MicroRNA-296, a suppressor non-coding RNA, downregulates SGLT2 expression in lung cancer
- Authors:
- Published online on: October 19, 2018 https://doi.org/10.3892/ijo.2018.4599
- Pages: 199-208
Abstract
Introduction
Lung cancer is the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for almost 80% of all lung cancer cases (1,2). In China, the overall 5-year survival rate for NSCLC patients is approximately 15% and the rate of recurrence remains high (3–7). Despite advances in early detection and diagnosis, chemical and immunotherapy, precision radiotherapy, and expert surgical intervention, eradicating cancer in patients remains a major challenge. Although our understanding of cancer cell biology has made significant progress, a definite cure for most types of cancer does not exist at present (8–11). Therefore, there is urgent need to discover novel biomarkers for diagnosis and treatment.
MicroRNAs (miRNAs or miRs) are small non-coding single-stranded RNAs of approximately 20-23 nt in length that regulate gene expression by binding to the 3′-untranslated regions (3′-UTR) of mRNAs (12-14). The expression levels of miRNAs have profound effects on cancer progression and human carcinogenesis (15). The expression of miR-296-5p has been shown to be significantly downregulated in lung cancer (3,16,17), breast cancer (18), diabetes (19-21) and other types of cancer and diseases (17,22,23). Therefore, exploring the function of miR-296-5p and the role of its possible target genes is essential to the understanding of the molecular mechanism of this miRNA in NSCLC. Sodium-glucose co-transporter-2 [SGLT2, also known as solute carrier family 5 member 2 (SLC5A2)], a sodium-dependent glucose transporter, is a common therapeutic target in the treatment of diabetes (24). In addition, SGLT2 promotes the development of pancreatic and prostate adenocarcinomas (25) and increases lung cancer metastasis (26). Therefore, we hypothesized that miR-296-5p may play a pivotal role in lung cancer tumorigenesis by targeting SGLT2.
In this study, we aimed to investigate this hypothesis. We demonstrate that miR-296-5p is downregulated in NSCLC patient samples and NSCLC cell lines. Moreover, we demonstrate that miR-296-5p directly targets SGLT2. These results may provide a potential molecular therapeutic target for the occurrence and development of NSCLC.
Materials and methods
Tissue samples
All NSCLC samples and non-tumor samples (also termed paracancerous tissue, i.e., tissue adjacent to cancerous tissue) were obtained from the Department of Oncology, Shanghai Chest Hospital (Shanghai, China) from October, 2014 to August, 2016 and their use was approved by the Ethics Committee of Shanghai Hospital and consent was obtained from all the patients. All the details of the tissue samples used in this study are listed in Table I. We obtained the corresponding results by analyzing the specific information of the patient tissue samples, such as sex, stage and size. Tumor size is the primary determinant of prognosis and metastasis. A previous study demonstrated that a small tumor size (≤3 cm) is associated with a lower probability of metastasis (27). Moreover, in a previous study, we demonstrated that miR-18a-targeted interferon regulatory factor 2 (IRF2) expression was downregulated in tumor tissues, and likely related to tumor size (28). Thus, in this study, we also used this method to assay the function of miR-296 in lung cancer.
Cell culture and cell transfection
The BEAS-2B, 16HBE and 293T cells were obtained from the Cell Bank, China Academy of Sciences (Shanghai, China). The A549, H1975, PC-9 and H1299 cells were purchased from the American Type Culture Collection (ATCC, Manassas, VA, USA). The A549, BEAS-2B, 293T and PC-9 cells were cultured in DMEM (Gibco). The H1975 and H1299 cells were cultured in RPMI-1640 medium. The culture conditions were set at 37°C in a 5% CO2 humidified environment. NSCLC cells were cultivated in 90% medium, 10% fetal bovine serum (FBS, HyClone Laboratories, Logan, UT, USA), 100 µg/ml penicillin, 100 µg/ml streptomycin (Gibco) and antibiotic cocktail. The BEAS-2B cell line was originally isolated from the normal bronchial epithelium.
The A549 and H1299 cells were transiently transfected with 30 nM miR-296-5p mimic, a negative control mimic (NC) and 100 nM SGLT2 siRNA (3 siSGLT2), or negative control siRNA (siNC) (Guangzhou RiboBio Co., Ltd., Guangzhou, China) using Invitrogen™ Lipofectamine 2000 (Thermo Fisher Scientific, Waltham, MA, USA) kit according to the manufacturer’s instructions. The sequences of the mimics and the siRNAs are presented in Table II. It is worth noting that we selected siSGLT2-3, the most effective from the 3 siRNAs against SGLT2, for use in the follow-up experiments. At 24 to 48 h post-transfection, the cells were used for RT-qPCR, cell proliferation analysis, colony formation analysis, cell cycle analysis and western blot analysis.
