Expression level of ACOT7 influences the prognosis in acute myeloid leukemia patients

Abstract

BACKGROUND

: ACOT plays an important role in lipid metabolism and recent studies found that ACOT participates in some kinds of tumorigenesis. However, both the role of ACOT and its significance have not been revealed in AML. Therefore, we conduct this study in order to investigate the association between AML and ACOT, and hopefully contributed to the management of AML.

METHODS

: One hundred and fifty-six AML patients were enrolled in our study whose data were derived from the Cancer Genome Atlas database. There were 85 patients who received only chemotherapy and other 71 patients underwent allo-HSCT.

RESULTS

: Patients in high ACOT7 group had a significant lower EFS and OS, while patients in high versus low expression levels of other types of ACOT showed no significant difference on the outcome. High level of ACOT7 related with poor outcome in both chemotherapy-only group and HSCT group.

CONCLUSIONS

: High expression level of ACOT7 indicates unfavorable outcome in AML patients. Allo-HSCT could not overcome the unfavorable effect of ACOT7 in these patients.

Keywords

ACOT7 acute myeloid leukemia chemotherapy allo-HCST prognosis

1. Introduction

Acute myeloid leukemia (AML) is a kind of highly genetically heterogeneous disease, which is characterized by the rapid proliferation and loss of differentiation of myeloid stem cells or progenitor cells in the bone marrow [1]. Though methods of diagnosis and therapy are improved greatly these years, AML is still considered to have poor outcomes with a five-year-survival rate of about 27.4% (Surveillance Epidemiology and End Results [SEER] Cancer Statistics Review 2008–2014) [2]. Recent advances in techniques of genomic analysis suggested many biomarkers for the prognosis of AML patients in the genetic level, including the mutation of NPM1, DNMT3A, FLT3-ITD/TKD, TET2, TP53, etc. [1, 3]. Detecting new biomarkers and understanding the specific roles of these biomarkers can not only inform prognosis, but also provide possible targets for therapies.

During the past decades, there has been an increasing interest in the metabolism of tumor cells, and recent studies reported that hematological malignancies and solid neoplasms can remodel the pathways of glucose and lipid metabolism to aerobic glycolysis (Warburg effect), supporting the formation of neoplasia [4, 5]. Acyl-CoA thioesterase (ACOT) is a superfamily of enzymes that control an critical step in catalyzing the hydrolysis of fatty acyl-CoA to coenzyme A (CoA) and free fatty acid (FFA) [6]. Previous studies have demonstrated the association between ACOT and cancers [5, 6, 7, 8, 9, 10, 11]. For example, ACOT8 in hepatocellular carcinoma [6], ACOT11 and ACOT13 in lung adenocarcinoma [11], and ACOT1 in gastric adenocarcinoma [5] are all suggested that the overexpression of ACOT can lead to a lower cumulative survival rate [5, 6, 11]. In addition, Patients with low ACOT7 levels shows longer overall survival periods in both breast cancer and lung cancer, and this conclusion had been confirmed by experiments in vitro [12]. These studies above confirm that ACOTs play a significant role in tumorigenesis.

However, both the function and contribution of ACOT in AML have not yet been investigated. In this study, we analyzed one hundred fifty six AML patients to identify the relationship between the expression levels of ACOT1-13 and the outcomes. The study of this relationship may provide us with a new therapeutic strategy to guide and support clinical decisions.

2. Materials and methods

2.1 Patients

A total of 156 de novo AML patients with ACOT expression data at diagnosis were enrolled in our study and data of these patients were all derived from The Cancer Genome Atlas (TCGA) database (https://can-cergenome.nih.gov/). Expression levels of ACOT were all obtained by next generation sequencing (NGS) technology. Data on demographic characteristics and molecular characteristics of AML patients, event-free survival (EFS), overall survival (OS), expression level of ACOT1-13, etc. were collected and analyzed. All the samples were collected between November of 2001 and March of 2010. All patients were between ages 18 and 88 and had previously untreated de novo AML. They were treated in accordance with NCCN guidelines (www.nccn.org), with an emphasis on enrollment in therapeutic clinical trials wherever possible [13]. Eighty-five patients received only chemotherapy and the other 71 patients received allogeneic hematopoietic stem cell transplantation (allo-HSCT), of whom two underwent haploidentical HSCT, 30 received sib allo-HSCT and the other 39 underwent matched unrelated donor (MUD) HSCT. Written informed consent was obtained from all patients, which was approved by the Human Research Ethics Committee of Washington University.

