Introduction

As the most common malignant tumor, breast cancer (BC) ranks as the leading cause of cancer-specific death among women worldwide1. Treatments based on molecular subtypes of BC have achieved hopeful results and the prognosis has been significantly improved to some extent2. However, the challenges of high rate in the recurrence and mortality are still exist. Inactivation of tumor suppressor genes by DNA methylation is frequently happened in human cancers. There is increasing evidence revealing an important association between methylated-associated tumor suppressor and malignant tumors3. Therefore, there is an urgent necessity to find effective therapeutic targets for BC from epigenetics direction.

cAMP is an important intracellular signaling regulator. In mammals, it is produced through ATP by nine membrane-bound adenylate cyclases (ACs) and one soluble AC4. cAMP signaling is closely related to the tumor depending on PKA or independent pathways. Targeted therapy against cAMP has shown a variety of anticancer effects, including conversion of mesenchymal cells into epithelial cells, inhibition of migration and cell growth, and enhancement of tumor cell sensitivity to antitumor drugs5,6,7. Because of their extensive expression and critical role in many biological processes, ACs have been excluded as a target for drug development due to potential serious adverse effects. However, knockdown and transgenic in vivo models of ACs have revealed significantly different biological functions. ACs are currently investigated as potential drug targets for neuropathic diseases, heart failure, bronchial asthma, and some compounds have entered clinical application8. It is noteworthy that the different AC isoforms can result in completely different cell signals, making them the pivotal enzymes in signal transduction. The cAMP signaling pathway is determined by its precise temporal and spatial changes, and the local increase in cAMP caused by a specific AC can selectively regulate related proteins4. There is a lack of evidence on the biological function of ACs in malignant tumors, and the molecular mechanism of AC isoforms in human tumorigenesis and progression needs to be explored. Although targeting agents for selective AC are still in initial development, AC-selective agents have many advantages in adverse effect control. Therefore, ACs may finally be considered an important therapeutic target.

In our previous study, bioinformatics analysis of different AC isoforms in human tumors revealed that adenylyl cyclase 4 (ADCY4) expression in BC was significantly downregulated and its promoter was methylated, which was significantly related to poor prognosis in BC patients. ADCY4 was found to be related with G protein-linked receptors and cAMP signaling9. All results show that ADCY4 plays a significant role in BC development. Further studies are urgently needed to uncover the biological role and molecular mechanism of ADCY4 in BC, as well as its potency as an epigenetic therapeutic target. This study reports on the role of ADCY4 in breast tumorigenesis via control of cAMP and downstream FAK/AKT and ERK signaling axis.

Materials and methods

Tissue samples, cell lines and lentivirus infection

Primary BC and corresponding tissues were obtained from Department of Endocrine and Breast Surgery, First Affiliated Hospital of Chongqing Medical University, China, and authenticated by pathologist. Patients’ informed consent was written and associated clinicopathological parameters were obtained. Institute Ethics Committee of First Affiliated Hospital of Chongqing Medical University approved this study, according to the Declaration of Helsinki. Eight cell lines were used in this work, including BT549, MDA-MB-231, MDA-MB-468, YCCB1, SK-BR-3, MCF-7, T47D, and ZR-75-110, were from the ATCC (American Type Culture Collection, Manassas, VA, USA) or collaborators. All cell lines were cultured in RPMI-1640 or DMEM (Hyclone, Utah, USA), added with 10% fetal bovine serum (FBS: Hyclone), and cultivated at 37 °C with 5% CO2. EX-T4852-Lv201 ADCY4 vectors were produced by pEZ-Lv201 (Genecopoeia, Rockville, USA). The lentivirus particles were generated by corresponding vectors with packaging plasmids in HEK 293T cells. Filtered supernatants including ADCY4 lentivirus were used to infect MDA-MB-231, MCF-7, and SK-BR-3 cells. 2 µg/mL puromycin (Abcam, Cambridge, UK) was applied to screening ADCY4 stably expressing cell lines for further research. The mRNA and protein expression of ADCY4 were also identified.

The extraction of DNA and RNA

Total DNA was isolated from BC cells and tissue specimens by QIAamp DNA Mini Kit (Qiagen, Duesseldorf, Germany) according to the operation manual11. Total RNA was extracted by TRIzol reagent (Invitrogen, Carlsbad, USA)11 and Animal Total RNA lsolation Kit (Foregene, Chengdu, China). The concentrations and qualities of DNA and RNA were tested by NanoDrop® 2000 spectrophotometry (Thermo, Waltham, USA).

Semi-quantitative reverse transcription (RT)-PCR

cDNA was synthesized by RNA using a Reverse Transcription System (Promega, Madison, USA)12. Semi-quantitative RT-PCR was executed using Go-Taq DNA polymerase (Promega) as previously described12. Amplified PCR products were 32 cycles for ADCY4 and 23 cycles for β-actin, and were assayed on 2% agarose gels. These PCR samples were subsequently visualized by ChemiDoc MP system (Bio-Rad Laboratories, Hercules, USA).

RT-quantitative PCR (RT-qPCR)

To quantitatively estimate mRNA expression, cDNA was synthesized from cell lines and tissues using Hifair® II 1st Strand cDNA Synthesis SuperMix (Yeasen, Shanghai, China) and PrimeScript RT reagent Kit (Takara, Osaka, Japan), respectively. Hieff® qPCR SYBR Green Master Mix (Yeasen) and TB Green™ Premix Ex Taq™ II (Tli RNaseH Plus) (Takara) were utilized for RT-qPCR according to the operation manuals, which were performed using ABI QuantStudio™ 12 K Flexa (Applied Biosystems, Thermo) and PIKOReal 96 (Thermo) real-time quantitative PCR instrument. Relative mRNA transcript of ADCY4 was evaluated using the 2−ΔΔCq method13.