RNA isolation, reverse transcription and RT-qPCR analysis
Total RNA was extracted from the cells and the patient tissues using TRIzol reagent (Sangon Biotech, Shanghai, China). The PrimeScript™ 1st Strand cDNA Synthesis kit (Takara, Dalian, China) was used for reverse transcription. At the same time, the PrimeScript®miRNA First-Strand cDNA Synthesis SuperMixQuantiMir cDNA kit (TransgenBiotec, Beijing, China) was used to synthesize a cDNA library of miRNAs. mRNA and miRNA expression levels were quantified by RT-qPCR using SYBR-GreenⅡ (Takara) and a CFX96™ Real-time System (Bio-Rad, Hercules, CA, USA). The annealing temperature of the SGLT2 mRNA was 53°C, for the duration of 1 min at 72°C, for 37 cycles, while the annealing temperature of miR-296 was 56°C, for the duration of 1 min at 72°C, for 39 cycles. The data for relative quantification of mRNAs and miRNAs were normal-ized to 18S RNA and U6 snRNA, respectively. The expression was determined using the relative quantification (2−∆∆Cq) method (29). The primer sequences are presented in Table III.
Cell proliferation assay
The cell proliferation assay was performed as previously described (30). The NSCLC cells were plated on a 96-well microplate. The density was 2×103 or 4×103 cells per well and the cells were incubated at 37°C in 5% CO2. After 24, 48 and 72 h of culture, 8 µl of CCK-8 (Dojindo, Tokyo, Japan) were added. The cultures were then returned to the incubation conditions (37°C in 5% CO2) for 2 h. The light absorbance at 450 nm was measured daily with a microplate reader, FLx8 (BioTek, Winooski, VT, USA). Each point was measured from 3 replicate wells.
Colony formation assay
The colony formation assay was performed as previously described (31). At 37°C in a 5% CO2 humidified environment, the cells were plated in 6-well plates at 300 or 600 cells per well and incubated for 2 weeks. Colonies were stained with crystal violet (Haoranbio, Shanghai, China) (0.5% w/v) for 12 min at room temperature following fixation with methanol, and then counted. Experiments were performed in triplicate.
Cell cycle analysis
Cell cycle analysis was performed as previously described (32). The cells (106/ml) were seeded in 6-well plates and transfected after 24–48 h in culture. The cells were then subjected to propidium iodide (PI) (BD Pharmingen, San Diego, CA, USA) staining at 4°C for 15 min. The results were determined with a MoFlo XDP flow cytometer (Beckman Coulter, Inc., Brea, CA, USA). FlowJo software (Tree Star Inc., Brea, CA, USA) was used for data analysis. The experiments were performed in triplicate.
Dual luciferase reporter assay
The dual luciferase reporter assay was performed as previously described (33). The 3′-UTR of the target gene (SGLT2) was amplified and inserted downstream of the Firefly luciferase reporter gene in the pGL3 miReport vector (Promega, Madison, WI, USA), named pGL3-SGLT2-3′-UTR. Mutated SGLT2 sequences were also constructed (pGL3-SGLT2-3′-mUTR), and confirmed by sequencing (Sangon Biotech). Moreover, the QuikChange Mutagenesis kit was used to conduct site-directed mutagenesis of the 3′-UTR. To measure luciferase activity, the 293T cells were cultured in 24-well plates. At 60-80% confluence, the 293T cells were co-transfected with 400 ng of luciferase vector pGL3-SGLT2-3′-UTR or pGL3-SGLT2-3′-mUTR and miR-296-5p mimic or NC miRNA. We also used 100 nM with 20 ng plasmid expressing the Renilla luciferase gene (pRL, Promega) as a final concentration for transfection efficiency as a control. Following incubation for 48 h, the luciferase activity was determined by an Orion II Microplate Illuminometer (Titertek-Berthold, South San Francisco, CA, USA). The primer sequences are presented in Table III.