2.2 Statistical analysis

EFS and OS were chosen as the primary end points in this study. EFS was defined as the time from the date of diagnosis to removal from the study due to the absence of complete remission, relapse or death. OS was defined as the time from the date of diagnosis to death due to any cause.

Descriptive statistics were used to summarize the clinical and molecular characteristics of patients. The student t-test and chi-square test were applied to two group comparisons. Fisher’s exact test was used if the sample size in the table was less than five. The EFS and OS rates were calculated by using the Kaplan-Meier method and compared using the log-rank test. We used cox proportional hazard model to assess the hazard ratios associated with the prognosis. For all statistical analyses, $P$ values were two-sided and $P$ -value $<$ 0.05 was considered significant. All statistical analyses were performed with SPSS software 22.0 and GraphPad Prism software 5.0.

Table 1
Comparison of EFS and OS between different expression levels of ACOT1-13 in chemotherapy-only group

Variables	EFS		OS
	$\chi^{2}$	$P$ -value	$\chi^{2}$	$P$ -value
ACOT1 (high vs. low)	0.538	0.463	0.355	0.551
ACOT2 (high vs. low)	1.129	0.288	1.365	0.243
ACOT4 (high vs. low)	0.055	0.814	0.221	0.638
ACOT6 (high vs. low)	1.025	0.311	0.682	0.409
ACOT7 (high vs. low)	11.923	0.001	9.734	0.002
ACOT8 (high vs. low)	0.011	0.915	0.031	0.860
ACOT9 (high vs. low)	0.989	0.320	0.956	0.328
ACOT11 (high vs. low)	0.003	0.959	0.010	0.921
ACOT12 (high vs. low)	0.411	0.521	0.199	0.656
ACOT13 (high vs. low)	0.025	0.875	0.103	0.748

Abbreviations: EFS, event-free survival; OS, overall survival.

