# Epigenetic Profiling of H3K4Me3 Reveals Herbal Medicine Jinfukang-Induced Epigenetic Alteration Is Involved in Anti-Lung Cancer Activity

Authors: Jun Lu; Xiaoli Zhang; Tingting Shen; Chao Ma; Jun Wu; Hualei Kong; Jing Tian; Zhifeng Shao; Xiaodong Zhao; Ling Xu
Journal: Evidence-Based Complementary and Alternative Medicine
 (2016)

---

## Abstract

Traditional Chinese medicine Jinfukang (JFK) has been clinically used for treating lung cancer. To examine whether epigenetic modifications are involved in its anticancer activity, we performed a global profiling analysis of H3K4Me3, an epigenomic marker associated with active gene expression, in JFK-treated lung cancer cells. We identified 11,670 genes with significantly altered status of H3K4Me3 modification following JFK treatment (P
<
0.05). Gene Ontology analysis indicates that these genes are involved in tumor-related pathways, including pathway in cancer, basal cell carcinoma, apoptosis, induction of programmed cell death, regulation of transcription (DNA-templated), intracellular signal transduction, and regulation of peptidase activity. In particular, we found that the levels of H3K4Me3 at the promoters ofSUSD2, CCND2, BCL2A1, andTMEM158 are significantly altered in A549, NCI-H1975, NCI-H1650, and NCI-H2228 cells, when treated with JFK. Collectively, these findings provide the first evidence that the anticancer activity of JFK involves modulation of histone modification at many cancer-related gene loci.


---

## Body

## 1. Introduction

Chromatin is the macromolecular complex of DNA and histone proteins that provides the scaffold for packaging the eukaryotic genome [1, 2]. Histones H2A, H2B, H3, and H4 are the basic components of nucleosomes, which form the fundamental unit of chromatin [3, 4]. Chemical modifications to the histones alter chromatin structure and regulate gene expression by altering noncovalent interactions within and between nucleosomes [2, 5]. H3K4Me3 is an active histone modification which is positively associated with gene expression [3, 6]. Previous studies have shown that the levels of H3K4Me3 modification are closely associated with the development, treatment, and diagnosis of disease [7–9]. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) has been developed to systematically characterize the contribution of epigenetic regulation in various biological processes via genome-wide profiling of various chemical modifications of histone proteins and genomic DNA methylation [10].Lung cancer has become the leading cause of cancer-related deaths worldwide [11]. Overall, only 16.8% of patients with lung cancer survive five years after their first definite diagnosis, mainly as a consequence of uncontrollable cell proliferation or tumor metastasis [12, 13]. Although various therapeutic interventions, including surgery, chemotherapy, and radiotherapy, have been developed to prolong the survival time of patients, drug side effects, pain, and emaciation are still significant problems for tumor sufferers and their physicians [14, 15].Traditional Chinese medicine (TCM) has been employed in the treatment of many diseases for several thousand years and still plays an important role in public health in present day [16]. Jinfukang (JFK), a TCM formula, has been clinically used for treating lung cancer patients for more than ten years, and its curative effects have been reported to be promising [14, 17–19]. However, although the clinical effects of JFK are known [17], its antitumor mechanism remains unclear. In previous study, researchers demonstrated that JFK modulates the expression of genes which are involved in the cell cycle and apoptosis [18]. In the present study, we examined the pattern with H3K4Me3 pattern modulated by JFK in A549 cells and the implication in its antitumor activity of JFK.


## 2. Materials and Methods

### 2.1. Animals and Treatments

All animals received humane care during the study, under a protocol that was in accordance with institutional guidelines. Sprague-Dawley rats were obtained from Shanghai SLAC Laboratory Animal Co., Ltd. All rats were fed laboratory rat-fodder and water, ad libitum, and were maintained at22
±
1°C and lighting was set for 12 h on, 12 h off. In this experiment, 20 rats were divided into two groups including control and JFK. Rats were administrated orally 1 mL saline for control group and 4 g Kg−1 body weight JFK (volume: 1 mL) for JFK group, respectively, three times a day for 15 consecutive days.


### 2.2. JFK Drug Serum Preparation

The procedures of drug serum preparation were performed according to a previous study [20]. Briefly, two hours after the last administration, all blood samples were collected by abdominal aortic method under the state of anesthesia using pentobarbital sodium. Each rat was sacrificed by cervical dislocation. The concretionary blood was centrifuged at 1,500 g for 15 min, and then the JFK drug serum was collected and stored at −80°C.


### 2.3. Cells and Cell Culture

The human lung cancer cell lines A549, NCI-H1975, NCI-H1650, and NCI-H2228 were obtained from the Shanghai Institute of Biochemistry and Cell Biology. Cells were cultured in RPMI-1640 Medium (Gibco, USA) and maintained at 37°C in a humidified atmosphere of 5% CO2. Growth media were supplemented with 10% fetal bovine serum (FBS) (Gibco, USA) and penicillin/streptomycin (Life Technologies, Inc., USA) final concentration is 100 U/mL. The cells were subcultured when they reached approximately 90% confluence using a 0.25% trypsin solution. For observation of JFK-induced cell alteration, 10% control serum and JFK drug serum were supplemented to growth media for replacing 10% FBS, respectively.


### 2.4. Cell Viability Analysis

Cells were cultured in 96-well plates overnight and incubated with indicated serums for 12 h, 24 h, 48 h, 72 h, 96 h, and 120 h, respectively. Cellular viability was measured by Cell Counting Kit 8 (CCK8) (Dojindo, Japan). In brief, the cell proliferation reagent WST-8 (10μL) was added to each well and cells were incubated for 2 h at 37°C. Viable cell numbers were estimated by measuring the optical density (OD) at 450 nm. Absorbance of control group was set as 100% viability, and absorbance of cell-free wells containing medium was set as zero.


### 2.5. DAPI Staining

A549 cells were fixed in 4% paraformaldehyde and then stained with DAPI (Sigma, USA) and observed using Confocal Laser Scanning Microscopy (CLSM) (Nikon, Japan). Cells were viewed to be damaged if the dissolution, condensation, or fragmentation of nuclei was observed.


### 2.6. PI Staining

A549 cells were fixed, stained with PI (Sigma, USA), and observed using fluorescence microscopy (Nikon, Japan). Pictures were obtained through fluorescence microscopy at the excitation wavelength of 536 nm. Cells were designated as being dead if they had highly red color and nondead if the staining was slight or none.