Western blot analysis
Western blot analysis was performed as previously described (28). Total protein from the A549 and H1299 cells was extracted using RIPA lysis buffer (CWBIO, Beijing, China) and a Protein BCA Assay kit (Bio-Rad) was used to quantify the protein content. Protein samples were separated by 10% SDS-PAGE and transferred to polyvinylidene difluoride (PVDF) membranes (Millipore Corporation, Billerica, MA, USA). After blocking in 5% powdered milk for at least 1 h at room temperature, the membranes were incubated with rabbit anti-SGLT2 (ab37296; Abcam, Cambridge, MA, USA), and anti-β-actin antibodies (CST 4970L; Cell Signaling Technology, Danvers, MA, USA) at 1:1,000 overnight at 4°C. The membranes were washed and incubated with a horseradish peroxidase (HRP)-conjugated secondary antibody (1:10,000; CST 7074S; Cell Signaling Technology) for 1 h at room temperature. Subsequent visualization was detected using a chemiluminescent HRP substrate (Millipore Corporation) and imaging with an E-Gel Imager. Densitometry (ImageJ software, 1.51d 16; June, 2016) was used to quantify the relative protein expression of SGLT2, following normalization to β-actin.
Statistical analysis
The results are expressed as the group means ± SEM and analyzed using GraphPad Prism 5 software (GraphPad Software, Inc., La Jolla, CA, USA), using t-tests for two-group comparisons. The expression of miR-296-5p in the different cell lines was determined by one-way ANOVA followed by Tukey’s Honest Significant difference post-hoc test. Moreover, miRNA target prediction databases were used, including TargetScan (http://www.targetscan.org/vert_71/), RNA22 (https://omictools.com/rna22-tool) and miRDB (http://www.mirdb.org/). Moreover, the data analysis website ‘TCGA’ (http://www.kmplot.com), including 1,926 NSCLC patients cases, was used for survival analysis with respect to SGLT2 expression. The negative correlation of miR-296-5p and SGLT2 was determined by Pearson’s correlation coefficient. Differences were considered statistically significant at a value of P<0.05.
Results
miR-296-5p is downregulated in NSCLC tissues and cells
The investigation of 46 lung cancer patient datasets (Table I) revealed that miR-296-5p expression was downregulated compared with the corresponding non-tumor lung tissues (Fig. 1A). The analysis of several other datasets (we obtained the corresponding results by analyzing the specific information of the patient tissue samples, such as sex, stage and size), including miRNA expression revealed that the downregulation of miR-296-5p was associated with tumor size (Fig. 1D), but was not associated with pathological stage (Fig. 1B) or sex (Fig. 1C). Moreover, we probed for the expression of miR-296-5p in NSCLC cell lines and found that miR-296-5p was significantly downregulated in the A549, H1299 (P<0.001) and PC-9 cells (P<0.01), compared with the BEAS-2B control normal lung cells (Fig. 1E). These findings indicate that the downregulation of miR-296-5p is associated with NSCLC carcinogenesis.
miR-296-5p inhibits cell proliferation and cell cycle progression
To determine whether miR-296-5p affects NSCLC cell proliferation, we first transfected the A549 and H1299 cells with the miR-296-5p mimic. The results of RT-qPCR analysis indicated that miR-296-5p levels were significantly increased in the cells transfected with the miR-296-5p mimic (Fig. 2A). Furthermore, we observed that cellular proliferation gradually decreased with miR-296-5p overexpression in the A549 and H1299 cells. The upregulation of miR-296-5p led to a significant decrease in NSCLC cell growth during a 24-72 h period, when compared with that of the negative control (NC), as assessed by CCK-8 assay (Fig. 2B). Furthermore, the overexpression of miR-296-5p significantly decreased colony-forming ability of the NSCLC cells, as determined by cell colony assays (Fig. 2C). Additionally, G1 arrest was mediated by the upregulation of miR-296-5p after 48 h (Fig. 2D). Overall, our findings demonstrated that miR-296-5p exerts a potential inhibitory effect on tumor formation.
