Molecular profiles of invasive mucinous and ductal carcinomas of the breast: a molecular case study

Estrogen switches pure mucinous breast cancer to invasive lobular carcinoma with mucinous features

Mucinous breast cancer (MBC) is mainly a disease of postmenopausal women. Pure MBC is rare and augurs a good prognosis. In contrast, MBC mixed with other histological subtypes of invasive disease loses the more favorable prognosis. Because of the relative rarity of pure MBC, little is known about its cell and tumor biology and relationship to invasive disease of other subtypes. We have now developed a human breast cancer cell line called BCK4, in which we can control the behavior of MBC. BCK4 cells were derived from a patient whose poorly differentiated primary tumor was treated with chemotherapy, radiation and tamoxifen. Malignant cells from a recurrent pleural effusion were xenografted in mammary glands of a nude mouse. Cells from the solid tumor xenograft were propagated in culture to generate the BCK4 cell line. Multiple marker and chromosome analyses demonstrate that BCK4 cells are human, near diploid and luminal, expressing functional estrogen, androgen, and progesterone receptors. When xenografted back into immunocompromised cycling mice, BCK4 cells grow into small pure MBC. However, if mice are supplemented with continuous estradiol, tumors switch to invasive lobular carcinoma (ILC) with mucinous features (mixed MBC), and growth is markedly accelerated. Tamoxifen prevents the expansion of this more invasive component. The unexpected ability of estrogens to convert pure MBC into mixed MBC with ILC may explain the rarity of the pure disease in premenopausal women. These studies show that MBC can be derived from lobular precursors and that BCK4 cells are new, unique models to study the phenotypic plasticity, hormonal regulation, optimal therapeutic interventions, and metastatic patterns of MBC.

Gene expression profiling of breast cancer

DNA microarray platforms for gene expression profiling were invented relatively recently, and breast cancer has been among the earliest and most intensely studied diseases using this technology. The molecular signatures so identified help reveal the biologic spectrum of breast cancers, provide diagnostic tools as well as prognostic and predictive gene signatures, and may identify new therapeutic targets. Data are best presented in an open access format to facilitate external validation, the most crucial step in identifying robust, reproducible gene signatures suitable for clinical translation. Clinically practical applications derived from full expression profile studies already in use include reduced versions of microarrays representing key discriminatory genes and therapeutic targets, quantitative polymerase chain reaction assays, or immunohistochemical surrogate panels (suitable for application to standard pathology blocks). Prospective trials are now underway to determine the value of such tools for clinical decision making in breast cancer; these efforts may serve as a model for using such approaches in other tumor types.

Integrated analysis of independent gene expression microarray datasets improves the predictability of breast cancer outcome

BACKGROUND

Gene expression profiles based on microarray data have been suggested by many studies as potential molecular prognostic indexes of breast cancer. However, due to the confounding effect of clinical background, independent studies often obtained inconsistent results. The current study investigated the possibility to improve the quality and generality of expression profiles by integrated analysis of multiple datasets. Profiles of recurrence outcome were derived from two independent datasets and validated by a third dataset.

RESULTS

The clinical background of patients significantly influenced the content and performance of expression profiles when the training samples were unbalanced. The integrated profiling of two independent datasets lead to higher classification accuracy (71.11% vs. 70.59%) and larger ROC curve area (0.789 vs. 0.767) of the testing samples. Cell cycle, especially M phase mitosis, was significantly overrepresented by the 60-gene profile obtained from integrated analysis (p < 0.0001). This profiles significantly differentiated poor and good prognosis in a third patient cohort (p = 0.003). Simulation procedures demonstrated that the change of profile specificity had more instant influence on the performance of expression profiles than the change of profile sensitivity.

CONCLUSION

The current study confirmed that the gene expression profile generated by integrated analysis of multiple datasets achieved better prediction of breast cancer recurrence. However, the content and performance of profiles was confounded by clinical background of training patients. In future studies, prognostic profile applicable to the general population should be derived from more diversified and balanced patient cohorts in larger scale.