Immunohistochemistry (IHC) and Immunofluorescence (IF) assay

To investigate the protein level of ADCY4 in BC tissues, 10 paired specimens were formalin-fixed, paraffin-embedded and sliced. In the IHC assay, slides were deparaffinized with xylene for 20 min, and were rehydrated for 5 min with a graded ethanol series. Antigen retrieval was processed by microwaving the slides for about 20 min with a gradient heating in ethylene diamine tetraacetic acid (EDTA). Primary antibody against ADCY4 (Cat. no. DF3507; 1:100; Affinity Biosciences, Cincinnati, USA) was used and incubated overnight. Next, the slides were incubated with HRP labeled secondary antibody (HRP-conjugated Affinipure Goat Anti-Rabbit IgG (Cat. no. SA00001-2; 1:1,000; Proteintech)). Signals were visualized after 5–10 min chromogenic reaction with diaminobenzidine (DAB), and the slides were redyed with hematoxylin. IHC scores were defined by staining intensity (0: negative; 1: weak; 2: moderate; 3: strong) and positive cells ratio (0: <5%; 1: 5–25%; 2: 26–50%; 3: 51–75%; 4: >75%). The final score was derived by intensity and positive ratio14. Similarly, tumors from nude mice were fixed in 4% paraformaldehyde. The primary antibody against Ki-67 (Cat. no. 28074-1-AP; 1:1,000; Proteintech) was incubated with the tumor samples. Immunofluorescence assay of ADCY4 was performed on BC tissues, using FITC-conjugated Affinipure Goat Anti-Rabbit IgG (Cat. no. SA00003-2; 1:500; Proteintech) as the secondary antibody. Nuclei were counterstained with diaminidine phenyl indole (DAPI).

5-Aza-2′-deoxycytidine (Aza) and trichostatin A (TSA) treatment

BC cells were treated with 10mM Aza (a DNA methyltransferases inhibitor: Sigma-Aldrich, Darmstadt, Germany). For combining Aza and TSA (a histonedeacetylase inhibitor: Sigma-Aldrich), cells were treated with Aza for 3 days and subsequently 100nM TSA for 24 h as previously described15. Total RNA and genomic DNA was extracted as aforementioned to investigate ADCY4 mRNA expression and its DNA methylation.

Bisulfite modification of DNA and methylation-specific PCR (MSP)

To investigate ADCY4 methylation in BC cells and tissues, MSP were performed as described previously16. Sodium bisulfite-modified DNA was amplified with methylation-specific (m1 and m2) or unmethylation-specific (u1 and u2) primers. MSP was processed for 40 cycles using AmpliTaq-Gold DNA Polymerase (Applied Biosystems). The MSP products were assayed on 2% agarose gels and 100 bp DNA ladder marker (MBI Fermentas, Thermo). These MSP samples were visualized as aforementioned. All sequences of primers are listed in Table S1.

Bioinformatics analysis

Using R 3.6.3 package, the mRNA expression of ADCY4 in BC was evaluated from the Cancer Genome Atlas (TCGA) database. The mRNA expression of ADCY4 expression in BC, tumor-adjacent, and normal samples were also performed online as well as the associations among ADCY4 mRNA, clinicalpathological parameters of BC, and patients’ survival using BC gene-expression miner (bc-GenExMiner: http://breastcancergenex.ico.unicancer.fr/) with TCGA, GTEx and SCAN-B datasets17. Furthermore, the prognostic values of ADCY4 in BC were confirmed using PrognoScan with GEO datasets (http://dna00.bio.kyutech.ac.jp/PrognoScan/index.html/)18. Meanwhile, we used EMBOSS-cpgplot explorer (https://www.ebi.ac.uk/Tools/seqstats/emboss_cpgplot/) to display the CpG islands in the sequence of ADCY419. Based on TCGA database from university of alabama at birmingham cancer data analysis portal (UALCAN: http://ualcan.path.uab.edu/), the DNA methylation status of ADCY4 in primary tumor and normal tissues was displayed20. The relationship between ADCY4 DNA methylation and its mRNA expression was investigated using cBioPortal online tool (https://www.cbioportal.org/) (METABRIC, Nature 2012 & Nat Commun 2016, 1866 samples)21. Based on the co-expressed genes of ADCY4 from cBioPortal, the Database for Annotation, Visualization and Integrated Discovery (DAVID: https://david.ncifcrf.gov/) was applied to analyze the KEGG pathways22. Then, R 3.6.3 software was used to visualize these enriched KEGG pathways. The gene set enrichment analysis (GSEA) was used to analyze whether a prior defined genes shows significant23.

Cell proliferation assay

The BC cells MDA-MB-231 and MCF-7 (7 × 103 cells/well) were plated into 96-well plates and grew for the next 24, 48, 72, and 96 h, respectively. MTT assay was applied to evaluate the ability of cell proliferation. Briefly, 20 µL (5 mg/mL) MTT (Sigma-Aldrich) was added and incubated for 4 h, then dimethylsulfoxide (DMSO) was added and the purple crystals were dissolved for 10 min. Finally, the absorbance at wavelength of 490 nm was measured by micro plate reader (PerkinElmer, Massachusetts, USA)24.

Colony formation assay

This assay was processed as previously described25. 200 cells were uniformly plated into 6-well plates and incubated for 2 weeks until visible colonies formed. Then the colonies were fixed with 4% paraformaldehyde (PFA: Beyotime, Shanghai, China) and stained with 0.1% crystal violet (Beyotime). The colonies were counted and photographed with a phase contrast microscope (Olympus, Tokyo, Japan). The software of photoshop was used to counting colonies number. Colony formation rate = (number of colonies/number of cells inoculated )× 100%.

