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Introduction

Promoter methylation is important in epigenetics and always leads to transcriptional silencing of tumor suppressor genes in acute myeloid leukemia (AML) (1). Although current chemotherapy regimens result in complete remission in many cases, there is no standard and efficient therapy for refractory AML (2). As aberrant DNA methylation is common in AML, clinical trials using epigenetically-targeted therapies have yielded particularly promising results in the treatment of hematopoietic malignancies (3). Several demethylating agents, including azacytidine and decitabine, have been demonstrated to improve AML prognosis (4).

Adenomatous polyposis col 2 (APC2) is a tumor suppressor gene, encoding a protein that controls the stability and nuclear export of β-catenin, which is a Wnt signaling pathway transcriptional coactivator (5). Wnt pathway inhibitors are methylated at a high frequency in AML patients (6). The cytochrome P450 family 1 subfamily B polypeptide 1 (CYP1B1) gene, which is a candidate target gene in numerous types of cancers, encodes a member of the cytochrome P450 enzyme superfamily. Furthermore, cytochrome P450 enzymes are involved in drug metabolism and the synthesis of cholesterol, steroids and other lipids (7). A previous study has revealed high CYP1B1 expression in human myeloid leukemia cell lines (8) and another study identified a significant incidence of methylation in the patients with acute leukemia (9).

Alterations in the promoter methylation status, which is considered to be an indicator of a molecular abnormality, can be used to predict the chemotherapeutic outcomes of multiple regimens towards individualized therapy. The aim of the present study was to investigate changes in the methylation status in bone marrow mononuclear cells during chemotherapy and to assess their potential prognostic value in Han Chinese AML patients.

Materials and methods

Patient samples

Bone marrow specimens and associated clinicopathological information documented prior to and following chemotherapy were collected from 30 AML patients treated at the Department of Hematology and Oncology at Yuyao People's Hospital (Ningbo, China). There were 13 male and 17 female patients, with a mean age of 47.8±15.4 years (range, 19–76 years). AML was diagnosed in accordance with the revised French-American-British classification, which included classification into subtypes M0-7 (10). In total, 13 different chemotherapy regimens were chosen according to the status of the patients. Among them only 6 patients were treated with one kind of drug, including one male of subtype M5 and four females (two of subtype M3, and one each of subtypes M4 and M6) who were treated with cytarabine (Ara-c), and one female M4 patient who was treated with idarubicin (IDA). The remaining 24 patients were treated with multi-drug chemotherapy regimens: HAA [homo-harringtonine (HHT) + cytarabine (Ara-C) + aclacinomycin (ACLA)]; IA (IDA + Ara-c); AAG [Ara-C + ACLA + granulocyte colony-stimulating factor (G-CSF)]; ATRA combined with arsenic trioxide (AS2O3); all trans–retinoic acid (ATRA) combined with AS2O3 and daunorubicin (DNR); HA (HHT + Ara-c); IA + HAG; AA (Ara-c + ACLA); HAG (HHT + Ara-c + G-CSF); HAG + IDA; and ATRA + As2O3 + HA. The clinical parameters of the patients with AML are summarized in Table I. The Ethics Committee at Yuyao People's Hospital approved the study. Written informed consent was obtained from all patients after the possible consequences of participating in the study had been explained.

Table I. Clinical parameters at baseline and following chemotherapy in patients with acute myeloid leukemia.

Table I.

Clinical parameters at baseline and following chemotherapy in patients with acute myeloid leukemia.