Novel markers for differentiation of lobular and ductal invasive breast carcinomas by laser microdissection and microarray analysis

Background

Invasive ductal and lobular carcinomas (IDC and ILC) are the most common histological types of breast cancer. Clinical follow-up data and metastatic patterns suggest that the development and progression of these tumors are different. The aim of our study was to identify gene expression profiles of IDC and ILC in relation to normal breast epithelial cells.

Methods

We examined 30 samples (normal ductal and lobular cells from 10 patients, IDC cells from 5 patients, ILC cells from 5 patients) microdissected from cryosections of ten mastectomy specimens from postmenopausal patients. Fifty nanograms of total RNA were amplified and labeled by PCR and in vitro transcription. Samples were analysed upon Affymetrix U133 Plus 2.0 Arrays. The expression of seven differentially expressed genes (CDH1, EMP1, DDR1, DVL1, KRT5, KRT6, KRT17) was verified by immunohistochemistry on tissue microarrays. Expression of ASPN mRNA was validated by in situ hybridization on frozen sections, and CTHRC1, ASPN and COL3A1 were tested by PCR.

Results

Using GCOS pairwise comparison algorithm and rank products we have identified 84 named genes common to ILC versus normal cell types, 74 named genes common to IDC versus normal cell types, 78 named genes differentially expressed between normal ductal and lobular cells, and 28 named genes between IDC and ILC. Genes distinguishing between IDC and ILC are involved in epithelial-mesenchymal transition, TGF-beta and Wnt signaling. These changes were present in both tumor types but appeared to be more prominent in ILC. Immunohistochemistry for several novel markers (EMP1, DVL1, DDR1) distinguished large sets of IDC from ILC.

Conclusion

IDC and ILC can be differentiated both at the gene and protein levels. In this study we report two candidate genes, asporin (ASPN) and collagen triple helix repeat containing 1 (CTHRC1) which might be significant in breast carcinogenesis. Besides E-cadherin, the proteins validated on tissue microarrays (EMP1, DVL1, DDR1) may represent novel immunohistochemical markers helpful in distinguishing between IDC and ILC. Further studies with larger sets of patients are needed to verify the gene expression profiles of various histological types of breast cancer in order to determine molecular subclassifications, prognosis and the optimum treatment strategies.

Gene expression analysis using human cancer xenografts to identify novel predictive marker genes for the efficacy of 5-fluorouracil-based drugs

The development of a diagnostic method for predicting the therapeutic efficacy or toxicity of anticancer drugs is a critical issue. We carried out a gene expression analysis to identify genes whose expression profiles were correlated with the sensitivity of 30 human tumor xenografts to 5-fluorouracil (5-FU)-based drugs (tegafur + uracil [UFT], tegafur + gimeracil + oteracil [S-1], 5'-deoxy-5-fluorouridine [5'-DFUR], and N4-pentyloxycarbonyl-5'-deoxy-5-fluorocytidine [capecitabine]), as well as three other drugs (cisplatin [CDDP], irinotecan hydrochloride [CPT-11], and paclitaxel) that have different modes of action. In the present study, we focused especially on the fluoropyrimidines. The efficacy of all anticancer drugs was assayed using human tumor xenografts in nude mice. The mRNA expression profile of each of these xenografts was analyzed using a Human Focus array. Correlation analysis between the gene expression profiles and the chemosensitivities of seven drugs identified 39 genes whose expression levels were correlated significantly with multidrug sensitivity, and we suggest that the angiogenic pathway plays a pivotal role in resistance to fluoropyrimidines. Furthermore, many genes showing specific correlations with each drug were also identified. Among the candidate genes associated with 5-FU resistance, the dihydropyrimidine dehydrogenase mRNA expression profiles of the tumors showed a significant negative correlation with chemosensitivity to all of the 5-FU based drugs except for S-1. Therefore, the administration of S-1 might be an effective strategy for the treatment of high dihydropyrimidine dehydrogenase-expressing tumors. The results of the present study may enhance the prediction of tumor response to anticancer drugs and contribute to the development of tailor-made chemotherapy.

