Analysis of the interaction of extracellular matrix and phenotype of bladder cancer cells

Abstract

Background: The extracellular matrix has a major effect upon the malignant properties of bladder cancer cells both in vitro in 3-dimensional culture and in vivo. Comparing gene expression of several bladder cancer cells lines grown under permissive and suppressive conditions in 3-dimensional growth on cancer-derived and normal-derived basement membrane gels respectively and on plastic in conventional tissue culture provides a model system for investigating the interaction of malignancy and extracellular matrix. Understanding how the extracellular matrix affects the phenotype of bladder cancer cells may provide important clues to identify new markers or targets for therapy.

Methods: Five bladder cancer cell lines and one immortalized, but non-tumorigenic, urothelial line were grown on Matrigel, a cancer-derived ECM, on SISgel, a normal-derived ECM, and on plastic, where the only ECM is derived from the cells themselves. The transcriptomes were analyzed on an array of 1186 well-annotated cancer derived cDNAs containing most of the major pathways for malignancy. Hypervariable genes expressing more variability across cell lines than a set expressing technical variability were analyzed further. Expression values were clustered, and to identify genes most likely to represent biological factors, statistically over-represented ontologies and transcriptional regulatory elements were identified.

Results: Approximately 400 of the 1186 total genes were expressed 2 SD above background. Approximately 100 genes were hypervariable in cells grown on each ECM, but the pattern was different in each case. A core of 20 were identified as hypervariable under all 3 growth conditions, and 33 were hypervariable on both SISgel and Matrigel, but not on plastic. Clustering of the hypervariable genes showed very different patterns for the same 6 cell types on the different ECM. Even when loss of cell cycle regulation was identified, different genes were involved, depending on the ECM. Under the most permissive conditions of growth where the malignant phenotype was fully expressed, activation of AKT was noted. TGFbeta1 signaling played a major role in the response of bladder cancer cells to ECM. Identification of TREs on genes that clustered together suggested some clustering was driven by specific transcription factors.

Conclusion: The extracellular matrix on which cancer cells are grown has a major effect on gene expression. A core of 20 malignancy-related genes were not affected by matrix, and 33 were differentially expressed on 3-dimensional culture as opposed to plastic. Other than these genes, the patterns of expression were very different in cells grown on SISgel than on Matrigel or even plastic, supporting the hypothesis that growth of bladder cancer cells on normal matrix suppresses some malignant functions. Unique underlying regulatory networks were driving gene expression and could be identified by the approach outlined here.

Figure 1

Venn diagram of hypervariable genes expressed on different matrixes. Each circle contains number of hypervariable genes unique and/or common for different matrixes. The size of circles does not represent relative number of genes in each group.

Figure 2

Hierarchical clustering of hypervariable genes across different cell lines on different matrixes. Hierarchical clustering of genes up- (red color) or downregulated (green color) on the given 6 cell lines. A, B and C show clustering of genes expressed on Matrigel, Plastic and SISgel, respectively. Colored bars outline individual clusters used for subsequent analysis.

Figure 3

Filtered maps of TREs on gene clusters of hypervariable genes identified in cells growing on different matrixes. A, B and C show significantly significantly overrepresented (p < 0.05) TREs from cells grown on Matrigel, Plastic and SISgel, respectively. Colored bars represent individual gene clusters. The TREs and the transcription factors that bind to them (linked to Enterz Gene) are CCAAT/NFYC; CP2/TFCP2; CREB/CREBP; CRE-BP1/ATF2; E2F/E2F2; Elk-1/ELK1; ER/ESR1; GATA-3/GATA-3; Hand1/HAND1; HFH-3/FOXI1; HNF-1/TCF1; HNF-3/FOXA1; myogenin/MYOG; Oct-1/POU2F1; v-Myb/MYB; XFD-3/FOXA1.