182 results about "Tumor Biomarkers" patented technology

Clinical management of human cancer is dependent on the accurate monitoring of residual and recurrent tumors. We have developed a method, called personalized analysis of rearranged ends (PARE), which can identify translocations in solid tumors. Analysis of four colorectal and two breast cancers revealed an average of nine rearranged sequences (range 4 to 15) per tumor. Polymerase chain reaction with primers spanning the breakpoints were able to detect mutant DNA molecules present at levels lower than 0.001% and readily identified mutated circulating DNA in patient plasma samples. This approach provides an exquisitely sensitive and broadly applicable approach for the development of personalized biomarkers to enhance the clinical management of cancer patients.

The invention encompasses molecular beacon (MB) probes for monitoring the presence of human breast cancer biomarkers and for the analysis of breast cancer metastasis. The molecular beacon is an oligonucleotide probe which sensitively and specifically identifies biomarker mRNA in samples, in the presence of serum, in minimal time using fluorescence detection. The molecular beacons may be comprised in kits for the detection / quantitation of cancer biomarkers in clinical samples. The invention provides improvements in simplicity, accuracy, and speed over current methods, which could allow for improved patient treatment and prognoses.

Systems and methods for enhancing knowledge discovery from data using multiple learning machines in general and multiple support vector machines in particular. Training data for a learning machine is pre-processed in order to add meaning thereto. Multiple support vector machines, each comprising distinct kernels, are trained with the pre-processed training data and are tested with test data that is pre-processed in the same manner. The test outputs from multiple support vector machines are compared in order to determine which of the test outputs if any represents a optimal solution. Selection of one or more kernels may be adjusted and one or more support vector machines may be retrained and retested. Optimal solutions based on distinct input data sets may be combined to form a new input data set to be input into one or more additional support vector machine. The methods, systems and devices of the present invention comprise use of Support Vector Machines for the identification of patterns that are important for medical diagnosis, prognosis and treatment. Such patterns may be found in many different datasets. The present invention also comprises methods and compositions for the treatment and diagnosis of medical conditions.

The invention provides a method for the assessment of biological markers in a sample of tissue, cells or fluid for the detection a malignant or pre-malignant condition. Aspects of the present invention are particularly useful in screening samples such as cervical smears from women to detect such markers. Identification of a malignant or pre-malignant condition may be followed by appropriate treatment.

The invention relates to glycoproteins having a cancer-specific glycoform. Cancer-specific glycoforms are useful in diagnostics and therapeutics.

Described herein are compositions and methods for cancer cell biomarkers, such as pancreatic ductal adenocarcinoma (PDAC) cell biomarkers, and binding molecules for diagnosis and treatment of cancer, e.g., PDAC. Methods of identifying “accessible” proteomes are disclosed for identifying cancer biomarkers, such as plectin-1, a PDAC biomarker. Additionally, imaging compositions are provided comprising magnetofluorescent nanoparticles conjugated to peptide ligands for identifying PDACs.