Systemic spread is an early step in breast cancer.

It is widely accepted that metastasis is a late event in cancer progression. Here, however, we show that tumor cells can disseminate systemically from earliest epithelial alterations in HER-2 and PyMT transgenic mice and from ductal carcinoma in situ in women. Wild-type mice transplanted with single premalignant HER-2 transgenic glands displayed disseminated tumor cells and micrometastasis in bone marrow and lungs. The number of disseminated cancer cells and their karyotypic abnormalities were similar for small and large tumors in patients and mouse models. When activated by bone marrow transplantation into wild-type recipients, 80 early-disseminated cancer cells sufficed to induce lethal carcinosis. Therefore, release from dormancy of early-disseminated cancer cells may frequently account for metachronous metastasis.

Breast cancer: a candidate gene approach across the estrogen metabolic pathway.

Polymorphisms within the estrogen metabolic pathway are prime candidates for a possible association with breast cancer risk. We investigated 11 genes encoding key proteins of this pathway for their potential contribution to breast cancer risk. Of these CYP17A1, CYP19A1, EPHX1, HSD17B1, SRD5A2, and PPARG2 participate in biosynthesis, CYP1A1, CYP1B1, COMT, GSTP1, and SOD2 in catabolism and detoxification. We performed a population-based case-control study with 688 incident breast cancer cases and 724 controls from Germany and genotyped 18 polymorphisms by matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), PCR based RFLP (restriction fragment length polymorphism), and TaqMan allelic discrimination. Genotype frequencies were compared between cases and controls and odds ratios were calculated by conditional logistic regression. Further statistical analyses were based on cluster analysis, multifactor dimensionality reduction, logic regression, and global testing. Single factor analyses pointed to CYP1B1_1294_GG as a possible breast cancer risk modulator (OR = 2.57; 95% CI: 1.34-4.93) and two way stratification suggested associations between BMI > or = 30 kg/m(2) and COMT_472_GG (P = 0.0076 and P = 0.0026), BMI < 20 kg/m(2) and HSD17B1_937_GG (P = 0.0082) as well as CYP17A1_-34_CC and HRT use > or =10 years (P = 0.0063). Following correction for multiple testing none of these associations remained significant. No significant association between breast cancer risk and genetic polymorphisms was observed in multifactor analyses. The tested polymorphisms of the estrogen metabolic pathway may not play a direct role in breast cancer risk. Therefore, future association studies should be extended to other polymorphisms and other regulatory pathways.

High-resolution genomic profiling reveals association of chromosomal aberrations on 1q and 16p with histologic and genetic subgroups of invasive breast cancer.

PURPOSE: Invasive ductal carcinoma and invasive lobular carcinoma (ILC) represent the major histologic subtypes of invasive breast cancer. They differ with regard to presentation, metastatic spread, and epidemiologic features. To elucidate the genetic basis of these differences, we analyzed copy number imbalances that differentiate the histologic subtypes. EXPERIMENTAL DESIGN: High-resolution genomic profiling of 40 invasive breast cancers using matrix-comparative genomic hybridization with an average resolution of 0.5 Mb was conducted on bacterial artificial chromosome microarrays. The data were subjected to classification and unsupervised hierarchical cluster analyses. Expression of candidate genes was analyzed in tumor samples. RESULTS: The highest discriminating power was achieved when combining the aberration patterns of chromosome arms 1q and 16p, which were significantly more often gained in ILC. These regions were further narrowed down to subregions 1q24.2-25.1, 1q25.3-q31.3, and 16p11.2. Located within the candidate gains on 1q are two genes, FMO2 and PTGS2, known to be overexpressed in ILC relative to invasive ductal carcinoma. Assessment of four candidate genes on 16p11.2 by real-time quantitative PCR revealed significant overexpression of FUS and ITGAX in ILC with 16p copy number gain. Unsupervised hierarchical cluster analysis identified three molecular subgroups that are characterized by different aberration patterns, in particular concerning gain of MYC (8q24) and the identified candidate regions on 1q24.2-25.1, 1q25.3-q31.3, and 16p11.2. These genetic subgroups differed with regard to histology, tumor grading, frequency of alterations, and estrogen receptor expression. CONCLUSIONS: Molecular profiling using bacterial artificial chromosome arrays identified DNA copy number imbalances on 1q and 16p as significant classifiers of histologic and molecular subgroups.

Genomic analysis of single cytokeratin-positive cells from bone marrow reveals early mutational events in breast cancer.

Chromosomal instability in human breast cancer is known to take place before mammary neoplasias display morphological signs of invasion. We describe here the unexpected finding of a tumor cell population with normal karyotypes isolated from bone marrow of breast cancer patients. By analyzing the same single cells for chromosomal aberrations, subchromosomal allelic losses, and gene amplifications, we confirmed their malignant origin and delineated the sequence of genomic events during breast cancer progression. On this trajectory of genomic progression, we identified a subpopulation of patients with very early HER2 amplification. Because early changes have the highest probability of being shared by genetically unstable tumor cells, the genetic characterization of disseminated tumor cells provides a novel rationale for selecting patients for targeted therapies.

Bi-specific immunomagnetic enrichment of micrometastatic tumour cell clusters from bone marrow of cancer patients.

Metastasis-the spread of tumour cells from a primary lesion to distant organs-is the main cause of cancer-related death, and bone marrow (BM) is a frequent site for the settlement of disseminated tumour cells. Many BM samples harbour isolated tumour cells, whereas tumour cell clusters, as the potential precursors of solid distant metastases, are rarely detected after current enrichment procedures. We have analysed BM samples from 43 patients with carcinomas of the breast, colon and ovaries; 41 of these patients had no clinical signs of overt metastases (stage M0). Tumour cells in BM were enriched with immunomagnetic beads coupled to monoclonal antibodies against both EpCAM and HER2/neu. After enrichment, tumour cells were identified by immunostaining with the anti-cytokeratin antibody A45-B/B3. In total, 886 CK-positive cells were detected in 16 (35%) samples after immunomagnetic enrichment as compared to 34 cells in 9 (21%) samples using Ficoll density centrifugation previously used as the standard enrichment technique. Most remarkably, clusters of 2 to 10 CK-positive cells were found in 75% of CK-positive samples enriched by immunobeads, whereas no CK-positive cell clusters were detected after Ficoll enrichment. The method described offers an excellent tool for the enrichment of micrometastatic tumour cell clusters; these clusters may represent the initial stage of development from a single disseminated tumour cell towards an overt metastasis.

Microarray-based copy number and expression profiling in dedifferentiated and pleomorphic liposarcoma.

Sixteen dedifferentiated and pleomorphic liposarcomas were analyzed by comparative genomic hybridization (CGH) to genomic microarrays (matrix-CGH), cDNA-derived microarrays for expression profiling, and by quantitative PCR. Matrix-CGH revealed copy number gains of numerous oncogenes, i.e., CCND1, MDM2, GLI, CDK4, MYB, ESR1, and AIB1, several of which correlate with a high level of transcripts from the respective gene. In addition, a number of genes were found differentially expressed in dedifferentiated and pleomorphic liposarcomas. Application of dedicated clustering algorithms revealed that both tumor subtypes are clearly separated by the genomic profiles but only with a lesser power by the expression profiles. Using a support vector machine, a subset of five clones was identified as "class discriminators." Thus, for the distinction of these types of liposarcomas, genomic profiling appears to be more advantageous than RNA expression analysis.