Recent advances in technologies for the detection of occult metastatic cells in bone marrow of breast cancer patients

Cancer dormancy: lessons from a B cell lymphoma and adenocarcinoma of the prostate

Cancer dormancy delineates a situation in which residual tumor cells persist in a patient with no apparent clinical symptoms. Although the precise mechanisms underlying cancer dormancy have not been explained, experimental models have provided some insights into the factors that might be involved in the induction and maintenance of a tumor dormant state. The authors of the present chapter studied a murine B cell lymphoma that can be made dormant when interacting with antibodies directed against the idiotype on its immunoglobulin Ig receptor. This experimental model of antibody-induced dormancy enabled the isolation and characterization of dormant lymphoma cells. The results indicated that anti-Ig antibodies activate growth-inhibiting signals that induced cycle arrest and apoptosis. This process appeared to be balanced by the growth of the tumor cells such that the tumor did not expand. In contrast, antibodies against HER-2expressed on prostate adenocarcinoma (PAC) cells were not growth inhibitory. However, an immunotoxin (IT) prepared by conjugating HER-2 to the A-chain of ricin (RTA) was internalized by PAC cells, followed by induction of cycle arrest and apoptotic death. Infusion of HER-2-specific IT into PAC-bearing immunodeficient mice did not eradicate the tumor but retained it dormant over an extended period of time. Hence, certain aspects of signaling receptors expressed on cancer can be manipulated by antibodies to induce and maintain a tumor dormant state.

Isolation of tumor cells using size and deformation

The isolation and analysis of circulating tumor cells (CTCs) from blood are the subject of intense research. Although tests to detect metastasis on a molecular level are available, progress has been hampered by a lack of tumor-specific markers and predictable DNA abnormalities. The main challenge in this endeavor is the small number of available cells of interest, 1-2 per mL in whole blood. We have designed a micromachined device to fractionate whole blood using physical means to enrich for and/or isolate rare cells from peripheral circulation. It has arrays of four successively narrower channels, each consisting of a two-dimensional array of columns. Current devices have channels ranging in width from 20 to 5 microm, and in depth from 20 to 5 microm. Several optimizations resulting in the fabrication of a total of 10 derivative devices have been carried out; only two types are used in this study. Both have increasingly narrower gap widths between the columns along the flow axis with 20, 15, 10, and 5 microm spacing all on one device. The first 20 microm wide segment disperses the cell suspension and creates an evenly distributed flow over the entire device, whereas the others were designed to retain increasingly smaller cells. The channel depth is constant across the entire device, the first type was 10 microm deep and the second type is 20 microm deep. When cells from each of eight tumor cell lines were loaded into the device, all cancerous cells were isolated. In mixing experiments using human whole blood, we were able to fractionate cancer cells without interference from the blood cells. Additionally, either intact cells, or DNA, could be extracted for molecular analysis. The ultimate goal of this work is to characterize the cells on the molecular level to provide non-invasive methods to monitor patients, stage disease, and assess treatment efficacy. Furthermore, this work will use gene expression profiles to gain insights into metastasis.

The molecular detection of micrometastatic breast cancer

BACKGROUND

The rapid evolution of molecular technology and novel markers provides the opportunity to establish a more effective means to detect micrometastatic breast cancer. Given the controversies concerning application and clinical relevance, this review critically evaluates the current status of these molecular staging technologies.

DATA SOURCES

Breast cancer literature addressing (1). molecular detection methodologies (immunohistochemistry, reverse transcriptase polymerase chain reaction, and microarray analysis); (2). specific tissue applications such as lymph nodes, bone marrow aspirate, and peripheral blood; (3). expert commentary concerning the clinical applications and pitfalls of these technologies; and (4). recent data from our molecular diagnostics laboratory.

CONCLUSIONS

Molecular detection technologies such as reverse transcriptase polymerase chain reaction and microarray analyses are being developed that will likely have future application as cancer diagnostics. Further work is needed to establish assays that are validated by prospective clinical studies. Early identification of clinically relevant disease could lead to new treatment or staging approaches for breast cancer.

Automated selection of DAB-labeled tissue for immunohistochemical quantification

The increased use of immunohistochemistry (IHC) in both clinical and basic research settings has led to the development of techniques for acquiring quantitative information from immunostains. Staining correlates with absolute protein levels and has been investigated as a clinical tool for patient diagnosis and prognosis. For these reasons, automated imaging methods have been developed in an attempt to standardize IHC analysis. We propose a novel imaging technique in which brightfield images of diaminobenzidene (DAB)-labeled antigens are converted to normalized blue images, allowing automated identification of positively stained tissue. A statistical analysis compared our method with seven previously published imaging techniques by measuring each one's agreement with manual analysis by two observers. Eighteen DAB-stained images showing a range of protein levels were used. Accuracy was assessed by calculating the percentage of pixels misclassified using each technique compared with a manual standard. Bland-Altman analysis was then used to show the extent to which misclassification affected staining quantification. Many of the techniques were inconsistent in classifying DAB staining due to background interference, but our method was statistically the most accurate and consistent across all staining levels.