Clinical and Biological Implications of Mutational Spectrum in Acute Myeloid Leukemia of FAB Subtypes M0 and M1

Acute myeloid leukemia (AML) is a heterogeneous malignancy characterized by clonal expansion and differentiation arrest of myeloid progenitors in the bone marrow and peripheral blood; historically AML had poor prognosis [1]. Optimizing treatment based on accurate diagnosis and prognostic evaluation in individual patients is particularly important due to disease heterogeneity [2]. Recently, next generation sequencing (NGS) has shown great potential in AML diagnosis and risk stratification because of its massive parallel sequencing ability and high throughput multiplexing capacity [3]. NGS helped characterizing several recurrent somatic mutations in AML, drawing the details of its mutational spectrum [4]. The growing list of mutations involve prognosticators such as NPM1, FLT3-ITD, CEBPA, DNMT3A, IDH1 and IDH2, as well as genes implicated in leukemogenesis, such as EZH2, U2AF1, SMC1A and SMC3 [5]. A recent study analyzed 1, 540 AML patients by cytogenetic profiling and targeted resequencing of 111 myeloid cancer genes, the patterns of co-occurrence and mutual exclusivities of genetic changes segregated AML patients into 11 nonoverlapping classes, each with a distinct clinical phenotype and outcome [6]. Another study analyzed the genomes of 200 adult AML patients by NGS, and mutations were divided into nine categories. Almost all AML patients had one or more mutations that fell into the nine categories, and a complex interplay of genetic alterations was found [5].

Several decades ago, in order to provide objectivity in the diagnosis of AML that would facilitate comparisons between series of cases, the French-American-British (FAB) Cooperative Group developed a classification system based on conventional morphologic and cytochemical characteristics and divided AML into FAB subtypes (M0-M7) [7], with AML-M0 and M1 being the poorly differentiated subtypes. Although advances in identification of prognostic genetic alterations have facilitated detailed risk stratification [8], currently no research has addressed the mutational spectrum of AML-M0 and M1. It’s unclear whether they differ in mutational spectrum and how genetic signatures influence their prognosis. We intended to describe the clinical and molecular prognostic factors for the development of optimal and individualized therapy for AML-M0 and M1 patients.

Sixty-five AML patients derived from The Cancer Genome Atlas (TCGA) database (https://cancergenome.nih.gov/) were enrolled in this study [5], including 19 AML-M0 and 46 AML-M1 patients. Poor-risk patients each underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) if there was no contraindication and a matched donor was available. Many intermediate risk patients also underwent allo-HSCT. The number of patients receiving allo-HSCT was 37 and the rest 28 had chemotherapy only. Whole-genome sequencing was performed to depict the mutational spectrum of each patient. Clinical characteristics at diagnosis, including peripheral blood (PB) white blood cell counts (WBC), blast percentages in PB and bone marrow (BM), French-American-British (FAB) subtypes and the frequencies of known recurrent genetic mutations were described. Detailed descriptions of clinical and molecular characteristics were publicly accessible from the TCGA website. Event-free survival (EFS) and overall survival (OS) were the primary endpoints of this study. EFS was defined as the time from diagnosis to the first event including relapse, death, absence of complete remission or the last follow up. OS was defined as the time from diagnosis to death from any cause or the last follow-up. All patients provided informed consent, and the study protocol was approved by the Washington University Human Studies Committee.

The clinical and molecular characteristics of patients were summarized using descriptive statistics. Data sets were described with median and/or range. Survival was estimated using the Kaplan-Meier method and the log-rank test. Univariate Cox proportional hazards models were used to identify clinical and molecular variables associated with survival. Multivariate proportional hazards models were constructed for EFS and OS, using a limited backward elimination procedure. P< 0.05 was considered statistically significant for all analyses. All statistical tests were two-sided and were performed by SPSS software 20.0 and GraphPad Prism software 5.0.

