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In a process called "Molecular Combing" DNA molecules attached at one end to a microscope slide are extended and aligned by a receding air-water interface and left to dry on the surface. The local action of the interface is the same on each of the molecules in solution: they are stretched in a reproducible manner to a constant value of 2kb/mum. Simple, controlled and reproducibleoptical mapping of total genomic DNA is made possible by applying Fluorescent Hybridization (FISH) or Immuno-Fluorescence (IF) to combed DNA. This technique using total human DNA easily prepared in agarose blocks allows combing of very high density of DNA molecules (103 genomes per slide) in a uniform and parallel fashion. These properties along with the scoring of single molecules allows for thorough staistical analysis of the hybridized clone sizes and distances yielding precise measurements. A physical map with a precision of a few kilobases (kb), can be obtained in this way, with no additional information from other techniques. An immediate application of screening of genomic DNA from patients for microdeliyions and translocation brekpoint at specific tumor susceptibility. The high level of resolution (2kb) within a range (5 - 300) not covered by the current methods (PCR, CGH) allows for more accurate diagnosis of specific loci. Molecular Combing is also more sensitive than CGH for the detection of low level amplifications (2-15) copies. Emphasis is now on automation in order to speed up data collection and analysis for high-throughput applications and dissemination of this of this novel technology. A second, more exploratory approach consists in scanning whole genomes of normal, precancerous cells for abnormal patterns of DNA replication units (replicons). Efficient DNA replication, dictated by regular replicon size, is necessary to maintain stable genomes. Many, if not most cancer cells show mutations in genes controlling the G1 phase of cell cycle, consequences of which might be a decrease of replication efficiency during the following S phase and increase in genomic instability. We will test this hypothesis by measuring replicon size using molecular combing in normal and transformed cells whose replication origins have been marked with bromo-deoxyuridine (BrdU). Deviation from standard values will be assessed as a general marker for genomic instability and malignancy.
Tumors are characterized by numerous genetic alterations ranging from point mutations in critical genes to a multitude of major alterations in the structure and number of chromosomes. Translocations, deletions, duplications and alterations in ploidy occur in almost all tumors and alter the expression of thousands of genes. The large number of alterations in the genome of a tumor cell can make it extremely hard to identify the specific genes whose change in expression is causal in the neoplastic process. Yet this knowledge is important since the identification of the causal genetic changes common to specific types of tumors will eventually lead to therapies based on a molecular profile. We propose to develop an automated method to generate a genome wide molecular profile of mouse and human tumors in a single experiment. This will enable the whole genome the whole genome to be analyzed in hundreds of tumors, which should facilitate the identification of common causal genetic changes. The technology to perform this analysis is based on comparative genomic hybridization (CGH) of fluorescently labeled DNA. We are applying CGH to high density microarrays of MAC clones of genomic DNA which have been covalently coupled on a glass microscope slide. To facilitate this we have developed a novel DNA-glass coupling chemistry which provides exquisite sensitivity. These arrays are co- hybridized with normal DNA and tumor DNA labeled with different colors and a laser scanner with photomultiplier detection is used to scan the array and convert the different colors and intensities of the fluorescence signals into an intensity ratio histogram. This provides a genome wide molecular profile of the tumor with respect to regions of the genome which are deleted or amplified compared with the normal genome at the resolution of a BAC (200kb). The "array analysis" of the genome of multiple tumor samples can be rapidly accomplished by this method. This technology will initially e developed for the mouse but will subsequently be developed for the human and applied to prostate cancer. Computational tools will be developed to analyze this data. This will enable the identification of alterations in key regions of the genome specific to certain tumor types. This can be correlated with knowledge of the response of the tumor to certain therapies to provide prognostic outcomes based on a molecular profile. This should also enable the specific genes which are causal in the neoplastic process to be identified.
