Abstract: Nuclear matrix proteins (NMP) which are characterized by a defined expression in tissue are provided. These NMPs are useful markers in diagnosing and monitoring the stage of malignancy of a cell and treating cell proliferative disorders associated with the NMP. Also provided are substantially purified polypeptides and nucleotide sequences encoding the NMPs of the invention.

Abstract: The present invention provides for enriching rare cells in a fluid comprising the rare cells and non-rare cells. Examples of rare cells enriched include prostate cancer cells.

Abstract: Nuclear matrix proteins (NMP) which are characterized by a defined expression in tissue are provided. These NMPs are useful markers in diagnosing and monitoring the stage of malignancy of a cell and treating cell proliferative disorders associated with the NMP. Also provided are substantially purified polypeptides and nucleotide sequences encoding the NMPs of the invention.

Abstract: Nuclear matrix proteins (NMP) which are characterized by a defined expression in tissue are provided. These NMPs are useful markers in diagnosing and monitoring the stage of malignancy of a cell and treating cell proliferative disorders associated with the NMP. Also provided are substantially purified polypeptides and nucleotide sequences encoding the NMPs of the invention.

Abstract: A method for screening individuals at risk for prostate cancer progression is disclosed. The method is useful for evaluating cells from patients at risk for recurrence of prostate cancer following surgery for prostate cancer. Specifically, the method uses specific Markovian nuclear texture factors, alone or in combination with other biomarkers, to determine whether the cancer will progress or lose organ confinement. In addition, methods of predicting the development of fatal metastatic disease by statistical analysis of selected biomarkers is also disclosed. The invention also contemplates a method that uses a neural network to analyze and interpret cell morphology data. Utilizing Markovian factors and other biomarkers as parameters, the network is first trained with a sets of cell data from known progressors and known non-progressors. The trained network is then used to predict prostate cancer progression in patient samples.

Abstract: A method for enriching cancer cells such as prostate cancer cells in a bodily fluid sample is disclosed comprising (a) obtaining the sample comprising cancer cells and non-rare cells; (b) subjecting the sample to multiple density gradient separation comprising a first density gradient and a second density gradient, wherein the second density gradient is greater than the first density gradient, and producing a first fluid comprising an increased concentration of cancer cells of a first density, and a second fluid comprising an increased concentration of cancer cells of a second density, wherein the second density is greater than the first density; wherein subjecting the sample to multiple density gradient separation includes producing a plasma layer, a first interface layer, a first gradient layer, a second interface layer, a second gradient layer, and a cell pellet; wherein producing the first fluid includes combining the first interface layer and the first gradient layer and forming a first suspension; and w

Abstract: Antibodies directed to nuclear matrix proteins (NMP) are provided. Such antibodies are useful markers in diagnosing and monitoring the stage of malignancy of a cell.

Abstract: Nuclear matrix proteins (NMP) which are characterized by a defined expression in tissue are provided. These NMPs are useful markers in diagnosing and monitoring the stage of malignancy of a cell. Also provided are substantially purified polypeptides and nucleotide sequences encoding the NMPs of the invention.

Abstract: Nuclear matrix proteins (NMP) which are characterized by a defined expression in tissue are provided. Also provided is an in vitro method for detecting prostate cancer in a sample employing a reagent that reacts with the NMP designated PC-1 (prostate cancer-1).