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Author Manuscript Published OnlineFirst on April 23, 2021; DOI: 10.1158/1078-0432.CCR-20-4375 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. 1 Integration of genomic and transcriptomic markers improves the 2 prognosis prediction of acute promyelocytic leukemia 3 4 Authors and Affiliations: 5 Xiaojing Lin1, Niu Qiao1, Yang Shen1, Hai Fang1, Qing Xue1, Bowen Cui1, Li Chen1, Hongming 6 Zhu1, Sujiang Zhang1, Yu Chen1, Lu Jiang1, Shengyue Wang1, Junmin Li1, Bingshun Wang2, 7 Bing Chen1, Zhu Chen1, Saijuan Chen1, 8 L.X.J., Q.N., S.Y. contributed equally to this work. 9 1Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National 10 Research Center for Translational Medicine (Shanghai), Rui-Jin Hospital, Shanghai Jiao Tong 11 University School of Medicine and School of Life Sciences and Biotechnology, Shanghai Jiao 12 Tong University, 200025, Shanghai, China 13 2Department of Biostatistics and Clinical Research Center, Shanghai Jiao Tong University 14 School of Medicine, 200025, Shanghai, China 15 16 Running head: Integrated genomic and transcriptomic model in APL 17 Keywords: APL, NRAS, genomics, transcriptomics, prognosis 18 Corresponding authors: 19 Saijuan Chen, State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, 20 National Research Center for Translational Medicine (Shanghai), Rui-Jin Hospital, Shanghai 21 Jiao Tong University School of Medicine and School of Life Sciences and Biotechnology, 22 Shanghai Jiao Tong University,197 Rui-Jin Er Road, 23 Shanghai, 200025,China 24 Tel: +86-21-33562658 25 Fax: +86-21-64743206 26 E-mail: [email protected] 27 28 29 Zhu Chen, MD, PhD 30 Shanghai Institute of Hematology, 31 Rui-Jin Hospital, 1 Downloaded from clincancerres.aacrjournals.org on September 25, 2021. © 2021 American Association for Cancer Research. Author Manuscript Published OnlineFirst on April 23, 2021; DOI: 10.1158/1078-0432.CCR-20-4375 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. 1 197 Rui-Jin Er Road, 2 Shanghai 200025,China 3 Tel: +86-21-33562658 4 Fax: +86-21-64743206 5 E-mail: [email protected] 6 7 Yang Shen, MD, PhD 8 Shanghai Institute of Hematology, 9 Rui-Jin Hospital, 10 197 Rui-Jin Er Road, 11 Shanghai 200025,China 12 Tel: +86-21-33562658 13 Fax: +86-21-64743206 14 E-mail: [email protected] 15 16 17 Competing interests 18 All authors declare no competing interest. 19 2 Downloaded from clincancerres.aacrjournals.org on September 25, 2021. © 2021 American Association for Cancer Research. Author Manuscript Published OnlineFirst on April 23, 2021; DOI: 10.1158/1078-0432.CCR-20-4375 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. 1 Statement of translational relevance 2 Acute promyeloid leukemia (APL), which is used to be one of the deadliest forms of cancer, 3 has gradually become highly curable. However, in a subset of APL patients, early death and 4 relapse remained challenges for the treatment. Moreover, with the treatment strategy evolved 5 from ATRA and chemotherapy (ATRA–chemotherapy)- to ATRA and ATO (ATRA–ATO)-based 6 synergistic targeted therapy, the classic risk stratification needs further improvement. In this 7 study, we identified a feasible and reliable way and established an integrated system to 8 discriminate APL patients into high- (HR) and standard-risk (SR) groups. The revised HR 9 group displayed significantly worse outcomes than the revised SR one. In summary, we could 10 better define the risks of APL, add predictive value to the choice of currently available 11 therapeutic tools, and make the clinical decision more convenient and clearer. 12 3 Downloaded from clincancerres.aacrjournals.org on September 25, 2021. © 2021 American Association for Cancer Research. Author Manuscript Published OnlineFirst on April 23, 2021; DOI: 10.1158/1078-0432.CCR-20-4375 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. 1 Abstract 2 Purpose: The current stratification system for acute promyelocytic leukemia (APL) is based on 3 the white blood cell (WBC) and the platelet counts (i.e., Sanz score) over the past two decades. 4 However, the borderlines among different risk groups are sometimes ambiguous, and for some 5 patients, early death and relapse remained challenges. Besides, with the evolving of the 6 treatment strategy from ATRA-chemotherapy to ATRA-ATO-based synergistic targeted therapy, 7 the precise risk stratification with molecular markers is needed. 8 Patients and Methods: This study performed a systematic analysis of APL genomics and 9 transcriptomics to identify genetic abnormalities in 348 patients mainly from the APL2012 trial 10 (NCT01987297) to illustrate the potential molecular background of Sanz score and further 11 optimize it. The least absolute shrinkage and selection operator (LASSO) algorithm was used 12 to analyze the gene expression in 323 cases to establish a scoring system (i.e., APL9 score). 