Abstract: Provided herein are, inter alia, methods and compositions to detect, monitor and treat cancer, wherein the cancer includes amplified extrachromosomal oncogenes. The methods are useful for personalized treatment and exploit differential expression of amplified extrachromosomal oncogenes in cancer cells versus healthy cells.

Abstract: Provided herein are, inter alia, methods and compositions to detect, monitor and treat cancer, wherein the cancer includes amplified extrachromosomal oncogenes. The methods are useful for personalized treatment and exploit differential expression of amplified extrachromosomal oncogenes in cancer cells versus healthy cells.

Abstract: Methods, systems, and apparatuses, including computer programs for identifying a gene fusion in a biological sample is disclosed. The method can include actions of obtaining first data that represents a plurality of aligned reads, identifying a plurality of fusion candidates included within the obtained first data, filtering the plurality of fusion candidates to determine a filtered set of fusion candidates, for each particular fusion candidate of the filtered set of fusion candidates: generating, by one or more computers, input data for input to a machine learning model that includes extracted feature data that to represents the particular fusion candidate, providing the generated input data as an input to the machine learning model that has been trained to generate output data representing a likelihood that a fusion candidate is a valid gene fusion, and determining whether the particular fusion candidate corresponds to a valid gene fusion based on the output data.

Abstract: Provided herein are, inter alia, methods and compositions to detect, monitor and treat cancer, wherein the cancer includes amplified extrachromosomal oncogenes. The methods are useful for personalized treatment and exploit differential expression of amplified extrachromosomal oncogenes in cancer cells versus healthy cells.