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. 2025 Oct 8;15:35165. doi: 10.1038/s41598-025-19053-z

Hypermethylation of microRNA-34c CpG Island predicts unfavorable prognosis in acute myeloid leukemia

Dongqin Yang 1,#, Meng Yan 1,#, Jian Guo 2,✉, Lingyun Wu 1,✉
PMCID: PMC12508102  PMID: 41062511

Abstract

The expression of microRNAs is regulated by CpG island hypermethylation in acute myeloid leukemia (AML). MiR-34c CpG island methylation status and miR-34c expression were tested in 205 de novo AML patients and 51 healthy controls. MiR-34c-mimics were transfected into THP-1 cells lines. Then Cell viability after transfection and apoptosis were detected. Western blot was used to detected the protein expression of p53. We found the down-regulation of miR-34c was associated with hypermethylation of the neighboring CpG island, and decitabine treatment rapidly restored miR-34c expression. Hypermethylation of the miR-34c CpG island was frequently observed in primary AML patients’ bone marrow but not in healthy donors’. Hypermethylation of the miR-34c CpG island correlated with shorter overall survival and was further confirmed by multivariate analyses. AML patients who received decitabine and achieved complete remission, methylation of miR-34c CpG island significantly decreased and expression of miR-34c significantly increased. MiR-34c CpG island hypermethylation group was positively associated with the presence of P53 and TET2 mutations but inversely correlated with CEBPA. MiR-34c CpG island regulates miR-34c expression and hypermethylation of miR-34c CpG island is frequent in AML. There is positive feedback exists between miR-34c demethylation and p53 protein expression.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-19053-z.

Keywords: MiR-34c, Methylation, P53, AML, Prognosis

Subject terms: Cancer genetics, Cancer therapy, Tumour biomarkers

Introduction

Acute myeloid leukemia (AML) is a broad range of disorders that are characterized by arrest maturation along with an uncontrollable proliferation of hematopoietic progenitor cells1. During the past years, in addition to karyotypic changes, the discoveries of gene mutations and epigenetic alterations have been proved to play crucial roles not only in the pathogenesis but also in the prognosis of AML2. Moreover, aberrant DNA methylation silencing leukemia-related oncogenes and tumor suppressor genes furnishes a theoretical basis for improving molecular prognostic model3.

Over the past years, a new class of small noncoding RNAs, named microRNAs (miRNAs), has changed the landscape of human genetics4. MiRNAs consist of 18–22 nucleotides with the function of regulating gene expression, for the most part, by targeting messenger RNAs (mRNAs) according to the degree of complementarity with their 3′ untranslated region (UTR)5. Recent reports have identified the presence of CpG island methylation-associated silencing of miRNAs with tumor suppressor features in human cancer6. Aberrant DNA methylation linked to the silencing of individual miRNA genes has been disclosed in AML7. Moreover, Aberrant methylation of several miRNAs, such as miR-193b, miR-181a, has been identified as relevant to the outcome of AML8,9. MicroRNA-34 (miR-34) family contains three members in vertebrate genomes (miR-34a, miR-34b, and miR-34c) and single orthologues in invertebrate species10. The tumor suppressor function of miR-34c has been identified in various tumors10. MiR-34c was found to undergo specific hypermethylation-associated silencing in several cancers11,12. Our previous study revealed that the low miR-34c level was a novel promising biomarker in predicting prognosis in patients with de novo AML13. However, there is limited information about miR-34c CpG island methylation status and its clinical significance in AML. In this study, we analyzed the methylation pattern of miR-34c CpG island in AML patients using a specific real-time methylation-PCR (qRT-MSP) and evaluated the effect of methylation on AML patients’ outcomes.

Materials and methods

All methods were performed in accordance with the relevant guidelines.

Patients

A total of 205 patients with a diagnosis of AML (age:18 to 95 years; Sex: 120 males/85 females), as well as 51 healthy donors (age:16 to 45 years; Sex: 35 males/16 females)were included in the study approved by the Department of Hematology, Shanghai Eighth People’s Hospital and Shanghai Sixth People’s Hospital, Shanghai, China. The diagnosis and classification of the patients were based on the 2016 World Health Organization (WHO) criteria. Bone marrow (BM) specimens were collected from all the patients and healthy donors after written informed consents were obtained. BM mononuclear cells were extracted from BM specimens by gradient centrifugation using Lymphocyte Separation Medium (Absin, Shanghai, China).

