Abstract: Disclosed herein are methods for monitoring a lung cancer patient during lung cancer therapy to determine whether the patient is responding to the therapy, and for predicting whether a lung cancer patient, prior to beginning lung cancer therapy, is likely to respond to the therapy. The methods involve generation and analysis of hydroxymethylation signatures, wherein, in monitoring efficacy, a patient 5hmC signature obtained during therapy is compared to a baseline 5hmC signature, while in predicting efficacy, the patient 5hmC signature is compared to a reference 5hmC profile. Analysis of 5hmC levels at certain hydroxymethylation biomarker loci indicate whether the patient is likely to benefit from or continue benefitting from a particular lung cancer therapy.

Abstract: The present invention provides a method for detecting pancreatic cancer in a cell-free DNA sample obtained from a patient's plasma, without need for a surgical biopsy or other invasive means. The method involves consideration of multiple feature types, including at least the following: 5-hydroxymethylcytosine (5hmC)-containing fragment counts in each of a plurality of genomic regions; cfDNA fragment size analysis; and copy number variation (CNV) determination. A probability score is calculated for each of a plurality of base models, with each base model corresponding to a feature set, and the probability scores are combined in an ensemble model to generate an overall probability score that a patient has pancreatic cancer.

Abstract: The present invention provides a method for detecting, assessing, and monitoring pancreatic cancer without need for a surgical biopsy or other invasive means.