### 2.7. Cell Apoptosis Analysis

Determination of phosphatidylserine (PS) and membrane integrity was performed by Annexin V-FITC/PI Apoptosis kit (Zoman, China). In brief, A549, NCI-H1975, NCI-H1650, and NCI-H2228 cells were harvested by trypsin (no EDTA) and washed twice with PBS, then stained with Annexin V-FITC/PI, and analyzed by flow cytometry (BD LSRFortessa, USA).


### 2.8. Chromatin Immunoprecipitation (ChIP) Assay

ChIP assay was performed as previously described [10]. In brief, 3.5 × 106 cells were rinsed with PBS, cross-linked with 1% formaldehyde and quenched with 2.5 M glycine (Sigma, USA), and then harvested in a 1.5 mL tube. 100 bp to 300 bp chromatin fragments were obtained after sonication with indicated condition. 1% total fragmented DNA was transferred to a new tube set as input. Immunoprecipitated DNA fragments were captured by H3K4Me3 antibody (Abcom, USA), following quantification by Picogreen measurement kit. Primers ofMYC andEGFR were designed for detecting whether the immunoprecipitated DNAs were enriched and qualified for library procedure. Primer sequences were showed in Table 1.Table 1
Primer sequences for ChIP-qPCR and RT-qPCR.
Type
Gene
GenBank
Forward (5′-3′)
Reverse (5′-3′)
ChIP-qPCR
MYC
[NM_002467]
CATTCCTGCGCTATTGACAC
AAAAACCATTCCCGTTTTCC
EGFR
[NM_005228]
AGGGAAGCTGAGGAAGGAAC
CGGCTTCAGTTTGAGACCTG
SUSD2
[NM_019601]
AGCCTCTGTCCATCTGTCAG
TTCTTCCCATCACCCCTAGC
PTN
[NM_002825]
GAGCCCTCCGAGAAATCGTA
CAACAAAGGCAGACTGAGCG
GLIS2
[NM_032575]
GGTGCCAAAGGATGTTGCTT
CACAAGGGCAGGATGGTTTG
CCND2
[NM_0201759]
CGCGTTCCCTAGTTTCTGTC
GAAACTTGAAGGGGTGAGCG
TM4SF4
[NM_004617]
GAGGCAGTGAGGAGCTTTTG
AAAGCAAGGGGAATGAGGGT
BCL2A1
[NM_004049]
TATCCACATCCGGGGCAATT
ACGGCATCATTAACTGGGGA
IL31RA
[NM_139017]
GCAGAGTGTCAGCTTGTTCC
TTGCGGACATTCACAGACAC
WISP2
[NM_003881]
CTTGGGTCAGCTCTGCAAAG
CTGCTGTAGTTGTGAAGCCC
TNFAIP6
[NM_007115]
TGCTTCATGGACTCTGAGCT
TTTCTGTACTGCAAGCTGGC
TMEM158
[NM_015444]
TTTGGAAAGGCTGGGAAACG
GGGAGAGGGCACGATTAGAA
RT-qPCR
SUSD2
[NM_019601]
CATGAAGCCAGCCCTCCT
GTCGGGTGGCAGGAACAT
CCND2
[NM_0201759]
CTCCTACTTCAAGTGCGTGC
TCGCACTTCTGTTCCTCACA
BCL2A1
[NM_004049]
AGGTGTGTGATTGTGCCATT
AATTGCCCCGGATGTGGATA
TMEM158
[NM_015444]
GCCTAGACTTCAGCCTGGAG
ACCAGGGTCATGAAGCAGG


### 2.9. Library Preparation and ChIP-Seq

For library, 40~50 ng immunoprecipitated DNAs and input DNAs were end-repaired and ligated adapters to the DNA fragments using NEBNext Ultra End-Repair/dA-Tailing Module and NEBNext Ultra Ligation Module (NEB, USA), respectively. DNA size selection was performed using 2% Agarose Gel; then 200~500 bp DNA fragments were excised and purified using Qiagen Gel Extraction Kit (Qiagen, Germany). Each sample was amplified for 14 cycles in a DNA thermal cycler using Q5 High-Fidelity DNA Polymerase (NEB, USA) and corresponding PCR Master Mix. Lastly, the PCR products were quantified using Nanodrop and performed standard single end sequencing with 50 bp reads using Illumina Hiseq 2000 (Illumina, USA). The raw sequencing data of this study are available in the EMBL database under accession number E-MTAB-3992:http://www.ebi.ac.uk/arrayexpress/.


### 2.10. Bioinformatic Analysis

Raw data were extracted and initially analyzed by Illumina software. We used FastQC software to detect data quality. After prefiltering the raw data by removing sequenced adapters and low quality reads, the sequence tags were aligned to human genome (NCBI/hg19) with Bowtie alignment tool [21]. After being filtered, at least 12 million unique reads per sample were used for peak detection. Peak detection was performed using the MACS program with a two-sample analysis where sequenced input (1%) was used as negative control [22]. Due to the differences in the number of reads between experimental data and input DNA data, a random subselection was applied to the larger data set for normalization. The statistics of RNA-seq data sets were shown in Table 2.Table 2
The statistics of ChIP-seq data sets.
Total reads
Unique mapping reads
Mapping rate
Sequencing quality (Q30)
Control input
36251128
31414275
86%
97.49
Control
26353782
20332230
77%
97.13
JFK input
17592377
10755542
61%
96.1
JFK
16435835
12904340
79%
97.22For identifying qualified peak regions, experimental data and input DNA data were consolidated in a window size of 100 bp andP value < 0.05. To compare JFK-treated versus control H3K4Me3 ChIP data sets, the two lists of peaks were matched based on overlapped genome positions. Matched peak regions were annotated using UCSC annotation database and genes with qualified peaks within 2,000 bp of the Transcriptional Start Sites (TSSs) were identified. Fold change was also calculated for each matched peak region comparing JFK-treated versus control H3K4Me3 peaks.The Database for Annotation, Visualization and Integrated Discovery (DAVID) bioinformatics resource was used to annotate gene functions and pathways [23]. Briefly, Gene Ontology (GO) analysis [24] and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis [25] were performed by uploading differential gene list to DAVID Bioinformatics Resources 6.7. Besides, network construction was performed using Reduce Visualize Gene Ontology (http://revigo.irb.hr/), and then network graph was modified using Cytoscape software (version 3.2.1).