The demographic and biological characteristics of the patients were summarized in Table 1. Median age was 58 (range 18-88) years, with 31 cases older than 60. Thirty-seven cases were men. Nineteen patients were AML-M0 and 46 were AML-M1. The median WBC count at diagnosis was 19.8×10⁹/L, and in 16 cases it was ≥50×10⁹/L. Forty-eight patients had BM blast percentage more than 70% and 28 had PB blasts more than 70%. Thirty-four patients had abnormal karyotypes. Sixty patients had intermediate or poor risk AML. Chemotherapy was differed in two patients due to old age and poor functional status. Thirty-seven patients received HSCT, of which 24 cases achieved complete remission. Forty-six patients had more than five recurrent genetic mutations. FLT3 had the highest mutation frequency (n=20, 31%), followed by NPM1 (n=18, 28%), DNMT3A (n=16, 25%), IDH1 (n=14, 22%), IDH2 (n=12, 18%), RUNX1 (n=11, 17%) and TET2 (n=7, 11%) (Fig. 1).

EFS and OS of different age (≥60 vs. < 60 years), WBC count (≥50 vs. < 50×10⁹/L), BM blasts (≥70% vs. < 70%), PB blasts (≥70% vs. < 70%), allo-HSCT (yes vs. no), FLT3-ITD (positive vs. negative), and the mutation status of other common AML mutations (NPM1, DNMT3A, IDH1, IDH2, RUNX1, CEBPA, TP53, PTPN11, MT-CO2, ASXL1, NRAS, KRAS, TTN and STAG2, mutated vs. wild type), were compared with the Kaplan-Meier method and the log-rank test, as listed in Table 2. Older patients (age ≥60) had shorter EFS and OS (P=0.013, P=0.002, respectively, Fig. 2A and 2B). WBC count ≥50×10⁹/L negatively affected EFS (P=0.002, Fig. 2C). Positive FLT3-ITD was associated with shorter EFS (P=0.031, Fig. 3A). Patients with TP53 mutations had shorter EFS and OS (P=0.028, P=0.002, respectively, Fig. 3E and 3F). Patients with NPM1 mutations had longer OS (P=0.032, Fig. 3D). Furthermore, patients received allo-HSCT had longer EFS and OS (P< 0.001, P< 0.001, respectively, Fig. 4A and 4B). Other variables did not demonstrate effect on EFS or OS.

To further explore the prognostic significance of the aforementioned factors, we did univariate analysis and selected factors that had statistical significance to construct the multivariate COX regression model for EFS and OS. Univariate analysis showed that age ≥60 years was an unfavorable factor for EFS and OS (P=0.015, P=0.003, respectively), as well as TP53 mutations (P=0.036, P=0.004 for EFS and OS, respectively), WBC count ≥50×10⁹/L and FLT3-ITD negatively affected EFS (P=0.003, P=0.034, respectively), whereas NPM1 mutations favorably affected OS (P=0.035), and alloHSCT was a favorable factor for EFS and OS (all P< 0.001) (Table 3). Multivariate analysis suggested that allo-HSCT was an independent favorable factor for EFS (HR: 0.358, 95% CI: 0.201-0.640, P=0.001), the effect was more prominent after adjusting for NPM1 mutation status (P=0.025) and WBC count (P=0.002). It was also an independent favorable factor for OS (HR: 0.374, 95% CI: 0.209-0.669, P=0.001), with more profound effect after adjusting for NPM1 (P=0.002) and TP53 mutation status (P=0.043) (Table 4).