Differentiation of tumours of ductal and lobular origin: II. Genomics of invasive ductal and lobular breast carcinomas

Breast cancer is considered to be a multifactorial disorder caused by both genetic and non-genetic factors. Different histological types of breast cancer differ in response to treatment and may have a divergent clinical course. Breast tissue is heterogeneous, with components of epithelial, mesenchymal, endothelial and lymphopoietic derivation. The genetic heterogeneity of invasive breast cancer is reflected by the wide spectrum of histological types and differentiation grades. Nevertheless, the influences of these cell types on the tumour's total pattern of gene expression can be estimated analytically. Microarrays permit total tissue analysis and provide a stable molecular portrait of tumours. Some investigations suggest differences in the gene expression profiling for ductal and lobular carcinomas. It has been reported that inactivating mutations of the E-cadherin gene are very frequent in infiltrating lobular breast carcinomas. Other than altered expression of E-cadherin, little is known about the underlying biology that distinguishes ductal and lobular tumour subtypes. However, about 8 genes have been identified differentially which are expressed in lobular and ductal cancers: E-CD, survivin, cathepsin B, TPI1, SPRY1, SCYA14, TFAP2B, and thrombospondin 4, osteopontin, HLA-G, and CHC1. Expression profiling of breast cancers can be used diagnostically to distinguish individual histologic subclassifications and may guide the selection of target therapeutics. However, future approaches will need to include methods for high throughput clinical validation and the ability to analyze microscopic samples.

Dissecting progressive stages of 5-fluorouracil resistance in vitro using RNA expression profiling

Resistance to anticancer drugs such as the widely used antimetabolite 5-fluorouracil (FU) is one of the most important obstacles to cancer chemotherapy. Using GeneChip arrays, we compared the expression profile of different stages of FU resistance in colon cancer cells after in vitro selection of low-, intermediate- and high-resistance phenotypes. Drug resistance was associated with significant changes in expression of 330 genes, mainly during early or intermediate stage. Functional annotation revealed a majority of genes involved in signal transduction, cell adhesion and cytoskeleton with subsequent alterations in apoptotic response, cell cycle control, drug transport, fluoropyrimidine metabolism and DNA repair. A set of 33 genes distinguished all resistant subclones from sensitive progenitor cells. In the early stage, downregulation of collagens and keratins, together with upregulation of profilin 2 and ICAM-2, suggested cytoskeletal changes and cell adhesion remodeling. Interestingly, 6 members of the S100 calcium-binding protein family were suppressed. Acquisition of the intermediate-resistance phenotype included upregulation of the well-known drug resistance gene ABCC6 (ATP-binding cassette subfamily C member 6). The very small number of genes affected during transition to high resistance included the primary FU target thymidylate synthase. Although limited to an in vitro model, our data suggest that resistance to FU cannot be explained by known mechanisms alone and substantially involves a wide molecular repertoire. This study emphasizes the understanding of resistance as a time-depending process: the cell is particularly challenged at the beginning of this process, while acquisition of the high-resistance phenotype seems to be less demanding.

Prognostic molecular markers in early breast cancer

A multitude of molecules involved in breast cancer biology have been studied as potential prognostic markers. In the present review we discuss the role of established molecular markers, as well as potential applications of emerging new technologies. Those molecules used routinely to make treatment decisions in patients with early-stage breast cancer include markers of proliferation (e.g. Ki-67), hormone receptors, and the human epidermal growth factor receptor 2. Tumor markers shown to have prognostic value but not used routinely include cyclin D1 and cyclin E, urokinase-like plasminogen activator/plasminogen activator inhibitor, and cathepsin D. The level of evidence for other molecular markers is lower, in part because most studies were retrospective and not adequately powered, making their findings unsuitable for choosing treatments for individual patients. Gene microarrays have been successfully used to classify breast cancers into subtypes with specific gene expression profiles and to evaluate prognosis. RT-PCR has also been used to evaluate expression of multiple genes in archival tissue. Proteomics technologies are in development.