Introduction
Ovarian cancer is one of the deadliest diseases that affects females worldwide. The high mortality of this cancer is due to its poor prognosis; therefore, most cases are diagnosed at the advanced stage with metastatic functions [
1,
2]. In spite of advances in treatment over the past decade, the cure rate of ovarian cancer has improved modestly [
2]. Therefore, better targeted therapies and biomarkers for diagnosis or prognosis are urgently needed. Recently, increasing evidence has shown that cancer cells display an altered metabolism; therefore, targeting abnormal cancer metabolism is a promising therapeutic approach for cancer surveillance [
3,
4]. Hence, the study of key regulators of cellular metabolism in cancer cells has attracted attention [
5‐
9].
AMP-activated protein kinase (AMPK) is a well-known cellular energy–balancing sensor [
10‐
12] that regulates cellular metabolism and protects living cells from environmental stresses, such as hypoxia and nutrient deficiency, which lead to elevations in the cellular AMP/ATP ratio. Recent evidence suggests that AMPK has a dual role in tumors. In metabolic stress microenvironements, such as the nutrient or oxygen deprivation conditions in early stage tumors where new blood vessels have not been formed or during the transformation state of normal cells, activated AMPK increases cell survival by regulating cellular NADPH levels to remove reactive oxygen species (ROS) [
13]. On the other hand, AMPK activation is involved in inhibiting cell proliferation by suppressing mTOR and upregulating p53 pathways [
14,
15]. In fact, AMPK has been shown to possess a strong capacity to inhibit the cell growth of advanced-stage cancers [
13,
16,
17]. Pharmacological activation of AMPK by AICAR or metformin commonly shows a strong inhibition of cell growth or induces apoptosis in a wide spectrum of cancer cells, such as chronic myelogenous leukemia (CML) and Ph + acute lymphoblastic leukemia (ALL) [
18,
19] as well as breast [
20], cervical [
16] and ovarian [
17,
21] cancers, which indicates that AMPK activity may hinder or enhance cancer oncogenesis. When and how tumor cells modulate AMPK activity during tumor progression is currently unclear. AMPK is a heterotrimer composed of a catalytic subunit (α) and two regulatory subunits (β and γ), and all three subunits are essential for AMPK activity [
22]. Multiple isoforms (encoded by distinct genes) of various AMPK subunits, namely, α1, α2, β1, β2, γ1, γ2 and γ3, have been reported. As mentioned, the functional aspects of AMPK in metabolic diseases and human cancers have been extensively studied and reviewed [
23‐
25]. However, the expression status of various AMPK subunits and their functional significance in human cancers have been sporadically investigated.
We previously reported a comprehensive study of AMPK subunits in ovarian cancer and showed that all subunits are generally upregulated in ovarian cancer [
26]. Intriguingly, the overexpressed AMPK-β1 that was found in early stages of ovarian cancer were significantly reduced in advanced stage ovarian cancer [
26]. Given that post-translation modifications of AMPK-β1 (i.e., myristoylation and phosphorylation) are essential for AMPK activity [
27], the expression status of AMPK-β1 may determine the AMPK activity in ovarian cancer progression.
In this study, we further investigated the expression and functional roles of the AMPK-β1 subunit in ovarian cancer. We demonstrated a progressive reduction in the expression of the AMPK-β1 subunit from early to late-stage ovarian cancer, whereas enforced expression of AMPK-β1 could inhibit the cell growth and other aggressive capacities of ovarian cancer cells through the AKT/ERK and JNK signaling pathways. Overall, our findings underscore the importance of AMPK-β1 in carcinogenesis through its ability to modulate AMPK activity and other oncogenic pathways during the progression of ovarian cancer.
Materials and methods
Ovarian cancer tissue array and cancer cell lines
Four ovarian cancer cell lines were used: A2780cp and OV2008 were obtained from Prof. B.K. Tsang (Department of Obstetrics and Gynecology, University of Ottawa), and SKOV3 and OVCA433 were obtained from ATCC (Rockville, MD, USA). Cell line authentication was performed using an in-house STR DNA profiling analysis, and the cell lines were cultured in minimum essential medium (MEM) supplemented with 10% FBS (Gibco, Invitrogen Life Technologies, Carlsbad, CA, USA) inside an incubator containing 5% CO2 at 37°C. An ovarian cancer tissue array (OVC1021) (Pantomics Inc., San Francisco, CA, USA), which consists of five cases of normal/benign tumors and 97 cases of ovarian cancers, was used for immunohistochemical analysis.