Table 2A

Clinical and molecular characteristics of patients in all patients

Characteristics	High ACOT7 ( $n=$ 78)		Low ACOT7 ( $n=$ 78)		$P$
Age/years, median (range)	61 (	18–88)	57 (	21–87)	0.204 ${}^{*}$
Age group/ $n$ (%)					0.025 ${}^{\mathsection}$
$<$ 60 years	32 (	41.0)	46 (	59.0)
$\geqslant$ 60 years	46 (	59.0)	32 (	41.0)
Gender/ $n$ (%)					0.053 ${}^{\mathsection}$
Male	49 (	62.8)	37 (	47.5)
Female	29 (	37.2)	41 (	52.6)
WBC/ $\times$ 10 ${}^{9}$ /L, median (range)	27.65 (	0.6–223.8)	18.75 (	0.7–297.4)	0.313 ${}^{*}$
BM blast/%, median (range)	74 (	30–98)	67 (	30–100)	0.554 ${}^{*}$
PB blast/%, median (range)	48.5 (	0–97)	34 (	0–98)	0.114 ${}^{*}$
FAB subtypes/ $n$ (%)
M0	5 (	6.6)	11 (	14.1)	0.126 ${}^{\mathsection}$
M1	26 (	34.2)	17 (	21.8)	0.086 ${}^{\mathsection}$
M2	20 (	26.3)	19 (	24.4)	0.780 ${}^{\mathsection}$
M3	1 (	1.3)	0 (	0.0)	0.494 ${}^{\mathsection}$
M4	9 (	11.8)	24 (	30.8)	0.004 ${}^{\mathsection}$
M5	10 (	13.2)	7 (	9.0)	0.408 ${}^{\mathsection}$
M6	2 (	2.6)	0 (	0.0)	0.242 ${}^{\mathsection}$
M7	3 (	3.9)	0 (	0.0)	0.118 ${}^{\mathsection}$
Cytogenetics/ $n$ (%)
Normal	36 (	47.4)	37 (	48.1)	0.933 ${}^{\mathsection}$
Complex karyotype	17 (	22.4)	6 (	7.8)	0.012 ${}^{\mathsection}$
8 Trisomy	3 (	3.9)	5 (	6.5)	0.719 ${}^{\mathsection}$
inv(16)/CBF $\beta$ -MYH11	2 (	2.6)	9 (	11.7)	0.056 ${}^{\mathsection}$
11q23/MLL	3 (	3.9)	3 (	3.9)	1.000 ${}^{\mathsection}$
-7/7q-	4 (	5.3)	2 (	2.6)	0.442 ${}^{\mathsection}$
t(15;17)/PML-RARA	1 (	1.3)	0 (	0.0)	0.497 ${}^{\mathsection}$
t(9;22)/BCR-ABL1	3 (	3.9)	0 (	0.0)	0.120 ${}^{\mathsection}$
t(8;21)/RUNX1-RUNX1T1	1 (	1.3)	6 (	7.8)	0.116 ${}^{\mathsection}$
Others	6 (	7.9)	9 (	11.7)	0.430 ${}^{\mathsection}$
Risk/ $n$ (%)
Good	4 (	5.3)	15 (	19.5)	0.013 ${}^{\mathsection}$
Intermediate	40 (	52.6)	46 (	59.7)	0.376 ${}^{\mathsection}$
Poor	32 (	42.1)	16 (	20.8)	0.004 ${}^{\mathsection}$
NPM1/ $n$ (%)					0.860 ${}^{\mathsection}$
Mutation	23 (	29.5)	22 (	28.2)
Wild type	55 (	70.5)	56 (	71.8)
FLT3-ITD/TKD/ $n$ (%)					0.075 ${}^{\mathsection}$
Positive	27 (	34.6)	17 (	21.8)
Negative	51 (	65.4)	61 (	78.2)
DNMT3A/ $n$ (%)					0.714 ${}^{\mathsection}$
Mutation	19 (	24.4)	21 (	26.9)
Wild type	59 (	75.6)	57 (	73.1)
IDH1/IDH2/ $n$ (%)					0.428 ${}^{\mathsection}$
Mutation	14 (	17.9)	18 (	23.1)
Wild type	64 (	82.1)	60 (	76.9)
NRAS/KRAS/ $n$ (%)					0.463 ${}^{\mathsection}$
Mutation	11 (	14.1)	8 (	10.3)
Wild type	67 (	85.9)	70 (	89.7)
TET2/ $n$ (%)					0.786 ${}^{\mathsection}$
Mutation	8 (	10.3)	7 (	9.0)
Wild type	70 (	89.7)	71 (	91.0)
TP53/ $n$ (%)					0.005 ${}^{\mathsection}$
Mutation	13 (	16.7)	2 (	2.6)
Wild type	65 (	83.3)	76 (	97.4)

Table 2A, continued
Characteristics	High ACOT7 ( $n=$ 78)		Low ACOT7 ( $n=$ 78)		$P$
RUNX1/ $n$ (%)					0.113 ${}^{\mathsection}$
Mutation	5 (	6.4)	11 (	14.1)
Wild type	73 (	93.6)	67 (	85.9)
Relapse/ $n$ (%)					0.631 ${}^{\mathsection}$
Yes	37 (	47.4)	40 (	51.3)
No	41 (	52.6)	38 (	48.7)

Abbreviations: WBC, white blood cell; BM, bone marrow; PB, peripheral blood; FAB, French American British; ‘*’ denotes Student $t$ -test; ‘§’ denotes chi-square test.

