Sanju Sinha, Rahulsimham Vegesna, Sumit Mukherjee, Ashwin V Kammula, Saugato Rahman Dhruba, Wei Wu, D Lucas Kerr, Nishanth Ulhas Nair, Matthew G Jones, Nir Yosef, Oleg V Stroganov, Ivan Grishagin, Kenneth D Aldape, Collin M Blakely, Peng Jiang, Craig J Thomas, Cyril H Benes, Trever G Bivona, Alejandro A Schäffer, Eytan Ruppin
Tailoring optimal treatment for individual cancer patients remains a significant challenge. To address this issue, we developed PERCEPTION (PERsonalized Single-Cell Expression-Based Planning for Treatments In ONcology), a precision oncology computational pipeline. Our approach uses publicly available matched bulk and single-cell (sc) expression profiles from large-scale cell-line drug screens. These profiles help build treatment response models based on patients' sc-tumor transcriptomics. PERCEPTION demonstrates success in predicting responses to targeted therapies in cultured and patient-tumor-derived primary cells, as well as in two clinical trials for multiple myeloma and breast cancer...
April 18, 2024: Nature Cancer