### 2.11. ChIP-qPCR Validation

Immunoprecipitated DNAs from control and JFK samples were obtained by ChIP assays which are described as previously mentioned. For validation of target genes H3K4Me3 modification fold change, all target gene primers were designed using Primer3 web (version 4.0.0). All primer sequences are showed in Table1.


### 2.12. Quantification of mRNA Level

Transcription level of genes of interest was evaluated using quantitative real-time PCR (RT-qPCR) with SYBR Green PCR Master Mix (Bestar, Germany). RT-qPCR was performed according to standard procedure. All primer sequences used for RT-qPCR were shown in Table1.


### 2.13. Statistical Analysis

Data are presented as the mean ± SD. The differences between the groups were examined using the standard one-way ANOVA. SPSS for Windows 14.0 software package was used. Differences were considered significant atP
<
0.05.


## 2.1. Animals and Treatments

All animals received humane care during the study, under a protocol that was in accordance with institutional guidelines. Sprague-Dawley rats were obtained from Shanghai SLAC Laboratory Animal Co., Ltd. All rats were fed laboratory rat-fodder and water, ad libitum, and were maintained at22
±
1°C and lighting was set for 12 h on, 12 h off. In this experiment, 20 rats were divided into two groups including control and JFK. Rats were administrated orally 1 mL saline for control group and 4 g Kg−1 body weight JFK (volume: 1 mL) for JFK group, respectively, three times a day for 15 consecutive days.


## 2.2. JFK Drug Serum Preparation

The procedures of drug serum preparation were performed according to a previous study [20]. Briefly, two hours after the last administration, all blood samples were collected by abdominal aortic method under the state of anesthesia using pentobarbital sodium. Each rat was sacrificed by cervical dislocation. The concretionary blood was centrifuged at 1,500 g for 15 min, and then the JFK drug serum was collected and stored at −80°C.


## 2.3. Cells and Cell Culture

The human lung cancer cell lines A549, NCI-H1975, NCI-H1650, and NCI-H2228 were obtained from the Shanghai Institute of Biochemistry and Cell Biology. Cells were cultured in RPMI-1640 Medium (Gibco, USA) and maintained at 37°C in a humidified atmosphere of 5% CO2. Growth media were supplemented with 10% fetal bovine serum (FBS) (Gibco, USA) and penicillin/streptomycin (Life Technologies, Inc., USA) final concentration is 100 U/mL. The cells were subcultured when they reached approximately 90% confluence using a 0.25% trypsin solution. For observation of JFK-induced cell alteration, 10% control serum and JFK drug serum were supplemented to growth media for replacing 10% FBS, respectively.


## 2.4. Cell Viability Analysis

Cells were cultured in 96-well plates overnight and incubated with indicated serums for 12 h, 24 h, 48 h, 72 h, 96 h, and 120 h, respectively. Cellular viability was measured by Cell Counting Kit 8 (CCK8) (Dojindo, Japan). In brief, the cell proliferation reagent WST-8 (10μL) was added to each well and cells were incubated for 2 h at 37°C. Viable cell numbers were estimated by measuring the optical density (OD) at 450 nm. Absorbance of control group was set as 100% viability, and absorbance of cell-free wells containing medium was set as zero.


## 2.5. DAPI Staining

A549 cells were fixed in 4% paraformaldehyde and then stained with DAPI (Sigma, USA) and observed using Confocal Laser Scanning Microscopy (CLSM) (Nikon, Japan). Cells were viewed to be damaged if the dissolution, condensation, or fragmentation of nuclei was observed.


## 2.6. PI Staining

A549 cells were fixed, stained with PI (Sigma, USA), and observed using fluorescence microscopy (Nikon, Japan). Pictures were obtained through fluorescence microscopy at the excitation wavelength of 536 nm. Cells were designated as being dead if they had highly red color and nondead if the staining was slight or none.


## 2.7. Cell Apoptosis Analysis

Determination of phosphatidylserine (PS) and membrane integrity was performed by Annexin V-FITC/PI Apoptosis kit (Zoman, China). In brief, A549, NCI-H1975, NCI-H1650, and NCI-H2228 cells were harvested by trypsin (no EDTA) and washed twice with PBS, then stained with Annexin V-FITC/PI, and analyzed by flow cytometry (BD LSRFortessa, USA).


## 2.8. Chromatin Immunoprecipitation (ChIP) Assay

ChIP assay was performed as previously described [10]. In brief, 3.5 × 106 cells were rinsed with PBS, cross-linked with 1% formaldehyde and quenched with 2.5 M glycine (Sigma, USA), and then harvested in a 1.5 mL tube. 100 bp to 300 bp chromatin fragments were obtained after sonication with indicated condition. 1% total fragmented DNA was transferred to a new tube set as input. Immunoprecipitated DNA fragments were captured by H3K4Me3 antibody (Abcom, USA), following quantification by Picogreen measurement kit. Primers ofMYC andEGFR were designed for detecting whether the immunoprecipitated DNAs were enriched and qualified for library procedure. Primer sequences were showed in Table 1.Table 1
Primer sequences for ChIP-qPCR and RT-qPCR.
Type
Gene
GenBank
Forward (5′-3′)
Reverse (5′-3′)
ChIP-qPCR
MYC
[NM_002467]
CATTCCTGCGCTATTGACAC
AAAAACCATTCCCGTTTTCC
EGFR
[NM_005228]
AGGGAAGCTGAGGAAGGAAC
CGGCTTCAGTTTGAGACCTG
SUSD2
[NM_019601]
AGCCTCTGTCCATCTGTCAG
TTCTTCCCATCACCCCTAGC
PTN
[NM_002825]
GAGCCCTCCGAGAAATCGTA
CAACAAAGGCAGACTGAGCG
GLIS2
[NM_032575]
GGTGCCAAAGGATGTTGCTT
CACAAGGGCAGGATGGTTTG
CCND2
[NM_0201759]
CGCGTTCCCTAGTTTCTGTC
GAAACTTGAAGGGGTGAGCG
TM4SF4
[NM_004617]
GAGGCAGTGAGGAGCTTTTG
AAAGCAAGGGGAATGAGGGT
BCL2A1
[NM_004049]
TATCCACATCCGGGGCAATT
ACGGCATCATTAACTGGGGA
IL31RA
[NM_139017]
GCAGAGTGTCAGCTTGTTCC
TTGCGGACATTCACAGACAC
WISP2
[NM_003881]
CTTGGGTCAGCTCTGCAAAG
CTGCTGTAGTTGTGAAGCCC
TNFAIP6
[NM_007115]
TGCTTCATGGACTCTGAGCT
TTTCTGTACTGCAAGCTGGC
TMEM158
[NM_015444]
TTTGGAAAGGCTGGGAAACG
GGGAGAGGGCACGATTAGAA
RT-qPCR
SUSD2
[NM_019601]
CATGAAGCCAGCCCTCCT
GTCGGGTGGCAGGAACAT
CCND2
[NM_0201759]
CTCCTACTTCAAGTGCGTGC
TCGCACTTCTGTTCCTCACA
BCL2A1
[NM_004049]
AGGTGTGTGATTGTGCCATT
AATTGCCCCGGATGTGGATA
TMEM158
[NM_015444]
GCCTAGACTTCAGCCTGGAG
ACCAGGGTCATGAAGCAGG