Cell cycle and apoptosis assay

Flow cytometry analyses were processed as previously described26. Cells were fixed in ice-cold 70% ethanol and stained with propidium iodide (PI: Biolegend, San Diego, USA) to measure for cell cycle distribution. The cell-cycle profiles were assayed using the CytoFLEX S flow cytometer (Beckman Coulter, Brea, USA), and was analyzed using a CytExpert software (Beckman Coulter). Apoptosis was evaluated with the staining of Annexin V-Alexa Fluor 647 and 7-AAD according to the manufacturers’ protocols (MultiSciences, Hangzhou, China). Briefly, cells were incubated in the darkness at room temperature. Flow cytometry analysis of apoptosis was immediately assayed.

Cell mobility and invasion assay

Cell mobility was investigated by in vitro transwell® assays ) and wound healing assays as previously described27. Invasion was analyzed using Transwell chambers with coated matrigel (BD Biosciences, Bedford,, USA). 5 × 104 cells with serum-free culture were seeded into the upper chamber. The lower chamber contained 600µL culture medium with 10% FBS. After incubation for 24 h, cells were fixed and stained with crystal violet. Three fields with equallyly distributed cells were chose for counting. In the analysis of cell migration, when the cells were syncretic, cell layers were artificially wounded with a sterilized pipette tip. After washing three times with PBS, cells continued to be cultured with serum-free culture medium. Open wound distances were photographed with a dephased microscope (Olympus) at 0, 6, 24 and 48 h and then measured.

In vivo assay

This experiment was processed according to guidelines approved by the Institute Ethics Committee of the Affiliated Hospital of Southwest Medical University (No. 20221222-001). Ten female, five-week-old BALB/c nude mice were purchased from Beijing Vitonglihua Biotechnology. After one week of acclimatization, the mice were randomly divided into two groups, with five mice per group. A total of 5 × 106 MCF-7 cells (resuspended in PBS) were injected subcutaneously into the right axillary region of each mouse. Tumor size was measured every three days using a vernier caliper, and tumor volume was calculated using the formula: Volume = 0.5 × length × width2. Body weight was also recorded at the same time points.

Measurement of cAMP concentration

Human cAMP ELISA Kit (Meimian Industry, Yancheng, China) was applied to quantitate the cAMP concentration according to operation manual. Each sample of cells was added with 100µL PBS containing 100µM Apremilast (a PDE inhibitor: Beyotime), and after repeated freeze-thawing, centrifuged at 3000 rpm for 20 min, the supernatant was taken as the samples to be detected. To determine the effect of ADCY4 on cellular cAMP concentration, cells were infected with control and ADCY4 lentivirus before the measurement of cAMP. The absorbance was measured at wavelength of 450 nm by micro plate reader (PerkinElmer).

Western blotting, antibodies, and reagents

RIPA Lysis Buffer (Beyotime), added with 1mM PMSF and protease inhibitors (Beyotime), was used to lyse cells. The concentration of protein was measured by Enhanced BCA Protein Assay Kit (Beyotime). The samples of protein were subsequently denatured and 30 µg of each sample was separated by 10% SDS-PAGE before transferring onto PVDF membranes. The following antibodies was used: ADCY4 (Cat. no. DF3507; 1:2,000; Affinity Biosciences), ERK(Cat. no. AF6240; 1:1,000; Affinity Biosciences), phosphorylated (p)-ERK (Thr202/Tyr204) (Cat. no. AF1015; 1:1,000; Affinity Biosciences), AKT (Cat. no. 10176-2-AP; 1:1,000; Proteintech, Chicago, IL, USA), phosphorylated (p)-AKT (Ser473) (Cat. no. 66444-1-lg; 1:2,000; Proteintech), FAK (Cat. no. 12636-1-AP; 1:2,000; Proteintech), phosphorylated (p)-FAK (Tyr397) (Cat. no. AF3398; 1:1,000; Affinity Biosciences), with β-actin (Cat. no. 66009-1-Ig; 1:10,000; Proteintech) used as the internal control. The secondary antibodies of horseradish peroxidase (HRP)-conjugated Affinipure Goat Anti-Rabbit IgG (Cat. no. SA00001-2; 1:5,000; Proteintech) and HRP-conjugated Affinipure Goat Anti-Mouse IgG (Cat. no. SA00001-1; 1:5,000; Proteintech) were added and incubated. These immune blots were visualized using an enhanced chemiluminescence (ECL: Junengbio, Wuhan, China), and photoed and analyzed using the ChemiDoc™XRS + Imaging System (Bio-Rad Laboratories). SQ22536 (a cAMP inhibitor: cat. no. HY-100396; MedChemExpress, Shanghai, China), SC79 (a AKT activator: cat. no. SF2730; Beyotime), and tBHQ (an ERK activator: cat. no. HY-100489; MedChemExpress) were purchased. All drugs were dissolved in DMSO.

Half maximal inhibitory concentration analysis

This analysis was performed as previously described25. Briefly, cells were treated with gradually increased concentrations to determine the half maximal inhibitory concentration (IC50). Paclitaxel (Lot. no. 12210806; Haikou Pharmaceutical Factory Co. Ltd, Haikou, China) was purchased. CCK-8 assay was performed (Dojindo, Kumamoto, Japan). The absorbance at wavelength of 450 nm was measured by micro plate reader (PerkinElmer). The value of IC50 was computed by non-linear regression analysis.

