Background
The Warburg effect is observed in most cancer cells, reflected as predominantly producing energy at a high rate of glycolysis followed by lactic acid fermentation. However, most normal cells demonstrated a comparatively low rate of glycolysis followed by oxidation of pyruvate in mitochondria. Malignant, rapidly growing tumor cells typically have glycolytic rates up to 200 times higher than those of their normal tissues of origin; this occurs even if oxygen is plentiful [
1‐
3]. In the other point of view, the glycolysis is positively correlated to the tumor growth and malignancy. Today, mutations in oncogenes and tumor suppressor genes are thought to be responsible for malignant transformation, and the Warburg effect is considered to be a result of these mutations rather than a cause [
2].
Since the glycolysis provides most of the building blocks required for cell proliferation, cancer cells (and normal proliferating cells) have been proposed to need to activate glycolysis, despite the presence of oxygen, to proliferate [
4]. A set of genes regulated the process of glycolysis, three of them are most important. They are hexokinase (HK), phosphofructokinase-1 (PFK1) and pyruvate kinase (PK), in which PKM2 is the last step within glycolysis and was detected to expressing in most cancers [
5].
Similar to other genes, PKM2 was regulated by miRNA. It has been reported that PKM2 can be targeted by the tumor-suppressive miRNA including miR-326 [
6], miR-122 [
7,
8], miR-124 [
9], miR-137 [
9], etc., thus to decrease the Warburg effects. However, although the expression of these miRNAs was detectable within tumors, over-expression of their targeting gene: PKM2 still appeared frequently. There are many explanations, in which SNP in miRNA, especially mature miRNA are one of the convincing reasons.
MicroRNAs (miRNAs) are endogenous 22 nt non-coding RNAs which play important regulatory roles in animals and plants by targeting 3′UTR of mRNAs for cleavage or translational repression [
10,
11]. Some SNPs in pre-microRNAs, flanking regions or target sites have been demonstrated to affect certain physiological processes or related to diseases [
12]. In the present study, we found one possible valuable SNP in the mature miR-379, in which could potentially affect the binding ability to PKM2. We postulated that this SNP might contribute to the various expression of PKM2 within invidious and further affects the metabolism and growth of the tumor.
Materials and methods
The hospital-based case–control study consists of 871 GC patients and 812 cancer-free controls. All the subjects were recruited from the Center Hospital of Nanjing between January 2012 and January 2016. Patients with other hematological disorders, previous history of cancers, and chemotherapy were excluded. This study was approved by the Ethics Review Board of Hospital of Nanjing, and every patient had written informed consent. The clinical features of all the cases and controls were presented in Table
1.
Table 1
Clinical characteristic of gastric cancer patients and cancer-free controls
Age (years) | | | | | 0.805 |
≤ 50 | 376 | 43.17 | 345 | 42.49 | |
> 50 | 495 | 56.83 | 467 | 57.51 | |
Gender | | | | | 0.248 |
Male | 318 | 36.51 | 319 | 39.29 | |
Female | 553 | 63.49 | 493 | 60.71 | |
H. pylori infection | | | | | < 0.0001 |
Positive | 664 | 76.23 | 189 | 23.28 | |
Negative | 207 | 23.77 | 623 | 76.72 | |
Differentiation |
G1 | 129 | 14.81 | | | |
G2 | 251 | 28.82 | | | |
G3 | 245 | 28.13 | | | |
G4 | 219 | 25.14 | | | |
Gx | 27 | 3.10 | | | |
Tumor size (cm) |
≤ 5 | 587 | 67.39 | | | |
> 5 | 284 | 32.61 | | | |
Metastasis |
Yes | 412 | 47.30 | | | |
No | 459 | 52.70 | | | |
Cell lines and cell culture
Gastric cancer cell lines including MKN-45 and AGS were purchased from American Type Culture Collection (ATCC). All cells were cultured in Dulbecco modified Eagle medium (DMEM) purchased from Gibco (CA, USA) supplemented with 10% fetal bovine serum (Invitrogen, Carlsbad, USA) and maintained in humidified 5% CO2 at 37 °C.
