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Precision oncology uses genomic evidence to match patients with treatment but often fails to identify all patients who may respond. The transcriptome of these “hidden responders” may reveal responsive molecular states. We describe and evaluate a machine-learning approach to classify aberrant pathway activity in tumors, which may aid in hidden responder identification. The algorithm integrates RNA-seq,...
An analysis of microarray data from 86 lung adenocarcinomas reveals hundreds of genes significantly correlated with tumor cell differentiation. A bioinformatics approach of linking these genes to public information from the Locuslink and KEGG databases yields evidence for a loss of tumor cell differentiation being associated with biological processes of cell division, protein degradation, pyrimidine...
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