Statistical analysis

SPSS software (version 13.0; SPSS Inc, Chicago, IL, USA) was applied to perform statistical analysis. Statistics data photos were generated by Graphpad Prism (version 5.0; GraphPad Software, San Diego, USA). One-way ANOVA, Wilcoxon signed-rank and Pearson’s chi-squared tests were applied to analyze data as appropriate. All experiments were carried out in three independent experiments. P < 0.05 was defined as statistically significant, *P < 0.05, **P < 0.01, ***P < 0.001 vs. the control group. All methods were performed in accordance with the relevant guidelines and regulations.

Results

ADCY4 is downregulated in BC and associated with poor prognosis

We investigated ADCY4 mRNA expression by RT-qPCR in paired BC and adjacent noncancer tissues. The expression of ADCY4 was downregulated in 90.0% (18/20) of tumors, compared with adjacent tissues (p = 0.0237, < 0.05) (Fig. 1A). To confirm the expression of ADCY4 in BC, we firstly performed an analysis using R 3.6.3 based on the TCGA datasets. The results demonstrated that ADCY4 mRNA expression is decreased in BC (n = 1096) compared to normal tissues (n = 112) (p = 7.262e-52, < 0.001) (Fig. 1B). Furthermore, using online bc-GenExMiner analysis, we observed that the ADCY4 mRNA was also decreased in BC (n = 1034), compared with adjacent noncancer (n = 104) and normal tissues (n = 92) (p < 0.0001) (Fig. 1C). Besides, the online analysis examined the role of ADCY4 in clinical significance of BC. As shown in Fig. S1, the significant difference of ADCY4 mRNA level was found between the groups of ≤ 51 years and > 51 years age (p = 0.0011, < 0.01). Moreover, human epidermal growth factor receptor type 2 (HER2) status, basal-like, triple negative BC (TNBC), Scarff-Bloom-Richardson (SBR) grade, Nottingham prognostic index (NPI), Ki-67 status, and P53 status were negatively associated with ADCY4 mRNA level (p < 0.0001). Conversely, ADCY4 mRNA level was positively related with estrogen receptor (ER) and progesterone receptor (PR) status (p < 0.0001).

Fig. 1
figure 1

ADCY4 is downregulated in BC and associated with poor prognosis. (A) ADCY4 mRNA expression in primary BC (n = 20) and paired adjacent noncancer tissues (n = 20) by qRT-PCR with β-actin as a control (p = 0.0237, < 0.05). (B) ADCY4 mRNA expression in normal tissues and BC from TCGA datasets using R 3.6.3. package (p = 7.262E-52, < 0.001). (C) ADCY4 mRNA expression in normal tissues (n = 92), adjacent noncancer (n = 104), and BC (n = 1034) from GTEx and TCGA datasets (p < 0.001). (D) The OS rate in the group of high and low ADCY4 expression from TCGA datasets (p = 0.0056, < 0.01). Cutoff value: the median expression level. (E) The difference of OS rate for BC in high and low ADCY4 based on GSE1456 (p = 0.021569, < 0.05). (F) The difference of OS rate for BC in high and low ADCY4 based on GSE3494 (p = 0.017310, < 0.05). (G) Representative IHC staining images of ADCY4 protein expression in adjacent normal breast and BC tissues. The IHC score of ADCY4 in 10 BC specimens (IHC score: 3.10 ± 0.88) was lower than paired 10 adjacent normal breast samples (IHC score: 10.50 ± 2.12) (Mean ± S.D). NC, adjacent normal breast tissues; BrCa, BC tissues. ***p < 0.001.

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Survival probability analysis was performed that the survival was significantly better in BC patients with high expression of ADCY4 than in those with low expression in TCGA datasets based on median expression cutoff (p = 0.0056, < 0.01) (Fig. 1D). We further verified the prognostic value of ADCY4 in BC based on GEO datasets. The high ADCY4 was markedly related with better overall survival (OS) in GSE1456 data [HR: 0.61 (0.40–0.93), p = 0.021569, < 0.05; Fig. 1E]. In GSE3494 data, the high ADCY4 was related with better OS [HR: 0.68 (0.49–0.93), p = 0.017310, < 0.01; Fig. 1F]. The protein expression of ADCY4 was also investigated with IHC. The immunoreactivity of ADCY4 in membrane and cytoplasm was remarkably lower in BC tissues compared with adjacent normal breast tissues (p < 0.001; Fig. 1G). Immunofluorescence assay of ADCY4 expression was shown in adjacent normal breast and BC tissues (Figure S2). Shortly, ADCY4 is downregulated in BC tissues and associated with short survival and poor prognosis. These results demonstrated that the ADCY4 may be a tumor suppressor gene in BC.

Identification of ADCY4 silenced by promoter methylation in BC

The nucleotide sequence analysis by the cpgplot tool included with the EMBOSS explorer identified that the ADCY4 promoter contains CpG islands (Fig. 2A). To investigate its DNA methylation status, we performed MSP analysis on 171 BC tissues and 11 adjacent normal breast tissues. ADCY4 methylation was detected in 164/171 (95.9%) BC tissues but only 2/11 (18.2%) breast normal tissues (Fig. 2B, Table S2), thus suggesting that the methylation of ADCY4 is a frequent event in BC. The statistical characteristics between ADCY4 methylation and clinicopathological feature are described in Table S3. The associations between ADCY4 methylation and patients’ clinicopathological features, including histological types, age, pathological grade, tumor size, lymph node metastasis, distant metastasis, TNM stage, molecular subtypes, and adverse prognostic event, were discovered no significant (p > 0.05). Similarly, we found that the difference of ADCY4 methylation in BC (n = 793) and breast normal tissues (n = 97) from TCGA datasets was significant (p < 0.001, Fig. 2C). In addition, based on cBioPortal online tool (n = 1253), we analyzed the relationship between ADCY4 expression and its methylation, and we found that they were negatively associated (r=-0.19, p = 1.35E-11, < 0.001) (Fig. 2D).

