Thioguanine Induces Apoptosis in Triple-Negative Breast Cancer by Regulating PI3K–AKT Pathway

Triple-negative breast cancer (TNBC) is notoriously difficult to treat due to the lack of biological targets and poor sensitivity to conventional therapies. Chemotherapy is the main clinical therapy, but the effective screening strategy for chemotherapy drugs is poorly investigated. Drug repositioning has been the center of attention in recent years attracting numerous studies. Here, we firstly found multiple common features between leukemia and TNBC by analyzing the global transcriptome profiles based on the transformed comparison data from NCI60. Therefore, we investigated the role of the classic leukemia drug thioguanine (6-TG) in TNBC cancer cells. Our results indicated that 6-TG inhibited cell proliferation and tumor cell progression by suppressing PI3K–AKT pathway via downregulating the DNA methylation level of PTEN. Moreover, apoptosis was induced via the activation of PI3K-AKT downstream TSC1 and the downregulation of methylation levels of DAXX, TNF, FADD and CASP8 etc. These findings indicated 6-TG exerts its anti-tumor effects in vitro and in vivo through regulating the DNA methylation levels of genes involved in PI3K–AKT and apoptosis pathway. Meanwhile, our study suggested that transcriptome-based drug screening has potential implications for breast cancer therapy and drug selection.


INTRODUCTION
TNBC is a breast cancer subtype that does not clinically express significant levels of the estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), representing only 15-20% of breast cancer cases (1)(2)(3). However, TNBC is the most aggressive breast cancer type without any approved targeted therapy (4,5). Currently, chemotherapies are the only therapeutic treatment for TNBC. Therefore, drug repurposing and repositioning have attracted increasing attention in recent years (6,7), such as thalidomide, a drug for morning sickness but currently is used for the treatment of multiple myeloma (8). Therefore, exploration of effective drug selection strategy for TNBC has become increasingly important. Recent studies have attempted to find the tumor pathogenesis through high throughput sequencing, but the integration of transcriptome maps of various tumors for drug discovery remains slow.
Recently, it is widely accepted that human oncovirus can induce malignant tumors after a long latency and in conjunction with environmental factors. Over 30 years ago, human T-cell leukemia virus type 1 (HTLV-1) was identified as the first human cancer-causing retrovirus (9). Since then, a variety of tumorassociated viruses have been discovered, including Epstein-Barr virus (10), classified as Class I carcinogen by the International Agency for Research on Cancer (IARC) (11,12), human papillomavirus (HPV), mouse breast cancer virus-like virus (MMTV-like). These viruses are involved in several different lymphoid and epithelial malignancies, including Burkitt's lymphoma (BL), Hodgkin's disease, non-Hodgkin's lymphoma, nasopharyngeal, gastric cancer, and breast cancer. Recent publications have shown that EBV, human papillomavirus (HPV), mouse breast oncovirus-like virus (MMTV-like), and polyamorous JCV can serve as cofactors in the oncogenic process in breast cancer and increase the aggressiveness of the disease (13). Therefore, we predicted that the occurrence of TNBC was probably related to oncovirus infection, based on its pathogenetic similarity to that of leukemia/lymphoma.
High-throughput sequencing technology has been considered as a promising and effective tool in discovering meaningful genetic and epigenetic variations during cancer development and identifying biomarkers for cancer diagnosis or prognosis (14). To date, less efforts have attempted to explore pathogenic mechanisms by comparing the transcriptional characteristics between breast cancer and other cancers. Here, we analyzed transcriptome profiles between breast cancer and leukemia/lymphoma and identified similar expression profiles in some pathways including PI3K-AKT pathway and viral infection pathways, which might imply the potential application of leukemia/lymphoma chemotherapeutics in TNBC treatment. Therefore, this study was aimed to evaluate the anti-tumor effect of the classic leukemia drug 6-TG on TNBC in vitro and in vivo and to elucidate the underlying mechanism(s). Our results will provide novel therapeutic options to TNBC patients.