ID	Gender	Age (years)	Subtype	Regimen	Remission	APC2 methylation level before and after treatment	CYP1B1 methylation level before and after treatment
1	Male	55	M1	HHT + Ara-C + ACLA	Yes	HM to HM	HM to HM
2	Male	49	M1	IDA + Ara-C	No	HM to HM	HM to HM
3	Male	76	M2	Ara-C + ACLA + G-CSF	No	HM to HM	HM to U
4	Male	66	M2	IDA + Ara-C	Yes	HM to HM	HM to HM
5	Male	23	M3	ATRA + As2O3	Yes	HM to HM	HM to HM
6	Male	40	M3	As2O3+ DNR + ATRA	No	HM to HM	U to HM
7	Male	59	M3	HHT + Ara-C	Yes	HM to HM	U to HM
8	Male	67	M4	IDA + Ara-C + ACLA + G-CSF + HHT	Yes	HM to HM	U to HM
9	Male	34	M4	HHT + Ara-C	Yes	HM to HM	HM to HM
10	Male	68	M5	Ara-C	Yes	HM to HM	HM to HM
11	Male	59	M5	Ara-C + ACLA	Yes	HM to HM	HM to HM
12	Male	48	M5	HHT + Ara-C + ACLA	No	HM to HM	HM to HM
13	Male	52	M6	HHT + Ara-C + G-CSF	Yes	HM to HM	HM to HM
14	Female	59	M1	Ara-C + ACLA + G-CSF	No	HM to HM	U to HM
15	Female	66	M2	Ara-C + ACLA + G-CSF	Yes	HM to HM	HM to HM
16	Female	56	M2	Ara-C + ACLA + G-CSF	Yes	HM to HM	HM to HM
17	Female	48	M2	HHT + Ara-C + ACLA	Yes	HM to HM	HM to HM
18	Female	50	M2	HHT + Ara-C + G-CSF + IDA	Yes	HM to HM	HM to HM
19	Female	19	M2	HHT + Ara-C + ACLA	Yes	HM to HM	HM to HM
20	Female	53	M2	HHT + Ara-C	Yes	HM to HM	HM to HM
21	Female	51	M3	ATRA + As2O3+ HHT + Ara-C	Yes	HM to HM	HM to HM
22	Female	42	M3	IDA + Ara-C	No	HM to HM	HM to U
23	Female	30	M3	Ara-C	Yes	HM to HM	U to HM
24	Female	31	M3	Ara-C	Yes	HM to HM	HM to HM
25	Female	30	M4	IDA	Yes	HM to HM	HM to HM
26	Female	30	M4	IDA + Ara-C	No	HM to HM	HM to HM
27	Female	19	M4	HHT + Ara-C + ACLA	Yes	HM to HM	HM to HM
28	Female	42	M4	Ara-C	Yes	HM to HM	HM to HM
29	Female	64	M6	HHT + Ara-C	No	HM to HM	HM to HM
30	Female	50	M6	Ara-C	Yes	HM to HM	HM to HM

[i] APC2, adenomatous polyposis col 2; CYP1B1, cytochrome P450 family 1 subfamily B polypeptide 1; M, DNA permethylation; HHT, homoharringtonine; Ara-C, cytarabine; ACLA, aclacinomycin; IDA, idarubicin; G-CSF, granulocyte colony-stimulating factor; As₂O₃, arsenic trioxide; DNR, daunorubicin; ATRA, all trans–retinoic acid; HM, DNA hemimethylation; U, DNA unmethylation.

DNA extraction and bisulfite DNA modification

Genomic DNA was isolated from bone marrow nucleated cells using a nucleic acid extraction analyzer (Lab-Aid 820; Zeesan Biotech, Xiamen, China). The DNA concentration of each specimen was measured via a NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific, Inc., Wilmington, NC, USA). All DNA samples were modified using the reagents provided in the ZYMO EZ DNA Methylation-Gold kit (Zymo Research Corp., Irvine, CA, USA). Following bisulfite treatment, the converted DNA samples were stored at −20°C.

Methylation-specific polymerase chain reaction (MSP PCR)

Modified DNA samples were subjected to MSP using APC and CYP1B1 MSP primers (11). Two pairs of primers were synthesized by Shanghai Sangon Biotechnology Co., Ltd. (Shanghai, China) according to the sequences listed in Table II. Methylated primers were used to amplify methylated regions and unmethylated primers to amplify unmethylated regions. Each PCR reaction contained 1.5 µl sodium bisulfite modified DNA, 0.5 µl each primer, 10 µl Zymo TaqTM Premix (Zymo Research, Orange, CA, USA) and 7.5 µl DNAase/RNAase-free water in a final reaction volume of 20 µl. DNA amplification was performed using a Veriti® PCR machine (Applied Biosystems, Thermo Fisher Scientific, Inc.). Thermocycling conditions were as follows: Initial denaturation step at 95°C for 10 min followed by 35 cycles of amplification, each cycle included a denaturation step at 94°C for 30 sec, an annealing step with a primer-specific temperature for 45 sec and an elongation step at 72°C for 1 min. The final extension step was performed at 72°C for 7 min. The methylation status of each sample was determined using one or two independent experiments. Water blank was used as a negative control. PCR products were analyzed using a Qsep100 DNA Analyzer (Bioptic Inc., Taiwan, China). Samples were considered as methylated or unmethylated according to the presence of clearly visible peaks by the Q-analyzer software (Fig. 1). The sequences and details of the methylated and unmethylated primers are provided in Table II. DNA samples were randomly sequenced using the Applied Biosystems 3730 DNA Analyzer (Thermo Fisher Scientific, Inc.) to confirm complete bisulfite conversion (Fig. 2).

Figure 1. Methylation status of the APC2 and CYP1B1 genes before and after chemotherapy. Primer sets for methylation-specific polymerase chain reaction were either M or U. APC2, adenomatous polyposis col 2; CYP1B1, cytochrome P450, family 1, subfamily B, polypeptide 1; M, methylated; U, unmethylated.

