Epigenetic control of Foxp3 in intratumoral T-cells regulates growth of hepatocellular carcinoma

More intratumoral Treg cells are detected in high-grade, large HCCs and correlate with poor prognosis

We examined intratumoral Treg cells (CD4+CD25+Foxp3+) in total T-cells (CD4+) in 40 HCC specimens (Table 1, Figure 1A). We found that the percentage of intratumoral Treg cells significantly increased with the tumor grade (IV>III>II>I, p<0.05, Figure 1B). The median size of these 40 dissected tumors was used as a cutting point to get 20 small-size HCCs and 20 large-size HCCs. We found that the percentage of intratumoral Treg cells in the large-size HCCs was significantly higher than those from the small-size HCCs (p<0.05, Figure 1C). Next, we used the median level of %Treg to separate %Treg-high (n=20) from %Treg-low patients (n=20) and examined their overall five-year survival. We found that the overall survival of %Treg-low patients was significantly better (p<0.05, Figure 1D). Thus, more intratumoral Treg cells are detected in high-grade, or large HCCs and correlate with poor prognosis.

Figure 1. More intratumoral Treg cells are detected in high-grade, large HCCs and correlate with poor prognosis. We examined intratumoral Treg cells (CD4+CD25+Foxp3+) in total T-cells (CD4+) in 40 HCC specimens. (A) Illustration of FAC soring of CD4+CD25+Foxp3+ cells. First, CD4+CD25+ cells were isolated (circled gating in the upper panel), and this population was further purified for Foxp3+ cells (circled gating in the lower panel). (B) Percentage of intratumoral Treg cells in specimens with different tumor grades. (C) The median size of these 40 dissected tumors was used as a cutting point to get 20 small-size HCCs and 20 large-size HCCs. The percentage of intratumoral Treg cells in the large-size HCCs and small-size HCCs was compared. (D) The median level of %Treg was used to separate %Treg-high (n=20) from %Treg-low patients (n=20) to compare their overall five-year survival. *p<0.05. N=40.

Lower Foxp3 promoter methylation is detected in intratumoral T-cells from high-grade, large HCCs and correlate with %Treg in T-cells

Since the epigenetic control (mainly through methylation) of Foxp3 promoter determines Treg differentiation and stability, we examined the levels of promoter methylation of Foxp3 in intratumoral T-cells in these 40 specimens. We found that the methylation levels of Foxp3 promoter in intratumoral T-cells significantly decreased with the tumor grade (IVFigure 2A). The median size of these 40 dissected tumors was used as a cutting point to get 20 small-size HCCs and 20 large-size HCCs. The methylation levels of Foxp3 promoter in intratumoral T-cells from the large-size HCCs were significantly lower than those from the small-size HCCs (p<0.05, Figure 2B). Moreover, a significant inverse correlation was detected between the methylation levels of Foxp3 promoter and the percentage of Treg cells in total intratumoral T-cells (p<0.0001, R=-0.57, Figure 2C). Thus, Lower Foxp3 promoter methylation is detected in intratumoral T-cells from high-grade, large HCCs and correlate with %Treg in T-cells. Finally, we used the median level of promoter methylation of Foxp3 in intratumoral T-cells to separate methylation-high (n=20) from methylation-low patients (n=20) and examined their overall five-year survival. We found that the overall survival of methylation-low patients was significantly better (p<0.05, Figure 2D).

Figure 2. Lower Foxp3 promoter methylation is detected in intratumoral T-cells from high-grade, large HCCs and correlate with %Treg in T-cells. (A) The relative methylation levels of Foxp3 promoter in intratumoral T-cells in HCC specimens with different tumor grades by MS-PCR. (B) The relative methylation levels of Foxp3 promoter in intratumoral T-cells in small versus large HCCs by MS-PCR. (C) Correlation between the methylation levels of Foxp3 promoter and the percentage of Treg cells in total intratumoral T-cells. (D) The median level of methylation level of Foxp3 promoter was used to separate methylaition-high (n=20) from methylation-low patients (n=20) to compare their overall five-year survival.*p<0.05. N=40.