Cells and Chemicals
The human TNBC cell line MDA-MB-231 was obtained from Northeast Forestry University; MDA-MB-231-Luciferase was purchased from ORIGENE (Beijing, China); normal breast epithelial cell line MCF-10A and human TNBC cell line HCC1937 were purchased from Procell (Wuhan, China). TNBC cells were cultured in RPMI 1640 medium (Gibco, Grand Island, USA) supplemented with 10% fetal calf serum, 100 IU/ml of penicillin and 100 mg/ml of streptomycin (HyClone, Los Angeles, USA) and MCF-10A Cell Culture Medium (Procell, Wuhan, China). The cells were cultured in a humid environment with 5% CO2 at 37°C. All human cell lines have been authenticated using STR profiling within the last three years. All experiments were performed with mycoplasmafree cells.

Proliferation Assay
Cells were treated with different concentrations of 6-TG (or CX-6258 HCl, or MI-463) then were subjected to the Cell Counting Kit-8 assay according to the manufacturer's protocol (DOjinDO, JAPAN). Briefly, 6.5 × 10 3 cells were seeded per well in a 96-well plate and treated with 6-TG at indicated concentration. Thereafter, CCK-8 solution was added, and the Absorbance (A) was measured using a microplate reader (BIO-RAD, California, USA) at 450 nm. IC50 values were calculated using GraphPad Prism 6.01 software. IC20 values were calculated using SPSS Statistics.

Colony Formation Assay
Four hundred cells per well were randomly plated in 6-well plates and were cultured in vehicle (control) or 6-TG (or CX-6258 HCl, or MI-463) containing medium. Triplicate wells were used for each group. The cells were cultured for 8-9 days until the cells grew up to 50 cells, which was considered as one colony. Then cells were stained with Giemsa and counting (SIGMA, Illinois, USA).

Migration Assay
Cells were seeded in 12-well plates and grew to confluence, followed by wound creation. Then cells were incubated with 6-TG or vehicle. Cell migration images were collected every 6 h until 24 h. Triplicate wells were used for each group. The migration rate was calculated using ImageJ software.

Apoptosis Assay
Cells were stained using the TransDetectTM Annexin V-EGFP/ PI Cell Apoptosis Detection Kit (TRAN, Beijing, China). Briefly, 2 × 10 5 cells were seeded in each well and treated with 2.5 mM 6-TG (or 3.9 mM CX-6258 HCl, or 13.9 mM MI-463) or vehicle. The cells were collected, followed by the addition of Annexin-V-FITC or propidium iodide (PI) or both of them to the cell suspension, then incubated for 15 min. The stained samples were analyzed by flow cytometry using a FACSCalibur flow cytometer (BD FACSCanto II, New Jersey, USA), and FlowJo VX was used to analyze the data.

Immunofluorescence Assay
Cells treated with 6-TG or vehicle were fixed and permeabilized with 0.1% Triton X-100 in PBS and were blocked with 1% bovine serum albumin, followed by incubation with the DNMT1 antibody (Genetex, Southern California, USA) overnight. Next, the cells were stained with secondary antibody (Proteintech, Chicago, USA), followed by staining with 4,6-diamidino-2phenylindole to visualize the nuclei. The analysis of fluorescence intensity was analyzed using ImageJ software (National Institutes of Health, Bethesda, MD) based on procedures described elsewhere (15,16).

RT2 Profiler PCR Array
RNA was isolated from about 2 × 10 7 cells using the ALLPrep DNA/RNA Mini Kit (QIAGEN, Germany), and cDNA was synthesized using the Transcript one-step gDNA Removal and cDNA Synthesis SuperMix. qPCR was performed using SYBR premix Ex Taq (Takara, Japan) on a LightCyclerR 96 Real-Time PCR System (17). The Human PI3K-AKT RT2 and Human Apoptosis RT2 profiler PCR arrays were performed according to the manufacturer's instructions. Primers sequences are listed in Table S1 and Table S2.

