Somatic mutations predict outcomes of hypomethylating therapy in patients with myelodysplastic syndrome

// Seung-Hyun Jung 1, * , Yoo-Jin Kim 2, * , Seon-Hee Yim 1 , Hye-Jung Kim 2 , Yong-Rim Kwon 2 , Eun-Hye Hur 3 , Bon-Kwan Goo 3 , Yun-Suk Choi 3 , Sug Hyung Lee 4 , Yeun-Jun Chung 1 , Je-Hwan Lee 3 1 Integrated Research Center for Genome Polymorphism, Department of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, Korea 2 Catholic Blood and Marrow Transplantation Center, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea 3 Department of Hematology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea 4 Department of Pathology, College of Medicine, The Catholic University of Korea, Seoul, Korea * These authors have contributed equally to this work Correspondence to: Yeun-Jun Chung, email: yejun@catholic.ac.kr Je-Hwan Lee, email: jhlee3@amc.seoul.kr Keywords: myelodysplastic syndrome, hypomethylating therapy, mutation, targeted sequencing Received: January 12, 2016      Accepted: May 28, 2016      Published: July 11, 2016 ABSTRACT Although hypomethylating therapy (HMT) is the first line therapy in higher-risk myelodysplastic syndromes (MDS), predicting response to HMT remains an unresolved issue. We aimed to identify mutations associated with response to HMT and survival in MDS. A total of 107 Korean patients with MDS who underwent HMT (57 responders and 50 non-responders) were enrolled. Targeted deep sequencing (median depth of coverage 1,623X) was performed for 26 candidate MDS genes. In multivariate analysis, no mutation was significantly associated with response to HMT, but a lower hemoglobin level (<10g/dL, OR 3.56, 95% CI 1.22-10.33) and low platelet count (<50,000/μL, OR 2.49, 95% CI 1.05-5.93) were independent markers of poor response to HMT. In the subgroup analysis by type of HMT agents, U2AF1 mutation was significantly associated with non-response to azacitidine, which was consistent in multivariate analysis (OR 14.96, 95% CI 1.67-134.18). Regarding overall survival, mutations in DNMT1 ( P =0.031), DNMT3A ( P =0.006), RAS ( P =0.043), and TP53 ( P =0.008), and two clinical variables (male-gender, P =0.002; IPSS-R H/VH, P =0.026) were independent predicting factors of poor prognosis. For AML-free survival, mutations in DNMT3A (P<0.001), RAS ( P =0.001), and TP53 ( P =0.047), and two clinical variables (male-gender, P =0.024; IPSS-R H/VH, P =0.005) were independent predicting factors of poor prognosis. By combining these mutations and clinical predictors, we developed a quantitative scoring model for response to azacitidine, overall- and AML-free survival. Response to azacitidine and survival rates became worse significantly with increasing risk-scores. This scoring model can make prognosis prediction more reliable and clinically applicable.