miR-296-5p directly targets SGLT2
Having identified miR-296-5p as a regulator in NSCLC tissues, we aimed to identify the miR-296-5p targets that mediate the observed effects. We first identified predicted targets of miR-296-5p using 3 different publicly available miRNA target prediction databases (TargetScan, RNA22 and miRDB). Three genes, namely bromo adjacent homology domain containing 1 (BAHD1), signal transducer and activator of transcription 3 (STAT3) and SGLT2 were among the predicted miR-296-5p targets present in the 3 databases. SGLT2 was selected for further analysis (Fig. 3A). To further verify that SGLT2 is targeted by miR-296-5p, we cloned the 3′-UTR of SGLT2 into the pGL3 vector, downstream of the luciferase open reading frame (ORF). In addition, to destroy the miR-296-5p binding site, we conducted site-directed mutagenesis of the 3′-UTR using the QuikChange Mutagenesis kit (Fig. 3B). Co-transfection of the 3′-UTR vectors with the miR-296-5p mimic led to a decrease in luciferase activity compared to the miR-control transfection of both the A549 and H1299 cells. By contrast, co-transfection of miR-296-5p mimic with the mutated form of the 3′-UTR resulted in no significant change in luciferase activity (Fig. 3C). Finally, we confirmed the silencing of SGLT2 by the miR-296-5p mimic at the mRNA and protein levels. The mRNA levels of SGLT2 decreased in the A549 cells following transfection with the miR-296-5p mimic (Fig. 3D). Of note, the levels of SGLT2 increased in the H1299 cells, mainly owing to miRNAs being involved in the regulation of the post-transcriptional of gene expression. The mechanisms of action are complex. miRNAs function mainly in two ways, one is the degradation of mRNA, and the other is to inhibit translation, playing a role in protein levels. Western blot analysis clearly indicated that the inhibitory effects of miR-296-5p are mediated, at least in part, by the targeting of SGLT2, as the protein expression of SGLT2 markedly decreased in the cells transfected with the miR-296-5p mimic (Fig. 3E and F). On the whole, these data suggest that miRNA can specifically target the 3′-UTR of SGLT2 in the A549 and H1299 cells.
SGLT2 is upregulated in NSCLC tissues and cells
To determine whether the expression of SGLT2 is affected by miR-296-5p, the expression of SGLT2 was detected in 46 tissues (Table I). Among the pairs of tissues, SGLT2 expression was upregu-lated relative to the matched para-cancerous tissues (P<0.05; Fig. 4A), but was not associated with pathological stage (Fig. 4B), sex (Fig. 4C), or tumor size (Fig. 4D). Therefore, based on the Pearson’s correlation coefficient, miR-296-5p was found to negatively correlate with SGLT2 (Fig. 4E).
Finally, we examined the effects of SGLT2 expression in lung cancer patients. We used the Kaplan-Meier Plotter online database (www.kmplot.com/analysis) (Fig. 4F) to generate a Kaplan-Meier survival curve of the patients with NSCLC with a low or high expression of SGLT2. Among the 1,926 cases, patients with NSCLC with a high expression of SGLT2 had lower survival rates.
Effects of the inhibition of SGLT2 on cell proliferation and cell cycle progression
To determine whether the biological effects of miR-296-5p may be attributed to the direct targeting of SGLT2, we silenced its expression using siRNA and detected alterations in cell proliferation and cell cycle progression, as previously described (26,34). Transfection of the NSCLC cells with SGLT2-directed siRNA suppressed the SGLT2 mRNA (Fig. 5A) and protein (Fig. 5B and C) levels, as compared to the control. Moreover, the results of CCK-8 and cell colony assays revealed that the proliferative capacity of the NSCLC cells was significantly downregulated at 72 h following transfection with siSGLT2 (Fig. 5D and E). We also found that at 48 h following SGLT2 knockdown, the proportion of cells in the G0/G1 phase increased as compared with the control (Fig. 5F). Taken together, our data highlight that the observed effects of miR-296-5p on cell proliferation and cell cycle progression are mediated by the targeting of SGLT2.
Discussion
Lung cancer does not have an exact cause, as some environmental factors, such as tobacco, radon, asbestos and other industrial carcinogens may increase the risk of developing lung cancer (8,35,36). NSCLC has a high incidence and high mortality, and has become the focus of research in recent years (37). However, the specific mechanisms of NSCLC remain unclear, and further investigations are required into this matter. The dysregulation of miRNAs has been linked to the development of various types of human cancer. Recently, increasing evidence supports the notion that the aberrant expression of miRNAs plays critical roles in NSCLC occurrence and progression (38,39) miRNAs can function as oncogenes or tumor suppressors (40,41). Our previous studies confirmed that miRNAs, such as miR-34a (32), miR-486-5p (42) and miR-181a-5p(43) can function as tumor suppressor genes, while miR-18a-5p (28) and miR-150 (44) can function as oncogenes in NSCLC.
