Leveraging artificial intelligence to predict ERG gene fusion status in prostate cancer

Leveraging artificial intelligence to predict ERG gene fusion status in prostate cancer

Abstract Background TMPRSS2-ERG gene rearrangement, the most common E26 transformation specific (ETS) gene fusion within prostate cancer, is known to contribute to the pathogenesis of this disease and carries diagnostic annotations for prostate cancer patients clinically. The ERG rearrangement statu...

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Bibliographic Details
Main Authors: Vipulkumar Dadhania, Daniel Gonzalez, Mustafa Yousif, Jerome Cheng, Todd M. Morgan, Daniel E. Spratt, Zachery R. Reichert, Rahul Mannan, Xiaoming Wang, Anya Chinnaiyan, Xuhong Cao, Saravana M. Dhanasekaran, Arul M. Chinnaiyan, Liron Pantanowitz, Rohit Mehra
Format: Article
Language:English
Published: BMC 2022-05-01
Series:BMC Cancer
Subjects:
Prostate cancer
ERG
Deep learning
Artificial intelligence
Gene fusion
Adenocarcinoma
Online Access:https://doi.org/10.1186/s12885-022-09559-4

Internet

https://doi.org/10.1186/s12885-022-09559-4

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