RNA isolation, reverse transcription and qRT-PCR

Total RNA was isolated using Trizol reagent (Invitrogen, Carlsbad, CA, USA). Reverse transcription reaction with 40 µL volume was composed of 5 × buffer 10 mM, 10 mM of dNTPs, 10 µM of random hexamers, 80 U of RNAsin, and 200 U of MMLV reverse transcriptase (MBI Fermentas, Hanover, USA). The reaction conditions were incubated for 10 min at 25 °C, 60 min at 42 °C, and then stored at −20°C. Quantitative Real-time PCR (qRT-PCR) was performed on a 7500 Thermo cycler (Applied Biosystems, CA, USA). The primer sequences for miR-34c expression were 5’-GCCGGGGACAAGAGAAGT-3’ (forward) and 5’-GAGGACGTATTTGCCAGCAT-3’ (reverse). The reaction system with 20 µL volume consisted of cDNA 20ng, 0.8 µM of primers, 10 µM of AceQ qPCR SYBR Green Master Mix (Vazyme Biotech Co., Piscataway, NJ, USA), and 0.4 µM of ROX Reference Dye 1 (Invitrogen, Carlsbad, CA, USA). The qRT-PCR reaction conditions were 95 °C for 5 min, followed by 45 cycles at 95 °C for 10 s, 63 °C for 30 s, 72 °C for 30 s, and 80 °C for 30 s to collect fluorescence, finally followed by 95 °C for 15 s, 60 °C for 60 s, 95 °C for 15 s, and 60 °C for 15 s. Both positive and negative controls were included in each assay. Relative miR-34 C transcript levels were calculated by the formulas N miR-34 C=(E miR-34 C)ΔCT miR-34 C (control-sample)÷(EABL)ΔCTABL (control-sample) and E = 10(−1/slope) (the slope referred to CT versus cDNA concentration plot).

DNA isolation, chemical modification and qRT-MSP

Genomic DNA was isolated using a genomic DNA purification kit (Gentra, Minneapolis, MN, USA) and was modified using the CpGenome DNA Modification Kit (Chemicon, Temecula, Canada) according to the manufacturer’s recommendations. The primer sequences for the methylated (M) miR-34c promoter were 5’- TTTAGTTACGCGTGTTGTGC − 3’ (forward) and 5’- ACTACAACTCCCGAACGATC − 3’ (reverse), and for the normally methylated (U) miR-34 C promoter were 5’- TGGTTTAGTTATGTGTGTTGTGT − 3’ (forward) and 5’- CAACTACAACTCCCAAACAATCC − 3’ (reverse).

Real-time quantitative methylation-specific

Quantitative Real-time PCR (qRT-MSP) was performed for M-MSP reaction, which was composed of primers 0.8 µM, 10 µM of AceQ qPCR SYBR Green Master Mix (PowerUp™ SYBR™ Green, Applied Biosystems™, USA) and 20 ng of modified DNA. The program for amplification was 95 °C for 5 min, 40 cycles for 10 s at 95 °C, 30 s at 64 °C, 72 °C for 30 s, and 80 °C for 30 s, finally a melting program of one cycle at 95 °C for 15 s, 60 °C for 60 s, 95 °C for 15 s, and 60 °C for 15 s. U-MSP reaction using the same reagents was incubated for 95 °C for 5 min, 40 cycles for 10 sat 95 °C, 30 s at 58 °C, and 30 s at 72 °C followed by a final 7 min extension step at 72 °C. Both positive and negative controls were included in each assay. The normalized ratio (N/M- miR-34c) calculated relative to the reference ALU was used to assess the level of miR-34c promoter methylation in samples. The normalized ratio (N-normally methylated-miR-34c) was used to evaluate the normally methylated level of miR-34c. N-normally methylated-miR-34c was determined using the 2−ΔΔCT method comparing the ALU gene level. This means that a higher value of N-normally methylated-miR-34c represents a lower methylation status or hypomethylation of miR-34c. The products of MSP were resolved in the concentration of 2% agarose gels to visualize under UV illumination.

Bisulfite sequencing

The primer sequences for bisulfite modified miR-34c promoter were 5’- AGGGGAGGTTTGGTATTTTT-3’ (forward) and 5’- AATTATAACCACCACAATACAATCA − 3’ (reverse). Bisulfite sequencing PCR (BSP) reaction system contained 1 × PCR buffer (KCl 0.25 mM), dNTP Mixture 6.25 µM, primers 0.5 µM, hot-start DNA polymerase 0.75U (Takara, Tokyo, Japan), and modified DNA 20ng. The BSP was carried out at 98 °C for 10 s,40 cycles for 10 s at 98 °C, 30 s at 56 °C, 72 °C for 30 s, and followed by a final 7 min extension step at 72 °C. The PCR products were analyzed on 2% agarose gels. The PCR products were purified and cloned into pMD19-T Vector (Takara, Tokyo, Japan), then transfected into DH5A competent cells (Vazyme, Carlsbad, CA, USA). Six clones from each sample were sequenced (BGI Tech Solutions Co, Shanghai, China).