Plasmids and DNA transfection
The pcDNA3.1–AMPK-β1–Flag-tagged plasmid (a gift from Prof. Yi Sun, University of Michigan, USA) was used to overexpress AMPK-β1 in ovarian cancer cells, and Lipofectamine™ 2000 Transfection Reagent (Invitrogen) was used for transfection experiments. Stable AMPK-β1-overexpressing clones were established from AMPK-β1 transfected cells using G418 selection. The shRNA plasmid shRNA-AMPK-β1 (shβ1) for targeting against AMPK-β1 was purchased from OriGene Technologies, Inc. (Rockville, MD, USA). Stable, AMPK-β1 knockdown clones were established by puromycin selection of shβ1-transfected cells, and all of the clones were verified by western blot analysis. The pEGFP- AMPK-β1 plasmid was used for immunofluorescence analysis and was constructed by subcloning AMPK-β1 from the pcDNA3.1–AMPK-β1–Flag tagged plasmid into pEGFP-C1 (Clontech Laboratories, Inc., Mountain View, CA, USA ).
Western blot, immunofluorescence and immunohistochemical analyses
Cells were lysed in lysis buffer containing a protease inhibitor and phenyl-methyl-sulfonyl-fluoride (Cell Signaling Technology, Beverly, MA, USA). Equal amounts of each sample were fractionated by SDS-PAGE and electroblotted onto an Immobilon-P Membrane (Millipore, Billerica, MA, USA). The membrane was blocked with 5% non-fat dry milk in a TBS with Tween (TBST) solution at room temperature for 1 h, followed by overnight incubation with various primary antibodies. Antibodies against AMPK-β1, AMPK-α, phospho-AMPK-α (Thr172), P70S6K, phospho-P70S6K (Thr389), AKT, phospho-AKT (Ser473), mTOR, and phospho-mTOR (Ser2448) were purchased from Cell Signaling, whereas antibodies against JNK, phospho-JNK (Thr183/Tyr185), ERK and phospho-ERK (Thr202/Tyr204) were purchased from Santa Cruz Biotechnology, Inc. (Santa Cruz, CA, USA). The blots were then incubated with goat anti-rabbit or anti-mouse secondary antibodies that were conjugated to horseradish peroxidase and visualized via an enhanced chemiluminescence system (Amersham Pharmacia Biotech, Cleveland, OH, USA). β-Actin (Sigma Chemical Co. St Louis, MO, USA) was used as the loading control.
For immunofluorescence analysis, SKOV3 cells were cultured on cover slips and transiently transfected with AMPK-β1-expressing plasmid. The preparation and examination of pEGFP-AMPK-β1-transfected cells were performed as previously described [
28].
Immunohistochemical (IHC) staining for AMPK-β1 was performed on an ovarian cancer tissue array (OVC1021), and an antibody against AMPK-β1 (Cell Signaling Technology) was used to examine the expression of AMPK-β1. Procedures and the scoring of results were performed as previously described [
29,
30], and the examination of immunohistochemical staining was performed by two independent observers.
Confocal microscopy
The cellular localization of AMPK-β1 was examined in A2780CP and SKOV3 cells after the transient expression of the pCMV6–AMPK-β1–GFP-tagged plasmid (OriGene Technologies). The analytical procedure was reported previously [
29], and fluorescence signals were captured using confocal microscopy.
Cell proliferation assay
The cell proliferation assay was performed using a cell proliferation kit (Invitrogen), and data were obtained from three separate experiments that were performed in triplicate.
Clonogenic assay
Approximately 800 cells were plated in triplicate in 6-well plates to form colonies for up to 2–4 weeks, and the medium was replaced every 3–7 days. The colonies were then stained with crystal violet and counted.
Anchorage-independent growth assay
A soft agar colony formation assay was used to determine the capacity of ovarian cancer cells to undergo anchorage-independent cell growth upon different treatments. Sterile 2% (bottom) and 0.6% agarose gel (top) stocks in 2× MEM containing 20% FBS were prepared, and single-cell suspensions were prepared by suspending 1000 cells in 2 ml of full medium containing 0.3% agar. The cell suspensions were plated on top of a solidified bottom layer (~2 ml) with 1% agar in the full medium, and the plates were incubated at 37°C in a humidified incubator for 14–21 days. The colonies were then counted using a dissecting microscope.
