Background
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide [
1]. Patients with early-stage HCC are asymptomatic; hence, HCC is usually detected at intermediate or advanced stages, in which patients cannot receive curative treatments such as ablation, surgical resection, or liver transplantation [
2]. Although surgical treatment has improved the disease outcome, the risk of recurrence remains substantial even for early HCC. In patients with advanced HCC, sorafenib (Nexavar), an orally active multikinase inhibitor, has been used as a first-line chemotherapeutic agent [
3]. Despite extending the median survival by 3–5 months, the high resistance rate and serious adverse side effects have significantly limited the benefits of sorafenib therapy [
4‐
6]. Therefore, there is an increasing need for a strategy to enhance the effects of sorafenib anti-cancer activity.
Sirtuins (SIRT1–7) have emerged as important regulators of tumorigenic processes such as proliferation, cell cycle progression, cell survival, metabolism, and angiogenesis [
7‐
9]. SIRT3, the best characterized mitochondrial sirtuin, deacetylates and activates several enzymes involved in cellular redox balance and defense against oxidative damage [
10‐
12]. Several reports suggest that SIRT3 has a dual role in cancer [
13‐
15]. SIRT3 functions as an oncogene in oral cancer and melanoma by maintaining ROS levels under a certain threshold to prevent apoptosis and promote cell proliferation [
16,
17]. In contrast, SIRT3 has been identified as a tumor suppressor in HCC [
18,
19], breast cancer [
20], ovarian cancer [
21], and leukemia [
22]. Further, it has been reported that SIRT3 plays a role in metabolic reprogramming (Warburg) and in triggering cell death under stress conditions [
23,
24]. Indeed, high SIRT3 expression is correlated with favorable outcomes and an increase in the overall survival rate of patients with HCC [
25]. In this regard, regulation of SIRT3 expression might be a novel strategy to investigate more personalized therapies against cancers. In addition, SIRT3 expression levels affect sensitivity to chemotherapeutic agents in HCC [
26].
In this study, we aimed to investigate the correlation between SIRT3 expression and glucose metabolism and proliferation in HCC. In addition, because a few compounds have been explored to modulate SIRT3 activity [
27,
28], we also attempted to identify effective compounds that increase the endogenous SIRT3 modulation mediated by the anti-cancer effect of sorafenib.
Methods
Human HCC samples
This study was approved by the Institutional Review Board at Yonsei University Health System Severance Hospital (Seoul, South Korea), and the study was conducted using the current guidelines for ethical research (Yonsei IRB number: 4–2015-0904). The selection of patients was performed as described previously [
29].
Chemicals
PD0332991 was purchased from TOCRIS Bioscience (Bristol, UK) and sorafenib was purchased from Santa Cruz (Dallas, TX, USA). PD0332991 and sorafenib were dissolved in DMSO (Sigma Aldrich, St. Louis, MO, USA) at a concentration of 10 mM. All reagents were stored at − 80 °C.
Cell lines and cell culture
The human HCC cell lines HepG2, Hep3B, skHep1, and Huh7 were purchased from the Korean Cell Line Bank. HepG2 was cultured in RPMI, and Hep3B, skHep1, and Huh7 were cultured in Dulbecco’s modified Eagle’s medium (DMEM). All media were supplemented with 10% fetal bovine serum (FBS; Hyclone) and 1% penicillin streptomycin. Cells were maintained in a humidified incubator with 5% CO2 at 37 °C. For the formation of three-dimensional spheroids, Costar® Ultra-Low attachment multiple-well plates (MerkKGaA → Corning, Darmstadt, Germany) were used. HCC cells were plated at 5000 cells/well and centrifuged at 179×g for 1 min. Spheroids were observed 1–2 days after plating. Hep3B, skHep1, and Huh7 cell lines were plated and incubated for 24 h before transfection. Lipofectamine or RNAiMAX reagent (Invitrogen, Carlsbad, CA, USA) was used to perform siRNA transfection following the manufacturer’s instructions. The plasmids for hSIRT3 (sc-61,555-SH) or scramble shRNA (sc-108,060) were cotransfected into HepG2 cells using Lipofectamine 2000 (Invitrogen, 12,566,014). After 72 h of incubation, the cells were treated with puromycin (2 μg/mL) to generate stable cell line clones.
