PERCEPTION predicts patient response and resistance to treatment using single-cell transcriptomics of their tumors
Sanju Sinha,
Rahulsimham Vegesna,
Sumit Mukherjee
et al.
Abstract:Tailoring the best treatments for individual cancer patients is an important open challenge. Here, we build a precision oncology computational pipeline for PERsonalized single-Cell Expression-based Planning for Treatments In ONcology (PERCEPTION). Our approach capitalizes on recently published matched bulk and single-cell (SC) transcriptome pro les of large-scale cell-line drug screens to build treatment response models from patients' SC tumor transcriptomics. We start by showing that PERCEPTION successfully p… Show more
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