Table 2B

Clinical and molecular characteristics of patients in different treatment groups

Characteristics	Chemotherapy-only group					Allo-HSCT group
	High ACOT7		Low ACOT7		$P$	High ACOT7		Low ACOT7		$P$
	( $n=$ 43)		( $n=$ 42)			( $n=$ 36)		( $n=$ 35)
Age/years, median (range)	67 (	35–88)	66 (	22–81)	0.167 ${}^{*}$	53 (	18–65)	51 (	21–72)	0.638 ${}^{*}$
Age group/ $n$ (%)					0.138 ${}^{\mathsection}$					0.205 ${}^{\mathsection}$
$<$ 60 years	10 (	23.3)	16 (	38.1)		24 (	66.7)	28 (	80.0)
$\geqslant$ 60 years	33 (	76.7)	26 (	61.9)		12 (	33.3)	7 (	20.0)
Gender/ $n$ (%)					0.066 ${}^{\mathsection}$					0.123 ${}^{\mathsection}$
Male	27 (	62.8)	18 (	42.9)		24 (	66.7)	17 (	48.6)
Female	16 (	37.2)	24 (	57.1)		12 (	33.3)	18 (	51.4)
WBC/ $\times$ 10 ${}^{9}$ /L, median (range)	17.0 (	1.4–171.9)	12.2 (	0.7–297.4)	0.553 ${}^{*}$	33.9 (	0.6–223.8)	27.1 (	1.2–202.7)	0.163 ${}^{*}$
BM blast/%, median (range)	76 (	32–98)	65.5 (	30–99)	0.081 ${}^{*}$	73.5 (	30–100)	64 (	39–99)	0.490 ${}^{*}$
PB blast/%, median (range)	46 (	0–97)	16 (	0–98)	0.106 ${}^{*}$	56.5 (	0–94)	38 (	0–96)	0.094 ${}^{*}$
FAB subtypes/ $n$ (%)
M0	4 (	9.5)	3 (	7.1)	1.000 ${}^{\mathsection}$	2 (	5.7)	7 (	20.0)	0.151 ${}^{\mathsection}$
M1	14 (	33.3)	6 (	14.3)	0.040 ${}^{\mathsection}$	14 (	40.0)	9 (	25.7)	0.203 ${}^{\mathsection}$
M2	9 (	21.4)	12 (	28.6)	0.450 ${}^{\mathsection}$	11 (	31.4)	7 (	20.0)	0.274 ${}^{\mathsection}$
M3	0 (	0.0)	0 (	0.0)	1.000 ${}^{\mathsection}$	1 (	2.9)	0 (	0.0)	1.000 ${}^{\mathsection}$
M4	6 (	14.3)	14 (	33.3)	0.040 ${}^{\mathsection}$	3 (	8.6)	10 (	28.6)	0.062 ${}^{\mathsection}$
M5	7 (	16.7)	6 (	14.3)	0.763 ${}^{\mathsection}$	2 (	5.7)	2 (	5.7)	1.000 ${}^{\mathsection}$
M6	1 (	2.4)	0 (	0.0)	1.000 ${}^{\mathsection}$	1 (	2.9)	0 (	0.0)	1.000 ${}^{\mathsection}$
M7	1 (	2.4)	1 (	2.4)	1.000 ${}^{\mathsection}$	1 (	2.9)	0 (	0.0)	1.000 ${}^{\mathsection}$
Cytogenetics/ $n$ (%)
Normal	18 (	43.9)	22 (	52.4)	0.440 ${}^{\mathsection}$	18 (	50.0)	15 (	44.1)	0.622 ${}^{\mathsection}$
Complex karyotype	9 (	22.0)	3 (	7.1)	0.067 ${}^{\mathsection}$	7 (	19.4)	4 (	11.8)	0.515 ${}^{\mathsection}$
8 Trisomy	2 (	4.9)	0 (	0.0)	0.241 ${}^{\mathsection}$	3 (	8.3)	3 (	8.8)	1.000 ${}^{\mathsection}$
inv(16)/CBF $\beta$ -MYH11	2 (	4.9)	4 (	9.5)	0.676 ${}^{\mathsection}$	1 (	2.8)	4 (	11.8)	0.192 ${}^{\mathsection}$
11q23/MLL	2 (	4.9)	1 (	2.4)	0.616 ${}^{\mathsection}$	1 (	2.8)	2 (	5.9)	0.609 ${}^{\mathsection}$
-7/7q-	2 (	4.9)	1 (	2.4)	0.616 ${}^{\mathsection}$	2 (	5.6)	1 (	2.9)	1.000 ${}^{\mathsection}$
t(15;17)/PML-RARA	0 (	0.0)	0 (	0.0)	1.000 ${}^{\mathsection}$	1 (	2.8)	0 (	0.0)	1.000 ${}^{\mathsection}$
t(9;22)/BCR-ABL1	1 (	2.4)	0 (	0.0)	1.000 ${}^{\mathsection}$	2 (	5.6)	0 (	0.0)	0.493 ${}^{\mathsection}$
t(8;21)/RUNX1-RUNX1T1	1 (	2.4)	5 (	11.9)	0.202 ${}^{\mathsection}$	0 (	0.0)	1 (	2.9)	0.486 ${}^{\mathsection}$
Others	4 (	9.8)	6 (	14.3)	0.738 ${}^{\mathsection}$	1 (	2.8)	4 (	11.8)	0.192 ${}^{\mathsection}$
Risk/ $n$ (%)
Good	3 (	7.3)	9 (	21.4)	0.116 ${}^{\mathsection}$	2 (	5.6)	5 (	14.7)	0.253 ${}^{\mathsection}$
Intermediate	22 (	53.7)	24 (	57.1)	0.750 ${}^{\mathsection}$	20 (	55.6)	20 (	58.8)	0.782 ${}^{\mathsection}$
Poor	16 (	39.0)	9 (	21.4)	0.081 ${}^{\mathsection}$	14 (	38.9)	9 (	26.5)	0.269 ${}^{\mathsection}$
NPM1/ $n$ (%)					0.275 ${}^{\mathsection}$					0.945 ${}^{\mathsection}$
Mutation	16 (	37.2)	11 (	26.2)		9 (	25.0)	9 (	25.7)
Wild type	27 (	62.8)	31 (	73.8)		27 (	75.0)	26 (	74.3)
FLT3-ITD/TKD/ $n$ (%)					0.100 ${}^{\mathsection}$					0.024 ${}^{\mathsection}$
Positive	15 (	34.9)	8 (	19.0)		15 (	41.7)	6 (	17.1)
Negative	28 (	65.1)	34 (	81.0)		21 (	58.3)	29 (	82.9)
DNMT3A/ $n$ (%)					0.248 ${}^{\mathsection}$					0.730 ${}^{\mathsection}$
Mutation	14 (	32.6)	9 (	21.4)		8 (	22.2)	9 (	25.7)
Wild type	29 (	67.4)	33 (	78.6)		28 (	77.8)	26 (	74.3)
IDH1/IDH2/ $n$ (%)					0.366 ${}^{\mathsection}$					0.368 ${}^{\mathsection}$
Mutation	6 (	13.9)	9 (	21.4)		7 (	19.4)	10 (	28.6)
Wild type	37 (	86.1)	33 (	78.6)		29 (	80.6)	25 (	71.4)
NRAS/KRAS/ $n$ (%)					0.563 ${}^{\mathsection}$					0.260 ${}^{\mathsection}$
Mutation	7 (	16.3)	5 (	11.9)		2 (	5.6)	5 (	14.3)
Wild type	36 (	83.7)	37 (	88.1)		34 (	94.4)	30 (	85.7)
TET2/ $n$ (%)					0.520 ${}^{\mathsection}$					1.000 ${}^{\mathsection}$
Mutation	7 (	16.3)	4 (	9.5)		2 (	5.6)	2 (	5.7)
Wild type	36 (	83.7)	38 (	90.5)		34 (	94.4)	33 (	94.3)