We wish to create a technical infrastructure that would serve as a foundation for the study of pathophysiology of DNA CpG methylation in cancer. It has been shown that epigenetic modification of DNA in form of CpG methylation can result in mutations, cancer, and possibly aging. For example, a very clear mechanism has been established relating 5 MeC to an increase in mutational load through the transition of 5MeC to thymidine. In addition, changes in CpG methylation have been correlated with gene silencing, functional Loss Of Heterozygosity (LOH), and loss of epigenetic imprint. No current landscape allows for the study of changes in methylation at the single cell/single chromosome level. The central focus of this proposal is to establish a robust in situ technology for detection of sequence specific changes in CpG methylation on mammalian chromosomes. This technology would be sequence specific, capable of surveying multiple loci simultaneously, preserve the three dimensional organization of the metaphase chromosome, and be capable of ascertaining changes in cytosine methylation on metaphase chromosomes in single cells. To create this as a practical and transferable technology certain specific technical achievements can be defined. These incremental steps will be satisfied and the resulting technology evaluated in model systems to establish a base line of performance. This microscopic method will permit the investigator to distinguish the presence or absence of specific and/or global methylation in single cells at specific points in tumor development. This technology will also permit the investigator to develop an understanding of the normal development of the methylated genome in isolated single cells.
The immediate goal of this program is to develop a hyperspectral imaging spectrometer capable of measuring DNA microarrays which simultaneously utilize ten or more fluorophore-labeled nucleic acid probes, at a rate of 500,000 samples per hour. The device will greatly increase the speed and reduce the cost of gene expression profiling and mutation and sequence divergence detection. It is expected that the identification of genes that are specifically expressed in disease states will provides clues into the maintenance of these states and perhaps their etiology. Such information is needed for understanding and diagnosing different forms of cancer, and may ultimately lead to the design of therapeutic agents. It should also improve the analysis of the mechanisms of action and side effects of those drugs. Ultimately, though not part of this program, the long-term objective is to adapt this instrument to directly image multiple- fluorophore-tagged samples of tissues and cells. Such a step will dramatically enhance the ability to define the spatial distribution of many tens of molecules at or below the cellular level of resolution, simultaneously and in situ. This capability should increase the capacity to rapidly and reliably provide an assessment of the disease state from biopsies and other tissue samples, and should ultimately allow a more detailed analysis of the interactions between cancerous and pre-cancerous cells and their normal neighbors. The program is a collaboration between Raytheon Optical Systems and Yale UNIVERSITY. It is structured in two phases, R21 and R33. The first is a feasibility and concept definition effort. The specific aims are: to clarify the system requirements for a hyperspectral imager; to validate the design concept, and hence justify progressing to the R33 phase; to define an appropriate test and evaluation program in R33; and to define the scope of sample preparation work required for R33. A major objective will be to demonstrate that hyperspectral unmixingalgorithms developed for earth remote sensing and military reconnaissance are effective in discriminating multiple fluorophores. The second phase is primarily an electro-optical instrument design, manufacture, integration and test effort. However, it also involves the fabrication of DNA microarrays, labeled with suitable fluorophores. At completion, the project will result in two research/development instruments which will be in place at Yale and available to the cancer research community.
The ability to rapidly re-sequence a genomic region or to determine the differential expression profile of a large number of genes that are potentially implicated in cancer development will be extremely valuable for the cancer researcher. There is a tremendous amount of DNA sequence information being generated by the CGAP and human genome programs, more than can be effectively analyzed and then represented in contemporary 'chip' style re- sequencing or expression arrays. This severely limits the number of clinical samples that can be thoroughly inspected. We propose to construct dedicated arrays which have immediately reconfigurable gene sequences identified and designed by computer. This phased innovation award will answer the following questions: 1) Can the array design software, Digital Optical Chemistry (DOC) chip manufacturing device, the MAGNA/HIC readout device, and analysis/gene network software be constructed and ruggedized for routine analysis of cancer samples to differentiate cancer non-cancer cells and their progression by gene expression profiling and chip based resequencing? 2) Can the customizable arrays made possible by the DOC approach be continuously expanded and improved as new genomic data is amassed to generate chips dedicated to analysis of different cancer cell types? 3) Can candidate cDNA sequences (CGAP) and larger genomic regions identified by computer analysis such as Virtual Expression Array calculations be re-sequenced to identify informative gross variations down to SNPs in cancer patient populations to identify new oncogenes or tumor suppressor genes? The specific aims of this program are: 1) To develop bioinformatics tools for the identification and ellucidation of candidate cancer related genes including software for the design, readout and analysis of gene expression and re-sequencing arrays; 2) to develop and complete a Digital Optical Chemistry (DOC) array fabrication unit capable of synthesis of at least 100,000 custom oligonucleotide array members on a single chip with the capability of rapidly constructing chips with different arrays every 2 hours; 3) to develop and construct a custom DOC readout system by modifying/replicating an in-house developed hyperspectral imaging microscope; and 4) the integration of the entire system of software and hardware for the design, fabrication, and data analysis of DNA microarray chips and their subsequent testing on clinical samples relevant for cancer research. The testing of the integrated system for use in mutation detection, SNP discovery, allelotyping, and expression analysis will progress to use archival and prospectively collected cells from biopsies and fine needle aspirates that have been purified with the new laser capture microdissection system. This will integrate our system with current major technologies to produce a tool that should be widely available in translational and clinical trials cancer research.
