Comparison of the expression profile in breast cancer and ovarian cancer

Background

Until now, microarray studies exploited the differences between cancer and corresponding normal tissues or the molecular differences between tumor histotypes originating from one tissue. However, a sound understanding of neoplastic transformation and progression will benefit from comparison of tumors originating from diverse tissues, especially if they share some biological or clinical properties. Such analysis may aid to seek novel therapeutic targets, which are tumor-specific rather than tissue-specific.

The aim of our study was to compare the expression profile in breast cancer (BC) and ovarian cancer (OC), two female adenocarcinomas with similar genetic background and comparable chemosensitivity and radiosensitivity.

Methods

We compared expression profiles of 21 breast carcinomas and 17 serous ovarian carcinomas. We used the GeneChip U133 2.0 Plus microarray and a standard amplification procedure. We applied two methods of data preprocessing, RMA and MAS5 algorithm, and compared the results (only RMA data are shown).

Results

Both preprocessing approaches resulted in a huge difference between BC and OC (4427 genes, False Discovery Rate lower than 0.1%). To base the comparison on well-described transcripts, we used the signature of neoplastic transformation proposed by Rhodes and colleagues [1] in a large meta-analysis of 40 cancer datasets. From 168 probe sets found on the U133 2.0 array that were corresponding to Rhodes genes, 30 were differentially expressed between BC and OC (the strongest differences were within KDELR2, PLK1, PPP2R5C, ACLY, G3BP, MMP9, TRA1, HSPD1) and the remaining 138 probe sets did not show differences in expression. The results confirm the Rhodes signature in BC and OC; however, these genes were not able to ensure the full subdivision of tumors into breast and ovarian (hierarchical clustering). Furthermore, we analyzed the tissue-specific expression of genes that were either uniformly or differentially expressed in BC versus OC, by comparison with normal tissues (data from GeneAtlas 2.0 [2]).

In the next step, we performed the unsupervised analysis of BC and OC expression profiles. By Singular Value Decomposition we revealed that the samples were divided into three large clusters, which corresponded to two groups of breast carcinomas (BC1 and BC2) and a separate group of ovarian cancers (OC). These groups were properly separated by expression of estrogen receptor probe set ESR1, which was low in BC1, showed variable and moderate expression in OC and showed very high expression in BC2. The expression of ESR1 was similar to the ER result in routine clinical test, with the exception of two BC cases with high ESR1 and negative ER by immunohistochemistry.

Conclusions

There is large similarity in expression of neoplastic transformation signature genes between breast and ovarian carcinomas. Thirty genes from this set are differentially expressed between these cancers. The most prominent difference in the gene expression profile of these tumors could be explained by ESR1 gene expression and may be related to the tissue hormonal profile.