Abstract: A computer-implemented machine learning system for, and method of, detecting a hypermetabolic cancer based on a nuclear magnetic resonance spectrum of a patient biofluid is presented. The techniques includes obtaining a nuclear magnetic resonance spectrum of a patient biofluid; providing the nuclear magnetic resonance spectrum to a machine learning system trained with a training corpus, the training corpus including a group of normal biofluid nuclear magnetic resonance spectra and a group of hypermetabolic cancer biofluid nuclear magnetic resonance spectra; and supplying an indication based on an output of the machine learning system, where the indication is representative of whether the nuclear magnetic resonance spectrum of the patient biofluid is indicative of cancer.

Abstract: The present invention relates to the field of cancer. More specifically, the present invention provides compositions and methods useful for preventing tumor recurrence and metastases. In one embodiment, a method for inhibiting lung cancer metastases in a post-resection patient comprises the step of administering low dose adjuvant epigenetic therapy (LDAET) to inhibit the migration of myeloid-derived suppressor cells from the bone marrow to the lung premetastatic environment.

Abstract: The present invention provides methods for identifying metastases by detecting nucleic acid hypermethylation of one or more genes in one or more samples, and in particular in the lymph nodes. The invention further relates to DNA methylation as a predictor of disease recurrence and patient prognosis, specifically in the field of cancer biology.

Abstract: The present invention provides methods for identifying metastases by detecting nucleic acid hypermethylation of one or more genes in one or more samples, and in particular in the lymph nodes. The invention further relates to DNA methylation as a predictor of disease recurrence and patient prognosis, specifically in the field of cancer biology.

Abstract: The present invention relates to the use of nucleic acid methylation and methylation profiles to detect predict sensitivity of cells to cytotoxic chemotherapies, and in particular to microtubule based therapies, for example taxanes. The invention relates to methods for identifying a methylation profile of the checkpoint with forkhead and ring finger domains gene (CHFR) that is associated with a sensitivity to agents directed at the microtubule.

Abstract: The present invention provides methods for identifying metastases by detecting nucleic acid hypermethylation of one or more genes in one or more samples, and in particular in the lymph nodes. The invention further relates to DNA methylation as a predictor of disease recurrence and patient prognosis, specifically in the field of cancer biology.