Construction of luciferase-based reporter plasmids
The full length of PKM2 cDNA as well as its 3′UTR were synthesized and sub-cloned into pGL3 plasmids. For the gene promoter activity assays, 3′UTR of PKM2 was synthesized and sub-cloned into a pGL3 plasmid (Promega, WI, USA). The construction containing different genotype of miR-379 was also synthesized and cloned into pSilence 2.1-U6. All the DNA synthesis and clones were performed in Genscript Co. (Nanjing, China).
Dual-luciferase reporter assay
The treated cells harvested 48 h after miRNA treatment, and the firefly luciferase expression was measured and normalized to Renilla activities. Dual-luciferase assays (Promega, Madison, WI) were performed according to the manufacturer’s protocol and detected with a Fluoroskan microplate reader (Thermo Labsystems, Helsinki, Finland). Transfection was repeated three times in triplicate (Additional file
1).
Cell proliferation assays
Cell proliferation was determined by using CCK-8 (Dojin Laboratories, Kumamoto, Japan) according to the manufacturer’s instructions. Briefly, the control and infected cells were seeded at a density of 1 × 103 cells/well in 96-well plates. 10 μL of CCK-8 was added to each well containing 100 µL of the culture medium, and the plate was incubated for 2 h at 37 °C. The viability of cells was evaluated by measuring the absorbance at 450 nm, using a microplate reader (Thermo Labsystems, CA).
Genotype
Genomic DNA was extracted from peripheral blood by using QIAamp DNA blood mini kits (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Genotyping was performed with the TaqMan SNP Genotyping Assay. The PCR reactions were carried out in a total volume of 5 μL containing TaqMan Universal Master Mix, SNP Genotyping AssayMix, DNase-free water and genomic DNA. The PCR conditions were 2 min at 50 °C, 10 min at 95 °C, followed by 40 cycles at 95 °C for 15 s and 60 °C for 1 min. The 384-well ABI 7900HT real-time PCR system was applied (ABI, CA, USA).
Immunohistochemistry (IHC)
Sections were stained according to the previous publication [
7]. The section was incubated within primary mouse anti-human Ab for PKM2 (ab38237), the sections were stained with DAB according to manufacturer’s protocols and mounted and photographed using a digitalized microscope camera (Nikon, Tokyo, Japan).
Plasma samples preparation and analysis by GC–TOF–MS
Metabolites extracted from plasma samples were analyzed using an Agilent 7890N gas chromatograph coupled with a Pegasus HT TOF mass spectrometer (Leco Corporation). Briefly, a 1 μL aliquot of the derivatized solution was injected with the splitless mode. Rxi-5 ms capillary column (30 m × 250 μm I.D., 0.25-μm film thickness; Restek Corporation, Bellefonte, PA, USA) was used for metabolites separation, with helium as the carrier gas at a constant flow rate of 1.0 mL/min. The temperature settings for injection, transfer interface, and ion source were 260, 260, and 210 °C, respectively. The separation was achieved with the following GC temperature program: 80 °C for 2 min, 10 °C/min to 220 °C, 5 °C/min to 240 °C, and 25 °C/min to 290 °C, and kept at 290 °C for 8 min. The data was collected with full scan mode (m/z 40–600), and an acquisition rate of 20 spectra/s. Electron impact ionization (70 eV) was used.
The data from GC–TOFMS was processed with ChromaTOF software (v4.22, Leco Co., CA, USA). Compound annotation was performed by comparing the mass fragments with NIST 08 Standard mass spectral databases with a similarity of more than 70% and finally verified by available reference standards. The annotated compounds from GC–TOFMS were imported to SIMCA-P software 12.0.1 (Umetrics, Umeå, Sweden) for multivariate statistical analysis. Supervised orthogonal partial least squares-discriminant analysis (OPLS-DA) was used to compare between groups. Differential metabolites were selected based on the criteria of variable importance in the projection (VIP) > 1 in OPLS-DA model and P value < 0.05 from Student’s t test.