Fig. 2
figure 2

Identification of ADCY4 silenced by promoter methylation in BC. (A) The CpG islands in the LTBP4 nucleotide sequence (EMBOSS-cpgplot). Each red arrows represents a single CpG island. (B) ADCY4 methylation in primary BC tissues (n = 171) and normal tissues (n = 11) measured by MSP. m-, methylated, u-, unmethylated. Gel images showed the representational graphs. (C) The differences in methylation levels of ADCY4 in primary BC (n = 793) and normal tissues (n = 97) from TCGA datasets. (D) The correlation between ADCY4 methylation and expression from TCGA-BRCA datasets was analyzed using cBioPortal online software (n = 1253, r=-0.19, p = 1.35E-11, < 0.001); (E) ADCY4 mRNA expression and methylation status in BC cell lines. m-, methylated, u-, unmethylated. (F) ADCY4 methylation status with 5-aza-2-deoxycytidine (A) and trichostatin A (T) treatments in BC cell lines. m-, methylated, u-, unmethylated. (G) ADCY4 expression with 5-aza-2-deoxycytidine (A) and trichostatin A (T) treatments in BC cell lines by qRT-PCR. **p < 0.01.

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By semi-quantitative RT-PCR, we found that the mRNA expression of ADCY4 was silenced in almost all BC cells but highly expressed in four normal breast tissues (#12, #13, #14, #15). Further MSP found that the promoter of ADCY4 was methylated in 8/8 (100%) BC cell lines, a finding associated with its mRNA downregulation. In contrast, no methylation was tested in normal breast tissue (#12) (Fig. 2E). To determine whether DNA methylation directly regulates ADCY4 mRNA downregulation, we treated the BC cells with Aza, alone or together with the TSA. A decrease in methylated alleles and an increase in unmethylated alleles were induced by this treatment (Fig. 2F). Meanwhile, this treatment restored the mRNA expression of ADCY4 in MDA-MB-231 and MCF-7 BC cell lines (Fig. 2G). Together, these results show that DNA methylation of ADCY4 is an important mechanism contributing to its mRNA downregulation in BC.

ADCY4 functions as a tumor suppressor in BC

To assess the tumor suppressive functions of ADCY4, we infected ADCY4 lentivirus to BC cell lines with silenced ADCY4. Restoration of ADCY4 was confirmed with RT-qPCR (Fig. 3A). Ectopic ADCY4 expression suppressed BC cell growth in the assays of cell proliferation (Fig. 3B) and colony formation (Fig. 3C). The cell proliferation of ADCY4-overexpressing MDA-MB-231 and MCF-7 was significantly lower (p < 0.05) than that of mock vector. To investigate the potential mechanism through which ADCY4 inhibits BC cell growth, we evaluated the effects of ADCY4 on cell cycle. Overexpression of ADCY4 significantly increased the proportion of G1 phase in BC cell lines, especially in MDA-MB-231 (p < 0.05) and MCF-7 cells (p < 0.05) (Fig. 3D).

Fig. 3
figure 3

ADCY4 suppresses BC in vitro. (A) Ectopic expression of ADCY4 in BC cell lines was measured by RT-qPCR. (B) Cell viabilities evaluated at 24, 48, 72, and 96 h after ectopic expressing ADCY4 in MDA-MB-231 and MCF-7 cells. (C) Representative colony formation of vector- and of ADCY4-expressing BC cells (left panel). Rates are shown as mean ± SD (right panel) from three independent experiments. (D) Cell cycle distribution measured in vector- and ADCY4-expressing BC cells by flow cytometry. Representative distribution plots and histograms of alterations are shown. (E) Percentages of apoptotic cells with ADCY4 ectopic expression were evaluated. Cell apoptosis alterations were revealed by histograms. (F) The cellular invasion abilities of BC cells upon ectopic expression of ADCY4 were measured by transwell assays with matrigel. (G) Cell migration abilities of BC cells evaluated by wound healing assays. Photographs captured at 0, 6, 24 and 48 h. Representative images were photographed following fixation and staining. Scale bars: 50 μm. ***p < 0.001, **p < 0.01, *p < 0.05.

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Furthermore, ectopic ADCY4 expression obviously increased the numbers of apoptotic cells in BC cell lines (p < 0.01), compared with mock vector (Fig. 3E). To investigate the effect of ADCY4 on BC cell invasion, we analyzed by using Transwell assays with matrigel. As shown in Fig. 3F, ectopic ADCY4 remarkedly decreased the numbers of invasive cells. We also analyze the effect of ADCY4 on BC cell migration through wound healing assays. ADCY4 stably expressed BC cells migrated slower than mock vector at 24 h and 48 h (p < 0.01, Fig. 3G). Taken together, ADCY4 can inhibit BC growth and play a suppressive role in BC in vitro.

To further confirm the suppressive role of ADCY4 in BC, we evaluated whether ADCY4 could inhibit BC cells in vivo (Fig. 4A). The nude mice xenograft model was used to investigate ADCY4 functions in vivo. The average volume and weight of xenograft were both lower in the ADCY4 group than the mock vector (p < 0.05) (Fig. 4B, C). Hematoxylin and eosin (HE) staining and IHC were applied to evaluate ADCY4 expression and xenograft features. Ki-67 staining was applied to assess cell proliferation. Tumor cells with few nuclear fragmentation were detected in xenografts with ADCY4 expression, along with decreased Ki-67 (Fig. 4D). Together, these results showed that ADCY4 inhibits BC growth in vivo.

