Whole-Genome Sequencing for Copy Number Abnormalities in Multiple Myeloma Supersedes Karyotype Analysis and Fluorescent in Situ Hybridization Jiali Li 1, Shaobing Gao 2, Zhenling Li 3, Yinyin Chang 4, Xiangxiang He 4, Yuexin Cheng 5, Manqian Li 4, Chunxiao Yao 4, Shiyong Li 6, Dandan Zhu 4, Shichun Tu 4, Mao Mao 6,7, #, Xi Zhang 1, #, Li Gao 1, # 1 The Xinqiao Hospital of Third Military Medical University, Chongqing 214426, China 2The Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital, Zhengzhou 450003, China 3China-Japan Friendship Hospital, Beijin100029,China 4Clinical Laboratories, Shenyou Bio, Zhengzhou 450000, China 5Yancheng No. 1 People's Hospital, The Yancheng Clinical College of Xuzhou Medical University, Yancheng 224006, China 6Research & Development, SeekIn Inc., Shenzhen 518000, China 7Yonsei Song-Dang Institute for Cancer Research, Yonsei University, Seoul 03722, Korea Corresponding authors. Tel.: +86-15601973722(Maomao); 13808310064(Xi Zhang) 13228686076(Li Gao) Corresponding authors Email: mao_m@yahoo.com (Maomao); zhangxxi@sina.com (Xi Zhang); gaotiantiantiger@163.com (Li Gao) Introduction Prognosis and management of multiple myeloma (MM) relies on risk stratification based on copy number abnormalities (CNA) detection results. CNA is conventionally evaluated by cytogenetic methods including karyotyping and flurescence in situ hybridization (FISH), both limited by the invasiveness, low proliferative activity of plasma cell and the low plasma cell count. LeukoPrint is a novel shallow whole-genome sequencing (sWGS) based approach to profile CNA in bone marrow cells and/or circulating cell-free DNA (cfDNA). We compared the CNA detection results by LeukoPrint, karyotyping and FISH using bone marrow or plasma samples from multiple myeloma patients. Methods A total of 128 patients were enrolled in this study. Karyotyping and FISH were performed by conventional approaches. CNA was detected by sWGS in genomic DNA from bone marrow aspiration samples and CD138+ enriched plasma cells as well as in plasma cfDNA. CNA degree was measured by log R ratio. Significant mutational peak region was identified by GISTIC2. Risk stratification was performed following the Mayo Stratification of Myeloma and Risk-adapted Therapy (mSMART) criteria. Results In this study, 908 CNAs were identified by sWGS in 96 (75.0%, 96/128) patients, while the positive rate of CNA detected by karyotyping and FISH was 7.9% and 56.7% , respectively. A total of 368 whole chromosome aberration events were identified by sWGS, 66.0% (243/ 368) of which were trisomy that defined 39.6% (38/96) of patients as hyperdiploidy and the remaining 60.4% (58/96) as non-hyperdiploidy. The most frequently mutational CNA peak region were amp(1q21), del(1p), del(6q), del(8p), del(13q14) and del(14q). The concordance rate between sWGS and FISH in detecting the four conventional loci (1q21 gain, 13q14 del, 13q14.3 del, and 17p13 del) was 81.8%. Comparing to the conventional approaches, sWGS provided new CNA information for 75.0% of the patients, and redefined the risk stratification for 17.2% of patients according to mSMART criteria. CNA detection results using paired bone marrow aspiration samples and enriched plasma cell samples from 8 patients were compared. We found that more CNAs (81 vs 58) and higher Log R ratio of CNAs were detected using enriched plasma cells than that using bone marrow aspiration samples. The concordance rate of the CNA detection results by sWGS between paired bone marrow genomic DNA and plasma cfDNA from another 9 patients was 83.3%. Conclusions LeukoPrint is an automated, convenient and cost-effective approach to depict CNA profile in genomic DNA or cfDNA. This method is superior to conventional approaches when used for CNA testing, and the practice of this method could improve prognostic stratification of MM patients.
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