Cell proliferation assay and glucose measurement
WST-1 colorimetric assays (Roche, Mannheim, Germany) for cell viability were performed 48 h after treatment according to the manufacturer’s recommendations. Huh7 cells were placed in 96-well plates and being transfected with MOCK or pcDNA-SIRT3 plasmid. After 48 h of treatment, the glucose uptake was determined using Glucose Assay (Promega, Germany) according to the manufacturer’s recommendation. Absorbances at 440 nm and 640 nm were measured using a microplate reader (Molecular Devices, CA, USA).
RNA isolation and sequencing
Total RNA was isolated using TRIzol reagent (Invitrogen). RNA quality was assessed by Agilent 2100 bioanalyzer using the RNA 6000 Nano Chip (Agilent Technologies, Amstelveen, The Netherlands), and RNA quantification was performed using ND-2000 Spectrophotometer (Thermo Inc., DE, USA). For control and test RNA samples, library was constructed using QuantSeq 3′ mRNA-Seq Library Prep Kit (Lexogen, Inc., Austria) according to the manufacturer’s instructions. Briefly, 500 ng total RNA was prepared for each sample, an oligo-dT primer containing an Illumina-compatible sequence at its 5′ end was hybridized to the RNA, and reverse transcription was performed. After degradation of the RNA template, second strand synthesis was initiated by a random primer containing an Illumina-compatible linker sequence at its 5′ end. The double-stranded library was purified using magnetic beads to remove all reaction components. The library was amplified to add the complete adapter sequences required for cluster generation. The amplified library was purified, and high-throughput sequencing was performed as single-end 75 sequencing using NextSeq 500 (Illumina, Inc., USA).
Real-time PCR
Total RNA was extracted with TRIzol (Invitrogen) and cDNA was synthesized from 500 ng of total RNA using the ReverTra Ace qPCR RT Master Mix with gDNA Remover (Toyobo, Osaka, Japan). Quantitative RT-PCR was conducted on C1000 a→ a C1000 Thermal Cycler (Bio-Rad) using SYBR Green Real-time PCR Master Mix (Toyobo, Osaka, Japan). Gene expression levels were normalized with beta-2 microglobulin (B2M) mRNA expression levels of corresponding cDNA samples. All PCR primers were purchased from Bioneer (Daejeon, Korea). The following primers were used: SIRT3 (Forward 5′-GAAACTACAAGCCCAACGTCA-3′, Reverse 5′-AAGGTTCCATGAGCTTCAACC-3′), RB1 (Forward 5′-GAAGCAACCCTCCTAAACCAC-3′, Reverse 5′-CTGCTTTTGCATTCGTGTTCG-3′), and B2M (Forward 5′-TTACTCACGTCATCCAGCAGA-3′, Reverse 5′-AGAAAGACCAGTCCTTGCTGA-3′).
Western blotting
Western blotting was performed as described previously [
29]. The primary antibodies in the present study were: SIRT3 (Cell Signaling Technology, Danvers MA, USA; clone C73E3; dilution 1:1000), CDK4 (DCS156, 1:1000), CDK6 (DCS83, 1:1000), Phospho-Rb (Ser807/811) (D20B12, 1:1000), Rb (4H1, 1:2000), PCNA (D3H8P, 1:2000), GLUT1 (1:2000) from Abcam (Cambridge, UK), and Ki67 (Santa Cruz, Dallas TX, USA; MIB-1, 1:500). Western blotting experiments from biological replicates showed similar expression data, attesting to the reproducibility of the results. We used ChemiDoc XRS (Biorad), which enables direct digital visualization of chemiluminescent western blots for the image of signals accumulated in the chemiluminescence reaction. For band quantification, images were analyzed using Image Lab software (Bio-Rad, Hercules, California, USA).