RNA Preparation and RNA-Seq
Total RNA was extracted with TRIzol (Invitrogen, California, USA) reagent following the manufacturer's instructions. The insert size was assessed using the Agilent Bioanalyzer 2100 system, and qualified insert sizes were accurately quantified using the StepOnePlus ™ Real-Time PCR System (Library valid concentration >10 nM). Sequencing libraries were generated using the NEBNext ® Ultra ™ RNA Library Prep Kit for Illumina ® (USA, NEB) following the manufacturer's recommendations, and index codes were added to attribute sequences to each sample (GEO number: GSE137418).

DNA Methylation Detection
DNA was isolated from 10 7 cells using the DNeasy Blood and Tissue Kit (QIAGEN, Germany). Approximately, 500 ng of genomic DNA from each sample was used for sodium bisulfite conversion using the EZ DNA methylation Gold Kit (Zymo Research, USA) following the manufacturer's standard protocol. Genome-wide DNA methylation was assessed using the Illumina Infinium HumanMethylation850K BeadChip (Illumina Inc., USA) according to the manufacturer's instructions. The array data (IDAT files) were analyzed using the ChAMP package in R to derive the methylation level.

Tumor Cell Inoculation and Injections
NOD-SCID mice (3-4 weeks) were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. Next, 1 × 10 6 exponentially growing MDA-MB-231 cells with luciferaselabeled (MDA-MB-231-Luc) were injected subcutaneously into the left groin of each NOD-SCID mouse, five mice each group. Tumor-bearing mice were injected with 1.5 mg/kg of 6-TG or solvent five times a week, 20 mg/kg Docetaxel once a week after tumors were inoculated for 7 days. When the tumors became palpable, a digital caliper was used to measure the tumor size every two days. Additionally, the tumor fluorescence intensity was detected with IVIS ® Lumina III (PerkinElmer, USA) weekly. Tumor volumes (Vs) were calculated as ellipsoids (V = p/6 · l ·w 2 , where l is the length, w is the width). Experiments ended when the tumor volumes reached approximately 1.5 cm 3 or earlier if necrotic. The mice were killed by CO 2 asphyxiation. All mice were raised in a specific pathogen-free environment with free access to food and water and received care in accordance with the guidelines outlined in the Guide for the Care and Use of Laboratory Animals. All procedures were approved by the Jilin University Animal Care and Use Committee.

HE Staining and Immunohistochemistry Staining
Allograft tumors and the livers and kidneys were dissected and fixed in 10% (v/v) neutral-buffer formalin. They were then dehydrated in ascending grades of ethanol and xylene and embedded in paraffin wax. Thereafter, the sections (4 mm) were cut with a microtome (Leica, Germany). Anti-DNMT1 antibody, anti-caspase-3 antibody and goat anti-rabbit antibody IgG (BOSTER, Wuhan, China) were used for immunostaining. For HE staining, after deparaffinization and rehydration, 4-mm sections were stained with hematoxylin solution for 5 min followed by 5 dips in 1% acid ethanol and then rinsing in water. Next, the sections were stained with eosin solution for 3 min, followed by dehydration with graded alcohol and clearing in xylene.

Statistical Analysis
Different statistical tools were used to analyze the data. The experiments were repeated at least two times in triplicate. In the graphs, the results are presented as mean ± SEM. Statistical analysis was performed using GraphPad Prism 6.01 (GraphPad Software, USA). Student's t-test was used to compare the control and experimental groups. For all comparisons, *p < 0.05, **p < 0.01, and ***p < 0.001 were considered to show a significant difference.

Data Availability
The data of RNA-seq was uploaded on GEO, the number is GSE137418. Other data is available from the corresponding author upon reasonable request.