Table 2B, continued
Characteristics	Chemotherapy-only group					Allo-HSCT group
	High ACOT7		Low ACOT7		$P$	High ACOT7		Low ACOT7		$P$
	( $n=$ 43)		( $n=$ 42)			( $n=$ 36)		( $n=$ 35)
TP53/ $n$ (%)					0.195 ${}^{\mathsection}$					0.115 ${}^{\mathsection}$
Mutation	8 (	18.6)	3 (	7.1)		4 (	11.1)	0 (	0.0)
Wild type	35 (	81.4)	39 (	92.9)		32 (	88.9)	35 (	100.0)
RUNX1/ $n$ (%)					0.483 ${}^{\mathsection}$					0.151 ${}^{\mathsection}$
Mutation	3 (	7.0)	5 (	11.9)		2 (	5.6)	6 (	17.1)
Wild type	40 (	93.0)	37 (	88.1)		34 (	94.4)	29 (	82.9)
Relapse/ $n$ (%)					0.821 ${}^{\mathsection}$					0.063 ${}^{\mathsection}$
Yes	15 (	35.7)	16 (	38.1)		28 (	77.8)	20 (	57.1)
No	27 (	64.3)	26 (	61.9)		8 (	22.2)	15 (	42.9)

Abbreviations: WBC, white blood cell; BM, bone marrow; PB, peripheral blood; FAB, French American British; ‘*’ denotes Student $t$ -test; ‘§’ denotes chi-square test.