Gene mutation detection

The detection of KIT, RUNX1, P53, SF3B1, ASXL1, TET2, FLT3, NPM1, CEBPA, N/K-RAS, IDH1/2, DNMT3A, U2AF1 mutations were performed for PCR products using HRMA with the Light Scanner platform (Idaho Technology Inc. Salt Lake City, Utah). All positive samples were confirmed by DNA direct sequencing.

Cell line and cell transfection

Human leukemic cell line, includingTHP-1 (Tohoku Hospital Pediatrics-1, a human monocytic cell line derived from an acute monocytic leukemia patient), Kasumi-1 (a myeloblast cell that was isolated from the peripheral blood of an acute myeloblastic leukemia Asian male patient), HL-60 (Human leukemia cells 60, a suspension cell line established from peripheral blood via leukapheresis from a patient with acute promyelocytic leukemia), HEL (Human Erythroleukemia, a erythroblast cell line isolated from the bone marrow of a patient with erthroleukemia), NB4 (a continuously growing cell line derived from the leukemic cells of a relapsed acute promyelocytic leukemia) (Cell Bank of Chinese Academy of Sciences, Shanghai, China) was cultured in RPMI 1640 medium (Gibco, Grand Island) containing 10% fetal bovine serum (FBS) (Gibco, Australia) and grown at 37 °C in 5% CO2 humidified atmosphere. For demethylation studies, cells were incubated with a final concentration of 0 µM, 0.1 µM, 1 µM, 10 µM, decitabine for 48 h. All cells were cultured until harvested for the extraction of RNA and DNA.

THP-1 cells and HEL cells (1 × 105 per well) were transfected in 24-well plates with HiPerFect Transfection Reagent (Qiagen, Germany) according to the manufacturer’s instructions. The cells were transfected with 7 µg of the miR-34c-mimics or blank load transfection. Then, stably transfected cells were selected using blasticidin (Invitrogen, USA) and cell sorting (BD Company). After selection, the transfected cells were harvested, and miR-34c expression was detected by qRT-PCR.

Cell proliferation assay

Cell proliferation was determined using a Cell Counting Kit-8 assay (CCK-8; Dojindo Laboratories, Kumamoto, Japan) in accordance with the manufacturer’s instructions. THP-1 were allocated into miR-34c-mimics as experimental groups or blank load transfection normal contrast (NC) groups. Cells from each group were plated as replicates of three in 96-well plates (5 × 103 cells/well) in 100 µL 1640 supplemented with 10% FBS. Subsequently, after 0, 24, 48, and 72 h cell culture. CCK-8 solution was then added to each well and incubated for 2 h at 37 °C. The optical density (O.D.) at 450 nm was measured using a microplate reader (S/N 415–2687, Omega Bio-Tek, Ortenberg, Germany).

Cell apoptosis assays

Cells (2 × 105 cells/mL) for 2 mL per well were seeded in a 6-well plate in RPMI 1640 medium containing 0% fetal calf serum. Annexin V-PE/7-AAD apoptosis detection (BD Pharmingen, San Diego, CA, USA) was used and then analyzed via flow cytometry (BD FACS Calibur, San Jose, CA, USA). Each experiment was repeated three times.

Western blot analysis

THP-1 cell lines were lysed in RIPA buffer containing protease inhibitors (CST, USA), and the protein concentration was quantified. Equal amounts of protein were separated on 12% SDS-polyacrylamide gels (SDS-PAGE) and transferred to polyvinylidene difluoride (PVDF) membranes (Millipore, USA) followed by incubation with corresponding primary and secondary antibodies. The target band of proteins was scanned using ImageQuant LAS 4000. GAPDH was used as the loading control. The primary antibodies for human P53 were purchased from Beyotime company (Beyotime, Shanghai, China). The secondary antibodies were purchased from Beyotime. HRP Antibody Detection Kit (GE Healthcare Life Sciences).

Statistical analysis

SPSS 20.0 software package (SPSS, Chicago, IL) was applied to perform statistical analyses. Mann-Whitney’s U test was carried to compare the difference of continuous variables between two groups. Pearson Chi-square analysis or Fisher exact test was employed to compare the difference of categorical variables. Correlation analysis between miR-34c expression and its promoter methylation was performed by the Spearman rank correlation test. Kaplan-Meier analysis and Cox regression (univariate and multivariate analyses) were used to analyze the impact of miR-34c methylation on survival, respectively. For all analyses, a two-tailed P < 0.05 was defined as statistically significant.