Flow cytometry
The DNA content, cell cycle distribution and percentage of apoptotic cells of each sample were assessed by flow cytometry. Cells were cultured in 6-well plates, and floating and attached cells were harvested by trypsinization, centrifuged and resuspended in PBS. The cells were then fixed overnight with 1 ml of 70% ethanol at 4°C followed by centrifugation at 4,000 × g at 4°C for 5 min and one wash with ice-cold PBS. RNase A was heated at 95°C for 10 minutes before use, and the cell pellets were resuspended in 500 μl of PBS containing 5 μl of RNase A (10 mg/ml stock) and then incubated at 37°C for 30 min. Afterwards, 125 μl of propidium iodide (250 μg/ml) was added to each sample and was kept at 4°C in dark before flow cytometry.
Wound healing, cell migration, and invasion assays
The wound healing assay was performed as follows. Equal numbers of cells were cultured in full medium in a 6-well plate until 90% confluency. Cells were then pretreated with 10 μg/ml of mitomycin C for 2 h, and three parallel “wounds” were created in each plate with a sterile 200 μl pipette tip. The plate was then washed with PBS, and the width of the wounds was photographed at different time points (0, 12, 24 and 36 h). The relative velocity of cell migration was calculated as the change in width/time.
Quantification of cell migration and invasion was performed using QCM™ 24-Well Colorimetric Cell Migration and Cell Invasion Assay Kits (Chemicon International, Inc., Temecula, CA, USA). Briefly, cells were resuspended in serum-free culture medium (5.0 × 104 cells for the cell migration assay and 2.0 × 105 cells for the invasion assay) and then seeded on the upper chamber. The full medium was then placed in the lower chamber as a chemo-attractant, and the cells were allowed to pass through the pores to the lower surface of the membrane (18 h for cell migration and 28 h for the cell invasion assay). The cells were then stained with the staining buffer and photographed in three different microscopic fields.
Statistical analysis
The SPSS 14.0 software was used for statistical analysis (SPSS, Chicago, IL, USA). Fisher’s exact test (for parametric data) and the Mann–Whitney test (for non-parametric data) were used to compare the values between subgroups, and data were expressed as the mean ± SD. The Student’s t-test was used to compare the values between subgroups, and P < 0.05 was considered to be a statistically significant difference between groups of data.
Discussion
AMPK is a well-known energy sensor in mammalian cells [
32]. Emerging evidence has demonstrated that AMPK exerts promoting and suppressing effects on tumor oncogenesis depending on the cancer cell type and the timing of tumor development. Recent studies show that AMPK enhances cell survival during metabolic stress in early stage tumors or when tumor cells detach from their extracellular matrix [
13,
33]. However, mounting evidence also suggests that low AMPK activity usually favors high cell proliferation in numerous, advanced-stage human cancers [
34‐
36]. Yet, the underlying molecular mechanism for modulating AMPK activity-mediated cell proliferation in cancers remains unclear. In this study, we report that the AMPK-β1 subunit of the AMPK complex shows a progressive reduction in expression level from early to advanced tumor stages of ovarian cancer. We found that the reduced AMPK-β1 is consistent with the lower AMPK activity that is found in advanced stage, high-grade and metastatic ovarian cancers. Using gain- and loss-of-function strategies, we demonstrated that AMPK-β1 profoundly impairs cell growth, migration and invasion capacities via activating AMPK but attenuating AKT, ERK and JNK activities in advanced ovarian cancer cells. To our knowledge, this is the first comprehensive study of AMPK-β1 expression, function and mechanism of action in human cancer cells.
Recent studies have suggested that AMPK acts as a metabolic tumor suppressor due to its roles in governing the activities of mTOR, p53 and other regulatory molecules as well as fatty acid synthesis [
37‐
39]. Hence, tumor cells must reduce the activity of AMPK to maintain their high proliferative capacity in oncogenesis. Loss of LKB1 is a well-known mechanism in suppressing AMPK activity and is commonly found in lung cancer, melanoma, gastrointestinal carcinoma and dysplastic hamartoma in Peutz-Jeghers syndrome [
40‐
42]. However, most human cancers with an intact LKB1 function still maintain low AMPK activity when exerting their tumorigenic properties [
43‐
45], indicating that multiple mechanisms exist that depress AMPK activity in such cancer cells. AMPK is a heterotrimeric complex consisting of a catalytic alpha-subunit and regulatory beta- and gamma-subunits. We previously reported that the AMPK subunits are differentially expressed and that different subunits have different clinical implications in the development of ovarian cancer [
46]. Of these subunits, we found that the mRNA level of
AMPK-β1 was dominantly expressed and tightly correlated with AMPK activity when compared with
AMPK-β2 during the progression of ovarian cancer [
47] and other human cancers [
48]. Consistent with our previous findings, the IHC data in this study further demonstrates that AMPK-β1 expression shows a stepwise reduction from early to late-stage ovarian cancer. In addition, reduced AMPK-β1 expression shows a significant association with late-stage, high-grade and metastatic ovarian cancers, suggesting that reduced AMPK-β1 expression decreases AMPK activity and enhances the aggressiveness of advanced ovarian cancer. Although the underlying molecular mechanisms leading to the downregulation of AMPK-β1 during ovarian cancer progression remain unknown, the recent finding of the underexpression of AMPK-α2 in liver cancer cells [
49] indicates that DNA methylation and histone deacetylation may be involved in silencing the expressions of AMPK subunits in ovarian cancer cells.