Fig. 4
figure 4

ADCY4 suppresses BC in vivo and is critical for cAMP/PKA and its downstream signaling pathways. (A) Representative photos showing tumor growth 30 days after subcutaneously injected MCF-7 cells with ADCY4-overexpression or not. (B) Tumors’ volume was measured on each three days. (C) The weight of vector-group and ADCY4-group tumors were measured respectively (n = 5). (D) Representative images of HE staining (original magnification: 800×), The protein levels of Ki-67 was determined by immunohistochemistry (original magnification: 400×). The histogram shows the intensity of immunostaining. All statistical data were shown as mean ± S.D. (E, F) ADCY4 promotes cAMP generation in MDA-MB-231 and MCF-7 cells. (G) WB analysis for phospho-FAK (Tyr397), FAK, phospho-AKT (Ser473), AKT, phospho-ERK1/2 (Thr202/Tyr204), ERK1/2 with ADCY4 ectopic expression, β-actin was used as a loading control. *p < 0. 05, ***p < 0.001.

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ADCY4 inhibits BC growth through suppressing FAK/AKT and ERK signaling pathways via conversing ATP to cAMP

cAMP, an important signaling regulator, is produced through ATP by ACs and closely related with tumor depending on PKA. To reveal the molecular mechanism through which ADCY4 suppress BC growth, we firstly investigate the change of cAMP levels and downstream signaling pathways in ADCY4-overexpressing BC cell lines. The results showed that ADCY4 promotes cAMP concentration in MDA-MB-231 (Fig. 4E, p < 0.001) and MCF-7 cells (Fig. 4F, p < 0.001). Moreover, we analyzed the downstream signaling of cAMP pathway. Compared with mock vector cells, downregulated phosphorylation of FAK at Tyr397, AKT at Ser473 and ERK1/2 at Thr202/Tyr204 in either MDA-MB-231-ADCY4 or MCF-7-ADCY4 cells were verified by WB assay (Fig. 4G).

We next investigated whether the FAK/AKT and ERK signaling is responsible for ADCY4-regulated BC cell growth. For this purpose, SC79 (Akt activator, 8ug/ml)28,29 and tBHQ (ERK activator, 40–50 µM)30,31 were applied to activate the AKT and ERK. As shown in Fig. 5A, SC79 effectively upregulated the phosphorylation levels of AKT at Ser473 in MDA-MB-231-ADCY4 and MCF-7-ADCY4 cell lines, respectively. In line with the effects on AKT signaling, SC79 significantly increased cell proliferation and decreased cell apoptosis in MDA-MB-231-ADCY4 and MCF-7-ADCY4 cells compared to untreated cells (Fig. 5B, C). In addition, we also found that tBHQ upregulated the phosphorylation of ERK1/2 at Thr202/Tyr204 in ADCY4-overexpressing cell lines (Fig. 5D). In line with the effects on ERK signaling, tBHQ also significantly increased cell proliferation and decreased cell apoptosis in ADCY4-overexpressing cells compared to untreated cells (Fig. 5E, F).

Fig. 5
figure 5

Phosphorylation of AKT and ERK signaling is suppressed by ADCY4 ectopic expression. (A) MDA-MB-231 and MCF-7 cells with ADCY4 ectopic expression or control cells were treated with vehicle (DMSO) or SC79, WB analysis for phospho-AKT (Ser473) and AKT. β-actin was used as a loading control. (B) MDA-MB-231 and MCF-7 cells with ADCY4 ectopic expression or control cells were treated the same as in (A), the cell viabilities were measured by MTT assay at 24, 48, 72, and 96 h. (C) MDA-MB-231 and MCF-7 cells with ADCY4 ectopic expression or control cells were treated the same as in (A), the percentages of apoptotic cells were measured. (D) MDA-MB-231 and MCF-7 cells with ADCY4 ectopic expression or control cells were treated with vehicle (DMSO) or tBHQ, WB analysis for phospho-ERK1/2 (Thr202/Tyr204) and ERK. β-actin was used as a loading control. (E) MDA-MB-231 and MCF-7 cells with ADCY4 ectopic expression or control cells were treated the same as in (D), the cell viabilities were measured by MTT assay at 24, 48, 72, and 96 h. (F) MDA-MB-231 and MCF-7 cells with ADCY4 ectopic expression or control cells were treated the same as in (D), the percentages of apoptotic cells were measured. ***p < 0.001, **p < 0.01, *p < 0.05.

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We further examined how ADCY4 regulates FAK/AKT and ERK signaling and plays suppressive function in BC cells. As cAMP is an important upstream regulator, we investigated the effects of pharmacological inhibition of cAMP in BC cells with ADCY4 overexpression. As shown in Fig. 6A, treatment with cAMP inhibitor SQ22536 led to an obvious downregulation in the levels of cAMP in MDA-MB-231-ADCY4 and MCF-7-ADCY4 cells. We also analyzed whether pharmacological activation of AKT and ERK would affect cAMP concentration. However, the results showed that SC79 and tBHQ did not perform any significant effects on cAMP (Fig. 6B, C). Furthermore, in line with the effects on cAMP signaling, SQ22536 significantly increased cell proliferation and decreased cell apoptosis in ADCY4-overexpressing cells compared to untreated cells (Fig. 6D, E). These data suggest that cAMP might be critical regulator for ADCY4-regulated FAK/AKT and ERK signaling in BC cells. In summary, the Fig. 6F displays the alternative mechanism of conversing ATP to cAMP and suppression of downstream FAK/AKT and ERK signaling through ADCY4 during breast carcinogenesis.