Figure 1.

Kaplan-Meier curves of EFS and OS in patients receive only chemotherapy. (A, B) EFS and OS for patients with high expression level of ACOT7 were obviously lower.

Figure 2.

Kaplan-Meier curves of EFS and OS in patients receive allo-HSCT. (A, B) EFS and OS for patients with high expression level of ACOT7 were obviously lower.

Table 3

Univariate analysis of EFS and OS in the chemotherapy-only group

Variables	EFS		OS
	HR (95%CI)	$P$ -value	HR (95%CI)	$P$ -value
ACOT7 (high vs. low)	2.278 (1.408–3.687)	0.001	2.105 (1.303–3.399)	0.002
Age ${}^{*}$	1.038 (1.018–1.060)	$<$ 0.001	1.038 (1.017–1.060)	$<$ 0.001
WBC ${}^{*}$	1.003 (0.998–1.009)	0.216	1.003 (0.998–1.008)	0.264
NPM1 (mutated vs. wild)	1.226 (0.744–2.022)	0.424	1.136 (0.689–1.874)	0.616
FLT3-ITD/TKD (present vs. absent)	1.383 (0.825–2.320)	0.219	1.330 (0.795–2.227)	0.278
DNMT3A (mutated vs. wild)	1.602 (0.957–2.681)	0.073	1.632 (0.977–2.728)	0.062
IDH1/2 (mutated vs. wild)	0.903 (0.494–1.652)	0.741	0.936 (0.512–1.711)	0.829
NRAS/KRAS (mutated vs. wild)	1.042 (0.533–2.038)	0.904	1.068 (0.546–2.088)	0.847
TET2 (mutated vs. wild)	0.836 (0.415–1.685)	0.616	0.733 (0.363–1.479)	0.386
TP53 (mutated vs. wild)	3.011 (1.535–5.906)	0.001	0.339 (0.173–0.663)	0.002
RUNX1 (mutated vs. wild)	1.451 (0.692–3.042)	0.325	1.586 (0.755–3.333)	0.224

Abbreviations: EFS, Event-free survival; OS, Overall survival; HR, hazard ratio; CI, confidence interval; WBC, white blood cell; BM, bone marrow; PB, peripheral blood; ITD, internal tandem duplication; TKD, tyrosine kinase domain. * Age and WBC are used as continuous variables.

3. Results

3.1 Relations between EFS and OS and expression levels of ACOT1-13

We divided the patients into two groups according to their expression level of ACOT1-13. Patients in high ACOT1-13 groups had an expression levels $\geqslant$ median level in chemotherapy-only group and other patients were defined as low ACOT1-13 expression. We did Kaplan-Meier analysis for EFS and OS on chemotherapy-only group and the results of the log-rank tests were summarized in Table 1. Patients in high ACOT7 group had a significant lower EFS and OS than patients in low group ( $p=$ 0.001 and $p=$ 0.002, respectively). However, patients in high versus low expression group of other types of ACOT showed no significant difference on EFS or OS.

3.2 Clinical and molecular characteristics

Here ACOT7 was chosen to do the further analysis as it had more significant impact on EFS and OS. All the 156 patients in our study were divided according to their expression of ACOT7. In this part, patients with an expression level $\geqslant$ median level of these 156 patients were classified as high ACOT7 expression group. The associations between expression level of ACOT7 and clinical and molecular characteristics were summarized in Table 2A. Patients with high expression level of ACOT7 were more observed in elder patients ( $p=$ 0.025) and it seems that high level of ACOT7 was associated with complex karyotype ( $p=$ 0.012), more patients at poor risk ( $p=$ 0.004). Nevertheless, high ACOT7 was relatively rare in patients of FAB M4 subtype ( $p=$ 0.003), patients at good risk ( $p=$ 0.013) and those harboring TP53 mutation ( $p=$ 0.005).