Previous findings have established miR-296-5p as a tumor suppressor through its ability to suppress cancer cells in different types of cancer (45-48). However, the roles of miR-296-5p in lung cancer tumorigenesis and the underlying mechanisms have not yet been completely reported. Therefore, in this study, we investigated the potential functions of miR-296-5p in the development and progression of NSCLC. Our results revealed that miR-296-5p was downregulated in the majority of the NSCLC patient samples examined and in several NSCLC cell lines. Moreover, we found that the low expression of miR-296-5p was related to tumor size according to case information analysis after measuring the expression of miR-296-5p in 46 pairs of patients by RT-qPCR. When the tumor is small, the expression of miR-296-5p is relatively high and in larger tumors, the expression of miR-296-5p relatively low, which is consistent with the role of miR-296-5p as a tumor suppressor in lung cancer. In addition, our data confirmed miR-296-5p as a tumor suppressor in lung cancer and that it directly targets SGLT2. In the future, we aim to further investigate the roles of miR-296-5p in suppressing invasiveness and the cell migratory capability in vitro and in vivo.
The findings of this study, and other studies shed some light into the role of miR-296-5p in regulating cancer. It has also been found that miR-296-5p plays an important role in diabetes mellitus (DM), which is regulated by SGLT2 (24,49-52). This study confirmed that miR-296-5p can suppress DM by targeting SGLT2 (data not shown). Therefore, miR-296 may have more functions than previously anticipated.
In conclusion, the present study demonstrates that miR-296-5p functions as a tumor suppressor in NSCLC by targeting SGLT2. Our findings provide a further understanding of the potential mechanisms through which miRNAs affect the development and oncogenesis of NSCLC. The findings of this study may aid in the development of more effective treatment strategies for NSCLC. Moreover, miR-296-5p may prove to be a useful prognostic marker for NSCLC.
Funding
This study was funded by the National Natural Science Foundation (grant no. 81601887).
Availability of data and materials
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Authors’ contributions
XIAOTIAN Z and XINJU Z conceived the experiments; XL developed the methodology; PQ and HW analyzed and interpreted the data; ZM and YC were involved in the conception and design of the study and edited the manuscript. All authors have read and approved the final manuscript.
Ethics approval and consent to participate
The use of patient samples was approved by the Ethics Committee of Shanghai Hospital and consent was obtained from all the patients.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Acknowledgments
The authors acknowledge Miss Fatemeh Alsadat Jafari Sheshtamad (Mashhad University of Medical Science, Mashhad, Iran) for the critical reading of the manuscript. The authors would also like to thank her for her valuable comments and suggestions and for the language editing of the article.
References
|
Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J and Jemal A: Global cancer statistics, 2012. CA Cancer J Clin. 65:87–108. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ and He J: Cancer statistics in China, 2015. CA Cancer J Clin. 66:115–132. 2016. View Article : Google Scholar : PubMed/NCBI | |
|
Xu C, Li S, Chen T, Hu H, Ding C, Xu Z, Chen J, Liu Z, Lei Z, Zhang HT, et al: miR-296-5p suppresses cell viability by directly targeting PLK1 in non-small cell lung cancer. Oncol Rep. 35:497–503. 2016. View Article : Google Scholar | |
|
Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, Abraham J, Adair T, Aggarwal R, Ahn SY, et al: Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet. 380:2095–2128. 2012. View Article : Google Scholar : PubMed/NCBI | |