Analysis of Pathogenic Molecular Pathways Between Breast Cancer and Leukemia
To explore the potential correlation between breast cancer and leukemia, we analyzed the global transcriptome profiles based on the transformed comparison data from NCI60. As shown in Figure 1A, the genes in Cluster C are shared by TNBC and lymphoma (SR: large-cell immunoblastic lymphoma). These 184 genes are mainly involved in cell adhesion molecules, human Tcell leukemia virus 1 infection, herpes simplex infection, and Epstein-Barr virus infection. Cluster B is a TNBC-specific

Signaling Pathways Altered by 6-TG Treatment in MDA-MB-231 Cells
To explore the underlying mechanisms that 6-TG could inhibit TNBC cell growth, we carried out RNA-seq study using the samples treated with or without 2.5 mM 6-TG in MDA-MB-231. The heatmap showed obvious changes in gene expression profile between the two groups ( Figure 2A) with 2,166 upregulated genes and 1,550 downregulated genes in response to 6-TG treatment. The downregulated genes were mainly involved in focal adhesion, proteoglycans in cancer, and PI3K-AKT signaling pathway ( Figure 2B). We structured a network of these genes and found that the PI3K-AKT pathway contained the most genes shared with others ( Figure 2C). Additionally, the virus infection pathways were almost completely inhibited by 6-TG ( Figure S2). The pathways related to mismatch repair, DNA replication, and proteasome displayed higher gene ratios in the upregulated genes, while pathways involved in cell apoptosis showed the highest degree of gene enrichment ( Figure 2D). These results suggested that 6-TG exerted anti-tumor activity by downregulating the genes in virus infection pathways, cancer development pathways and upregulating the genes in mismatch repair and apoptosis. It is worthy of attention that the PI3K-AKT pathway, which was abnormally highly activated in TNBC, was inhibited by 6-TG.

PI3K-AKT Pathway Was Attenuated by 6-TG Treatment in MDA-MB-231 Cells
Based on the results of RNA-seq, the expression profile of members in the PI3K-AKT pathway was investigated by qPCR array. The expression of 53 genes was upregulated, and 31 genes were downregulated ( Figure S3). The pathway enrichment of upregulated genes analyzed by FunRich showed that the genes were mainly involved in p75 mediated signaling (46.8%) ( Figure  3A). However, the downregulated genes were mainly involved in PI3K signaling events (83.3%) and EGF receptor signaling pathway (83.3%) ( Figure 3B). The top 10 upregulated DEGs were PTEN, TSC1, BAD, JUN, CASP9, EIF2AK2, EIF4EBP1, TOLLIP ( Figure 3C), while the top 10 downregulated DEGs were ITGB1, PTK2, CCND1, PAK1, PDK1, PRKLA, RASA1 ( Figure 3D). We used Western blotting analysis to confirm that p-AKT (T308) was significantly decreased by 6-TG treatment ( Figure 3E). These results suggested that 6-TG blocked the PI3K-AKT pathway by activating PTEN, and the activation of downstream genes such as BAD, CASP9, TSC1 also supported these data. More importantly, the upregulation of tumor suppressor genes in the PI3K-AKT pathway such as TSC1, CASP9, and PTEN indicates a possible role of 6-TG in promoting apoptotic signaling pathways.

Apoptosis Was Induced by 6-TG in MDA-MB-231 Cells
To further investigate whether 6-TG inhibits TNBC cell growth via triggering apoptosis signaling, we assessed apoptotic cell death by Annexin V/PI staining ( Figure 4A). The ratios of apoptotic cells were 7.02% in the control group and 15.72% in the 6-TG groups, respectively, indicating 6-TG treatment led to a significant increase of apoptosis (P < 0.001). To explore the underlying molecular basis of effects of 6-TG on cell apoptosis, we carried out apoptosis PCR array, and discovered 67 upregulated genes and 17 downregulated genes ( Figure S4-A). The upregulated genes were mainly involved in TRAIL signaling pathway (90.7%) and FAS signaling pathway (48.8%) ( Figure  4B), while the majority of downregulated genes were related to TRAIL signaling pathway (80%), TNF signaling pathway (46.7%) ( Figure 4C). Results in Figure S4-B and Figure S4-C displayed the top 20 upregulated or eight downregulated DEGs, respectively. Moreover, the genes in the extrinsic apoptosis pathways were significantly increased than those related to intrinsic apoptosis pathways ( Figure 4D). Meanwhile, the results of the antibody array for apoptosis showed that proteins related to apoptosis were increased after 6-TG treatment ( Figure 4E). The top 10 upregulated proteins with the highest fold-change were P53, Cytochrome c, FADD, Fas etc. ( Figure 4F). These results indicated that 6-TG induced cell apoptosis, mainly through regulating TRAIL signaling.