We also performed statistical analysis separately in chemotherapy-only group and HSCT group to assess if there were any inter-group differences (Table 2B). The median expression level of the chemotherapy-only group and allo-HSCT group were selected as the cut-off points, respectively. The association between high expression level of ACOT7 and less FAB M4 subtype was noticed in chemotherapy-only group ( $p=$ 0.040). However, FAB-M1 subtype patients were more observed in ACOT7 high-level group in those patients who received only chemotherapy ( $p=$ 0.040). In patients undergoing HSCT, on the other side, there were more patients carrying FLT3-ITD/TKD in ACOT7 high level group ( $p=$ 0.024). These inter-group differences might have an influence on our further analysis.

3.3 Prognostic effect of ACOT7 expression level

To evaluate the influence of ACOT7 and other clinical and molecular variables on the outcome of AML patients, we chose chemotherapy-only group to do univariate and multivariate analysis. Results of univariate analysis were showed in Table 3. Patients who had high expression level of ACOT7 had a significant higher risk of poor outcome ( $p=$ 0.001 for EFS and $p=$ 0.002 for OS). Patients had other characteristics like age ( $p<$ 0.001 for EFS and OS) and having mutations in TP53 ( $p=$ 0.001 for EFS and $p=$ 0.002 for OS) also at the risk of having bad prognosis.

In multivariate analysis, variates like expression level of ACOT7 (high vs. low), age $\geqslant$ white blood cell (WBC) count $\geqslant$ and status of some common genes in AML (FLT3-ITD/TKD, present vs. absent; NPM1 and DNMT3A, mutated vs. wild) were chosen and results were summarized in Table 4. High expression level of ACOT7 ( $p=$ 0.011 for EFS and $p=$ 0.018 for OS) and older age ( $p<$ 0.001 for EFS and OS) contributed to poor EFS and OS independently.

Table 4
Multivariate analysis of EFS and OS in the chemotherapy-only group

Variables	EFS		OS
	HR (95%CI)	$P$ -value	HR (95%CI)	$P$ -value
ACOT7 (high vs. low)	1.950 (1.169–3.252)	0.011	1.846 (1.113–3.061)	0.018
Age ${}^{*}$	1.043 (1.021–1.066)	$<$ 0.001	1.041 (1.019–1.064)	$<$ 0.001
WBC ${}^{*}$	1.004 (0.998–1.010)	0.149	1.005 (0.999–1.011)	0.121
FLT3-ITD/TKD (present vs. absent)	1.167 (0.640–2.129)	0.614	1.084 (0.596–1.973)	0.791
NPM1 (mutated vs. wild)	0.877 (0.474–1.623)	0.676	0.781 (0.421–1.447)	0.432
DNMT3A (mutated vs. wild)	1.333 (0.730–2.434)	0.349	1.510 (0.853–2.673)	0.157

In survival analysis, patients who had a high level of ACOT7 expression had significant lower EFS and OS than those patients with respectively low expressions in chemotherapy-only group ( $p<$ 0.001 for EFS and $p=$ 0.003 for OS, Fig. 1). In patients who received allo-HSCT, the results of survival analysis of EFS and OS were similar with chemotherapy-only group. As showed in Fig. 2, patients with high expression level of ACOT7 had poor EFS ( $p=$ 0.003) and poor OS ( $p=$ 0.010) in HSCT group as well.

4. Discussion

In this study, we analyzed the impacts of expression level of ACOT7 on the prognosis of AML patients. High levels of ACOT7 had a worse influence on the prognosis of our patients as EFS and OS were significant lower in ACOT7 high expression group. This impact could not be overcome by allo-HSCT. Expression level of ACOT7 was an independent factor on the prognosis of AML patients.

Since Ramakrishna et al. found ACOT8 gene copy number from patients with ovarian cancer, ACOT family members had attracted much attention from academia and the function of ACOT in cancer has also been studied [9]. In 2010, the high expression level of ACOT2 and ACOT4 was found to act as adverse factors in breast cancer through modulating the production of prostaglandin [8, 10]. Then in 2013, studies reported that ACOT8 was correlated with lymph node metastasis in lung adenocarcinoma and poor outcome in hepatocellular carcinoma in succession [6, 7]. Besides ACOT8, ACOT11 and ACOT13 were found to associate with the outcome of lung adenocarcinoma by Hung et al. in 2017 [11]. Also, ACOT7 has been suggested to be involved in breast cancer and lung cancer due to its overexpression [12]. Most recently, ACOT1 was observed to overexpress in gastric adenocarcinoma in 2018 [5]. However, the relevance of ACOT and hematological disease was still unclear. Our study gave the first glimpse into the prognostic of ACOTs especially ACOT7 in AML patients. We demonstrated that patients in high ACOT7 group had a significant lower EFS and OS than patients in low group, but other types of ACOT showed no significant difference.

