Molecular Staging of Breast Cancer Progression
|Institution:||University of Southern California|
Cheng-Ming Chuong , M.D., Ph.D. -
|Award Cycle:||2000 (Cycle VI)||Grant #: 6JB-0030||Award: $244,320|
|Award Type:||IDEAS II|
|Imaging, Biomarkers, & Molecular Pathology>Biomarkers and novel screening approaches: unmasking the hidden signs|
Initial Award Abstract (2000)
The chances for breast cancer survival would be improved if an early and accurate diagnosis could be performed. Biomedical researchers are working to develop a set of "molecular signatures" for breast cancer that can help us to predict the outcome of clinical course. The development of this new technology will require progress in three areas: 1) increasing our ability to detect genes that are only turned on in a small specific region of breast cancer; 2) developing a standard methodology to identify the genes that are turned on differentially in various cell types; and 3) identifying molecular markers that strongly correlate with clinical outcome. If we are not able to detect genetic changes in a small number of cells, we will not be able to maximize the potential to identify clinically relevant markers. In this proposal a team of basic and clinical scientists will focus on developing a technology that will be able to resolve genetic alterations down to a single cell. Previous methods are not sensitive enough to generate a complete genetic picture (cDNA library) from a single cancer cell. As a result, many previous results are based on the use of cancer cell lines or tissues have been problematic since they often contain a mixture of normal tissue and different stages of cancer. Here we propose to develop a fast, simple and specific method to analyze genes from a very small number of normal mammary gland epithelial cells and abnormal breast cancer epithelial cells. The technique, named single-cell cDNA library amplification (SCLA), provides a fast, accurate and efficient method for generating a complete full-length cDNA library a single cell in a cancer specimen isolated from pathological sections or aspirates. Libraries generated from different stages of cancer progression can then be compared and a stage-specific diagnostic set established for clinical testing. We hope to increase the resolution of current technology and increase the precision of the prediction value of cancer signatures.
Final Report (2002)
A major goal of current tumor biology is to understand the molecular changes that take place at different stages of disease progression. However, current methods to analyze gene expression require a large number of cells. Since tumor cells are frequently found in close proximity to normal cells, it is impossible to obtain a pure tumor cell population for this analysis. The presence of normal cells in the tumor population will increase the noise of the system and decrease the sensitivity of detection techniques. Also, sample degradation will decrease the sensitivity. To alleviate these problems, we set out to increase signal strength from a smaller cell population using a novel gene amplification procedure that maintains sample integrity. This method does not skew the results, but amplifies both single and multiple copy RNAs and maintains their ratio of expression. Hence, instead of one million cells, we can analyze the genes that are expressed by about 100 cells. Since we only need to isolate 100 cells, we can use microdissection techniques and obtain a pure cell population. The RNA is isolated from these cells, amplified with our method, labeled and used to probe a set of genes placed very close together on a small grid (microarray). These data provide a snapshot of the genes that the cells were expressing at the moment they were collected. During the course of this grant, we improved the fidelity of this amplification method and showed its applicability to purified RNA and cultured cells. We are in the process of testing its application to organized tissues. In order for this method to be truly useful, it must be prepared as a kit that can be performed in any hospital and not require intense training or special expertise. Our goal is to simplify the method to increase its utility to a broader audience. We are hopeful that the method can be used to discern the molecular changes that underlie cancer progression. This will identify new targets for future therapeutics.