Decreased DNA Methylation in Apoptosis-Related Genes in MDA-MB-231 Cells
Given the causal relationship between DNMT1, DNA methylation, and 6-TG, we interrogated the role of 6-TG in regulating the DNA methylation level of apoptosis-related genes A B D C October 2020 | Volume 10 | Article 524922 mentioned above. Immunofluorescence (IF) staining showed that the DNMT1 protein level in the 6-TG group (13.62 ± 0.3347) was lower than that in the control group (21.32 ± 0.2879) ( Figure 5A), which is consistent with the result tested by western blotting analysis indicating a reduced protein level of DNMT1 upon 6-TG treatment ( Figure 5B) (P < 0.001). Furthermore, the methylation differences were also measured by Illumina's Methylation EPIC850K BeadChip. The volcano plot showed 2,242 and 6,084 genes with down-or upregulated methylation levels, respectively (FC > 2; P < 0.01) ( Figure S5). The DNA methylation level of PTEN was decreased; meanwhile, the DNA methylation levels of BAD, CASP9, TSC1, TNF, DAXX, FADD, TRADD, CASP8 and FAS were all reduced by 6-TG treatment ( Figure 5C). Moreover, the genes with downregulated DNA methylation were mainly enriched in TRAIL, FAS, and extrinsic signaling pathways ( Figure 5D). These results proved 6-TG regulating the DNA methylation levels of apoptosis-related genes mentioned in Figure 3C and Figure 4D. To illustrate the link between apoptosis-related genes and genes involved in the PI3K-AKT pathway, we constructed a main effective network of these genes and discovered an interaction between them ( Figure  5E). We further detected the survival curves of the CpG sites of these genes ( Figure 5F). The plots showed that the survival of breast cancer patients with reduced methylation of TSC1 (cg14350545), FADD (cg02794589), and TRADD (cg05178604) was significantly improved. These results altogether showed that the reduced methylation of PTEN which would active PTEN will inhibit PI3K-AKT pathway and activated BAD, CASP9, TSC1 via interaction between them (18). Moreover, the reduced DNA methylation levels of these apoptosis promoting genes will activate them and subsequently induce apoptosis.

6-TG Treatment Retarded Tumor Growth In Vivo
To further investigating the negative regulation of 6-TG on tumor cell growth, we performed the xenograft experiment in vivo. Docetaxel was used as a positive control. As shown in Figures 6A, B, 6-TG treatment significantly retarded the growth of tumor xenografts in mouse models, and its effect was similar to that of docetaxel (***p < 0.001). Meanwhile, the fluorescence signal intensities were weaker, and the fluorescence area sizes were smaller in the 6-TG group than that in the control group from day 20 after inoculation to the last detection ( Figure S6). Consistently, the tumor weights were significantly reduced after 6-TG treatment (***p < 0.001) ( Figure 6C, and 6-TG had no significant effect on body weight of the animals during the treatment ( Figure 6D). Hematoxylin-eosin (HE) staining showed several pathological mitotic events in the control group but not in the 6-TG group ( Figure 6E), which further confirmed that tumor growth was inhibited. To further investigate the underlying mechanisms, immunohistochemistry staining was performed; the DNMT1 expression reduced, and caspase-3 expression increased in 6-TG treated tumors ( Figure 6F). Furthermore, the HE staining of livers and kidneys of tumor bearing mice showed no significant difference between control group and 6-TG group. Specifically, the structures of the central vein (red arrows), hepatic plate, and hepatic sinusoid of livers, and cortex, medulla, renal corpuscle (black arrows), proximal convoluted tubule (black boxes) of the kidney were clear, suggesting that 6-TG have no side-effects on mice under the way we treat it ( Figure 6G). These results coherently indicated that 6-TG treatment could retard tumor growth in vivo through downregulation of the DNMT1 which could increase the DNA methylation of tumor promoting genes.

