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Abstract

Provided herein are computer-implemented methods of identifying programmed-death ligand 1 (PD-L1) expression status of a subject's sample comprising a cancer cell. In exemplary embodiments, the method comprises receiving an unlabeled expression data set for the subject's sample; aligning the unlabeled expression data set to labeled expression data according to a trained PD-L1 predictive model, wherein the trained PD-L1 predictive model has been trained with a plurality of labeled expression data sets, each labeled expression data set comprising expression data for a sample of a labeled cancer type and a labeled PD-L1 expression status; wherein aligning the unlabeled gene expression data set to labeled expression data according to the trained PD-L1 predictive model identifies PD-L1 expression status for the subject's sample. Further provided are related methods of preparing a clinical decision support information (CDSI) report and methods of determining treatment for a subject. Additionally provided are CDSI reports and computing devices.

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First Claim