Metastasis is one of the most devastating aspects of cancer. Thus, discovering therapies that inhibit metastasis is an important goal in cancer treatment. In order to do this, proteins involved in cancer cell invasiveness that could be targets for therapeutic drugs must be validated and this is often a rate-limiting step in drug discovery. The overall objective is to develop an enhanced high throughput screen (HTS) using chromophore assisted laser inactivation (CALI) for target validation of surface proteins that act in cancer cell invasiveness. CALI targets laser energy using a dye-labeled antibody to inactivate the function of the bound antigen. In the R21 phase, an HTS Transwell assay will be developed and used to show that CALI will increased markedly the number of phage display antibodies that disrupt invasiveness. Single chain Fv fusion phage libraries that bind specifically to surface proteins of HT-1080 human fibrosarcoma cells will be generated and used for a pilot screen (n=96 antibodies) using CALI. The achievement of these aims will establish the feasibility of an HTS using CALI for the validation of targets involved in cancer cell invasiveness. In the R33 phase, a full scale automated screen will be conducted (n= 10,000 antibodies) and protein targets validated by this screen will be identified using high resolution mass spectrometry. This proposed technology will provide a low cost and rapid means of target validation and will contribute a number of targets for anti-metastasis drug discovery. The methods developed are general; they will have an application to cell processes in cancer and other diseases. As such, they will be of great utility for pharmaceutical companies and academic labs.
Correlating cancer induction with specific mutations is critically dependent on the availability of technologies that can effectively screen for unknown mutations in several genes simultaneously. This proposal will optimize and streamline a newly developed technology (ALBUMS) for the sensitive and large scale screening of base substitutions, which are the mutations predominantly generated by a wide range of mutagens and are found in several human cancers. DNA from cancerous and normal cells are annealed and hybridized to generate mismatches at the positions of base substitutions. ALBUMS utilizes the covalent and specific binding of novel molecules at unique chemical groups (aldehydes) generated at the position of mismatches by highly specific mismatch - recognition enzymes, in order to isolate mutation - containing DNA. The microplate-based design of the assay allows to screen hundreds or thousands of diverse genes simultaneously, isolate those with mutations and apply them on existing large - scale hybridization DNA arrays for a single - step identification of the mutated genes. The R21 phase (feasibility) will (a) define the optimal operating conditions for detecting and isolating mutation-containing genes (genotypic selection). ALBUMS will be used to isolate cDNA from a single mutated gene (p53) in the presence of increasing amounts of normal alleles, and also to detect p53 mutants in cell lines known to contain p53 mutations. And (b) will establish feasibility for the single-step screening of several hundred or thousands of human genes by combining ALBUMS and commercial DNA hybridization arrays (chips). The second phase (R33) will develop technology to screen in a single step hundreds or thousands of genes in human tumor samples for mutations, on DNA chips. Sets of mutations will be mapped and verified by conventional sequencing in order to establish the utility of the new technology to define the molecular profile of cancer. In the last step, this high throughput technology will be streamlined to provide a procedure with easy access to researchers and clinicians for cost - effective, large - scale mutation screening of cancer samples. Further envisioned ALBUMS applications include genotyping and polymorphism studies and role of mutations in diseases other than cancer.