|
Jain RK and Chen H: Spotlight on brigatinib and its potential in the treatment of patients with metastatic ALK-positive non-small cell lung cancer who are resistant or intolerant to crizotinib. Lung Cancer (Auckl). 8:169–177. 2017. | |
|
Goffin J, Lacchetti C, Ellis PM, Ung YC and Evans WK; Lung Cancer Disease Site Group of Cancer Care Ontario’s Program in Evidence-Based Care: First-line systemic chemotherapy in the treatment of advanced non-small cell lung cancer: A systematic review. J Thorac Oncol. 5:260–274. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Gao Y, Gao F, Ma JL, Sun WZ and Song LP: The potential clinical applications and prospects of microRNAs in lung cancer. OncoTargets Ther. 7:901–906. 2014. View Article : Google Scholar | |
|
Kanwal M, Ding XJ and Cao Y: Familial risk for lung cancer. Oncol Lett. 13:535–542. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Ye Y, Li SL and Wang SY: Construction and analysis of mRNA, miRNA, lncRNA, and TF regulatory networks reveal the key genes associated with prostate cancer. PLoS One. 13:e01980552018. View Article : Google Scholar : PubMed/NCBI | |
|
Morales S, De Mayo T, Gulppi FA, Gonzalez-Hormazabal P, Carrasco V, Reyes JM, Gómez F, Waugh E and Jara L: Genetic variants in pre-miR-146a, pre-miR-499, pre-miR-125a, pre-miR-605, and pri-miR-182 are associated with breast cancer Ssusceptibility in a South American Population. Genes (Basel). 9:92018. View Article : Google Scholar | |
|
Tian W, Du Y, Ma Y, Gu L, Zhou J and Deng D: MALAT1-miR663a negative feedback loop in colon cancer cell functions through direct miRNA-lncRNA binding. Cell Death Dis. 9:8572018. View Article : Google Scholar : PubMed/NCBI | |
|
Dua K, Hansbro NG, Foster PS and Hansbro PM: MicroRNAs as therapeutics for future drug delivery systems in treatment of lung diseases. Drug Deliv Transl Res. 7:168–178. 2017. View Article : Google Scholar | |
|
Cho WC: MicroRNAs: Potential biomarkers for cancer diagnosis, prognosis and targets for therapy. Int J Biochem Cell Biol. 42:1273–1281. 2010. View Article : Google Scholar | |
|
Bartels CL and Tsongalis GJ: MicroRNAs: Novel biomarkers for human cancer. Clin Chem. 55:623–631. 2009. View Article : Google Scholar : PubMed/NCBI | |
|
Bowen T, Jenkins RH and Fraser DJ: MicroRNAs, transforming growth factor beta-1, and tissue fibrosis. J Pathol. 229:274–285. 2013. View Article : Google Scholar | |
|
Fu Q, Song X, Liu Z, Deng X, Luo R, Ge C, Li R, Li Z, Zhao M, Chen Y, et al: miRomics and proteomics reveal a miR-296-3p/ PRKCA/FAK/Ras/c-Myc feedback loop modulated by HDGF/ DDX5/β-catenin complex in lung adenocarcinoma. Clin Cancer Res. 23:6336–6350. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Vaira V, Faversani A, Dohi T, Montorsi M, Augello C, Gatti S, Coggi G, Altieri DC and Bosari S: miR-296 regulation of a cell polarity-cell plasticity module controls tumor progression. Oncogene. 31:27–38. 2012. View Article : Google Scholar : | |
|
Savi F, Forno I, Faversani A, Luciani A, Caldiera S, Gatti S, Foa P, Ricca D, Bulfamante G, Vaira V, et al: miR-296/Scribble axis is deregulated in human breast cancer and miR-296 restoration reduces tumour growth in vivo. Clin Sci (Lond). 127:233–242. 2014. View Article : Google Scholar | |
|
Barbagallo D, Piro S, Condorelli AG, Mascali LG, Urbano F, Parrinello N, Monello A, Statello L, Ragusa M, Rabuazzo AM, et al: miR-296-3p, miR-298-5p and their downstream networks are causally involved in the higher resistance of mammalian pancreatic α cells to cytokine-induced apoptosis as compared to β cells. BMC Genomics. 14:622013. View Article : Google Scholar | |
|