13 Results: Through combining NRAS mutations, APL9 score with WBC, 321 cases can be 14 stratified into two groups with significantly different outcomes. The estimated 5-year overall (P 15 = 0.00031), event-free (P < 0.0001), and disease-free (P = 0.001) survival rates in the revised 16 standard-risk group (95.6%, 93.8%, and 98.1%, respectively) were significantly better than 17 those in the revised high-risk group (82.9%, 77.4%, and 88.4%, respectively), which could be 18 validated using The Cancer Genome Atlas dataset. 19 Conclusions: We have proposed a two-category system improving prognosis in APL patients. 20 Molecular markers identified in this study may also provide genomic insights into the disease 21 mechanism for improved therapy. 22 4 Downloaded from clincancerres.aacrjournals.org on September 25, 2021. © 2021 American Association for Cancer Research. Author Manuscript Published OnlineFirst on April 23, 2021; DOI: 10.1158/1078-0432.CCR-20-4375 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. 1 Introduction 2 Acute promyelocytic leukemia (APL) is a unique subtype of acute myeloid leukemia (AML), 3 characterized by the expansion and accumulation of leukemic cells blocked at the 4 promyelocytic stage of granulocytic differentiation and the presence of a specific disease driver 5 fusion gene encoding the PML–RARA oncoprotein. In the last two decades, the 6 all-trans-retinoic acid (ATRA) and arsenic trioxide (ATO)-based combination (ATRA–ATO) 7 showed a considerable advantage over traditional ATRA and chemotherapy combination 8 (ATRA–chemotherapy)-based protocol and has become the standard APL core treatment 9 regimen nowadays (1-3). Meanwhile, the Sanz score was widely used to classify APL patients 10 into three risk categories according to white blood cell (WBC) and platelet (PLT) counts 11 (low-risk: WBC count ≤ 10 × 109/L and PLT count > 40 × 109/L; intermediate-risk: WBC count 12 ≤ 10 × 109/L and PLT count ≤ 40 × 109/L; and high-risk: WBC count >10 × 109/L) (4). 13 While Sanz score represents a very useful first-generation tool to stratify APL, we propose to 14 further enrich the current APL risk evaluation system taking into consideration several factors. 15 First, although the hemogram criteria of the risks of APL seem to be easily applicable, such 16 criteria appear not so straightforward for some patients, especially due to the fluctuation in 17 WBC and PLT levels caused by infection and drugs. Notably, now ATRA is routinely used to 18 treat APL, often causing leukocytosis syndrome (5). The inclusion of reliable molecular 19 markers can be of great value in this aspect. Second, the data to generate the Sanz risk score 20 was mostly from the clinical trials of ATRA–chemotherapy, which showed significant inferior 21 results as compared to current ATRA–ATO treatment in low- and intermediate-risk categories 22 (6). Third, the identification of biological markers related to distinct disease outcomes may 23 allow not only a better understanding of the molecular mechanisms underlying different clinical 24 phenotypes as those in Sanz score but also a precision use of novel therapeutic methods, 25 such as targeted drugs or immune therapies. 26 Therefore, we generated gene mutations and expression profiles of 348 APL patients enrolled 27 in the APL2012 trial (NCT01987297), the largest cohort ever reported(7). Integration of 28 genomics and transcriptomics allowed us to panoramically clarify the importance of gene 29 mutations and expression profiles on the risk assessment and the prognosis of APL. 5 Downloaded from clincancerres.aacrjournals.org on September 25, 2021. © 2021 American Association for Cancer Research. Author Manuscript Published OnlineFirst on April 23, 2021; DOI: 10.1158/1078-0432.CCR-20-4375 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. 1 Patients and Methods 2 Patients 3 A total of 348 APL patients with available bone marrow (BM) samples were included in this 4 study, including a majority part of the patients (n = 304) coming from the APL2012 clinical trial 5 (NCT01987297) from December 6, 2012 to December 31, 2017, and a small group of the 6 patients (n = 44) from the historical cases between June 1, 2012 to November 31, 2012, who 7 received the similar treatment (Table 1). It is noteworthy that the key part in APL2012 trial for 8 randomization into two groups with or without ATO was at the phase of consolidation while all 9 patients received ATRA–ATO treatment for remission induction and maintenance. As a result, 10 there were no statistically significant differences in terms of 3-year disease-free survival (DFS) 11 as well as estimated 7-year DFS and overall survival (OS) between the two groups(7). When 12 the 348 cases investigated in the present work were scrutinized for their treatment and 13 outcome data, there were 22 cases of early death during remission induction and two cases 14 who were lost during follow-up.
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