Our results indicate that the inhibitory effect of AMPK-β1 on cell growth is mediated through an increase in AMPK activation and a simultaneous decrease in AKT pathway activity. In the AMPK heterotrimeric complex, the AMPK-β subunit acts as a scaffold to support the binding of the catalytic α and regulatory γ subunits [
50,
51]. We postulated that AMPK-β1 upregulation most likely leads to an increase in the number of AMPK heterotrimeric complexes, which, in turn, facilitates induced activation of AMPK by either microenvironemental stresses or pharmaceutical activators. In contrast, lower AMPK-β1 expression may reduce the number of AMPK heterotrimeric complexes, which leads to lower AMPK activity in advanced ovarian cancers. A previous study has demonstrated that knockouts of AMPK-β1 and -β2 led to reduced AMPK activity in most tissues and significant reductions in bone mass in mice [
52]. Additionally, the post-translational modification of AMPK-β1, that is, myristoylation and phosphorylation, could affect AMPK activity [
53]. Based on these findings, we believe that reduced expression of AMPK-β1 diminishes the amount of AMPK heterotrimeric complexes and their activity in aggressive, advanced ovarian cancer cells.
Our findings on the negative regulation of the AKT pathway by AMPK-β1 is in line with those reported by Feng
et al. [
54]. AMPK-β1 has been found to be a stress-responsive gene that can be induced in a p53-dependent or p53-independent manner [
54,
55]; therefore, induction of AMPK-β1 expression could negatively regulate the IGF-1–AKT–mTOR pathways [
56]. The ability to simultaneously upregulate AMPK activity and down-regulate AKT signaling leads to cell growth inhibition. Moreover, AMPK-β1 overexpression could inhibit ovarian cancer cell migration and invasion, and this effect is most likely mediated through the down-regulation of the JNK pathway. We have previously demonstrated that down-regulation of the JNK pathway using a JNK inhibitor (SP600125) significantly inhibited cell motility [
57]. Similarly, inhibition of the AKT and ERK pathways using their respective inhibitors, wortmannin and U0126, could reduce cell proliferation rates [
57], which indicates the importance of AMPK-β1 expression in controlling cell proliferation, migration, and invasion. Indeed, AMPK-β1 expression correlates well with clinicopathologic data, which show that early stage tumors have high levels of AMPK-β1, whereas advanced stage, high-grade or metastatic ovarian cancers have lower AMPK-β1 levels.
In conclusion, our findings suggest that the expression level of AMPK-β1 is able to determine the amount of AMPK heterotrimeric complexes and, hence, the activity level of AMPK in advanced ovarian cancer cells. Downregulation of AMPK-β1 seems to be another mechanism that leads to lower AMPK activity in advanced ovarian cancer cells. Based on the data showing that enforced expression of AMPK-β1 elevates AMPK activity but decreases AKT, ERK and JNK activities as well as abrogates its oncogenic capacities in cell growth, migration, invasion and sensitizing chemoresistant ovarian cancer cells to cisplatin-induced cell apoptosis, AMPK-β1 may be a potential therapeutic target in advanced ovarian cancer treatment.
Competing interests
All authors disclose no potential competing interest.
Authors’ contributions
CL, DC and VL designed the research; CL, VL and PC performed the experiments; DC, VL and KY contributed new reagents-analytical tools; CL, DC, VL and HN analyzed and interpreted the data; CL and DC wrote the manuscript; and DC, VL and HN supervised the study. All authors were involved in editing the manuscript and had final approval of the submitted and published versions.