Results

MiR-34c CpG Island hypermethylation in primary AML patients

To examine the methylation status of miR-34c promoter in AML patients, the MSP and BSP primer sets were designed at the CpG islands of the miR-34c promoter (Fig. 1A). We evaluated the status of miR-34c CpG island methylation in primary AML patients and healthy controls according to qRT-MSP. Compared with healthy controls (median 0.014, range 0.000–1.000), miR-34c promoter was significantly methylated in AML patients (median 0.100, range 0.000-14.574, P = 0.001) (Fig. 1B). To further examine the density of miR-34c CpG island methylation, three healthy controls were selected randomly and three methylated AML samples were selected according to qRT-MSP. The density of miR-34c CpG island methylation was extremely low in three controls (3.15%, 3.60% and 5.41%, respectively) and higher density of miR-34c methylation was presented in three hypermethylated AML patients (63.51%, 63.96% and 73.42%, respectively) (Fig. 1C).

Fig. 1.

Fig. 1

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MiR-34c CpG island hepermethylation in primary AML patients. (A) CpG islands of the miR-34c promoter. (B) Methylation of miR-34c CpG islands in AML patients and controls. (C) Methylation density. Black lollipop: methylated CpG dinucleotide; Blank lollipop: normally methylated CpG dinucleotide. (a–c) Three heathy doners samples; (d–f) Three hypermethylated samples.

The expression of miR-34c was regulated by miR-34c CpG Island methylation

Our previous study detected the expression level of miR-34c. The association between miR-34c expression and methylation was examined in 118 AML patients with available miRNA. The results showed that miR-34c expression correlated inversely to miR-34c CpG island methylation (R = − 0.275, P = 0.010) (Fig. 2).

Fig. 2.

Fig. 2

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The expression of miR-34c was negative correlation with miR-34c CpG island methylation. Spearman correlation test was used (R=−0.275, P = 0.010).

MiR-34c CpG Island hypermethylation correlated with short OS in AML

To investigate the prognostic impact of miR-34c hypermethylation in AML, survival data was obtained for 187 AML patients with a median follow-up time of 9.5 months (range, 1–136 months). The AML patients were divided into two groups, the one with hypermethylated miR-34c CpG island and the other with normally methylated miR-34c CpG island, based on the value of the mean plus 1 SD (0.014 + 0.263) in healthy controls. Kaplan-Meier analysis revealed that miR-34c CpG island hypermethylation patients had significantly shorter OS than miR-34c normally methylated patients in AML (median 6 and 12 months, respectively, P = 0.036) (Fig. 3).

Fig. 3.

Fig. 3

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MiR-34c CpG island hypermethylation correlated with short OS in AML. Kaplan–Meier survival curve showing miR-34c CpG island hypermethylation patients had shorter OS time in AML (P = 0.036).

Multivariate analyses, including age (≤ 60/>60 y), WBC (≥ 30/<30 × 109/L), karyotypic classifications (favorable/intermediate/poor), U2AF1 mutation (+/-), P53 mutation (+/-), ASXL1 mutation(+/-), CEBPA mutations(+/-), N/K-RAS mutation(+/-) and miR-34c CpG island methylation (hypermethylation/normally methylated) with P < 0.200 in univariate analysis, also identified that miR-34c CpG island hypermethylation was an independent adverse prognostic factor in AML patients (P = 0.004) (Table 1).

Table 1.

Univariate and multivariate analyses of prognostic factors for overall survival in AML patients.

Prognostic factors Univariate analyses Multivariate analyses
Hazard ratio (95% CI) P value Hazard ratio (95% CI) P value
Age (> 60/≤60 years) 2.786 (1.940-4.000) < 0.001 2.196 (1.985–3.248) < 0.001
WBC(≥ 30/<30 × 109/L) 2.487 (1.765–3.506) < 0.001 1.955 (1.325–2.884) 0.001

Karyotype classifications

(poor/intermediate/favorable)

