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Title: A genomic-augmented multivariate prognostic model for the survival of Natural-killer/T-cell lymphoma patients from an international cohort.
Authors: Lim, Jing Quan 
Huang, Dachuan 
Chan, Jason Yongsheng
Laurensia, Yurike
Wong, Esther Kam Yin
Cheah, Daryl Ming Zhe
Chia, Burton Kuan Hui
Chuang, Wen-Yu
Kuo, Ming-Chung
Su, Yi-Jiun
Cai, Qing-Qing
Feng, Yanfen
Rao, Huilan
Feng, Li-Na
Wei, Pan-Pan
Chen, Jie-Rong
Han, Bo-Wei
Lin, Guo-Wang
Cai, Jun
Fang, Yu
Tan, Jing
Hong, Huangming
Liu, Yanhui
Zhang, Fen
Li, Wenyu
Poon, Michelle LM
Ng, Siok-Bian 
Jeyasekharan, Anand 
Ha, Jeslin Chian Hung
Khoo, Lay Poh
Chin, Suk Teng
Pang, Wan Lu
Kee, Rebecca
Cheng, Chee Leong 
Grigoropoulos, Nicholas Francis
Tang, Tiffany
Tao, Miriam
Farid, Mohamad 
Puan, Kia Joo
Xiong, Jie
Zhao, Wei-Li
Khor, Chiea Chuen 
Hwang, William
Kim, Won Seog
Campo, Elias
Tan, Patrick 
Teh, Bin Tean 
Chng, Wee-Joo 
Rötzschke, Olaf
Tousseyn, Thomas
Huang, Hui-Qiang
Rozen, Steve
Lim, Soon Thye 
Shih, Lee-Yung
Bei, Jin-Xin
Ong, Choon Kiat 
Issue Date: 20-Jun-2022
Publisher: Wiley
Citation: Lim, Jing Quan, Huang, Dachuan, Chan, Jason Yongsheng, Laurensia, Yurike, Wong, Esther Kam Yin, Cheah, Daryl Ming Zhe, Chia, Burton Kuan Hui, Chuang, Wen-Yu, Kuo, Ming-Chung, Su, Yi-Jiun, Cai, Qing-Qing, Feng, Yanfen, Rao, Huilan, Feng, Li-Na, Wei, Pan-Pan, Chen, Jie-Rong, Han, Bo-Wei, Lin, Guo-Wang, Cai, Jun, Fang, Yu, Tan, Jing, Hong, Huangming, Liu, Yanhui, Zhang, Fen, Li, Wenyu, Poon, Michelle LM, Ng, Siok-Bian, Jeyasekharan, Anand, Ha, Jeslin Chian Hung, Khoo, Lay Poh, Chin, Suk Teng, Pang, Wan Lu, Kee, Rebecca, Cheng, Chee Leong, Grigoropoulos, Nicholas Francis, Tang, Tiffany, Tao, Miriam, Farid, Mohamad, Puan, Kia Joo, Xiong, Jie, Zhao, Wei-Li, Khor, Chiea Chuen, Hwang, William, Kim, Won Seog, Campo, Elias, Tan, Patrick, Teh, Bin Tean, Chng, Wee-Joo, Rötzschke, Olaf, Tousseyn, Thomas, Huang, Hui-Qiang, Rozen, Steve, Lim, Soon Thye, Shih, Lee-Yung, Bei, Jin-Xin, Ong, Choon Kiat (2022-06-20). A genomic-augmented multivariate prognostic model for the survival of Natural-killer/T-cell lymphoma patients from an international cohort.. Am J Hematol. ScholarBank@NUS Repository.
Abstract: With lowering costs of sequencing and genetic profiling techniques, genetic drivers can now be detected readily in tumors but current prognostic models for Natural-killer/T cell lymphoma (NKTCL) have yet to fully leverage on them for prognosticating patients. Here, we used next-generation sequencing to sequence 260 NKTCL tumors, and trained a genomic prognostic model (GPM) with the genomic mutations and survival data from this retrospective cohort of patients using LASSO Cox regression. The GPM is defined by the mutational status of 13 prognostic genes and is weakly correlated with the risk-features in International Prognostic Index (IPI), Prognostic Index for Natural-Killer cell lymphoma (PINK) and PINK-Epstein-Barr virus (PINK-E). Cox-proportional hazard multivariate regression also showed that the new GPM is independent and significant for both progression-free survival (PFS, HR: 3.73, 95% CI 2.07-6.73; P<0.001) and overall survival (OS, HR: 5.23, 95% CI 2.57-10.65; P=0.001) with known risk-features of these indices. When we assign an additional risk-score to samples, which are mutant for the GPM, the Harrell's C-indices of GPM-augmented IPI, PINK and PINK-E improved significantly (P<0.001, χ2 test) for both PFS and OS. Thus, we report on how genomic mutational information could steer towards better prognostication of NKTCL patients. This article is protected by copyright. All rights reserved.
Source Title: Am J Hematol
ISSN: 03618609
DOI: 10.1002/ajh.26636
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