Current prognostic scoring systems based on clinicopathologic variables are inadequate in predicting the survival and treatment response of extranodal natural killer/T-cell lymphoma (ENKTL) patients undergoing non-anthracyline-based treatment. We aimed to construct a classifier based on single-nucleotide polymorphisms (SNPs) for improving predictive accuracy and guiding clinical decision-making. The data of 722 patients with ENKTL from international multicenters were analyzed. A 7-SNP-based classifier was constructed using LASSO Cox regression in the training cohort (n=336) and further validated in the internal testing (n=144) and two external validation cohorts (n=142; n=100). The 7-SNP-based classifier showed good prognostic predictive efficacy in the training cohort and the three validation cohorts. Patients with high and low risk scores calculated by the classifier exhibited significantly different progression-free survival (PFS) and overall survival (OS) (all p<0.001). The 7-SNP-based classifier was further proved to be an independent prognostic factor by multivariate analysis, and its predictive accuracy was significantly better than clinicopathological risk variables. The application of the 7-SNP-based classifier was not affected by sample types. Notably, chemotherapy combined with radiotherapy significnalty improved PFS and OS versus radiotherapy alone in high risk Ann Anbor stage I patients, while there was no statistical difference between the two therapeutic modalities among low risk patients. A nomogram was constructed comprised of the classifier and clinicopathological variables, and showed remarkably better predictive accuracy than that of each variable alone. The 7-SNP-based classifier is a complement to existing risk stratification systems in ENKTL, which could have significant implications for clinical decision-making for ENKTL patients.
Xiao-Peng Tian, Shu-Yun Ma, Ken H Young, Choon Kiat Ong, Yanhui Liu, Zhihua Li, Qiongli Zhai, Hui-Qiang Huang, Tongyu Lin, Zhiming Li, Zhong-Jun Xia, Liye Zhong, Huilan Rao, Mei Li, Jun Cai, Yuchen Zhang, Fen Zhang, Ning Su, Peng-Fei Li, Feng Zhu, Zijun Yidan Xu-Monette, Esther Kam Yin Wong, Jeslin Chian Hung Ha, Lay Poh Khoo, Le Ai, Runfen Cheng, Jing Quan Lim, Sanjay de Mel, Siok-Bian Ng, Soon Thye Lim, Qingqing Cai