Cancer-relevant signal transduction involves a large number of signaling proteins with many parallel steps and interconnected feedback mechanisms. These properties of signal transduction processes cannot readily be measured by current techniques, which limits researchers ability to validate each of the more than 10,000 human signaling proteins as potential drug targets for cancer therapy. Over the last several years, my laboratory has made three separate developments that can now be integrated into a technology to systematically characterize complex signal transduction networks. In this approach, cell arrays will be made for simultaneously monitoring a large number of signaling processes. The proposed Evanescent Wave Cell Array Technology (ECAT) incorporates: 1) a microvolume electroporation method for RNA transfection, 2) a set of single cell GFP-tagged biosensors (such as Akt, PKC, Grb-2, GAP and Raf isoforms) that can monitor diverse signaling processes by their plasma membrane translocation or dissociation, and 3) an evanescent wave microscope setup to quantitatively monitor these plasma membrane translocation and dissociation events. In Phase I of the project, we will develop and test a 4 x 3 prototype cell array and, in Phase II, we will expand the cell array to 15 x 10. These two arrays will be used to simultaneously monitor different receptor or transformation induced signaling events in each of the 12, or 150, separate cell array segments on the same glass slide. While phase I includes a test of principle using existing biosensors and dominant negative and constitutively active interference proteins, Phase II will develop a library of such fluorescent translocation biosensors. Furthermore, we will develop two libraries of interference proteins by mutating a large number of serine/threonine kinases and small GTP-binding proteins into constitutively active and dominant negative constructs. As a test of the usefulness and the limitations of the ECAT method, we will determine the role of each member of these two interference libraries by testing them in the context of different receptor stimuli using the existing and newly developed fluorescent biosensors. Overall, this proposal will provide a new approach to signal transduction research and will provide a technological platform for the validation of cancer drug targets and the advancement of drug discovery.
This is a vertically integrated project that will advance the emerging technology of laser scanning cytometry (LSC) to the point that it will a) enable the performance of clinically relevant tissue profiling studies consisting of 50-100 fluorescent and immunofluorescent measurements per sample in human solid tumors, grouped in panels of 5-10 correlated measurements per cell on each of approximately 5,000 cells per panel, and, b) enable extensive analysis of the data, using hypothesis-testing and/or exploratory approaches. Starting with a commercially available instrument (CompuCyte Corp., Cambridge, MA) and multicolor protocols previously developed for lymphoid tissues, during the R-21 phase we will a) develop cell preparatory methods that are suitable for epithelial tumors, b) identify the best initial measurements for identifying and contouring individual cells for multiparameter analysis (light scatter vs cytokeratin, or tubulin), c) develop one or more dye combinations to serve as templates for subsequent development of additional multicolor panels, each encompassing 4-6 correlated measurements per cell, and d) determine the conditions under which individual cells can be revisited and restained with up to 5 additional fluorescent probes per cell. During the R-33 phase we will a) develop a core set of 5-10 multicolor immunofluorescent panels for tissue profiling, each consisting of 5-10 measurements per cell with restaining, using antibodies that have been optimized with respect to non-crossreactivity and binding affinity, b) develop software that will have the capability to capture, preprocess, display, analyze, store, and export mixed data sets consisting of mixtures of correlated, partially correlated, and uncorrelated data, c) extend the capabilities of the CompuCyte instrument by adding additional lasers, and doing custom dye development to increase the number of potential correlated measurements per cell, and d) expand interactions with clinical departments within our institution, in anticipation of devising specific translational clinical studies to explore tissue profiling for prognosis and treatment planning, and launching such studies by the time this grant period has been completed.
Over the last project period, we have achieved the goal of detecting the expression of many genes in a single cell using multiplexed probes to develop a barcode for eleven transcription sites for specific genes and their alleles. This single cell gene expression profiling method allows assessment of each cell's pattern of expression as well as allowing a population analysis of the regulation of these genes. The extensive data complexity that results from the gene-to-gene analyses indicates that this will be an informative approach to validate the gene expression patterns pertaining to cancer gene expression as well as to discover new correlations of genes with the cancer phenotype. The aim of this proposal is to apply this methodology we have developed to tissue samples in order to derive specific gene expression information, ultimately from patient specimens. The approach is to optimize this technology by developing reagents, protocols and imaging hardware and software to achieve a high signal of expressed genes and reduced background of tissue autofluorescence. Central to this development is the use of two new instruments, the Leica confocal microscope, and the VarispecTM liquid crystal tunable filter, which allow a complete spectral analysis of the hybridized tissue, and hence extraction of the principal dye components used for the probe. This provides a means by which we can multiplex the barcoding probes using more spectral bandwidth and obtain gene expression profiling of up to 247 genes in a single nucleus. The statistical analysis of the expression of these genes in tissue combined with a preserved tissue morphology will provide an eventual platform for interrogation of patient specimens where the outcomes are known. The expression patterns obtained from tumor cells in pathological samples will allow a correlation of specific genes with disease progression.
