Abstract: Disclosed herein are methods for classifying a tumor using a trained classifier. The method may include providing a methylation profile to a classifier trained to identify tumor classes using unsupervised clustering, generating a classification of the tumor based on the methylation profile and a reference set, where the reference set is generated from training the classifier, generating a confidence score based on the correlation of the methylation profile to the classification from the classifier, and updating the classifier and reference set with the methylation profile and classification. The classifier may include a plurality of family sub-classifiers and/or a plurality of class sub-classifiers.

Abstract: The invention provides a method of detecting a proliferative disease, such as a disease associated with the abnormal expression of BORIS, in a mammal comprising detecting antibodies to BORIS in a sample obtained from the mammal. The invention also provides BORIS polypeptides as well as compositions and kits comprising the BORIS polypeptides and methods of using the same. The invention further provides a method of inducing an immune response in a mammal using BORIS polypeptides.

Abstract: The invention provides a method comprising detecting autoantibodies to BORIS in a sample obtained from a mammal, as well as BORIS polypeptides and epitopes, and kits comprising the BORIS polypeptides and epitopes, and a method of inducing an immune response to BORIS in a mammal.

Abstract: The present invention provides peptide and recombinant protein mimetics specifically representing the antiviral and antiproliferative activities of interferons with avoiding interferons' undesirable side effects during treatment of a variety of diseases. The basic embodiment of the present invention was to link together, through a short artificial spacer, two primary protein sequences locating distant to each other in the interferon's native structure.