Statistical analysis
All experiments were performed in triplicate and repeated at least three times. Data were expressed as mean ± SD. The association between rs61991156 genotypes and the risk of GC was evaluated by calculating the odds ratios (ORs) and their 95% confidence intervals (CIs) using univariate and multivariate logistic regression analysis. Differences between two independent groups were tested with Student’s t test. All statistical analyses were carried out using SPSS version 18.0 and presented with Graph-pad prism software. Kaplan–Meier survival curves were plotted, and the log-rank test was done. The significance of various variables for survival was analyzed by the Cox proportional hazards model in a multivariate analysis. The results were considered to be statistically significant at P < 0.05.
Discussion
The general point of views on miR-379 were controversial. Some reports regarded it as a tumor suppressor which capable of down-regulating many oncogenes by targeting their 3′UTR region. For example, miR-379 was reported to be boosted by rifampicin and blocking the expression of ABCC2 (multidrug resistance-associated protein 2) thus to sensitize the HCC cells to chemotherapy [
14]. Others also indicated that miR-379 was overexpressed in malignancies, and might serve as an indicator for bad prognosis. miR-379 expression was elevated in bone-metastatic prostate cancer cell lines and tissues. The expression of miR-379 was also correlated with shortened progression-free survival of patients with prostate cancer [
15]. In our study, the results revealed that miR-379 was a tumor suppressor in human GC. From the clinical investigation, miR-379 GG genotype was associated with small tumor size, well differentiation, and non-metastasis which is related relatively low expression of PKM2 in gastric cancer. In line with the expression level, the glycolysis level within GC patients with GG genotype was also the weakest. We speculated that these results might result from rs61991156 in the mature form of miR-379.
In the present study, we found the SNP rs61991156 located within the mature form, generating three different genotypes of miR-379, among which A > G mutation generate an 8-mer complementary sequence in the 3′UTR of PKM2. The G allele might have significantly stronger the binding affinity to 3′UTR of PKM2 compared to the A allele. We thought this was the reason why miR-379 GG can significantly decrease the expression of PKM2 and in turn to attenuate both the proliferation and glycolysis of GC cells. Similar results concerning miRNA SNP have been reported previously resulting in either “Gain” or “LOSS” regulation of the targeting genes. miR-SNPs in miR-125a and Kaposi’s sarcoma-associated herpes virus-encoded miR-K5 were reported to impair miRNA processing by the Drosha/DGCR8 complex [
16,
17]. SNP of miR-196a2 at rs11614913 in the mature miR-196a2 was reported to be associated with a significantly decreased rate of survival in individuals with non-small cell lung cancer, and the same research team of this study also suggested an association of rs11614913 with enhanced processing of mature miR-196a [
18]. miR-146a-SNP (rs2910164) within the pre-miR-146a sequence reduced both the amount of pre- and mature miR-146a and apparently affected the Drosha/DGCR8 processing step [
18,
19]. miR-196a2-SNP, miR-146a-SNP, miR-149-SNP (rs2292832), and miR-499-SNP (rs3746444) are each associated with increased breast cancer risk [
20].
Conclusion
So far, there is almost no report concerning the SNP of miR-379, we reported firstly that A > G SNP in 12nt of miR-379 might enhance the binding affinity to the 3′UTR of PKM2, thus to might be associated with low glycolysis level, well differentiation, as well as slower tumor growth. And the detection of rs61991156 might be associated with low occurrence and less aggressiveness of gastric cancer in Chinese population due to the enhanced regulations on PKM2.
Authors’ contributions
Conception and design: XWW and NC. Collection and assembly of data: ML and NC; Data analysis and interpretation: YRW and ML. Contribution of reagents, materials, and analysis tools, wrote the paper: XWW and NC. All authors read and approved the final manuscript.
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