## 2.9. Library Preparation and ChIP-Seq

For library, 40~50 ng immunoprecipitated DNAs and input DNAs were end-repaired and ligated adapters to the DNA fragments using NEBNext Ultra End-Repair/dA-Tailing Module and NEBNext Ultra Ligation Module (NEB, USA), respectively. DNA size selection was performed using 2% Agarose Gel; then 200~500 bp DNA fragments were excised and purified using Qiagen Gel Extraction Kit (Qiagen, Germany). Each sample was amplified for 14 cycles in a DNA thermal cycler using Q5 High-Fidelity DNA Polymerase (NEB, USA) and corresponding PCR Master Mix. Lastly, the PCR products were quantified using Nanodrop and performed standard single end sequencing with 50 bp reads using Illumina Hiseq 2000 (Illumina, USA). The raw sequencing data of this study are available in the EMBL database under accession number E-MTAB-3992:http://www.ebi.ac.uk/arrayexpress/.


## 2.10. Bioinformatic Analysis

Raw data were extracted and initially analyzed by Illumina software. We used FastQC software to detect data quality. After prefiltering the raw data by removing sequenced adapters and low quality reads, the sequence tags were aligned to human genome (NCBI/hg19) with Bowtie alignment tool [21]. After being filtered, at least 12 million unique reads per sample were used for peak detection. Peak detection was performed using the MACS program with a two-sample analysis where sequenced input (1%) was used as negative control [22]. Due to the differences in the number of reads between experimental data and input DNA data, a random subselection was applied to the larger data set for normalization. The statistics of RNA-seq data sets were shown in Table 2.Table 2
The statistics of ChIP-seq data sets.
Total reads
Unique mapping reads
Mapping rate
Sequencing quality (Q30)
Control input
36251128
31414275
86%
97.49
Control
26353782
20332230
77%
97.13
JFK input
17592377
10755542
61%
96.1
JFK
16435835
12904340
79%
97.22For identifying qualified peak regions, experimental data and input DNA data were consolidated in a window size of 100 bp andP value < 0.05. To compare JFK-treated versus control H3K4Me3 ChIP data sets, the two lists of peaks were matched based on overlapped genome positions. Matched peak regions were annotated using UCSC annotation database and genes with qualified peaks within 2,000 bp of the Transcriptional Start Sites (TSSs) were identified. Fold change was also calculated for each matched peak region comparing JFK-treated versus control H3K4Me3 peaks.The Database for Annotation, Visualization and Integrated Discovery (DAVID) bioinformatics resource was used to annotate gene functions and pathways [23]. Briefly, Gene Ontology (GO) analysis [24] and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis [25] were performed by uploading differential gene list to DAVID Bioinformatics Resources 6.7. Besides, network construction was performed using Reduce Visualize Gene Ontology (http://revigo.irb.hr/), and then network graph was modified using Cytoscape software (version 3.2.1).


## 2.11. ChIP-qPCR Validation

Immunoprecipitated DNAs from control and JFK samples were obtained by ChIP assays which are described as previously mentioned. For validation of target genes H3K4Me3 modification fold change, all target gene primers were designed using Primer3 web (version 4.0.0). All primer sequences are showed in Table1.


## 2.12. Quantification of mRNA Level

Transcription level of genes of interest was evaluated using quantitative real-time PCR (RT-qPCR) with SYBR Green PCR Master Mix (Bestar, Germany). RT-qPCR was performed according to standard procedure. All primer sequences used for RT-qPCR were shown in Table1.


## 2.13. Statistical Analysis

Data are presented as the mean ± SD. The differences between the groups were examined using the standard one-way ANOVA. SPSS for Windows 14.0 software package was used. Differences were considered significant atP
<
0.05.


## 3. Results

### 3.1. A549 Cell Viability and Cell Nucleus Morphology Are Changed after Incubation with JFK

The survival rate and changes to the nuclear morphology of A549 cells were monitored via a multimode reader and optical microscopy. We observed that cell viability decreases significantly after 24 h incubation with JFK drug serums obtained from day 7 and day 14 (Figure1(a)). In addition, time-dependent assays suggest that cell viability reduces significantly when A549 cells are exposed to the JFK serum from day 14 for incubation times longer than 24 h (Figure 1(b)). Thus, we chose a 48 h incubation time with JFK for all future experiments. Interestingly, nuclear staining with DAPI revealed alterations to the nuclear morphology in response to JFK. As shown in Figures 1(c) and 1(d), after the JFK treatment for 48 h, many nuclei were markedly larger compared to those in the control, indicating that these cells are in a state of abnormality.Figure 1
Treatment with JFK induces proliferation inhibition and nuclear morphology alteration in A549 cells. (a) A549 cells were treated with JFK drug serums from day 3, day 7, and day 14, respectively (n
=
3, P
∗
<
0.05). (b) A549 cells were treated with JFK drug serum from day 14 for 12 h, 24 h, 48 h, 72 h, 96 h, and 120 h, respectively (n
=
3, P
∗
<
0.05, P
∗
∗
<
0.01, and P
∗
∗
∗
<
0.001). (c, d) A549 cells were stained with DAPI for detecting nucleus changes using CLSM. Scale bar: 25 μm.
(a)
(b)
(c)
(d)