Fig. 6
figure 6

cAMP plays an important role in ADCY4-regulated signaling pathways. (A) MDA-MB-231 and MCF-7 cells with ADCY4 ectopic expression or control cells were treated with vehicle (DMSO) or SQ22536, cAMP concentration was measured by ELISA assay. (B) MDA-MB-231 and MCF-7 cells with ADCY4 ectopic expression or control cells were treated with vehicle (DMSO) or SC79, cAMP concentration was measured the same as in (A). (C) MDA-MB-231 and MCF-7 cells with ADCY4 ectopic expression or control cells were treated with vehicle (DMSO) or tBHQ, cAMP concentration was measured the same as in (A). (D) MDA-MB-231 and MCF-7 cells with ADCY4 ectopic expression or control cells were treated the same as in (A), the cell viabilities were measured by MTT assay at 24, 48, 72, and 96 h. (E) MDA-MB-231 and MCF-7 cells with ADCY4 ectopic expression or control cells were treated the same as in A), the percentages of apoptotic cells were measured. (F) Proposed model of alternative mechanism of conversing ATP to cAMP and suppression of downstream FAK/AKT and ERK signaling via ADCY4 during breast carcinogenesis. Loss of ADCY4 is detected in BC and tightly correlated with promoter CpG methylation. ADCY4 restoration inhibits breast carcinoma cell growth and metablism through cAMP/PKA and its downstream FAK/AKT and ERK signaling pathways. ***p < 0.001, **p < 0.01, *p < 0.05.

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The potential mechanism of ADCY4 in BC

To further evaluate the potential mechanism of ADCY4 in BC, the co-expression genes of ADCY4 were predicted by cBioPortal. We visualized the KEGG pathways (p < 0.001) by using DAVID and R package analysis based on co-expression genes of ADCY4. The result showed that the ADCY4 co-expression genes was counted most in metabolic pathways (hsa01100), and with most remarkable significance in cell cycle (hsa04110), amyotrophic lateral sclerosis (hsa05014), and parkinson disease (hsa05012) etc. (Figure S3A). To access the potential pathways associated with ADCY4 in BC, GSEA identified remarkable significance (FDR q-value < 0.05) in MSigDB collection (c2.cp.kegg.v6.2.symbols.gmt). The RNA degradation, cell cycle, glycolysis gluconeogenesis, and pyruvate metabolism were significantly enriched in ADCY4-low expression phenotype (FDR q-value < 0.01) (Figure S3B). Importantly, the MAPK, JAK-STAT signaling pathway, cellular adhesion molecules (CAMs), and NOTCH signaling pathway were enriched in ADCY4-high expression (FDR q-value < 0.05) (Figure S3B). Taken together, ADCY4 may involve in cell cycle and MAPK signaling pathways in BC.

ADCY4 increased the sensitivity to Paclitaxel of BC cells

In the previous results, ectopic ADCY4 expression induced cell cycle arrest of G1 phase in BC cells. The cell cycle of tumor cells could influence sensitivity of tumor cells to chemotherapeutic drugs such as paclitaxel. Given the paclitaxel was an important and frequent used drug for BC, we analyzed whether ADCY4 could affect the chemosensitivity of BC cells. We detected the paclitaxel sensitivity of BC cells by using IC50 assay with overexpressed ADCY4. The results showed a decreased viability rate on ADCY4 overexpressed MDA-MB-231, MCF-7, and SK-BR-3 cell lines with a decreased IC50 of paclitaxel (Fig. 7A–C). Especifically, ectopic ADCY4 expression could reduce the IC50 of paclitaxel from 9.748 to 3.507 (nM), 56.50 to 24.65 (nM), and 32.64 to 13.48 (nM) in MDA-MB-231, MCF-7, and SK-BR-3 cells, respectively (Fig. 7D). Therefore, ADCY4 could sensitize BC cells to chemotherapy drug paclitaxel. This result finds a new insight of the cooperative role of ADCY4 in the chemotherapy of BC.

Fig. 7
figure 7

ADCY4 sensitized the respond of BC cells to paclitaxel. (A–C) Viability rate of proliferation in ADCY4 ectopic expression or control BC cells (MDA-MB-231, MCF-7, and SK-BR-3) treated with gradient concentration of Paclitaxel. (D) IC50 values of paclitaxel for BC cells.

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Discussion

Our previous work was the first to identify the epigenetic regulation mechanisms and potential functions of ACs in human cancers, especially ADCY4 in BC based on public datasets9. The present study further explores a mechanism of cAMP signaling and downstream pathways in BC through DNA-methylated inhibition of ADCY4. Gain-of-function analysis revealed that ADCY4 expression induced the inhibition of cell growth, invasion, and migration. ADCY4 was found to play tumor-suppressive functions by upregulating cAMP level and further attenuating downstream ERK and FAK/AKT signaling. These inhibitory functions were terminated in the presence of cAMP inhibitors, ERK, or AKT activators. Furthermore, ADCY4 expression sensitized cells to chemotherapy in BC. These results demonstrate a causal role of ADCY4 silencing in aberrant cAMP/PKA signaling pathways during breast carcinogenesis. They also demonstrate a tumor suppressive role of ADCY4 in downstream ERK and FAK/AKT signaling activation in BC.