 1.723 (1.433–2.073) < 0.001 1.395 (1.114–1.748) 0.004
MiR-34c methylation* (+/-) 1.596 (1.117–2.514) 0.040 1.848 (1.241–2.752) 0.002
KIT mutation(+/-) 1.413 (0.5190–3.776) 0.551 --- ---
RUNX 1 mutation(+/-) 1.377 (0.787–2.409) 0.262
P53 mutation(+/-) 4.106 (1.861–9.274) < 0.001 3.001 (1.711–8.098) 0.019
SF3B1 mutation(+/-) 1.415 (0.077–3.638) 0.258
ASXL1 mutation(+/-) 2.015 (0.932–4.891) 0.055 1.611(0.932–4.013) 0.115
TET2 mutation(+/-) 1.365 (0.670–2.660) 0.418
FLT3 mutation(+/-) 1.130 (0.608–2.101) 0.899 --- ---
NPM1 mutation(+/-) 1.012 (0.543–1.883) 0.970 --- ---
CEBPA mutations(+/-) 0.611 (0.410–1.713) 0.191 0.534 (0.410–1.542) 0.087
N/K-RAS mutation(+/-) 1.777 (0.951–3.319) 0.071 1.553 (0.741–3.151) 0.189
IDH1/2 mutation(+/-) 1.485 (0.751–2.936) 0.355 --- ---
DNMT3A mutation(+/-) 1.203 (0.587–2.469) 0.613 --- ---
U2AF1 mutation(+/-) 2.385 (1.037–5.485) 0.041 1.818 (0.898–4.995) 0.066
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*, + hypermethylation, - normally methylated.

MiR-34c CpG island hypermethylation AML patients were more sensitive to demethylation treatment

As mentioned above, miR-34c CpG island hypermethylation indicates a poor prognosis. But the sensitivity of miR-34c hypermethylation patients to demethylation drugs has not been reported. In this study, We detected the CR rate between miR-34 C normally methylated and hypermethylated AML patients who received decitabine treatment. The results shown that miR-34c hypermethylation AML patients had higher induced CR than miR-34c normally methylated (Table 2). But there was no difference in overall survival (Fig. 4A). In addition, we randomly selected 15 AML patients who received decitabine treatment and achieved CR. We found that the methylation of miR-34c CpG island significantly decreased and the expression of miR-34c significantly increased after remission (Fig. 4B, C).

Table 2.

Correlation between miR-34c CpG Island methylation and patient’s parameters.

Patient’s parameters Status of miR-34c CpG island methylation
Normally methylated normally methylated(n = 128) hypermethylation
(n = 77)		 P
Sex, male/female 80/48 40/37 0.146
Median age, years (range) 56 (18–95) 55 (19–84) 0.549
Median WBC, ×109/L (range) 11.5 (0.4–318.0) 12.6 (0.3-203.6) 0.834
Median hemoglobin, g/L (range) 78 (32–148) 74 (40–134) 0.128
Median platelets, ×109/L (range) 39.5 (3-264) 40.0 (5-431) 0.406
BM blasts, % (range) 41.8 (14.0-98.1) 56.5 (11.9–94.5) 0.054
Karyotype classification 0.627
Favorable 38 19
Intermediate 68 43
Poor 14 11
No data 8 4
Gene Mutations*
KIT (+/-) 10/78 6/47 1.000
RUNX 1(+/-) 7/81 3/50 0.743
P53(+/-) 6/82 11/42 0.018
SF3B1 (+/-) 7/81 5/48 0.764
ASXL1 (+/-) 9/79 5/48 1.000
TET2 (+/-) 11/77 15/38 0.025
FLT3 (+/-) 10/78 10/43 0.224
NPM1(+/-) 20/68 7/46 0.190
CEBPA (+/-) 15/73 2/51 0.029
N/K-RAS (+/-) 9/79 5/48 1.000
IDH1/2 (+/-) 5/83 3/50 1.000
DNMT3A (+/-) 8/80 9/44 0.188
U2AF1 (+/-)12 9/79 4/49 0.767
No data 40 24
CR(+/-) 0.020
+ 66 24
- 52 41
No data 10 12
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*, +: positive; -: negative. Because not all the patients had taken the gene mutation test, the number of gene mutations were different.

Fig. 4.

Fig. 4

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MiR-34c CpG island hypermethylation AML patients more sensitive to demethylation treatment. (A) Overall survival of MiR-34c normally methylated and hypermethylation. (B) MiR-34c CpG island was detected by BSP. (C) MiR-34c expression was detected by RT-PCR.

MiR-34c CpG Island hypermethylation was associated with several gene mutations

To investigate the clinical relevance of miR-34c CpG island methylation in AML, clinical and laboratory data were collected. No significant differences were observed in age, gender, white blood cells, hemoglobin, platelet and karyotype classification between the two groups (P > 0.05). But, miR-34c CpG island hypermethylation groups had a higher percentage of BM blasts than normally methylated groups (P = 0.054). Moreover, AML patients with MiR-34c CpG island hypermethylation had a significantly lower CR rate than those with MiR-34c CpG island normally methylated (35.29% vs. 51.56%, P = 0.020, Table 2).