Specific target and alteration of DNMT1 levels in T-cells

DNA (cytosine-5)-methyltransferase 1 (DNMT1) is a major methylation inducer. We used an adeno-associated virus (AAV) carrying either DNMT1, or scrambled (as a control) or shDNMT1 under a CD4 promoter (AAV-pCD4-DNMT1, AAV-pCD4-scrambled, AAV-pCD4-shDNMT1) to successfully target T-cells and alter the levels of DNMT1 (Figure 3A). These AAVs were used to infect a human T-cell line, HM2 and a human non-T-cell, HEK293. We found that HM2 cells were transduced, while HEK293 cells were not, based on expression of GFP reporter (Figure 3B.). The changes in DNMT1 levels were assessed by RT-qPCR (Figure 3C), and by Western blot (Figure 3D), confirming the effects of DNMT1 overexpression or depletion.

Figure 3. Specific target and alteration of DNMT1 levels in T-cells. (A) We used an AAV carrying either DNMT1, or scrambled (as a control) or shDNMT1 under a CD4 promoter (AAV-pCD4-DNMT1, AAV-pCD4-scrambled, AAV-pCD4-shDNMT1) to successfully target T-cells and alter the levels of DNMT1. (B) Direct fluorescence for GFP in transduced cells. (C, D) RT-qPCR (C) and Western blot (D) for DNMT1. *p<0.05. N=5. Scale bars are 20 μm.

Epigenetic alteration in intratumoral T-cells affects tumor growth

A mouse HCC cell line Hepa1-6 that expresses luciferase reporter was subcutaneously implantated into C57/BL6 mice to generate detectable tumor. From the second week after transplantation, intratumoral injection with AAV-pCD4-DNMT1, or AAV-pCD4-scrambled, or AAV-pCD4-shDNMT1 was done every week till 8 weeks, when the mice were sacrificed. The bioluminescence analysis showed that intratumoral injection with AAV-pCD4-DNMT1 significantly educed tumor size, while intratumoral injection with AAV-pCD4-shDNMT1 significantly increased tumor size, by representative images (Figure 4A), and by quantification (Figure 4B). Measurement of dissected tumor weights showed that intratumoral injection with AAV-pCD4-DNMT1 significantly reduced tumor mass, while intratumoral injection with AAV-pCD4-shDNMT1 significantly increased tumor mass, by representative images (Figure 4C), and by quantification (Figure 4D). Together, these data suggest that epigenetic alteration in intratumoral T-cells affects tumor growth.

Figure 4. Epigenetic alteration in intratumoral T-cells affects tumor growth. A mouse HCC cell line Hepa1-6 that expresses luciferase reporter was subcutaneously implantated into C57/BL6 mice to generate detectable tumor. From the second week after transplantation, intratumoral injection with pAAV-pCD4-DNMT1, or pAAV-pCD4-scrambled, or pAAV-pCD4-shDNMT1 was done every week till 8 weeks, when the mice were sacrificed. (A–B) The bioluminescence analysis at sacrifice, shown by representative images (A), and by quantification (B). (C–D) Measurement of dissected tumor mass, shown by representative images (C), and by quantification (D). *p<0.05. N=3.

Promoter and CpG regions are the major sites where methylation is regulated by DNMT1

Foxp3 has 3 known sites that are susceptible for methylation, promoter, enhancer and CpG region. We analyzed the changes in methylation status at these sites in intratumoral T-cells by DNMT1 alterations. Intratumoral T-cells were purified by CD4-based flow cytometry (Figure 5A). First, we examined the DNMT1 levels in CD4+ T-cells and found that intratumoral injection with AAV-pCD4-DNMT1 significantly increased DNMT1 levels in intratumoral T-cells, while intratumoral injection with AAV-pCD4-shDNMT1 significantly decreased DNMT1 levels in intratumoral T-cells (Figure 5B). Moreover, CD4+CD25+Foxp3+ Treg cells were quantified in tumors and showed significant increase in AAV-pCD4-shDNMT1-injected tumor but significant decrease in AAV-pCD4-DNMT1-injected tumor (Figure 5C). We found that the methylation status of Foxp3 on promoter (Figure 5D) and CpG regions (Figure 5F), but not the enhancer region (Figure 5E), was significantly altered by pAAV-pCD4-DNMT1 or pAAV-pCD4-shDNMT1.