cAMP signaling has been considered to have a significant role in human cancers, including inducing cell transformation, inhibiting cell growth, and enhancing cell sensitivity to anti-tumor drugs6. As an intracellular signaling regulator, cAMP is produced through ATP by nine membrane-bound ACs and one soluble AC4. However, current studies on different ACs in human cancers focus on biomarker screening. In addition, these ACs have been mentioned in studies related to the interaction with other genes and small RNAs or tumor drug resistance32,33,34. Research focusing on specific ACs is rare. Yi et al. found that high expression of ADCY9 is a poor prognostic effector for disease-free survival in colon cancer35. Moreover, ADCY7 deficiency resulted in inhibited growth, increased apoptosis, and decreased c-Myc in leukemia cells, suggesting that ADCY7 may be a new treatment target for leukemia36. At the same time, the potential role of ADCY1 in chemotherapy resistance of lung cancer requires further study37. Although some ACs that may be involved in tumorigenesis have been identified in BC38there is a lack of direct evidence exploring their biological role from the perspective of epigenetics. Our group and others have previously reported on epigenetic disruption of different AC members. DNA methylation of ADCY8, CDH8, and ZNF582 and HPV genotypes are associated with tumor cytological grade in cervical cancer39. ADCY3 expression is mediated by DNA methylation. As an oncogene, ADCY3 is involved in the tumorigenic process of gastric cancer, further revealing the mechanism of ADCY3 in the occurrence of gastric cancer and providing a new direction for molecular targets40. A recent study found that ADCY6 gene expression, DNA methylation, and immune-related pathways in luminal BC are closely related and are positively correlated with patient prognosis41. Although only rare genetic alterations in ADCY4 were detected in BC9a dominant role of DNA methylation in ADCY4 expression was also identified in the present study. ADCY4 was frequently downregulated with DNA methylation in BC. In addition to its expression regulation mechanism, downregulated ADCY4 was also associated with poor survival and prognosis in BC.

ADCY4 belongs to the AC family that structurally consists of two adenylate and guanylate cyclase catalytic domains, adenyl cyclase N-terminal extracellular and transmembrane region, and a domain of unknown function (DUF1053)42. However, reports on ADCY4 mechanisms are rare. The significance of endothelin receptor type B (EDNRB) in hepatocellular carcinoma were previously discussed43. Protein interaction analysis results suggested that ADCY4, KDR, VEGFC, FLT1, and CDH5 may be the key genes related to EDNRB, but further experiments are needed to confirm this idea. Another study suggested that FPR2, GNG11, and ADCY4 are the key genes in lung squamous cell carcinoma based on weighted gene co-expression network and protein interaction network analyses44. Furthermore, studies have reported that ADCY4 expression is low in lung squamous cell carcinoma and is closely related to its overall survival, while GSEA analysis suggested that its expression may be related to the spliceosome and cell adhesion factors45. Based on the dataset analysis, ADCY4 may be a candidate key gene for lung adenocarcinoma and is correlated with overall survival46,47. Another report showed a strong association with LUAD, in which RXFP1, AVPR2, CALCRL, ADRB1, RAMP3, RAMP2, VIPR1, and ADCY4 were hub genes48. A prior investigation also noted that purine metabolism may contribute to inflammation-related lung tumorigenesis, which included significantly altered ADCY4 protein and metabolites49. In the present study, ADCY4 suppressed the downstream ERK and FAK/AKT signaling to inhibit BC growth, except for upstream cAMP/PKA signaling activation (Fig. 6F). Another study showed that FAK can phosphorylate PI3K and then activate downstream AKT50. A similar study reported that FAK acts as an important player in epithelial-mesenchymal transition by activating AKT51. A recent report also demonstrated that FAK/PI3K/AKT signaling mediates the tumorigenesis of hepatocellular carcinoma52. Many studies showed that FAK has a significant role in cancer signaling pathways of progression and metastasis53 Moreover, FAK phosphorylation has been found in BC cells54. Interestingly, FAK/Src complex formation allows to phosphorylate FAK to mediate the activation of the RAS-ERK signaling pathway55. FAK interaction with SHC also contributes to ERK pathway activation56. However, the association between FAK and ERK was not identified in the present study. Furthermore, ADCY4 suppressed FAK/AKT and ERK signaling by converting ATP to cAMP. As we known, the cAMP involves a number of downstream effectors, including PKA and CREB57. Silvio et al. found that leptin-dependent signaling is affected by an increase in cAMP, offering an instance of how cAMP/PKA may play an inhibitor role of the ERK1, 2, and STAT3 signaling in MDA-MB-231 BC cells58. Other studies demonstrated that PKA inhibition plays a significant role in CB1 cannabinoid receptor stimulation of neuronal FAK59.

The role of cAMP in BC cell growth has been investigated. Dibutryl-cAMP in conjunction with arginine suppressed the proliferation of MCF-7 cell line60. Subsequently, an increase in cAMP levels was confirmed to block the growth of MCF-7 cells in an anchorage-independent manner61. This finding also indicated that cAMP may play a significant role in preventing the transformed phenotype in mammary epithelial cells. The present study demonstrated that ectopic ADCY4 in ADCY4-deficient BC cells increased the levels of cAMP. Accordingly, ADCY4 overexpression in BC cells revealed its tumor suppressor functions involving cell growth and migration/invasion in vitro or in vivo. DAVID KEGG and GSEA analyses also showed that ADCY4 may be involved in the metabolic pathways of glycolysis gluconeogenesis and pyruvate and signaling pathways of JAK-STAT, CAMs, and NOTCH, excluding cell cycle and MAPK pathways. Therefore, these results suggest that ADCY4 can serve as a negative adjuster of cAMP-ATP synthesis and exert its tumor suppressor role in BC.

In summary, this study explored the biological function of ADCY4 from molecular mechanisms to breast carcinogenesis, showing that it can act as a tumor suppressor in BC by producing cAMP and inhibiting downstream signaling pathways. The significant role of DNA methylation of ACs in breast carcinogenesis was further highlighted, which was in line with our previous findings of AC involvement in other human cancers. Restoration of ADCY4 activity through epigenetic or pharmacologic intervention should be explored as a therapeutic strategy. However, further investigation of its tumor suppressive roles in other human cancers is needed. In addition to cAMP signaling and downstream pathways, whether other cross-talk signaling may be associated with ADCY4 during tumorigenesis should be determined.