Figure 2. Validation of methylation-specific products by sequencing. APC2, adenomatous polyposis col 2; CYP1B1 cytochrome P450 family 1 subfamily B, polypeptide 1; M, DNA permethylation; U, DNA unmethylation.

Table II. Primers and PCR amplification conditions.

Table II.

Primers and PCR amplification conditions.

Gene	Primer set	Primer sequence (5′-3′)	Amplified fragment length (bp)/Annealing Temperature (°C)
APC2	MF	GTCGTTTGTTTAGGTTCGGATC	98/60
	MR	GACCCGAAATAACCTCGAAACG
	UF	TGGTAGTGTTGTTTGTTTAGGTTTGGATTG	105/57
	UR	ACCAAAAATCCCAACCCAAAATAACCTCAAAACA
CYP1B1	MF	CGCGTTTTTAAGTCGAGC	125/60
	MR	ACCCACGTTTCCATTATACG
	UF	GGGTGTGTTTTTAAGTTGAGT	125/55
	UR	ACCCACATTTCCATTATACAATA

[i] Thirty-five PCR cycles were used for all reactions. PCR, polymerase chain reaction; bp, base pair; APC2, adenomatous polyposis col 2; CYP1B1, cytochrome P450, family 1, subfamily B, polypeptide 1; MF, methylated forward; MR, methylated reverse; UF, unmethylated forward; UR, unmethylated reverse.

Statistical analysis

Comparisons between APC2 and CYP1B1 promoter methylation were performed using the correction formula of a χ 2 test. Statistical analyses were performed using the SPSS 18.0 Evaluation version software for Windows (SPSS Inc., Chicago, IL, USA). MSP results were compared in samples pre- and post-chemotherapy.

Results

Chemotherapy

As shown in Table I, the chemotherapy agents used included Ara-C, ATRA, As2O3, HHT, G-CSF, IDA, ACLA and DNR. A total of 22 patients in remission and eight patients with a poorer prognosis were treated with these 13 agents, either in single or combined regimens.

MSP was performed on pre- and post-chemotherapy bone marrow samples from 30 AML patients in order to determine whether the chemotherapy treatment was able to alter APC2 and CYP1B1 promoter methylation levels. APC2 promoter methylation status remained unchanged by chemotherapy. In contrast, seven patients demonstrated CYP1B1 promoter changes during chemotherapy.

Regimen-based subgroup analyses of CYP1B1 promoter methylation changes in AML patients

Seven patients treated with six regimens exhibited CYP1B1 promoter methylation changes, including five samples with hypermethylation and two samples demonstrating hypomethylation. Of the five patients with induced hypermethylation, three patients in remission were treated with Ara-C, HHT + Ara-C and IDA + Ara-C + ACLA + G-CSF + HHT regimens, and two patients treated with As2O3 + DNR + ATRA. Ara-C + ACLA + G-CSF regimens resulted in a poor patient prognosis. Two patients with induced hypomethylation were treated with Ara-C + ACLA + G-CSF, and IDA + Ara-C regimens and had a poorer prognosis.

Analyses of CYP1B1 promoter methylation changes in patients based on AML subtypes

The results of the present study were obtained from three patients diagnosed with the M1 AML subtype, eight with M2, seven with M3, six with M4, three with M5 and three with M6. Outcomes associated with chemotherapy-induced CYP1B1 promoter methylation changes varied according to the subtypes. Chemotherapy-induced methylation changes were more often observed in M3 patients (57.1%, 4/7) compared with patients diagnosed with other subtypes (M1: 33.3%, 1/3; M2: 12.5%, 1/8; M4: 16.7%, 1/6; M5: 0%, 0/3; and M6: 0%, 0/3).

Age-based subgroup analyses of CYP1B1 promoter methylation changes in AML patients

As shown in Table I, of the 24 patients aged ≤60 years, 20 patients exhibited induced hypermethylation and four patients showed induced hypomethylation. Among the six patients aged >60 years old, five exhibited induced hypermethylation and one demonstrated induced hypomethylation. By further categorizing patients according to age, chemotherapy-induced methylation changes were observed to be more often present among AML patients >60 years of age (33.3%, 2/6) compared with patients ≤60 years of age (20.8%, 5/24). Among the patients aged ≤60 years, one patient of the M1 subtype (Ara-C + ACLA + G-CSF; aged 59 years) exhibited an induced hypermethylation and worse consequence, one patient of M3 subtype (As2O3 + DNR + ATRA; aged 40 years) showed an induced hypermethylation along with a poor prognosis, two M3 patients (HHT + Ara-C; aged 59 years and Ara-C; aged 30 years) demonstrated induced hypermethylation along with remission and one patient of the M3 subtype (IDA + Ara-C; aged 42 years) exhibited induced hypomethylation along with a poor prognosis. As for patients >60 years of age, one M2 subtype patient (Ara-C + ACLA + G-CSF, aged 76 years) exhibited an induced hypomethylation along with a poor prognosis and one M4 subtype patient (IDA + Ara-C + ACLA + G-CSF + HHT, aged 67 years) demonstrated hypermethylation along with an improved prognosis.

