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
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引用次数: 0
Abstract
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. It also captures the resistance development in patients with lung cancer treated with tyrosine kinase inhibitors. PERCEPTION outperforms published state-of-the-art sc-based and bulk-based predictors in all clinical cohorts. PERCEPTION is accessible at https://github.com/ruppinlab/PERCEPTION . Our work, showcasing patient stratification using sc-expression profiles of their tumors, will encourage the adoption of sc-omics profiling in clinical settings, enhancing precision oncology tools based on sc-omics. Sinha and colleagues present PERCEPTION, a precision oncology computational pipeline that can predict the response and resistance of patients by analyzing single-cell transcriptomic data from their tumor samples.
期刊介绍:
Cancer is a devastating disease responsible for millions of deaths worldwide. However, many of these deaths could be prevented with improved prevention and treatment strategies. To achieve this, it is crucial to focus on accurate diagnosis, effective treatment methods, and understanding the socioeconomic factors that influence cancer rates.
Nature Cancer aims to serve as a unique platform for sharing the latest advancements in cancer research across various scientific fields, encompassing life sciences, physical sciences, applied sciences, and social sciences. The journal is particularly interested in fundamental research that enhances our understanding of tumor development and progression, as well as research that translates this knowledge into clinical applications through innovative diagnostic and therapeutic approaches. Additionally, Nature Cancer welcomes clinical studies that inform cancer diagnosis, treatment, and prevention, along with contributions exploring the societal impact of cancer on a global scale.
In addition to publishing original research, Nature Cancer will feature Comments, Reviews, News & Views, Features, and Correspondence that hold significant value for the diverse field of cancer research.