The capability for identifying proteins and measuring changes with good precision of proteomes (the complement of proteins produced by a given organism or cell) for model organisms would provide a powerful tool for understanding the interrelated roles of individual gene products underlying the molecular basis of cancer. In this four year two phase (R21/R33) project we will develop a new approach for obtaining such broad systems level views of differential protein expression. The approach would involve two-dimensional capillary electrophoretic separations for rapid proteome separations and advanced mass spectrometry for the rapid identification of proteins and their modifications. The approach will be at least 2 to 3 orders of magnitude more sensitive than existing 2-D PAGE methodologies and able to rapidly identify and measure relative expression levels for thousands of proteins in a single analysis. A component of our approach involves on-line analysis using Fourier transform ion cyclotron resonance mass spectrometry for protein identification based upon very high mass measurement accuracy and multiplexed MS/MS measurements for polypeptides. We will also develop novel isotopic labeling (e.g., 13C, isotopic depletion or enrichment) methods allowing comparison of two proteomes in the same separation, effectively providing an internal standard, and enabling precise determination of expression levels. Phase 1 will involve initial development and validation of the instrumental approach. Phase 2 efforts will involve its extension to an automated format, further extension of its sensitivity, expansion of its applicability to more complex proteomes and the determination of modifications, and provide for computer-based "differential displays" of results. The eukaryotic yeast strain Saccharomyces cerevisiae will serve the model system for evaluation of the technology. The technology to be developed will enable rapid and sensitive differential proteome displays for the study complex mechanisms and pathways for research into the molecular basis of cancer.
An emerging theme in our current understanding of human oncogenesis is that cancers arise as mutations and epigenetic alterations accumulate in individual cells. The ultimate consequence of such changes is to alter the expression profile of the genome. Knowledge of the identity and function of genes whose expression is altered in particular types of cancer, would enable the correlation of specific genes and pathways to unique cancer induced phenotypes. This information would help our understanding of cancer biology and would provide new biomarkers for cancer detection as well as novel gene targets for therapeutic strategies. Thus, a high priority of current cancer research is to reveal the molecular variations that distinguish cancer cells from wild type and to determine the function of the affected genes. Of the possible genes whose altered expression may mark the molecular signature of cancer, primary candidates include those that encode proteins that function to regulate the expression of the genome and catalyze its replication and repair, collectively referred to as nucleic acid binding proteins (NBPs). Maintaining the integrity of the genome and regulating its appropriate expression are important first tier intracellular processes that must be controlled. Since genetic diseases such as cancer can result from alterations in the genome which ultimately change the expression profile of genes that function in nucleic acid house keeping and regulatory functions, our first goal, in the R21 phase of this proposal, is to examine the feasibility of developing a functional genomics technology aimed at identifying human genes selected by their ability to encode proteins that bind to DNA and/or RNA. Several additional components of the technology will be addressed in the R33 expanded development phase of the proposal. One encompasses a novel sorting phase that will rapidly distinguish between different classes of NBPs according to their (encoded) binding properties for particular nucleic acids types and conformations. We will also develop bioinformatic tools that can be used in both virtual and microarray based expression profiling to sample whether the expression of selected genes or gene clusters is altered in normal versus specific cancer cells. When developed, this new technology will enable the functional identification, categorization and expression profiling of genes that act to maintain and regulate the genome. It will directly improve the quality of data in the Cancer Genome Anatomy Project (CGAP) and it will likely identify new genes that confer a predisposition for cancer when their relative expression within a cell is altered. Such technology does not presently exist.
