Background: The integrity of RNA molecules is of paramount importance for experiments that try to reflect the snapshot of gene expression at the moment of RNA extraction. Until recently, there has been no reliable standard for estimating the integrity of RNA samples and the ratio of 28S:18S ribosomal RNA, the common measure for this purpose, has been shown to be inconsistent. The advent of microcapillary electrophoretic RNA separation provides the basis for an automated high-throughput approach, in order to estimate the integrity of RNA samples in an unambiguous way.

According to the present view, metastasis marks the end in a sequence of genomic changes underlying the progression of an epithelial cell to a lethal cancer. Here, we aimed to find out at what stage of tumor development transformed cells leave the primary tumor and whether a defined genotype corresponds to metastatic disease. To this end, we isolated single disseminated cancer cells from bone marrow of breast cancer patients and performed singlecell comparative genomic hybridization. We analyzed disseminated tumor cells from patients after curative resection of the primary tumor (stage M0), as presumptive progenitors of manifest metastasis, and from patients with manifest metastasis (stage M1). Their genomic data were compared with those from microdissected areas of matched primary tumors. Disseminated cells from M0-stage patients displayed significantly fewer chromosomal aberrations than primary tumors or cells from M1-stage patients (P < 0.008 and P < 0.0001, respectively), and their aberrations appeared to be randomly generated. In contrast, primary tumors and M1 cells harbored different and characteristic chromosomal imbalances. Moreover, applying machine-learning methods for the classification of the genotypes, we could correctly identify the presence or absence of metastatic disease in a patient on the basis of a single-cell genome. We suggest that in breast cancer, tumor cells may disseminate in a far less progressed genomic state than previously thought, and that they acquire genomic aberrations typical of metastatic cells thereafter. Thus, our data challenge the widely held view that the precursors of metastasis are derived from the most advanced clone within the primary tumor.T he prevailing paradigm of carcinogenesis suggests that epithelial cells sequentially accumulate multiple genetic and epigenetic changes underlying the disorganization of tissue morphology and uncontrolled growth (1). The model predicts that certain additional genomic events initiate invasiveness of the tumor and subsequently progression to metastasis. However, this hypothesis of an ''additional event'' initiating metastasis relatively late in tumorigenesis was recently challenged by another model based on global gene expression analysis of primary breast cancers in which groups of genes were identified that predicted the development of distant metastasis (2). Thus it was concluded that the proclivity to metastasize is acquired early during multistep tumorigenesis, although it manifests only much later after mutation of other genes (3).A closer analysis of the natural course of breast cancer reveals several inconsistencies with both models. Why, after curative resection of a primary tumor and its regional lymph nodes, does it often take years or decades until clinical metastases appear? It is difficult to understand how a cell that has been selected at the primary site for acquisition of self-sufficiency in growth signals, unlimited proliferative potential, sustained angiogenesis, and unresponsiveness to growth inhibitory signals...

Cytokeratin-positive cells in the bone marrow of prostate cancer patients are only prognostically relevant when detected before surgery. Because we could not identify significant genetic differences between pre- and postoperatively isolated tumor cells before manifestation of metastasis, we postulate the existence of perioperative stimuli that activate disseminated tumor cells. Patients with cytokeratin-positive cells in bone marrow before surgery may therefore benefit from adjuvant therapies.

Only few selected cancer cells drive tumor progression and are responsible for therapy resistance. Their specific genomic characteristics, however, are largely unknown because high-resolution genome analysis is currently limited to DNA pooled from many cells. Here, we describe a protocol for array comparative genomic hybridization (array CGH), which enables the detection of DNA copy number changes in single cells. Combining a PCR-based whole genome amplification method with arrays of highly purified BAC clones we could accurately determine known chromosomal changes such as trisomy 21 in single leukocytes as well as complex genomic imbalances of single cell line cells. In single T47D cells aberrant regions as small as 1–2 Mb were identified in most cases when compared to non-amplified DNA from 106 cells. Most importantly, in single micrometastatic cancer cells isolated from bone marrow of breast cancer patients, we retrieved and confirmed amplifications as small as 4.4 and 5 Mb. Thus, high-resolution genome analysis of single metastatic precursor cells is now possible and may be used for the identification of novel therapy target genes.