Apoptosis Was Induced by CX-6258 HCl and MI-463 in MDA-MB-231 Cells
Furthermore, CX-6258 HCl and MI-463, which are also used to treat leukemia, were selected stochastically to evaluate their effect on TNBC cells. As shown in Figures 7A, B, the IC50 of CX-6258 HCl and MI-463 showed low concentration of IC50 (3.9 and 13.99 mM, respectively) in MDA-MB-231 cells. We observed that, in comparison with the control (vehicle), CX-6258 HCl and MI-463 treatment led to significant inhibition of colony formation ( Figures 7C, D). In contrast, flow cytometry assay showed that CX-6258 HCl and MI-463 treatment led to a marked increase of apoptotic cells (Figures 7E-F). Altogether, these data suggested that both CX-6258 HCl and MI-463 could efficiently inhibit cell proliferation and induce cell apoptosis in MDA-MB-231.

DISCUSSION
Over the past decade, advances in next-generation sequencing technology have greatly promoted the blowout growth of multiomics data derived from various tumors. Researchers have attempted to investigate the pathogenesis of cancer using different tools including genomic DNA copy number arrays, DNA methylation, mRNA arrays, and microRNA sequencing (19,20). Perou et al. synthetically analyzed the comprehensive molecular characterization of breast cancer and suggested that the PI3K and RAS-RAF-MEK pathways were amplified in this malignancy (21). Additionally, some controversial studies focused on the effect of viral infections on breast cancer development (22,23). In our study, when we integrated the transcriptome map from leukemia and breast cancer cell lines, we found that besides the PI3K pathway, other pathways, including those involving proteoglycans in cancer, focal adhesion, and human papillomavirus infection were abnormally activated in TNBC. Many pathways, such as T-cell leukemia virus 1 infection, Herpes simplex infection, and Epstein-Barr virus infection, were elevated and enriched in TNBC than in other breast cancer types and lymphomas. Therefore, we speculated that TNBC was likely a cancer type with high expression levels of PI3K-AKT, proteoglycans in cancer, focal adhesion pathway, as well as a cancer type caused by virus (HTLV, HPV and EBV) infection similar to leukemia/ lymphoma. Based on these findings, we proposed that leukemia drugs could have potential therapeutic effects on TNBC.
To verify our proposal, we chose 6-TG as a candidate drug to investigate its therapeutic role in TNBC. 6-TG is a classic   (26), and low concentrations of 6-TG could inhibit cell growth. However, the underlying mechanism of 6-TG to suppress cancer cell growth and trigger apoptosis was unclear.
It was well studied that PTEN acts as a negative regulator of PI3K signaling and subsequent AKT activation (27,28). However, we did not find any research indicating that 6-TG has a function on tumor suppressor genes PTEN and TSC1. Interestingly, our results showed that 6-TG inhibited PI3K-AKT pathway via activating PTEN. Previous study showed Akt played a critical role in regulating Bad, Bcl-2, Cyto-c, Apaf-1, CASP9, and caspase-3 (18). In line with this, we found that inhibition of PI3K-AKT led to an increased expression of BAD, TSC1, and CASP9 ( Figure 3C). Consistently with other reports, we also observed that the expression of JUN was increased which might be caused by cellular stress (29,30). Meanwhile, the finding that apoptosis-related genes including TNF, DAXX, FADD, TNFRSF10B, CASP8, FADD, TRAIL, and TRADD were all activated, indicated that 6-TG could induce cell apoptosis through extrinsic apoptosis pathways (activated by death receptors). Here our data indicated that 6-TG exhibited remarkable ability in inhibiting the highly activated oncogene  pathways, inducing cell death and activating tumor suppressor genes in MDA-MB-231 cells. Furthermore, the effect of other two leukemia drugs on MDA-MB-231 cell growth was also tested. Consistently, both of them induced cell apoptosis and retarded cell growth in low concentrations, which suggested that our proposal might be reasonable. Although the underlying mechanisms of these two drugs inducing apoptosis need further investigation. 