An important aspect of developing treatments against cancer consists in correcting the defects caused by the abnormal activity of oncogenes and tumor suppressor genes. This usually includes the assignment of cancer-related gene products to their respective biochemical pathways. It has been shown that the genetics available in model organisms such as yeast, nematodes, flies, and mice can be highly advantageous for these projects. Despite the power of model organisms, the number of genes with a function assigned is relatively small and thus the functional analysis of cancer-related orthologs is still relatively tedious. However, with the complete sequence of the genome of most model organisms anticipated to be available soon, several laboratories have initiated the development of genome-wide gene-function analysis projects. Such projects, collectively referred to as "functional genomics" include genome-wide expression analysis, gene knock-outs and protein-protein interaction mapping. They are expected to reveal gene functions at a drastically increased rate. In this context, the long-term goal of our laboratory is to generate a comprehensive protein-protein interaction map for the nematode C. elegans. This will be achieved in three steps: Step I: validation of our improved version of the yeast two-hybrid system to generate protein interaction maps (funded by an R01 grant from the NHRGI); Step II: development of new high-throughput technologies for protein interaction mapping (object of this grant); step III: production phase (planned for the long-term and not the object of this grant). In step II, we plan to automate most steps of the two-hybrid methodology using a new cloning method, referred to as Gateway cloning. Gateway allows the transfer of DNA inserts between donor plasmids (or PCR products) and recipient plasmids. It is based on an in vitro site- specific recombination event mediated by purified phage lambda proteins and thus eliminates the need for restriction enzymes and ligases. It is fast and reversible, and the whole procedure can take place in 96- well plates, which means that automation is possible. In summary, Gateway will allow us to go in and come out of the two-hybrid in a completely automated series of steps. We will first develop the Gateway technology in the context of the two- hybrid system (R21). Then we will develop high-throughput methods for protein interaction mapping based on the use of the Gateway/two-hybrid system (R33). We will also adapt the technology so that other worm functional projects can benefit from it.
As a step toward understanding the complex differences between normal and cancer cells, much research has been devoted to analyses of genes that are differentially expressed in particular cells. Though recent technological advances have made it possible to conduct serial and/or simultaneous analysis of the expression patterns of thousands of genes, no comprehensive study has been reported on how many genes are expressed differentially and whether most differences are cell line-specific. The long- term goal of this research is to develop intelligent data mapping and visual explanation technologies to improve information exploration and interpretation from high-throughput gene expression profiles for molecular analysis of cancer. Suggested by preliminary evidence from mRNA profiles of breast/prostate cancer cells that transcriptome patterns are rich in information about mechanisms that underlie cancer development, in the R21 research, multidisciplinary knowledge of molecular biology and computational intelligence are applied to (1) design cost effective molecular experiments to establish gene transcriptome distributions across cell lines, (2) pilot test the existence of transcriptome clusters in the molecular species space that correlate to cell phenotypes, and (3) identify key biomarkers that differentiate different cell lines with the highest prediction values. Since new knowledge can only be further acquired by exploring all of the interesting aspects of complex transcriptome data in high-dimensional space, in this R33 application a statistically principled hierarchical visual exploration technique is proposed to effectively reveal and interpret the intrinsic but hidden characteristics of transcriptome clusters that should better define the nature of cancer biology and therapeutic targets. A novel integration of information theory and computer graphics will permit (1) an automatic identification and modeling of biomarker clusters, (2) a probabilistic component analysis to form hierarchical visualization spaces allowing the complete data set to be analyzed at the top level with best separated sub-clusters analyzed at deeper levels, and (3) an interactive intelligent interface for task/hypothesis driven data mining and decision making. The innovative nature of the research relies on the concept of combining (1) a hybrid stepwise nonlinear discriminant analysis for biomarker identification and (2) a hierarchical visual exploration of multi-foci high-dimensional transcriptome distribution to interpret the complex relationships between molecular events and cell phenotypes.
Magnetic resonance microscopy (MRM), including microscopic imaging and spectroscopy are becoming increasingly important in cancer diagnosis and treatment. Both morphometric and metabolic changes in cells can be detected with MRM which may assist in early evaluation of therapeutic response. However, the results are often ambiguous due to heterogeneity of responses and the long measuring times circumvent the potential for following dynamic cellular processes. To improve this situation, we propose to develop and test a microscope in which proton MRM and optical microscopy (OM) can be performed simultaneously to study heterogeneous mammalian cell populations. With this technology, information from OM measurments will be used to guide MRM measurements, significantly improving the speed and accuracy by which MRM measurements can be obtained. High resolution OM (fluorescent) images will be used to select a subpopulation of cells undergoing a physiological response. These OM images will then be used to guide MRM experiments such that water images and metabolite spectra are obtained from only the cells of interest within the population. In the R21 phase of this proposal, an integrated OM/MR microscope in which 2 or more monolayers of cultured human cells growing within a perfusion system will be designed, constructed and tested. Each layer will have a field of view of 1 mm2. The probe will operate in a standard wide-bore (89 mm) vertical magnet with a field of 11.7 Tesla. Our goal is that this probe will be able to determine OM images with 1.5 muM spatial resolution in seconds, and measure proton MR metabolite spectra of 1,000-2,000 randomly distributed human cells within 15-60 minutes. In the R33 phase of this research, the utility and limitations of the integrated microscope will be evaluated by examining cells undergoing apoptosis, a process of critical importance to cancer therapy. Studies will be conducted to evaluate the ability of the instrumentation to identify subpopulations of cells at early and late phases of apoptosis induced by both chemicals and expression of specific genes. The ability of OM to guide MR measurements to specific cell populations or to neighboring populations will be determined. It is anticipated that the successful development of this instrumentation will, ultimately, greatly enhance the speed, specificity and utility of noninvasive MR methods in cancer research.