According to NCCN guidelines, there are several genetic mutations that play important roles in leukemogenesis. In order to analyze the correlation of mutational data with miR-34c CpG island methylation, a total of 13 common gene mutations in 141 AML patients were screened. The results showed that miR-34c hypermethylation group was positively associated with the presence of P53 (P = 0.018) and TET2 mutations (P = 0.025) but inversely correlated with CEBPA (P = 0.029) (Table 2).

MiR-34c exhibited anti-proliferative and pro-apoptotic effects in leukemia cells

To investigate the gene function of miR-34c, we detected the expression levels of miR-34c in a panel of leukemia cell lines, and found that miR-34c expression was decreased in Kasumi-1, HL-60, THP-1, NB4, but increased in HEL (Fig. 5A). Therefore, we selected THP-1 (the lowest expression of miR-34c) and HEL (the highest expression of miR-34c) for gene function study. We transfected miR-34c-mimics or blank load (normal control groups, NC groups) into THP-1 cells and selected transfected cells using neomycin and cell sorting. We observed the effect of transfection by fluorescence microscopy (Figure. 5B) and detected miR-34c expression by qRT-PCR. Increased miR-34c expression in miR-34c-mimics THP-1 cells was observed by qRT-PCR (Fig. 5C). Additionally, We transfected miR-34c-inhibitors or blank load (NC groups) into HEL cells and decreased expression of miR-34c in HEL cells (Fig. 5D and E).

Fig. 5.

Fig. 5

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MiR-34c exhibited anti-proliferative and pro-apoptotic effects in leukemia cells. (A) Expression levels of miR-34c in a panel of leukemia cell lines; (B) Constructs high express miR-34c THP-1 celllines (Pictures of cells with green fluorescent protein). (C) The expression of miR-34c was detected by in miR-34c-mimics THP-1 cells; (D) Constructs low express miR-34c HEL cellines (Pictures of cells with green fluorescent protein). (E) The expression of miR-34c was detected by in miR-34c-inhibitors HEL celllines; (F) CCK-8 Kit analysis the cell proliferation in miR-34c-mimics THP-1 cells; (G) CCK-8 Kit analysis the cell proliferation in miR-34c-inhibitors HEL celllines; (H) Flow cytometry was used to detect the apoptosis of miR-34c transfected cells. (a. NC; b. MiR-34c-mimics; d. NC; e. MiR-34c-inhibitors; c&f. statistical analysis of flow cytometry test results.)

To study the role of miR-34c in regulating cell growth, the proliferative capacity of the miR-34c-mimics groups and NC groups were determined by the CCK-8 assay. The result showed that proliferation of miR-34c-mimics THP-1 cells was down-regulated than NC-THP-1 cells proliferation (Figure. 5 F). Similarly, the growth rate of miR-34c-inhibitors-HEL cells was obviously higher than that of the NC-HEL cells (Fig. 5G). These experiments revealed that miR-34c expression inhibits leukemia cell proliferation. To investigate the contribution of miR-34c to induced cell apoptosis in THP-1 cells, the effect of miR-34c overexpression on cell apoptosis was examined by flow cytometry. Compare with normal control group, the overall apoptotic rate of miR-34c-mimics-THP-1 cells was significantly increased (Fig. 5H-a, b, c). On the other hand the the overall apoptotic rate of miR-34c-inhibitors-HEL cells was decreased (Fig. 5H- d, e, f). These results suggested that miR-34c could promote the apoptosis of leukemia cells.

A positive feedback loop between P53 expression and miR-34c demethylation

As is well known, miR-34c, transcriptionally activated by p53, is considered a critical mediator of p53 function14. In this study, THP-1 cell lines were treated with different doses of decitabine (0, 0.1 µM, 1.0 µM, 10.0 µM). The results showed that the miR-34c CpG island was remarkably demethylated (Fig. 6A) and the expression of miR-34c was significantly up-regulated with the increasing of the decitabine concentration (Fig. 6B). Meanwhile, the p53 protein expression was increased with miR-34c demethylating (Fig. 6C). Moreover, we also detected the p53 protein expression in miR-34c mimics THP-1 cell lines and we found the p53 protein expression was increased too (Fig. 6D). This may indicate that positive feedback exists between miR-34c demethylation and p53 protein expression.

Fig. 6.

