapy treatment in ovarian cancer spheroids
Sylvain L'Espérance et al. BMC Genomics. 2008.
Abstract
Background: Chemotherapy (CT) resistance in ovarian cancer (OC) is broad and encompasses diverse unrelated drugs, suggesting more than one mechanism of resistance. To better understand the molecular mechanisms controlling the immediate response of OC cells to CT exposure, we have performed gene expression profiling in spheroid cultures derived from six OC cell lines (OVCAR3, SKOV3, TOV-112, TOV-21, OV-90 and TOV-155), following treatment with 10,0 microM cisplatin, 2,5 microM paclitaxel or 5,0 microM topotecan for 72 hours.
Results: Exposure of OC spheroids to these CT drugs resulted in differential expression of genes associated with cell growth and proliferation, cellular assembly and organization, cell death, cell cycle control and cell signaling. Genes, functionally involved in DNA repair, DNA replication and cell cycle arrest were mostly overexpressed, while genes implicated in metabolism (especially lipid metabolism), signal transduction, immune and inflammatory response, transport, transcription regulation and protein biosynthesis, were commonly suppressed following all treatments. Cisplatin and topotecan treatments triggered similar alterations in gene and pathway expression patterns, while paclitaxel action was mainly associated with induction of genes and pathways linked to cellular assembly and organization (including numerous tubulin genes), cell death and protein synthesis. The microarray data were further confirmed by pathway and network analyses.
Conclusion: Most alterations in gene expression were directly related to mechanisms of the cytotoxics actions in OC spheroids. However, the induction of genes linked to mechanisms of DNA replication and repair in cisplatin- and topotecan-treated OC spheroids could be associated with immediate adaptive response to treatment. Similarly, overexpression of different tubulin genes upon exposure to paclitaxel could represent an early compensatory effect to this drug action. Finally, multicellular growth conditions that are known to alter gene expression (including cell adhesion and cytoskeleton organization), could substantially contribute in reducing the initial effectiveness of CT drugs in OC spheroids. Results described in this study underscore the potential of the microarray technology for unraveling the complex mechanisms of CT drugs actions in OC spheroids and early cellular response to treatment.
Figures
Figure 1
Functional analysis for a dataset of differentially expressed genes (≥1.5 fold) in OC spheroids following CT drugs treatments. A. Functional analysis following all drugs (cisplatin, topotecan and paclitaxel) treatment, B. Functional analysis following cisplatin treatment. Top functions that meet a _p_-value cutoff of 0.05 are displayed.
Figure 2
Network analysis of dynamic gene expression in OC spheroids based on the 1.5-fold common gene expression list obtained following treatment with all CT drugs used (cisplatin, topotecan and paclitaxel). The five top-scoring networks were merged and are displayed graphically as node (genes/gene product) and edges (the biological relationships between the nodes). Intensity of the node color indicates the degree of up- (red) or downregulation (green). Nodes are displayed using various shapes that represent the functional class of the gene product (square, cytokine, vertical oval, transmembrane receptor, rectangle, nuclear receptor, diamond, enzyme, rhomboid, transporter, hexagon, translation factor, horizontal oval, transcription factor, circle, other). Edges are displayed with various labels that describe the nature of relationship between the nodes: ---- binding only, → acts on. The length of an edge reflect the evidence supporting that node-to-node relationship, in that edges supported by article from literature are shorter. Dotted edges represent indirect interaction.
Figure 3
Network analysis of dynamic gene expression in OC spheroids based on the 1.5-fold common gene expression list obtained following cisplatin treatment. The three top-scoring networks were merged and are displayed graphically as nodes (genes/gene products) and edges (the biological relationships between the nodes). Figure legends are as described in Fig. 2.
Figure 4
Functional analysis for a dataset of differentially expressed genes (≥1.5 fold) in OC spheroids following CT drugs treatments. A. Functional analysis following topotecan treatment, B. Functional analysis following paclitaxel treatment. Top functions that meet a _p_-value cutoff of 0.05 are displayed.
Figure 5
Network analysis of dynamic gene expression in OC spheroids based on the 1.5-fold common gene expression list obtained following topotecan treatment. The five top-scoring networks were merged and are displayed graphically as nodes (genes/gene products) and edges (the biological relationships between the nodes). Figure legends are as described in Fig. 2.
Figure 6
Network analysis of dynamic gene expression in OC spheroids based on the 1.5-fold common gene expression list obtained following paclitaxel treatment. The three top-scoring networks were merged and are displayed graphically as nodes (genes/gene products) and edges (the biological relationships between the nodes). Figure legends are as described in Fig. 2.
Figure 7
A. Example images of compact and aggregate spheroid structures derived from OC cells. B. Hierarchical clustering of OC spheroids following treatment with all used drugs (cisplatin, topotecan and paclitaxel (taxol)), that discriminates between compact spheroids and aggregates. A subset of candidate genes were initially obtained by filtering on signal intensity (2-fold), retaining 527 genes. One-way ANOVA parametric test (Welch _t_-test, variances not assumed equal, p ≤ 0.03) further selected 85 genes. Clustering analysis based on the 85 gene list was performed using the standard Condition Tree algorithm provided in GeneSpring. The mean appears grey, whereas red signifies up-regulation, and green signifies down-regulation (see legend bar). Compact spheroids are indicated in brown, aggregates are indicated in grey. Each cell line is indicated with different color.
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