### 3.2. Proapoptotic Effects of JFK on A549 Cells

To further understand the effects of JFK on A549 cells, we examined the number of apoptotic cells by staining with PI and using fluorescence microscopy. As shown in Figure2(a), cells colored red, indicative of apoptosis, are found following treatment with JFK, suggesting that JFK could induce apoptosis in these cells. Flow cytometric analysis also showed a significant increase in JFK-induced apoptosis compared to a vehicle treatment control (Figure 2(b)). In particular, the total apoptosis rate calculated as Annexin and PI positive cells and the early apoptosis rate calculated as Annexin positive cells, respectively, by flow cytometry were significantly increased in A549 cells after JFK treatment, compared to those in vehicle treated A549 cells (Figure 2(c)).Figure 2
Treatment with JFK induces cell death and apoptosis in A549 cells. (a) A549 cells were stained with PI for detecting deathbed cells using fluorescence microscope. Scale bar: 50μm. (b) A549 cells were treated with JFK, and the apoptotic progression was determined by flow cytometry. (c) Total apoptosis and early apoptosis ratios were analyzed based on results of flow cytometry (n
=
3, P
∗
∗
∗
<
0.001).
(a)
(b)
(c)


### 3.3. JFK Induces an Alteration in the H3K4Me3 Pattern in A549 Cells

Previous studies have reported that the level of H3K4Me3 modification in TSSs is linked to transcriptional activation [3, 6]. To examine the alteration of H3K4Me3 modification upon exposing A549 cells to JFK, we performed genome-wide mapping of H3K4Me3 modification by ChIP-seq. Firstly, we examinedMYC andEGFR, two genes which are known to have high levels of H3K4Me3 in A549 cell. As shown in Figure 3(a), the degree of H3K4Me3 at these genes significantly decreases following treatment with JFK. To further characterize these changes, a genome-wide peak detection analysis was performed using the MACS program. Compared to control, the H3K4Me3 enrichment status at many TSSs in the JFK-treated cells was significantly altered (Table S1 in Supplementary Material available online at http://dx.doi.org/10.1155/2016/7276161). A heat map analysis of the top 2,000 genes showing altered levels of H3K4Me3 (P
<
0
.
05), including those exhibiting lower and greater levels of modification, identified promising candidates for further bioinformatic analysis (Figure 3(b)).Figure 3
Gene Ontology analysis of JFK-induced A549 cell H3K4Me3 modification altered genes. (a) ChIP tag density profiles of H3K4Me3 modification at TSSs onMYC andEGFR genes. Fold change ofMYC andEGFR H3K4Me3 modification status are detected by ChIP-qPCR (n
=
4, P
∗
∗
∗
<
0.001). (b) Heat map of top 2000 H3K4Me3 modification altered genes from upregulation and downregulation, respectively, in A549 cells with or without JFK treatment (P
<
0.05). (c) KEGG pathway analysis of upregulated and downregulated genes.
(a)
(b)
(c)


### 3.4. Gene Ontology Analysis of Genes with Altered H3K4Me3 Modification after JFK Treatment

We next analyzed the H3K4Me3 modification fold enrichment within 2,000 bp of TSSs between control- and JFK-treated A549 cells. We then identified the top 2,000 genes exhibiting altered levels of H3K4Me3 (P
<
0
.
05) for further GO analysis and KEGG pathway analysis. The top ten GO terms are presented in Table 3. These results suggest that treatment with JFK could downregulate H3K4Me3 modification levels at those genes involved in many pathways including ion transport, Wnt receptor signaling pathway, and positive regulation of transferase activity. By contrast, those genes with greater levels of H3K4Me3 following JFK treatment are involved in programmed cell death, induction of apoptosis, positive regulation of T cell activation, and so forth.Table 3
GO analysis of top 2000 downregulated genes and upregulated genes, respectively.
Category
Item
Count
P value
Downregulated
GO:0006811
Ion transport
112
2.02
E
-
05
GO:0016055
Wnt receptor signaling pathway
29
8.47
E
-
05
GO:0051347
Positive regulation of transferase activity
43
1.66
E
-
04
GO:0006350
Transcription
255
1.67
E
-
04
GO:0007242
Intracellular signaling cascade
162
2.22
E
-
04
GO:0051338
Regulation of transferase activity
59
2.88
E
-
04
GO:0033674
Positive regulation of kinase activity
41
2.95
E
-
04
GO:0043549
Regulation of kinase activity
57
3.12
E
-
04
GO:0045859
Regulation of protein kinase activity
55
4.21
E
-
04
GO:0045860
Positive regulation of protein kinase activity
39
5.70
E
-
04
Upregulated
GO:0012501
Programmed cell death
65
1.94
E
-
0
6
GO:0006917
Induction of apoptosis
39
3.86
E
-
0
6
GO:0050870
Positive regulation of T-cell activation
14
4.85
E
-
0
5
GO:0006915
Apoptosis
65
4.97
E
-
04
GO:0006631
Fatty acid metabolic process
27
5.34
E
-
04
GO:0012502
Induction of programmed cell death
39
5.74
E
-
04
GO:0031348
Negative regulation of defense response
9
8.36
E
-
04
GO:0052547
Regulation of peptidase activity
15
1
.
15
E
-
0
3
GO:0006793
Phosphorus metabolic process
97
1
.
3
8
E
-
0
3
GO:0006796
Phosphate metabolic process
97
1
.
72
E
-
0
3KEGG pathway analysis suggests that the downregulated genes are enriched in pathways involved in pathways in cancer, basal cell carcinoma, pyrimidine metabolism, and so forth, whereas the upregulated genes are enriched in those pathways involved in tryptophan, apoptosis, base excision repair, and so forth (Figure3(c)). Network analysis of the top 50 downregulated GO terms in the JFK-treated A549 cells identified key signal transduction networks affected. As shown in Figure 4(a), three prominent GO terms associated with the downregulated genes include regulation of transcription (DNA-templated), intracellular signal transduction, and regulation of MAPK cascade. For top 50 upregulated GO terms, regulation of peptidase activity plays an important role in the whole network which can interact with induction of programmed cell death and apoptotic process indirectly (Figure 4(b)). Thus, overall, this Gene Ontology analysis suggests that JFK-induced apoptosis could be attributed to alteration in the levels of H3K4Me3 modification in many tumor-related genes.Figure 4
Network analysis of upregulated and downregulated genes. (a, b) Parts of top 50 GO terms from downregulated and upregulated genes, respectively, have mutual effect between each other. Degree of red color represents theP value of GO terms (the lower P value, the more red).
(a)
(b)