Fig. 6

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Positive feedback loop between P53 expression and miR-34c demethylation. (A) MiR-34c CpG island was demethylated after different doses of decitabine treated. (B) MiR-34 expression was increased after different doses of decitabine treated. (C) P53 protein expression was increased with miR-34c demethylating. (D) P53 protein expression was increased with increasing of miR-34c expression.

Discussion

Dysregulation of miRNA expression is commonly observed in wide varieties of cancers, and miRNAs located within CpG islands can be transcriptionally regulated by DNA methylation15. For example, miR-127 is the first microRNA known to be activated by epigenetic drug (5-aza-2’-deoxycytidine) treatment in cancer cells16. In addition, methylation-associated silencing of miR-9 promotes nasopharyngeal carcinoma progression17and miR-203 is epigenetically silenced in hematopoietic malignancies, which leads to enhanced expression of ABL1 and BCR-ABL118. MiR-34c has been strongly implicated in cancer which induces apoptosis, cell cycle arrest and senescence, and it has been recognized as a tumor suppressor molecule19. We focused on miR-34c because recent studies have shown that it is a direct target of p5310. More importantly, our previous study indicated that the expression of miR-34c was down-regulated in AML patients13. The same results were reported by Danyue P et al.20. A number of studies have reported that miR-34c was silenced by CpG methylation11,12,21. In this study, we found that the miR-34c CpG island was hypermethylated in the great majority of primary AML patients and the expression of miR-34c was negatively associated with miR-34c methylation. Furthermore, after being treated with decitabine, the expression of miR-34c was significantly upregulated, along with the methylation density of CpG island decreased in AML cells. That is to say, miR-34c expression is regulated by CpG methylation. Of course, methylation status also were affected by many other factors, such as age, gender.

Moreover, we aimed to investigate whether miR-34c hypermethylation could act as a potential biomarker for predicting prognosis in AML. Although it has been reported that miR-34c CpG island hypermethylation had a poor prognosis in the colon, gastric cancer, it hasn’t been studied in AML patients11,12. We found that miR-34c CpG island hypermethylation AML patients had a lower CR rate. A number of genetic mutations had been identified associated with the prognosis and treatment of AML22. However, the frequencies of those gene mutations are relatively low in AML. That is to say, new molecular markers are warranted to identify those who are at the risk of poor outcome and to optimize treatment strategies in AML. Our study by both Kaplan–Meier and multivariate analyses revealed the negative prognostic value of miR-34c hypermethylation in AML patients. Taken together, the above-mentioned data indicate that miR-34c hypermethylation may be useful as a biomarker to predict a worse prognosis in AML patients. In addition, we further identified that miR-34c methylation was changed in response to demethylation treatment in AML. MiR-34c methylation was significantly decreased and miR-34c expression was increased in AML patients who achieved CR than newly diagnosed. Moreover, miR-34c hypermethylation AML patients had higher induced CR than miR-34c normally methylated which implicated that miR-34c methylation played a role in AML therapy. We speculate that miR-34c CpG island hypermethylation AML patients receiving demethylation treatment may be a better choice. This has a important significance in the research of AML treatment. Of course, due to the small cohort of the patients and different treatment regimens, a large and independent cohort of studies and clinical trials are required to validate the prognostic value of miR-34c methylation before it can be used routinely as a potential biomarker for risk stratification in AML.

However, althought hypermethylated patients show greater CR with decitabine, but no OS benefit. These findings were intriguing and consistent with previous findings in myelodysplastic syndromes and AML studies23 The reason is currently unclear. But most of investigators believe it was related to decitabine does not eliminate leukemic stem cells, which may drive relapse despite apparent remission24. This may provide guidance for future clinical treatment of AML: For patients with miR-34c hypermethylation, combination therapy that includes demethylation drugs may be a better choice. For example, the combination of demethylation drugs and chemotherapy for induction therapy will significantly improve the remission rate, enhance the quality of life for patients, and provide more possibilities for subsequent curative treatments such as hematopoietic stem cell transplantation. As a tumor suppress gene, miR-34c plays an important role in promoting apoptosis and inhibiting proliferation25. In order to further investigate the potential role of miR-34c in AML, we performed functional experiments in vitro. These results suggested that enhancing miR-34c expression in THP-1 cells exhibited anti-proliferative and pro-apoptotic effects in accordance with previous literature showing the role of miR-34c in solid tumors26,27.

Genetic alterations, especially in gene mutations, played vital roles in the disease progression of AML28. Mutations were considered as progression-related drivers in AML, such as in P53, TET2, DNMT3A, EZH2, ASXL129. P53-mutated AML is a subset of AML with especially poor response to chemotherapy and consistently dismal outcomes29. Due to a small number of cases with specific mutations, the statistical power might be limited.