Certain tumors shed neoplastic cells into the blood before the primary tumor growth can be detected in the body. It has been shown recently that epithelial cells from the tumor can be detected in the blood at concentrations as low as 1 cell per ml of blood, and that the presence of rare cancer cells in blood has an important diagnostic value. The current screening methods are limited by relatively low speed of Fluorescent Activated Cell Scanning. (FACS),and complexity of preenrichment methods. The overall objective of this proposal is to develop a high-throughput, immunomagnetically based cell separating system to recover as many rare cancer cells in human blood as possible, for further molecular analysis (such as PCR, biological assays and other). The specific aims are as follows. First: the primary separation will be conduced using a novel continuos, flow-through immunomagnetic unit developed in our laboratories. Continuos units are intrinsically more efficient with respect to high throughput. We propose to develop experimental and theoretical basis for the next generation system which will sort cells at a rate of 10/7 cells/s, and allow a non- destructive screening of an entire volume of blood product used for cancer cell therapy ( typically 0.5 to 1.0 liters) in a short period of time (< 1hour). Second: the continuos cell separation process can be staged, unlike the currently used batch systems. We propose to develop experimental and theoretical basis for the continuos staged separation process which will further increase the purity and decrease the volume of the cell product, and thus increase the rate of success of analysis downstream of the cell separation step. Third: the current cell labeling procedure may require modifications and optimization for the best performance in targeting and isolating rare cancer cells. We propose to screen available monoclonal antibodies and colloidal magnetic labels for the highest sensitivity and specificity in targeting rare cancer cells using unique Cell Tracking Velocimetry instrument developed in our laboratories. In summary, this proposal focuses on the "front-end" of cancer screening namely a high-throughoutput device to rapidly isolate and concentrate rare cancer cells form large numbers of cells. This proposal is responsive to PAR-98-067, Innovative Technologies for the Molecular analysis of Cancer, and we believe it addresses the second objective of the PAR, namely "novel technologies that will allow high- throughput analysis of genetic alterations, expression of genome products, and monitoring of signal transduction pathways to cancer."
The word proteome was coined in 1995 to refer to the total protein complement of a genome. The human genome encodes roughly 100,000 genes, corresponding to a similar number of proteins. Not all genes are expressed in all tissues; roughly 10,000 proteins are found in any particular cell. The fraction of the proteome that is expressed by an organism varies between tissues and in response to the environment. Conventional proteome analysis is preformed by two-dimensional gel electrophoresis and requires the protein from roughly a million cells. We have improved the sensitivity of proteome analysis by six orders of magnitude. In preliminary work, we have demonstrated that we can perform a simple analysis of the proteome in a single human cancer cell. Our Preliminary work will be expanded in this R33 proposal. We will automate the manipulations of single cells, we will multiplex the instrument so that 96 cells can be analyzed simultaneously, we will expand our proteome analysis to two-dimensional electrophoresis, and we will evaluate the technology by monitoring the evolution of protein expression in mouse skin tumors.Single cell proteome analysis offers several important advantages. In particular, we can monitor the distribution in the expression of protein markers that are correlated with cancer stage. Like ploidy measurements, the distribution of protein expression may have valuable prognostic value. Sub-populations of metastatic or therapy-resistant cells may be identified at an early stage to guide treatment.