AML is a genetically heterogeneous disease resulting from complex interactions among different leukemogenic pathways, so integrated mutational analysis is highly valuable for evaluation [5, 9]. Formerly, the mutational spectrum of AML-M0 and M1 was unclear. In this study, we found that FLT3-ITD, NPM1, DNMT3A, IDH1, IDH2, RUNX1 and TET2 were mutated in more than 10% of all patients with FLT3-ITD exhibiting the highest frequency; CEBPA, TP53, PTPN11, MT-CO2, ASXL1, NRAS, KRAS, TTN and STAG2 also had more than 5% mutation frequency. This was different from previous reports which showed that CEBPA, NPM1, DNMT3A, FLT3-ITD, NRAS, IDH2 and WT1 were mutated in more than 10% and CEBPA mutations were more frequent in intermediate-risk AML [10, 11]. The reported frequency of CEBPA mutations in cytogenetically normal AML (CN-AML) was also higher, about 35% [12]. The discrepancy suggested that poorly differentiated AML might have a distinct mutational spectrum.

In uni- and multivariate analyses, we found that age ≥60 years was an adverse factor for EFS and OS, which was consistent with the fact that AML patients younger than 60 years had improved prognosis and approximately 35-40% of them would get cured [13]. WBC count ≥50×10⁹/L was also related to shorter EFS and OS, which was consistent with previous finding that WBC count had a significant impact on complete remission rate, EFS and OS in AML patients [14].

FLT3 is a class III family receptor tyrosine kinase that acts as a cytokine receptor for the FLT3 ligand. FLT3 is strongly expressed in hematopoietic stem cells with important roles in cell survival and proliferation [15]. FLT3-ITD was among the most frequent mutations observed in AML, it could activate FLT3 signaling, promoting blast proliferation [16]. Furthermore, FLT3-ITD was associated with increased risk of relapse in AML [17]. NPM1 is involved in numerous cellular functions, such as ribosome biogenesis, DNA repair and regulation of apoptosis. NPM1 mutations were among the most common genetic changes in AML, especially in CN-AML [18]. In the absence of FLT3-ITD, NPM1 mutations were associated with improved outcomes for CN-AML patients. NPM1 mutations have been associated with chemo-sensitivity to intensive chemotherapy in both young and old patients, which might account for improved outcomes [19]. NPM1 mutations were also associated with other recurrent genetic abnormalities, such as DNMT3A, FLT3-ITD and IDH mutations [20]. The pattern of co-mutations largely shaped clinical outcomes. TP53 mutations were rare in patients lacking chromosomal deletions, and it conferred an adverse prognosis with documented chemo-resistance [21, 22]. TP53 mutations might be responsible for the poor prognosis of complex karyotype AML [23]. Our results showed that FLT3-ITD and TP53 mutations were associated with shorter EFS and OS, while NPM1 mutations were associated with favorable prognosis, consistent with previous results. Furthermore, studies indicated that allo-HSCT could lead to better clinical outcomes for patients with unfavorable-risk cytogenetics in the first complete remission [24]. The favorable effect of allo-HSCT was also replicated in our univariate analysis, and the effect was still exist after adjusting for potential confounding factors (age, WBC, FLT3-ITD, NPM1 and TP53).

Several limitations need to be acknowledge. First, due to the limited number of our cases, we didn’t stratify data more precisely based on factors that could affect the prognosis. So, our results didn’t fully account for the effect of mutational spectrum and clinical data on prognosis. Second, our study was a retrospective study which could suffer from inherited biases as opposed to prospective studies.

In summary, we conducted a TCGA database-derived analysis on the mutational profiles and prognosis of AML-M0 and M1 and compared our findings with previous studies. Our study provided new insights into the clinical and biological implications of mutational spectrum in AML-M0 and M1. FLT3-ITD, NPM1 and TP53 could be incorporated into AML-M0 and M1 risk stratification and these patients would likely benefit from allo-HSCT.

This work was supported by grants from the National Natural Science Foundation of China (81500118, 61501519), the China Postdoctoral Science Foundation funded project (project No.2016M600443), Jiangsu Province Postdoctoral Science Foundation funded project (project No.1701184B) and PLAGH project of Medical Big Data (project No.2016MBD-025).

The authors declare to have no conflict of interests.

K. Hu, Q. Zhang, J. Shi, L. Fu contributed equally to this work.