Hae Yong Yoo1,2,10, Min Kyung Sung3,10, Seung Ho Lee1, Sangok Kim4,5, Haeseung Lee4,5, Seongjin Park3, Sang Cheol Kim3, Byungwook Lee3, Kyoohyoung Rho6, Jong-Eun Lee6, Kwang-Hwi Cho7, Wankyu Kim4,5, Hyunjung Ju2, Jaesang Kim4,5, Seok Jin Kim2,8, Won Seog Kim2,8, Sanghyuk Lee4,5 & Young Hyeh Ko2,9
1Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Korea. 2Samsung Biomedical Research Institute, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Korea. 3Korean Bioinformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology, Daejeon, Korea. 4Ewha Research Center for Systems Biology (ERCSB), Ewha Womans University, Seoul, Korea. 5Department of Life Science, Ewha Womans University, Seoul, Korea. 6DNA Link, Inc., Seoul, Korea. 7School of Systems Biomedical Science, Soongsil University, Seoul, Korea. 8Division of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. 9Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea. 10These authors contributed equally to this work.
Correspondence to: Sanghyuk Lee or Young Hyeh Ko
The molecular mechanisms underlying angioimmunoblastic T cell lymphoma (AITL), a common type of mature T cell lymphoma of poor prognosis, are largely unknown. Here we report a frequent somatic mutation in RHOA (encoding p.Gly17Val) using exome and transcriptome sequencing of samples from individuals with AITL. Further examination of the RHOA mutation encoding p.Gly17Val in 239 lymphoma samples showed that the mutation was specific to T cell lymphoma and was absent from B cell lymphoma. We demonstrate that the RHOA mutation encoding p.Gly17Val, which was found in 53.3% (24 of 45) of the AITL cases examined, is oncogenic in nature using multiple molecular assays. Molecular modeling and docking simulations provided a structural basis for the loss of GTPase activity in the RHOA Gly17Val mutant. Our experimental data and modeling results suggest that the RHOA mutation encoding p.Gly17Val is a driver mutation in AITL. On the basis of these data and through integrated pathway analysis, we build a comprehensive signaling network for AITL oncogenesis.