Flow cytometry analysis
For quantification of apoptosis, double staining was performed according to the manufacturer’s instructions using Annexin V-FITC Apoptosis Detection Kit (BD Pharmingen™, NJ, USA) and propidium iodide (PI). After HepG2 and Huh7 cells were collected after incubation with indicated compound, cells were washed twice with ice-cold PBS and resuspended in 200 μL of binding buffer. Annexin V-FITC was added to the cells and incubated for 15 min in the dark at 25 °C. PI (10 mL) was added to the tube followed by 5 min of incubation at 4 °C in the dark. After incubation, the samples were analyzed by a flow cytometer using CELL Quest software (BD) and 1.0 × 105 events per sample were counted. The fraction of cell population in different quadrants was analyzed using quadrant statistics. Cells in the lower right quadrant (Annexin-V+/PI−) represented early apoptosis and those in the upper right quadrant (Annexin-V+/PI+) represented late apoptosis. For cell cycle analysis, after HepG2 and Huh7 cells were collected after incubation with indicated compound, the cells were incubated in 70% ethanol at 4 °C for 1 h. After washing with PBS, cells were incubated with PI at a concentration of 5 μg/mL and RNaseA at a concentration of 10 mg/mL for 30 min–4 h at 37 °C. The DNA contents were analyzed using FlowJo Software (Tree StarInc., Ashland, OR, USA).
Migration assay
Chemomigration assays were performed using 24-well plates with uncoated polycarbonate membrane inserts (BioCoat; BD Biosciences, Heidelberg, Germany). A total of 50,000 cells in medium containing 0.1% FBS and sorafenib, PD0332991, or combination of sorafenib and PD033291 were added onto the insert. The lower well was filled with a medium supplemented with 10% FBS. Twenty-four hours later, the cells that had migrated were fixed in 100% methanol and stained with 1.5% (w/v) toluidine blue in water. Images were recorded using an Olympus BX53 microscope with Olympus Cell Sens software (Carl Zeiss Microscopy, GmbH, Jena, Germany).
Immunostaining
Immunohistochemistry (IHC) and immunofluorescence (IF) were performed as described previously [
30]. After antigen retrieval, immunostaining was performed using various antibodies. The primary antibodies used were: SIRT3 (Cell Signaling Technology, Danvers MA, USA; clone C73E3; dilution 1:500); Ki67 (Dako, Glostrup, Denmark; MIB-1; 1:500); GLUT1 (1:500), and Ki67 (SP6, 1:500) from Abcam (Cambridge, UK). Images were recorded using an Olympus BX53 microscope with Olympus Cell Sens software (Carl Zeiss Microscopy, GmbH, Jena, Germany). The percentage of Ki67-positive cells and phosphorylated retinoblastoma protein (pRb) was calculated by counting the number of cells with DAPI-stained nuclei.
The Cancer genome atlas (TCGA) data analysis
mRNA levels of TCGA liver HCC data were obtained from the OncoLnc TCGA data portal (
www.oncolnc.org). A set of 360 HCC samples with high and low gene expression groups (50–50 percentile) was used for correlation graphs of two different genes. GraphPad Prism 5 (GraphPad Software, San Diego, CA, USA) was used for mapping.
Statistical analysis
Statistical analyses were performed using GraphPad Prism Software (GraphPad Software, Inc., San Diego, CA). Results are expressed as mean ± SE (range). P values < 0.05 were considered statistically significant. Comparisons between groups were made using the Mann-Whitney test.
Discussion
Several studies have emphasized the importance of SIRT3 in carcinogenesis [
9,
24,
35]. However, there have been few studies on the mechanisms that control SIRT3 expression or on the discovery of clinically applicable drugs that can modulate it. In this study, we investigated a novel function of CDK4 /6 inhibitor as an inducer of SIRT3, resulting in enhanced sensitivity to sorafenib treatment in HCC cells.
