Evaluating the transcriptional fidelity of cancer models

Evaluating the transcriptional fidelity of cancer models

Abstract Background Cancer researchers use cell lines, patient-derived xenografts, engineered mice, and tumoroids as models to investigate tumor biology and to identify therapies. The generalizability and power of a model derive from the fidelity with which it represents the tumor type under investi...

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Bibliographic Details
Main Authors: Da Peng, Rachel Gleyzer, Wen-Hsin Tai, Pavithra Kumar, Qin Bian, Bradley Isaacs, Edroaldo Lummertz da Rocha, Stephanie Cai, Kathleen DiNapoli, Franklin W. Huang, Patrick Cahan
Format: Article
Language:English
Published: BMC 2021-04-01
Series:Genome Medicine
Subjects:
Cancer models
Machine learning
Cancer cell lines
PDX
GEMM
Tumoroid
Online Access:https://doi.org/10.1186/s13073-021-00888-w

Internet

https://doi.org/10.1186/s13073-021-00888-w

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