6-TG can facilitate the proteasome-mediated degradation of DNMT1 and reactivate epigenetically silenced genes in acute lymphoblastic leukemia cells (31). Therefore, we speculated that 6-TG might induce apoptosis by reducing DNA methylation in MDA-MB-231 cells. Maintenance of genomic methylation patterns is mediated primarily by DNMT1 (32). Su et al. showed that the epithelial-mesenchymal transition (EMT) could be inhibited by DNA methyltransferase inhibitors (5-azacytidine, decitabine, guadecitabine/SGI-110) in TNBC (33). Our previous findings also suggested that changes in the methylation levels could affect the EMT pathway in MDA-MB-231 cells (34). However, no analysis related to apoptosis and DNA methylation triggered by 6-TG in TNBC was reported. According to relevant research, CASP8 and CASP10 were both recruited to Fas by interacting with FADD, whereas DAXX binds directly to Fas, initiating a death pathway independent of FADD, which can enhance Fas-induced apoptosis by activating the JNK kinase cascade (35,36). However, few studies reported the DNA methylation of these genes in TNBC. In fact, our results indicated the DNA methylation levels of tumor suppressor genes such as PTEN, TSC1 and apoptosis-related genes such as FADD, BAD, DAXX were downregulated by 6-TG ( Figure 5C). Importantly, when we focused on the pathway enrichment of downregulated genes, we found that they were enriched in TRAIL, FAS, and apoptosis pathways. This suggests that the mechanism underlying 6-TG activity in MDA-MB-231 was the regulation of DNA methylation in tumor suppressor genes and apoptosisrelated genes. Based on these findings, we further found that the downregulation of DNA methylation of three CpG sites, TSC1 (cg14350545), FADD (cg02794589), and TRADD (cg05178604) could significantly prolong the survival of breast cancer patients (DNA methylation survival curves in the TCGA). Therefore, the downregulation in DNA methylation of negative regulators of PI3K-AKT pathway PTEN explained why the abnormally activated pathways were inhibited. Meanwhile, 6-TG downregulated the DNA methylation levels of genes in the TRAIL and Fas pathways such as DAXX and CASP8 through inhibiting the expression of DNMT1, subsequently inducing extrinsic apoptosis.
Altogether, our results demonstrate that 6-TG can markedly inhibit MDA-MB-231 cell growth, induce apoptosis through reactivating methylation-silenced genes in the apoptosis pathway and PI3K-AKT signaling pathways via blocking DNMT1 activity. Our data suggested a new strategy for detecting potential TNBC therapeutic drugs using bioinformatics analysis.

DATA AVAILABILITY STATEMENT
The datasets generated for this study can be found in the GEO number: GSE137418.

ETHICS STATEMENT
The animal study was reviewed and approved by Jilin University Animal Care and Use Committee.

AUTHOR CONTRIBUTIONS
DZ: formal analysis, investigation, resources, data curation, writing (original draft, review, and editing), and visualization. XA: formal analysis, resources and writing (original draft and review),. QL: investigation, data curation. XM, MC, and HL: data checking, statistical analysis and investigation. NZ and XD: investigation, writing (review). HY: conceptualization, methodology, data analysis, writing (original draft and review). ZL: conceptualization, methodology, formal analysis, data