It is important to have the capability to perform precise measurements of gene expression levels in tumor cells. Available technology permits the assessment of levels of gene expression in samples containing a minimum of 10,000 cells. Thus, there is a need for methods that will permit such measurements in samples containing fewer tumor cells. A specific aim of this proposal is to complement a new approach that will yield quantitative data on the relative concentration of specific mRNA molecules in tissue samples containing less than 200 cells. Sequence detection is accomplished on oligonucleotide microarrays, using a target-directed DNA ligation step coupled to a Rolling Circle Amplification (RCA) unimolecular detection system. Each target detection event generates a primer that can be amplified by RCA. Each amplified DNA molecule generated by RCA remains localized on the array surface, and is imaged as a discrete fluorescent signal, indicative of a specific molecular ligation event. Expression profiles are generated as histograms of single molecule counts. Additionally, the DNA ligation step can e adapted to the detection of mRNAs containing point mutations. This capability will be developed for detection of one somatic mutant mRNA molecule in a background of 1000 wild type mRNA molecules, using K- ras mutations as an experimental model. Arrays for the analysis of 100 different gene products will include mRNAs known to be up- or down- regulated in cancer cells, wild type or mutant K-ra mRNAs, and housekeeping genes. Adequate controls will be incorporated in the system to insure its reliability. Another specific aim is to evaluate the coupling of this highly sensitive detection technology with laser- assisted tissue microdissection. We will combine these two technologies to demonstrate the capability for high resolution tissue analysis in: (a) normal and cancerous prostate, and prostate tissue with varying degrees of prostatic intraepithelial neoplasia; (b) normal colonic epithelium, as well as adenomatous epithelium with varying degrees of dysplasia, and colonic adenocarcinoma. The capability for measuring gene expression levels in samples containing as few as 10-20 cells, together with the capability for detection of somatic point mutations at several loci known to be altered with high frequency, will provide the infrastructure to address the question of possible microheterogeneity in gene expression profiles in small clusters of cells in dysplasia and cancer.
The reduced complexity and non-stoichiometric amplification intrinsic to RNA arbitrarily primed PCR (RAP-PCR) could be used to advantage to generate probes for differential screening of cDNA arrays. RAP-PCR fingerprints have a reduced complexity compared to the whole mRNA population because they sample only small parts of some of the mRNAs in a mixture. The reduced complexity should result in a lower background hybridization to non-homologous clones when compared to a full complexity probe. RAP-PCR fingerprints are non-stoichiometric because the probability of amplification of a particular cDNA PCR product is dependent on the match with the arbitrary primer. Thus, a rare mRNA may yield an abundant PCR product. This non-stoichiometry allows each different RAP-PCR fingerprint to amplify a different set of rate mRNAs that can then e detected easily on inexpensive arrays. We will experiment with various parameters to optimize the properties of the probe. We will (1) adjust the complexity of the non-stoichiometric probe, (2) bias sampling by the primers to increase the probability of sampling particular sequences of interest and, (3) explore stoichiometric methods to reduce probe complexity. These methods will be applied to simple cell culture systems and to a small set of samples from cancer patients. Our search for differentially expressed genes in these systems will help to compare the performance of the various strategies.
The objective of this project is to develop microfabricated devices for the comprehensive of cellular proteins to normal, precancerous and cancerous tissues. Specifically, we propose to develop lab-on-a-chip technologies as an alternative to the slow and labor-intensive two dimensional (2D) gel methods currently used for comprehensive protein analysis. The microchips will integrate on a single structure elements that enable multidimensional separations of protein mixtures, with either on-chip labeling for fluorescence detection or electrospray ionization (ESI) of the analytes for direct, on line interfacing with mass spectrometry (MS). Successful completion of the project will result in high throughput, automated devices for use in identifying disease markers and elucidating the molecular basis of cellular transformation. These devices will have research applications for understanding cellular transitions from normal to diseased states. In addition, these research tools will also find application in clinical diagnosis and therapy development.
We propose to develop an approach to allow rapid identification of proteins in complex mixtures suitable for protein expression mapping in total cell lysates. A robust approach to identify proteins as mixtures will advance cancer research in several areas. First, the approach has the potential to significantly improve the sensitivity of analysis of proteins. Benefits to cancer research will derive from the ability to identify proteins using smaller numbers of cells leading to direct examination of tumor biopsy samples. Rigorous molecular analysis at the protein level, encompassing separation, visualization, and identification, is currently difficult for small quantities of protein. The methodology proposed is general and therefore can be applied to the monitoring of gene produce expression, analysis and detection of cellular localization and post translational modification of proteins, and monitoring of major signal transduction networks involved in cancer. Second, the approach has great potential for automation allowing the technique to be transferred to laboratories involved in cancer research eliminating the need to collaborate with experts. Last, by developing the ability to quantitate and perform subtractive analyses changes in protein expression related to neoplastic transformation could be observed.