It’s reported that mutation of P53 occurs in nearly 50% of cancer but occurs in only 10–15% of AML cases28,30. There is a 25–36% P53 mutation ratio among patients with erythroleukemias, and P53 mutations have been associated with the progression of AML from polycythemia vera and essential thrombocythemia31–33. Across a wide range of studies, P53-mutated AML patients tend to be poor responses to cytotoxic induction chemotherapy and be short OS34. In multivariate analysis, P53 mutations have been associated with inferior responses and OS across a range of studies34,35. A low dose of decitabine treatment does not cause direct cytotoxicity but is incorporated into DNA, where it acts to alter epigenetic signatures36. Several studies have found that the presence of adverse-risk karyotypes did not affect the response rates or OS of patients treated with decitabine37. Recent studies using 5-day schedules of decitabine noted 62% response rates in P53-mutated AML cases, and cell-line analysis further suggests a potential sensitivity of P53-mutated cells to demethylating agents38,39. Recent studies have shown that miR-34c are direct targets of p5310. THP-1 cells were reported to lack p5340 . In the current study, the protein expression level of p53 was also very low but was detectable. Interestingly, In vitro, accompanied by the demethylation of the miR-34c promoter region, the p53 protein expression level was increased. And enhance miR-34c expression in THP-1 showed the same results: p53 protein expression was increased. It indicated there is positive feedback exists between miR-34c demethylation and p53 protein expression. Moreover, the result helped explain why AML patients with p53 mutations might be sensitive to demethylation drugs. Of course, the mechanisms underlying P53 recovery remain to be investigated. Taken together, the methylation of CpG island can regulate the expression of miR-34c, thereby indirectly regulating the expression of p53.

Conclusion

In conclusion, our findings revealed that miR-34c CpG island hypermethylation is a prognostic and predictive biomarker in AML. More interestingly, the high frequency of miR-34c CpG island methylation in AML and their contribution to the p53 network imply that miR-34c functions as an important tumor suppressor in response to leukemogenesis. Thus, the reactivation of miR-34c by demethylation drugs may be an effective therapeutic strategy for the treatment of AML.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary Material 1 (1.5MB, png)
Supplementary Material 2 (2.6MB, png)
Supplementary Material 3 (509.3KB, png)

Acknowledgements

We thank Ying Tao and Hong Liu (Department of Hematology Laboratory, Shanghai Sixth People’s Hospital, Affiliated to Shanghai Jiaotong University Pathology) for their excellent pathological technology help.

Abbreviations

AML

acute myeloid Leukemia

BM

bone marrow

BSP

bisulfite sequencing

CR

complete remission

CCK-8

Cell Counting Kit-8 assay

NC

normal control

MiR-34c

microRNA-34c

qRT-PCR

quantitative real-time Polymerase Chain Reaction

qRT-MSP

quantitative real-time methylation-Polymerase Chain Reaction

WHO

World Health Organization

WBC

white blood cells

Author contributions

Ling-Yun Wu conceived designed the experiments. Dong-Qin Yang and Jian Guo analyzed the data and performed the experiments. Meng Yan collected the clinical data. Ling-Yun Wu and Dong-Qin Yang offered technical and funding support. Dong-Qin Yang wrote the paper. All authors read and approved the final manuscript.

Funding

This study was funded by grants from the National Natural Science Foundation of China (81770121, 81670121) and the Xuhui District Health Committee (SHXH202039, SHXH202307). All these study sponsors have no roles in the study design, in the collection, analysis and interpretation of data.

Data availability

The data underlying this article will be shared on reasonable request to the corresponding author. Bisulfite sequencing data were deposited into the NCBI database under accession number PRJNA1312507 and are available at the following URL: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1312507.

Declarations

Competing interests

The authors declare no competing interests.

Ethics statement

The study was conducted and performed after approval by the Clinical Research Ethics Committee of Shanghai Eighth People’s Hospital and Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiaotong University. Signed informed consent was obtained from each patient.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Dongqin Yang and Meng Yan contributed equally to this work and share first authorship.

Contributor Information

Jian Guo, Email: drguoja@163.com.

Lingyun Wu, Email: lincy2032@163.com.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1 (1.5MB, png)
Supplementary Material 2 (2.6MB, png)
Supplementary Material 3 (509.3KB, png)

Data Availability Statement

The data underlying this article will be shared on reasonable request to the corresponding author. Bisulfite sequencing data were deposited into the NCBI database under accession number PRJNA1312507 and are available at the following URL: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1312507.

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