### 3.5. JFK Induces H3K4Me3 Alteration in Specific Tumor-Related Genes in A549 Cells

To further understand the relationship between JFK-induced effects on A549 cell and changes in H3K4Me3 levels at tumor-related genes, we analyzed the modification changes at five survival-regulated genes (SUSD2, PTN, GLIS2, CCND2, andTM4SF4) and five apoptosis-regulated genes (BCL2A1, IL31RA, WISP2, TNFAIP6, andTMEM158). As shown in Figure 5(a), treatment of A549 cells with JFK for 48 h downregulated the H3K4Me3 modification levels atSUSD2, PTN, GLIS2, CCND2, andTM4SF4 genes, whereas those atBCL2A1, IL31RA, WISP2, TNFAIP6, andTMEM158 genes were upregulated compared to those genes in control. The ChIP tag density profiles also matched these fold change results (Figure 5(b)). We also performed ChIP-qPCR to validate these high-throughput findings, and all genes, exceptGLIS2, showed similar changes (Figure 5(c)).Figure 5
Analysis of H3K4Me3 pattern in the promoter regions of tumor-related genes after exposure to JFK. (a) Analysis of H3K4Me3 modification fold change in tumor-related genes based on ChIP-seq data. (b) ChIP tag density profiles of H3K4Me3 modification at TSSs on tumor-related genes. (c) Verification of H3K4Me3 modification altered genes using ChIP-qPCR (n
=
3).
(a)
(b)
(c)


### 3.6. Verification of JFK-Induced H3K4Me3 Alteration in Other Lung Cancer Cell Lines

The above results suggest that JFK-induced A549 cell apoptosis could be due to changes in the H3K4Me3 modification levels around the TSSs of some important genes. Therefore, we performed ChIP-qPCR to examine the H3K4Me3 modification status of genes mentioned in the previous section in NCI-H1975, NCI-H1650, and NCI-H2228 cells treated with JFK for 48 h. We found that the levels of H3K4Me3 modification atSUSD2 andCCND2 are significantly decreased and those atBCL2A1 andTMEM158 are markedly increased in each of these cell lines (Figures 6(a)–6(c)). Furthermore, an examination of the gene expression levels demonstrated that the levels of H3K4Me3 modification are indeed positively correlated with the levels of gene expression (Figures 6(d) and 6(e)).Figure 6
Analysis of JFK-induced H3K4Me3 pattern and mRNA levels alteration in human lung cancer cell lines. Cells were treated with JFK for 48 h and fold change of H3K4Me3 modification was detected by ChIP-qPCR (n
=
3). (a) NCI-H1975 cell line. (b) NCI-H1650 cell line. (c) NCI-H2228 cell line. Cells were treated with JFK for 48 h and the mRNA levels ofSUSD2,CCND2,BCL2A1, andTMEM158 were detected by RT-qPCR (n
=
3). (d) Fold change ofSUSD2 andCCND2 expression. (e) Fold change ofBCL2A1 andTMEM158 expression.
(a)
(b)
(c)
(d)
(e)


## 3.1. A549 Cell Viability and Cell Nucleus Morphology Are Changed after Incubation with JFK

The survival rate and changes to the nuclear morphology of A549 cells were monitored via a multimode reader and optical microscopy. We observed that cell viability decreases significantly after 24 h incubation with JFK drug serums obtained from day 7 and day 14 (Figure1(a)). In addition, time-dependent assays suggest that cell viability reduces significantly when A549 cells are exposed to the JFK serum from day 14 for incubation times longer than 24 h (Figure 1(b)). Thus, we chose a 48 h incubation time with JFK for all future experiments. Interestingly, nuclear staining with DAPI revealed alterations to the nuclear morphology in response to JFK. As shown in Figures 1(c) and 1(d), after the JFK treatment for 48 h, many nuclei were markedly larger compared to those in the control, indicating that these cells are in a state of abnormality.Figure 1
Treatment with JFK induces proliferation inhibition and nuclear morphology alteration in A549 cells. (a) A549 cells were treated with JFK drug serums from day 3, day 7, and day 14, respectively (n
=
3, P
∗
<
0.05). (b) A549 cells were treated with JFK drug serum from day 14 for 12 h, 24 h, 48 h, 72 h, 96 h, and 120 h, respectively (n
=
3, P
∗
<
0.05, P
∗
∗
<
0.01, and P
∗
∗
∗
<
0.001). (c, d) A549 cells were stained with DAPI for detecting nucleus changes using CLSM. Scale bar: 25 μm.
(a)
(b)
(c)
(d)


## 3.2. Proapoptotic Effects of JFK on A549 Cells

To further understand the effects of JFK on A549 cells, we examined the number of apoptotic cells by staining with PI and using fluorescence microscopy. As shown in Figure2(a), cells colored red, indicative of apoptosis, are found following treatment with JFK, suggesting that JFK could induce apoptosis in these cells. Flow cytometric analysis also showed a significant increase in JFK-induced apoptosis compared to a vehicle treatment control (Figure 2(b)). In particular, the total apoptosis rate calculated as Annexin and PI positive cells and the early apoptosis rate calculated as Annexin positive cells, respectively, by flow cytometry were significantly increased in A549 cells after JFK treatment, compared to those in vehicle treated A549 cells (Figure 2(c)).Figure 2
Treatment with JFK induces cell death and apoptosis in A549 cells. (a) A549 cells were stained with PI for detecting deathbed cells using fluorescence microscope. Scale bar: 50μm. (b) A549 cells were treated with JFK, and the apoptotic progression was determined by flow cytometry. (c) Total apoptosis and early apoptosis ratios were analyzed based on results of flow cytometry (n
=
3, P
∗
∗
∗
<
0.001).
(a)
(b)
(c)