Carreras-Badosa G, Bonmatí A, Ortega FJ, Mercader JM, Guindo-Martínez M, Torrents D, Prats-Puig A, Martinez-Calcerrada JM, de Zegher F, Ibáñez L, et al: Dysregulation of placental miRNA in maternal obesity is associated with pre- and postnatal growth. J Clin Endocrinol Metab. 102:2584–2594. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Togliatto G, Dentelli P, Rosso A, Lombardo G, Gili M, Gallo S, Gai C, Solini A, Camussi G and Brizzi MF: PDGF-BB carried by endothelial cell-derived extracellular vesicles reduces vascular smooth muscle cell apoptosis in diabetes. Diabetes. 67:704–716. 2018. View Article : Google Scholar : PubMed/NCBI | |
|
Shivapurkar N, Mikhail S, Navarro R, Bai W, Marshall J, Hwang J, Pishvaian M, Wellstein A and He AR: Decrease in blood miR-296 predicts chemotherapy resistance and poor clinical outcome in patients receiving systemic chemotherapy for metastatic colon cancer. Int J Colorectal Dis. 28:8872013. View Article : Google Scholar | |
|
Wang L, Bo X, Zheng Q, Xiao X, Wu L and Li B: miR-296 inhibits proliferation and induces apoptosis by targeting FGFR1 in human hepatocellular carcinoma. FEBS Lett. 590:4252–4262. 2016. View Article : Google Scholar : PubMed/NCBI | |
|
Gallo LA, Wright EM and Vallon V: Probing SGLT2 as a therapeutic target for diabetes: Basic physiology and consequences. Diab Vasc Dis Res. 12:78–89. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Scafoglio C, Hirayama BA, Kepe V, Liu J, Ghezzi C, Satyamurthy N, Moatamed NA, Huang J, Koepsell H, Barrio JR, et al: Functional expression of sodium-glucose transporters in cancer. Proc Natl Acad Sci USA. 112:E4111–E4119. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Ishikawa N, Oguri T, Isobe T, Fujitaka K and Kohno N: SGLT gene expression in primary lung cancers and their metastatic lesions. Jpn J Cancer Res. 92:874–879. 2001. View Article : Google Scholar : PubMed/NCBI | |
|
Yao Y, Shao J, Wu J, Zhang Q, Wang J, Xiao D and Huang F: The functional variant in the 3′UTR of PTPRT with the risk of esophageal squamous cell carcinoma in a Chinese population. Cell Physiol Biochem. 36:306–314. 2015. View Article : Google Scholar | |
|
Liang C, Zhang X, Wang HM, Liu XM, Zhang XJ, Zheng B, Qian GR and Ma ZL: MicroRNA-18a-5p functions as an oncogene by directly targeting IRF2 in lung cancer. Cell Death Dis. 8:e27642017. View Article : Google Scholar : PubMed/NCBI | |
|
Livak KJ and Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 25:402–408. 2001. View Article : Google Scholar | |
|
Shao Y, Sun Q, Liu X, Wang P, Wu R and Ma Z: tRF-Leu-CAG promotes cell proliferation and cell cycle in non-small cell lung cancer. Chem Biol Drug Des. 90:730–738. 2017. View Article : Google Scholar : PubMed/NCBI | |
|
Zhang B, Ma Z, Li X, Zhang C, Shao Y, Liu Z, Li Y and Jin Y: Tanshinones suppress non-small cell lung cancer through up-regulating miR-137. Acta Biochim Biophys Sin (Shanghai). 48:768–770. 2016. View Article : Google Scholar | |
|
Li YL, Liu XM, Zhang CY, Zhou JB, Shao Y, Liang C, Wang HM, Hua ZY, Lu SD and Ma ZL: MicroRNA-34a/EGFR axis plays pivotal roles in lung tumorigenesis. Oncogenesis. 6:e3722017. View Article : Google Scholar : PubMed/NCBI | |
|
Wang P, Liu X, Shao Y, Wang H, Liang C, Han B and Ma Z: MicroRNA-107–5p suppresses non-small cell lung cancer by directly targeting oncogene epidermal growth factor receptor. Oncotarget. 8:57012–57023. 2017.PubMed/NCBI | |
|
Hine J, Paterson H, Abrol E, Russell-Jones D and Herring R: SGLT inhibition and euglycaemic diabetic ketoacidosis. Lancet Diabetes Endocrinol. 3:503–504. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Brinker TJ, Alfitian J, Seeger W, Groneberg DA, von Kalle C, Enk AH, Herth FJF, Kreuter M, Bauer CM, Gatzka M, et al: A face-aging smoking prevention/cessation intervention for nursery school students in Germany: An appearance-focused interventional study. Int J Environ Res Public Health. 15:152018. View Article : Google Scholar | |
|
Ma H, Chen X, Hu H, Li B, Ying X, Zhou C, Zhong J, Zhao G and Duan S: Hypermethylation of MDFI promoter with NSCLC is specific for females, non-smokers and people younger than 65. Oncol Lett. 15:9017–9024. 2018.PubMed/NCBI | |
