Somatic mutations predict outcomes of hypomethylating therapy in patients with myelodysplastic syndrome
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Seung-Hyun Jung1,*, Yoo-Jin Kim2,*, Seon-Hee Yim1, Hye-Jung Kim2, Yong-Rim Kwon2, Eun-Hye Hur3, Bon-Kwan Goo3, Yun-Suk Choi3, Sug Hyung Lee4, Yeun-Jun Chung1, Je-Hwan Lee3
1Integrated Research Center for Genome Polymorphism, Department of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, Korea
2Catholic Blood and Marrow Transplantation Center, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
3Department of Hematology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
4Department of Pathology, College of Medicine, The Catholic University of Korea, Seoul, Korea
*These authors have contributed equally to this work
Yeun-Jun Chung, email: [email protected]
Je-Hwan Lee, email: [email protected]
Keywords: myelodysplastic syndrome, hypomethylating therapy, mutation, targeted sequencing
Received: January 12, 2016 Accepted: May 28, 2016 Published: July 11, 2016
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.
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