## 3.3. JFK Induces an Alteration in the H3K4Me3 Pattern in A549 Cells

Previous studies have reported that the level of H3K4Me3 modification in TSSs is linked to transcriptional activation [3, 6]. To examine the alteration of H3K4Me3 modification upon exposing A549 cells to JFK, we performed genome-wide mapping of H3K4Me3 modification by ChIP-seq. Firstly, we examinedMYC andEGFR, two genes which are known to have high levels of H3K4Me3 in A549 cell. As shown in Figure 3(a), the degree of H3K4Me3 at these genes significantly decreases following treatment with JFK. To further characterize these changes, a genome-wide peak detection analysis was performed using the MACS program. Compared to control, the H3K4Me3 enrichment status at many TSSs in the JFK-treated cells was significantly altered (Table S1 in Supplementary Material available online at http://dx.doi.org/10.1155/2016/7276161). A heat map analysis of the top 2,000 genes showing altered levels of H3K4Me3 (P
<
0
.
05), including those exhibiting lower and greater levels of modification, identified promising candidates for further bioinformatic analysis (Figure 3(b)).Figure 3
Gene Ontology analysis of JFK-induced A549 cell H3K4Me3 modification altered genes. (a) ChIP tag density profiles of H3K4Me3 modification at TSSs onMYC andEGFR genes. Fold change ofMYC andEGFR H3K4Me3 modification status are detected by ChIP-qPCR (n
=
4, P
∗
∗
∗
<
0.001). (b) Heat map of top 2000 H3K4Me3 modification altered genes from upregulation and downregulation, respectively, in A549 cells with or without JFK treatment (P
<
0.05). (c) KEGG pathway analysis of upregulated and downregulated genes.
(a)
(b)
(c)


## 3.4. Gene Ontology Analysis of Genes with Altered H3K4Me3 Modification after JFK Treatment

We next analyzed the H3K4Me3 modification fold enrichment within 2,000 bp of TSSs between control- and JFK-treated A549 cells. We then identified the top 2,000 genes exhibiting altered levels of H3K4Me3 (P
<
0
.
05) for further GO analysis and KEGG pathway analysis. The top ten GO terms are presented in Table 3. These results suggest that treatment with JFK could downregulate H3K4Me3 modification levels at those genes involved in many pathways including ion transport, Wnt receptor signaling pathway, and positive regulation of transferase activity. By contrast, those genes with greater levels of H3K4Me3 following JFK treatment are involved in programmed cell death, induction of apoptosis, positive regulation of T cell activation, and so forth.Table 3
GO analysis of top 2000 downregulated genes and upregulated genes, respectively.
Category
Item
Count
P value
Downregulated
GO:0006811
Ion transport
112
2.02
E
-
05
GO:0016055
Wnt receptor signaling pathway
29
8.47
E
-
05
GO:0051347
Positive regulation of transferase activity
43
1.66
E
-
04
GO:0006350
Transcription
255
1.67
E
-
04
GO:0007242
Intracellular signaling cascade
162
2.22
E
-
04
GO:0051338
Regulation of transferase activity
59
2.88
E
-
04
GO:0033674
Positive regulation of kinase activity
41
2.95
E
-
04
GO:0043549
Regulation of kinase activity
57
3.12
E
-
04
GO:0045859
Regulation of protein kinase activity
55
4.21
E
-
04
GO:0045860
Positive regulation of protein kinase activity
39
5.70
E
-
04
Upregulated
GO:0012501
Programmed cell death
65
1.94
E
-
0
6
GO:0006917
Induction of apoptosis
39
3.86
E
-
0
6
GO:0050870
Positive regulation of T-cell activation
14
4.85
E
-
0
5
GO:0006915
Apoptosis
65
4.97
E
-
04
GO:0006631
Fatty acid metabolic process
27
5.34
E
-
04
GO:0012502
Induction of programmed cell death
39
5.74
E
-
04
GO:0031348
Negative regulation of defense response
9
8.36
E
-
04
GO:0052547
Regulation of peptidase activity
15
1
.
15
E
-
0
3
GO:0006793
Phosphorus metabolic process
97
1
.
3
8
E
-
0
3
GO:0006796
Phosphate metabolic process
97
1
.
72
E
-
0
3KEGG pathway analysis suggests that the downregulated genes are enriched in pathways involved in pathways in cancer, basal cell carcinoma, pyrimidine metabolism, and so forth, whereas the upregulated genes are enriched in those pathways involved in tryptophan, apoptosis, base excision repair, and so forth (Figure3(c)). Network analysis of the top 50 downregulated GO terms in the JFK-treated A549 cells identified key signal transduction networks affected. As shown in Figure 4(a), three prominent GO terms associated with the downregulated genes include regulation of transcription (DNA-templated), intracellular signal transduction, and regulation of MAPK cascade. For top 50 upregulated GO terms, regulation of peptidase activity plays an important role in the whole network which can interact with induction of programmed cell death and apoptotic process indirectly (Figure 4(b)). Thus, overall, this Gene Ontology analysis suggests that JFK-induced apoptosis could be attributed to alteration in the levels of H3K4Me3 modification in many tumor-related genes.Figure 4
Network analysis of upregulated and downregulated genes. (a, b) Parts of top 50 GO terms from downregulated and upregulated genes, respectively, have mutual effect between each other. Degree of red color represents theP value of GO terms (the lower P value, the more red).
(a)
(b)


## 3.5. JFK Induces H3K4Me3 Alteration in Specific Tumor-Related Genes in A549 Cells

To further understand the relationship between JFK-induced effects on A549 cell and changes in H3K4Me3 levels at tumor-related genes, we analyzed the modification changes at five survival-regulated genes (SUSD2, PTN, GLIS2, CCND2, andTM4SF4) and five apoptosis-regulated genes (BCL2A1, IL31RA, WISP2, TNFAIP6, andTMEM158). As shown in Figure 5(a), treatment of A549 cells with JFK for 48 h downregulated the H3K4Me3 modification levels atSUSD2, PTN, GLIS2, CCND2, andTM4SF4 genes, whereas those atBCL2A1, IL31RA, WISP2, TNFAIP6, andTMEM158 genes were upregulated compared to those genes in control. The ChIP tag density profiles also matched these fold change results (Figure 5(b)). We also performed ChIP-qPCR to validate these high-throughput findings, and all genes, exceptGLIS2, showed similar changes (Figure 5(c)).Figure 5
Analysis of H3K4Me3 pattern in the promoter regions of tumor-related genes after exposure to JFK. (a) Analysis of H3K4Me3 modification fold change in tumor-related genes based on ChIP-seq data. (b) ChIP tag density profiles of H3K4Me3 modification at TSSs on tumor-related genes. (c) Verification of H3K4Me3 modification altered genes using ChIP-qPCR (n
=
3).
(a)
(b)
(c)