ACOT7 (also known as ACT, CH1, BACH, LACH, LACH1, hBACH and CTE-II) belongs to the type II thioesterases for it contains the HotDog fold structure, and ACOT7 shows a preference for long-chain acyl-CoA substrates [14]. ACOT7 is reported to have a broad expression mainly in brain and kidney, and decreased expression of ACOT7 may be associated with mesial temporal lobe epilepsy characterized by hippocampal sclerosis [15]. Previous studies have identified that ACOT7 participated in inflammatory reactions through regulating the production of arachidonic acid (AA) which has an important role in cell signaling and proliferation [16]. Recently Jung et al. found that ACOT7 depletion upon treatment with ionizing radiation (IR) and doxorubicin (Doxo) can induced cytostasis through the PKC $\zeta$ -p53-p21 signaling pathway in both MCF7 human breast carcinoma and A549 human lung carcinoma cells [12]. In our univariate and multivariate analysis, ACOT7 expression has an independent effect on outcomes of AML patients. Higher expressions of ACOT7 predicts shorter EFS and OS. These results might be explained partly by the accumulation of ACOT7. According to previous researches, we speculate that the PKC signaling pathway may be unable to activate normally because of the overexpression and accumulation of ACOT7, so ACOT7 depletion-mediated cell cycle arrest cannot work against tumor proliferation [12]. The absence of this effect may contribute to the tumor recurrence as well as unfavorable prognostic outcome. Nevertheless, there might be other possible mechanisms that we didn’t know since both the role of ACOT7 and its significance remain inadequately studied in AML.

Previous studies have indicated that NPM1 can have positive effects on the outcomes of AML patients, whereas FLT3-ITD, KRAS, TET2, and TP53 mutations will have adverse effects and mutations of NRAS were thought to have little to no influence on those studies [17, 18, 19, 20, 21, 22]. However, in our study, we did not observe a significant prognosis impact of NPM1 or FLT3 mutation. The reason for this might be the small sample size of our study. In addition, there might be some confounding factors such as the age distribution of our patients.

Currently, induction therapy of AML had developed rapidly but it is still a significant challenge to increase tumor sensitivity to anti-tumor drugs. Our study pointed out that ACOT7 may serve as potential targets in medical treatments as ACOT7 had an obvious impact to the EFS and OS of AML patients independently. Further detailed studies on the molecular mechanisms of ACOT7 may help to better understand the development and progression of AML, and it might have potentials to increase tumor sensitivity to IR and chemotherapeutic drugs.

Allo-HSCT is a powerful method in the treatment of AML patients especially with molecular risk factors [23]. Our study found that the high expression level of ACOT7 has an adverse effect on patients’ EFS and OS both in chemotherapy-only group and HSCT group. These results meant that allo-HSCT could not surmount the adverse effect of ACOT7 overexpression in AML patients.

Our study also analysis the associations between expression level of ACOT7 and clinical and molecular characteristics. We found that high expression level of ACOT7 was more observed in male patients and there may be potential relevance between expression level and FAB subtypes as well as cytogenetics, etc.

The main limitation of this paper is that our study cannot provide a comprehensive review of molecular mechanisms due to practical constraints. Also, the results of small-scale trial may require further confirmation.

5. Conclusion

In conclusion, for the first time, we demonstrated the importance of ACOT7 in the prognosis of AML. High expression levels of ACOT7 indicate unfavorable prognostic outcome and allo-HSCT could not overcome the effect of ACOT7 in these patients. Our study presents a wide range of possibilities for the further development that ACOT7 might act as a new biomarker for its significant prognostic function. Further detailed studies on ACOT7 shall be done to improve the clinical outcomes and management of AML.

Footnotes

Acknowledgments

This work was supported by grants from the National Natural Science Foundation of China (815001 18, 61501519), the China Postdoctoral Science Foundation funded project (project No. 2016 M600443), and the PLAGH project of Medical Big Data (Project No. 2016MBD-025).

Conflict of interest

The authors have no conflict of interest to declare.

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