|
Cheong HT, Xu F, Choy CT, Hui CWC, Mok TSK and Wong CH: Upregulation of Bcl2 in NSCLC with acquired resistance to EGFR-TKI. Oncol Lett. 15:901–907. 2018.PubMed/NCBI | |
|
Romero-Cordoba SL, Salido-Guadarrama I, Rodriguez-Dorantes M and Hidalgo-Miranda A: miRNA biogenesis: Biological impact in the development of cancer. Cancer Biol Ther. 15:1444–1455. 2014. View Article : Google Scholar : PubMed/NCBI | |
|
Tutar Y: miRNA and cancer; computational and experimental approaches. Curr Pharm Biotechnol. 15:4292014. View Article : Google Scholar : PubMed/NCBI | |
|
Ji W, Sun B and Su C: Targeting microRNAs in cancer gene therapy. Genes (Basel). 8:82017. View Article : Google Scholar | |
|
Ebrahimi A and Sadroddiny E: MicroRNAs in lung diseases: Recent findings and their pathophysiological implications. Pulm Pharmacol Ther. 34:55–63. 2015. View Article : Google Scholar : PubMed/NCBI | |
|
Shao Y, Shen YQ, Li YL, Liang C, Zhang BJ, Lu SD, He YY, Wang P, Sun QL, Jin YX, et al: Direct repression of the oncogene CDK4 by the tumor suppressor miR-486-5p in non-small cell lung cancer. Oncotarget. 7:34011–34021. 2016. View Article : Google Scholar : PubMed/NCBI | |
|
Ma Z, Qiu X, Wang D, Li Y, Zhang B, Yuan T, Wei J, Zhao B, Zhao X, Lou J, et al: miR-181a-5p inhibits cell proliferation and migration by targeting Kras in non-small cell lung cancer A549 cells. Acta Biochim Biophys Sin (Shanghai). 47:630–638. 2015. View Article : Google Scholar | |
|
Wang DT, Ma ZL, Li YL, Wang YQ, Zhao BT, Wei JL, Qi X, Zhao XT and Jin YX: miR-150, p53 protein and relevant miRNAs consist of a regulatory network in NSCLC tumorigenesis. Oncol Rep. 30:492–498. 2013. View Article : Google Scholar : PubMed/NCBI | |
|
Lee H, Shin CH, Kim HR, Choi KH and Kim HH: MicroRNA-296-5p promotes invasiveness through downregulation of nerve growth factor receptor and caspase-8. Mol Cells. 40:254–261. 2017. View Article : Google Scholar : | |
|
Lee KH, Lin FC, Hsu TI, Lin JT, Guo JH, Tsai CH, Lee YC, Lee YC, Chen CL, Hsiao M, et al: MicroRNA-296-5p (miR-296-5p) functions as a tumor suppressor in prostate cancer by directly targeting Pin1. Biochim Biophys Acta. 1843:2055–2066. 2014. View Article : Google Scholar : PubMed/NCBI | |
|
Li T, Lu YY, Zhao XD, Guo HQ, Liu CH, Li H, Zhou L, Han YN, Wu KC, Nie YZ, et al: MicroRNA-296-5p increases proliferation in gastric cancer through repression of Caudal-related homeobox 1. Oncogene. 33:783–793. 2014. View Article : Google Scholar | |
|
Maia D, de Carvalho AC, Horst MA, Carvalho AL, Scapulatempo-Neto C and Vettore AL: Expression of miR-296-5p as predictive marker for radiotherapy resistance in early-stage laryngeal carcinoma. J Transl Med. 13:2622015. View Article : Google Scholar : PubMed/NCBI | |
|
Watanabe A, Choe S, Chaptal V, Rosenberg JM, Wright EM, Grabe M and Abramson J: The mechanism of sodium and substrate release from the binding pocket of vSGLT. Nature. 468:988–991. 2010. View Article : Google Scholar : PubMed/NCBI | |
|
Cramer SC, Pardridge WM, Hirayama BA and Wright EM: Colocalization of GLUT2 glucose transporter, sodium/glucose cotransporter, and gamma-glutamyl transpeptidase in rat kidney with double-peroxidase immunocytochemistry. Diabetes. 41:766–770. 1992. View Article : Google Scholar : PubMed/NCBI | |
|
Vallon V, Rose M, Gerasimova M, Satriano J, Platt KA, Koepsell H, Cunard R, Sharma K, Thomson SC and Rieg T: Knockout of Na-glucose transporter SGLT2 attenuates hyperglycemia and glomerular hyperfiltration but not kidney growth or injury in diabetes mellitus. Am J Physiol Renal Physiol. 304:F156–F167. 2013. View Article : Google Scholar : | |
|
Chao EC and Henry RR: SGLT2 inhibition--a novel strategy for diabetes treatment. Nat Rev Drug Discov. 9:551–559. 2010. View Article : Google Scholar : PubMed/NCBI |