To date,
SIRT3 is known as a tumor suppressor gene [
23], and overexpression of SIRT3 reduces cell growth and proliferation in HCC [
23,
25,
26]. SIRT3 also induces apoptosis in abnormal cells through the upregulation of MnSOD, p53, Bax, and Fas [
19]. Wang et al., determined patient survival and outcome in patients with HCC according to SIRT3 expression [
36]. In fact, reduced expression of SIRT3 was associated with poor prognosis, whereas intra-tumoral SIRT3 expression was reported as a good prognostic factor in the early stages. So far, the effect of SIRT3 on glucose metabolism has been studied in cancers other than HCC [
37‐
39]. Finley et al. proposed that SIRT3 loss increases ROS levels and promotes tumorigenesis by altering global cellular metabolism [
24]. In this study, patients with HCC were divided into low and high glycolytic groups by 18F-FDG-PET analysis. Consistent with previous results with other tumor types, we found high SIRT3 and low Ki67 expression in the low glycolytic group of patients with HCC. Thus, our study suggests that SIRT3 expression is associated with glycolysis and proliferation in human HCCs. Indeed, upregulation of SIRT3 by CDK4/6 inhibition and treatment with PD0332991 induced the downregulation of glycolysis-related genes in our gene analysis.
Selective CDK4/6 inhibitors, including PD0332991, are currently used for the treatment of a variety of tumor types, including breast cancer, melanoma, and non-small cell lung cancer [
40‐
42]. In this study, we found that CDK4/6 inhibition by treatment with siCDK4/6 or PD0332991 upregulated SIRT3 expression. Previous studies have determined that SIRT1 is involved in the regulation of SIRT3 expression by deacetylation and binding as a transcription factor [
43]. In addition, SIRT1 is involved in the deacetylation of retinoblastoma (Rb), leading to dissociation of E2F1 and enhanced cell proliferation [
44]. Therefore, there might be a correlation among SIRT3, SIRT1, and pRB expression levels in HCC cells. Indeed, there was a negative correlation between SIRT1 and SIRT3 expression in data from patients with HCC from the TCGA database (Supplementary Fig.
1C). However, the mechanism of SIRT3 expression by CDK4/6 inhibition remains unclear, and should be investigated in future studies.
Sorafenib has not been effective in patients with advanced HCC, and its use is often associated with reduction of drug sensitivity. Therefore, it is very important to identify a drug candidate that can replace or be used together with sorafenib. Tao et al. found that upregulation of SIRT3 expression can enhance the sensitivity of HCC cells to chemotherapeutic agents [
26]. In our study, we found that the upregulation of SIRT3 by transfection in HCC cells reduced cell proliferation and significantly increased sensitivity to sorafenib. Moreover, the restoration of SIRT3 by PD0332991 could increase sensitivity to sorafenib, resulting in enhanced inhibition of proliferation and migration in HCC cells.
Thus, we propose SIRT3 expression as a predictor of sorafenib response. To concrete our observations in the in vitro system, preclinical studies will be conducted in the future.18F-FDG is a surrogate imaging modality to measure glucose metabolism in patients with HCC. However, there are few studies on 18F-FDG imaging in patients treated with sorafenib [
45]. Our results prove the negative correlation between the expression of SIRT3 and glucose metabolism using human HCC tissues and HCC cells in vitro. Since the expression of SIRT3 is a predictor of response to sorafenib, [18F] FDG-PET imaging could monitor the drug sensitivity in HCC patients clinically during sorafenib treatment.
Conclusion
In summmary, our data indicate the importance of CDK4/6 inhibitors as a new approach to improve HCC therapy. Moreover, our study shows that induction of SIRT3 by CDK4/6 inhibition causes inhibition of cell growth and glucose metabolism and increased susceptibility to chemotherapy. Thus, the modulation of SIRT3 might be a novel treatment in patients with HCC and, possibly, other cancers in which SIRT3 acts as a tumor suppressor.
Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit
http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (
http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.