Figure 5. Promoter and CpG regions are the major sites where methylation is regulated by DNMT1. (A) Intratumoral T-cells were purified by CD4-based flow cytometry from the HCC-bared mice that had received intratumoral injection with AAV-pCD4-DNMT1, or AAV-pCD4-scrambled, or AAV-pCD4-shDNMT1. (B) RT-qPCR for DNMT1 in CD4+ cells from AAV-pCD4-DNMT1-, or AAV-pCD4-scrambled-, or AAV-pCD4-shDNMT1- injected tumor. (C) % CD4+CD25+Foxp3+ Treg cells in total CD4+ cells. (D–F) Methylation status of 3 known sites on Foxp3 (promoter (D), enhancer (E) and CpG (F) region) were assessed by MS-PCR. *p<0.05. NS: non-significant. N=3.

Animal and experimental protocols

All the experimental methods including animal experiments have been approved by the research committee and the Institutional Animal Care and Use Committee at the Shanghai Jiao Tong University School of Medicine.

Human samples

The research work on human samples was done following these guidelines and in accordance with the instruction from institutional Ethics Committee. Surgically removed specimens of HCC were obtained from 40 patients who underwent surgery between 2011 and 2013 at Ruijin Hospital (Table 1). Fresh tissue was digested with 0.25% Trypsin (Sigma-Aldrich, San Jose, CA, USA) for 45 minutes, followed by T-cell (CD4+) and Treg cell (CD4+CD25+Foxp3+) isolation by flow cytometry. Total CD4+ cell population was used for promoter methylation analysis.

Cell culture and treatment

A human T-cell line HM2, a human cell line HEK293, and a mouse HCC cell line Hepa1-6 were all purchased from ATCC (American Type Culture Collection, Manassas, VA, USA). These cells were cultured in Dulbecco's Modified Eagle's Medium supplemented with 10 % Fetal Bovine Serum (FBS, Invitrogen, Carlsbad, CA, USA) in a 37 °C incubator with an atmosphere of 5 % CO₂.

Plasmids, AAVs, and cell transfection

DNMT1-coding sequence was amplified from cDNA from human bone marrow. CD4 promoter was cloned from human genomic DNA. Short-hairpin small interfering RNA for DNMT1 (shDNMT1) used the targeting sequence of “5′-GCCCAATGAGACTGACATCAA-3′”. A scrambled sequence (5′-CACCGAGCCCACCACAGCTCAAG-3′) was used as a control. The plasmids for generating vectors were prepared from a pAAV-CAG-GFP plasmid (Clontech, Mountain View, CA, USA). By molecular cloning assay, CAG promoter was replaced with CD4 promoter. DNMT1, or scrambled, or shDNMT1 with a 2A sequence (allows equally expression of 2 genes by one promoter) was inserted immediately before GFP reporter, to generate pAAV-pCD4-DNMT1, or pAAV-pCD4-scrambled, or pAAV-pCD4-shDNMT1. Transfection of HM2 or HEK293 cells was performed using Lipofectamine 3000 (Invitrogen), as instructed. AAVs were prepared with a packaging kit (Clontech). Hepa1-6 cells were transduced with an AAV-pCMV-luciferase (Clontech) to allow in vivo detection in the live animals.