## 3.6. Verification of JFK-Induced H3K4Me3 Alteration in Other Lung Cancer Cell Lines

The above results suggest that JFK-induced A549 cell apoptosis could be due to changes in the H3K4Me3 modification levels around the TSSs of some important genes. Therefore, we performed ChIP-qPCR to examine the H3K4Me3 modification status of genes mentioned in the previous section in NCI-H1975, NCI-H1650, and NCI-H2228 cells treated with JFK for 48 h. We found that the levels of H3K4Me3 modification atSUSD2 andCCND2 are significantly decreased and those atBCL2A1 andTMEM158 are markedly increased in each of these cell lines (Figures 6(a)–6(c)). Furthermore, an examination of the gene expression levels demonstrated that the levels of H3K4Me3 modification are indeed positively correlated with the levels of gene expression (Figures 6(d) and 6(e)).Figure 6
Analysis of JFK-induced H3K4Me3 pattern and mRNA levels alteration in human lung cancer cell lines. Cells were treated with JFK for 48 h and fold change of H3K4Me3 modification was detected by ChIP-qPCR (n
=
3). (a) NCI-H1975 cell line. (b) NCI-H1650 cell line. (c) NCI-H2228 cell line. Cells were treated with JFK for 48 h and the mRNA levels ofSUSD2,CCND2,BCL2A1, andTMEM158 were detected by RT-qPCR (n
=
3). (d) Fold change ofSUSD2 andCCND2 expression. (e) Fold change ofBCL2A1 andTMEM158 expression.
(a)
(b)
(c)
(d)
(e)


## 4. Discussion

The traditional Chinese medicine formula, JFK, had been used in clinical practice for treating human lung cancer patients for more than ten years [17]. Although the effectiveness of JFK has been well recognized by patients and physicians, the cellular and molecular mechanism remains unclear. Previous study demonstrated that JFK could modulate the expression of genes that are involved in the cell cycle and apoptosis [18]. Therefore, the objective of the present study was to understand the relationship between changes at the cellular level and changes in the degree of H3K4Me3 modification and attempt to identify interesting gene targets that could play an important role in JFK-induced lung cancer cell apoptosis.Previous studies have suggested that herbal formulas that suppress tumor growth and promote tumor cell apoptosis can be attributed to an inhibition of cell proliferation and activation of cell apoptosis [16, 26]. Due to the complicated composition of herbal formulas, serum pharmacology of Traditional Chinese Medicine has been developed to understand the mechanism of TCM [27, 28]. In this study, we examined the effects of JFK serums on cell growth and the cell nucleus in A549 cells. These results suggest that JFK lowered cell viability, inhibited cell growth, and altered cell nucleus morphology. Previous work has also demonstrated that tumor cells can be induced to death or apoptosis when they are exposed to formula extracts for fixed time [29, 30]. Our results suggest that many A549 cells are induced to death or apoptosis after exposure to JFK for 48 h. Since the levels of H3K4Me3 modification at promoter regions have been linked to disease development, therapy, and prognosis, we performed ChIP-qPCR assays to examine the levels of H3K4Me3 modification at two oncogenes (MYC andEGFR) in control- and JFK-treated A549 cells, respectively. Previous studies found that there is a significant enrichment of H3K4Me3 modification in the TSS regions ofMYC andEGFR genes in many tumor cells [31, 32]. Our results not only verified these earlier results in A549 cells, but also suggested that JFK can significantly reduce the levels of H3K4Me3 modification at these genes.H3K4Me3 is an active histone modification, which can positively regulate gene expression [3, 6]. Previous studies suggested that the levels of H3K4Me3 modification of many genes can be altered after exposure to exogenous chemicals or metals [33, 34]. Previous study revealed significant changes in gene expression and protein expression after JFK treatment [18]. However, the underlying epigenetic mechanism remained unclear. Here, we performed genome-wide mapping of H3K4Me3 deposition in the promoter regions within 2000 bp flanking the TSSs by ChIP-seq to enable characterization of the levels of H3K4Me3 modification at nearly all genes with or without JFK treatment in A549 cells. We found that the genes with altered H3K4Me3 modification induced by JFK are enriched in multiple signal pathways. Tumor proliferation and apoptosis related signal pathways are known as important targets for many antitumor drugs [30]. Here, Gene Ontology analysis indicated that JFK-induced A549 cell proliferation inhibition and apoptosis promotion could be due to the alteration of levels of H3K4Me3 modification on genes that belong to multiple tumor-related pathways including pathways in cancer, basal cell carcinoma, apoptosis, regulation of transcription (DNA-templated), and regulation of peptidase activity.Previous study has suggested thatSUSD2 interacts with galectin-1 (Gal-1), a 14 kDa secreted protein that is synthesized by carcinoma cells and promotes tumor immune evasion, angiogenesis, and metastasis [35].CCND2 is a cyclin whose function is to regulate the subunit ofCDK4 orCDK6 and whose activity is required for cell cycle G1/S transition [36]. We found that the JFK-induced cell proliferation arrest could be owing to a reduction in the levels of H3K4Me3 modification atSUSD2 andCCND2 in A549 cells.BCL2A1 is well-known antiapoptosis protein that converts into a proapoptotic protein when bound to NuBCP-9 [37].TMEM158 is a transmembrane protein that is upregulated in response to activation of the Ras pathway and has been proposed to be a tumor-suppressor gene and a target gene in the mutator pathway [38]. The present study suggests that the increase in the H3K4Me3 modification levels following JFK treatment atBCL2A1 andTMEM158 could explain JFK-induced A549 cell apoptosis. We note that, for other important genes, the significant changes in H3K4Me3 modification observed in A549 cells after exposure to JFK for 48 h are not also found in NCI-H1975, NCI-H1650, and NCI-H2228 cell lines.Taken together, this work presents the first report of JFK inducing proliferation inhibition and the promotion of apoptosis in A549 cells through a possible epigenetic mechanism and shows that JFK significantly altered the H3K4Me3 histone modification levels at many genes that play critical roles in tumor survival related pathways. In particular,SUSD2, CCND2, BCL2A1, andTMEM158 could be potential targets of JFK in human lung cancers. Further studies are needed to assess the mechanism by which the changes in the levels of H3K4Me3 modification at these genes lead to changes in gene or protein expression and eventually understand the utility of epigenetically altered genes as drug targets in the treatment of human lung cancers.



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*Source: 7276161-2016-03-20.xml*