Gender-based subgroup analyses of CYP1B1 promoter methylation changes in AML patients

As shown in Table I, 4/13 male and 3/17 female patients demonstrated CYP1B1 promoter methylation status changes. Among them, one M3 subtype male patient (HHT + Ara-C) and one M4 subtype male patient (IDA + Ara-C + ACLA + G-CSF + HHT) displayed induced hypermethylation along with remission. One M3 subtype male patient (As2O3 + DNR + ATRA) exhibited induced hypermethylation along with a poor prognosis, and one M2 subtype male patient (Ara-C + ACLA + G-CSF) demonstrated induced hypomethylation along with a poor prognosis. The remaining nine male patients did not exhibit any methylation changes induced by chemotherapy.

In the female subgroup, one M1 subtype patient (Ara-C + ACLA + G-CSF) exhibited induced hypermethylation with a poor prognosis, one M3 subtype patient (IDA + Ara-C) exhibited induced hypomethylation with a poor prognosis, and one M3 subtype patient (Ara-C) demonstrated induced hypermethylation along with remission. However, the remaining 14 female patients did not show any methylation changes following chemotherapy.

Discussion

The present study aimed to explore the chemotherapy-induced methylation changes of the APC2 and CYP1B1 promoter in bone marrow samples from AML patients and their association with the treatment outcome.

Consistent with its role in the Wnt signaling pathway, APC2 promoter methylation was associated with the progression of various cancers, particularly colorectal cancer (12). However, APC2 methylation is rarely observed in epithelial tumors (6). The results of the present study demonstrated that APC2 promoter methylation remained unchanged by various chemotherapy treatments.

CYP1B1 contributes to the development and progression of various diseases, including tumorigenesis and multidrug resistance (13). CYP1B1 promoter methylation is downregulated in colorectal cancer (14) and stratifies prognosis in patients with tamoxifen- and non tamoxifen-treated breast cancer (15). The results demonstrated that CYP1B1 promoter methylation changed following treatment with various chemotherapy regimens, indicating complex regulation of CYP1B1 methylation in the bone marrow. In addition, different AML subtypes displayed distinct responses to multiple chemotherapy regimens, which may influence the changes of CYP1B1 methylation and the outcome of chemotherapy. Among the AML subtypes, M3 patients often revealed chemotherapy-induced changes in CYP1B1 methylation. The present study demonstrated that CYP1B1 hypermethylation in M3 patients may be associated with an improved prognosis if treated with Ara-C, HHT + Ara-C or IDA + Ara-C chemotherapy regimens. This observation provides a response tendency that is potentially useful for individualized AML therapy.

The incidence rates of acute leukemia are significantly higher in males compared with females (16). The present study demonstrated that male patients were more susceptible to induced methylation changes compared with female patients following chemotherapy. Furthermore, the CYP1B1 promoter methylation changes during chemotherapy may serve as a potential biomarker to predict the outcome of therapy in male patients.

However, there are some limitations in the present study. Firstly, a relatively small sample size was used. The sample size of 30 patients used may prevent powerful statistical significance. Therefore, a larger sample size is required to confirm our observations in the future. Secondly, a conclusion was drawn through patients treated with 13 types of chemotherapy regimens, however, future investigation with more samples and a patient cohort treated with the same chemotherapy are required. Thirdly, the main population of the present study were people from Ningbo and studies in other regions are required in order to elucidate an integrated conclusion on the association between changeable gene methylation levels and chemotherapeutic outcomes.

In conclusion, the results of the present study demonstrated that chemotherapy-induced changes in CYP1B1 promoter methylation were associated with the AML subtype, gender and age of the patients. However, future analyses on the mechanisms by which CYP1B1 promoter methylation is altered by chemotherapeutic regimens are required.

Acknowledgements

The present study was supported by the grants from the National Natural Science Foundation of China (grant nos. 31100919 and 81371469), the Zhejiang Provincial Natural Science Foundation (grant no. LR13H020003), the Ningbo City Medical Science and Technology Projects (grant no. 2014A20) and the K. C. Wong Magna Fund in Ningbo University.

References