Tumor graft model in mice

The male C57/BL6 mice at 12-week-old (SLAC Laboratory Animal Co. Ltd, Shanghai, China) were used for subcutaneous implantation of 10⁶ AAV-pCMV-luciferase-transduced mouse Hepa1-6 cells at their flanks (n=3 for each group). From the second week after transplantation, intratumoral injection with 10¹¹ viral particles pAAV-pCD4-DNMT1, or pAAV-pCD4-scrambled, or pAAV-pCD4-shDNMT1 was done every week till 8 weeks, when the mice were sacrificed and the bioluminescence and the size of the dissected tumor weights were measured. The bioluminescence detection was performed and the images were recorded with IVIS imaging system (Xenogen Corp., Alameda, CA, USA), with an acquisition time of 60-second and binning of 10.

Flow cytometry

Tumor was digested with 0.25% Trypsin (Sigma-Aldrich) for 45 minutes, followed by flow cytometry analysis and cell sorting. The cell preparations were labeled with PE-conjugated anti-CD4 antibody, APC-conjugated anti-CD25 antibody and Pacific blue-conjugated anti-CD4 antibody (Becton-Dickinson Biosciences, San Jose, CA, USA), GFP was detected by direct fluorescence. Flow cytometry was performed using a FACSAria (Becton-Dickinson Biosciences) flow cytometer, and the data were analyzed and presented using Flowjo software version 10 (Flowjo LLC, Ashland, OR, USA).

Quantitative reverse transcription polymerase chain reaction (RT-qPCR) and methylation-specific PCR (MS-PCR)

TaqMan quantitative PCR (RT-qPCR, two step) was applied to examine the relative levels of the genes, using GAPDH as an internal control. The total RNA was isolated using TRIzol® reagent (Invitrogen), according to the manufacturer’s instructions. RNA was then reverse transcribed into cDNA using the High Capacity cDNA Reverse Transcription kit (Applied Biosystems, Foster City, CA, USA). TaqMan Gene Expression Assays were done using pre-designed primers on an ABI 7500 Fast Real-time PCR system (Applied Biosystems). Relative quantification of gene expression was performed using the 2-ΔΔCt method.

MS-PCR was performed to identify the methylation status of Foxp3. Bisulfite conversion of DNA was done with an EZ-96 DNA Methylation-Gold kit (Zymo Research, Irvine, CA, USA). Each 15 ml MS-PCR included 7.5 ml Qiagen Multiplex Master Mix (Qiagen, Hilden, Germany), 3 ml Q solution (Qiagen), 0.3 ml forward primers, 0.3 ml reverse primers, 2.9 ml of RNAse-free water and 1 ml of bisulfite-converted template DNA. The primer sequences used in the MS-PCR were shown in Table 2. MS-PCR products were analyzed by agarose gel electrophoresis. Samples were defined as methylated or unmethylated depending upon the visual band amplified with methylated or unmethylated primers.

Western blot

Cells were lysed in lysis buffer (Sigma-Aldrich) for 30 minutes. A BCA kit (Pierce Biotechnology, Rockford, IL, USA) was used to determine protein concentrations. After gel electrophoresis, membrane transfer and blocked with 5% non-fat milk, the blots were probed with antibodies against DNMT1 (Abcam, Beijing, China) and GAPDH (Cell signaling, Shanghai, China) overnight. The blots were then washed and incubated with horseradish peroxidase-conjugated secondary antibodies (Santa Cruz Biotechnology, Inc., Nanjing, China) for 1 hour at room temperature, followed by development of the signal by an ECL detection reagent (Pierce Biotechnology) and quantification with densitometry using Image J software (Bethesda, MA, USA). Blotting images were representative from 5 repeats.

Statistical analysis

GraphPad Prism 7 (GraphPad, Chicago, IL, USA) software was used in the current study. The methods include one-way and two-way ANOVA with a Bonferroni correction, followed by Fisher’s Exact Test for comparison between two groups. All values are depicted as mean ± standard deviation and are considered significant if p < 0.05. Bivariate correlations were calculated by Spearman's rank correlation coefficients. Kaplan-Meier curve was applied to record the overall survival of the patients included in this study.