LncRNA SNHG3 promotes clear cell renal cell carcinoma proliferation and migration by upregulating TOP2A

Experimental Cell Research 384 (2019) 111595

Contents lists available at ScienceDirect

Experimental Cell Research journal homepage: www.elsevier.com/locate/yexcr

LncRNA SNHG3 promotes clear cell renal cell carcinoma proliferation and migration by upregulating TOP2A

T

Chong Zhanga,b, Yan Quc, Haibing Xiaod, Wen Xiaod, Jing Liub, Yunhui Gaob, Manping Lic, Juntian Liua,∗ a

Department of Pharmacology, Xi'an Jiaotong University School of Medicine, Xi'an, 710061, China School of Pharmacy, Xinxiang Medical University, Xinxiang, 453003,China c School of Basic Medical Sciences, Xinxiang Medical University, Xinxiang, 453003, China d Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China b

A R T I C LE I N FO

A B S T R A C T

Keywords: SNHG3 TOP2A miR-139-5p Clear cell renal cell carcinoma

LncRNA plays a vital role in many diseases, and abnormal expression of LncRNA has been reported in many types of tumors. In this study, we analyzed the available public TCGA and GEO databases, and found that the expression of SNHG3 was increased in clear cell renal cell carcinoma (ccRCC), which was positively correlated with many clinicopathological parameters, and the higher expression of SNHG3 predicted worse clinical prognosis. Functional experiments indicated that knockdown of SNHG3 could significantly inhibit the proliferation and metastasis of ccRCC in vitro and in vivo. Subsequently, through luciferase reporter assays, qPCR and rescue experiments, it was found that SNHG3 could bind to miR-139-5p, thereby up-regulating the expression of its target gene TOP2A, and play a role in promoting tumor progression in ccRCC. The correlation analysis showed that there was a significant positive correlation between the expression of SNHG3 and TOP2A, and both of them were significantly negative correlated with the expression of miR-139-5p. Our work suggested that the SNHG3/ miR-139-5p/TOP2A axis plays an important role in the proliferation and metastasis of ccRCC, and was expected to be a new biomarker for diagnosis, prognosis and a target for treatment of ccRCC.

1. Introduction Renal cell carcinoma (RCC) constitutes 5% of adult malignancies and is the second leading cause of death associated with urinary malignancies. It is estimated that about 73,820 new cases and 14,770 deaths of RCC in 2019 in the USA [1]. Clear-cell renal cell carcinoma (ccRCC) is the most common subtype which accounting for 75% of RCC [2], and characterized by high morbidity and mortality. Since it is not sensitive to conventional radiotherapy and chemotherapy, surgery remains the main treatment fashion. Recently, targeted therapy has effectively prolonged the survival time of patients, but the resistance to targeted drugs makes the treatment of ccRCC still a big obstacle [3,4]. Therefore, further investigating the mechanisms underlying ccRCC development and progression, and identifying novel promising therapeutic targets are requisite and pressing. With the advances in high throughput sequencing technology, more and more non-coding RNA has been found. LncRNAs are a group of poorly conserved endogenous RNA molecules longer than 200 nucleotides in length, and little protein coding ability [5]. Emerging evidences

∗

manifested that LncRNAs regulates diversified physiological and pathological processes in cancers, such as proliferation, stemness, differentiation, metastasis, metabolism and resistance and so on [6]. LncRNAs can act as an oncogene or a tumor suppressor in cancers. For example, LncRNA SPRY4-IT1 promotes proliferation and metastasis of bladder cancer cells through up-regulating EZH2 as a miR-101-3p sponges [7]; MALAT1 plays a tumor-suppressive role in glioma by attenuating ERK/MAPK-mediated growth and MMP2-mediated invasiveness [8]; Lnc-DILC binds to the promoter region of IL-6, inhibits the transcription of IL-6 and the activation of IL-6/STAT3 signaling pathway, thus inhibiting the self-renewal of hepatocellular carcinoma stem cells [9]. As a typical LncRNA, SNHG3 (small nucleolar RNA host gene 3) locus in the chromosome 1p35.3, and was implicated in various cancers as a regulator, including hepatocellular carcinoma [10], lung adenocarcinoma [11], ovarian cancer [12], osteosarcoma [13], colorectal cancer [14] and so on. LncRNA SNHG3 regulates invasion and migration of osteosarcoma via SNHG3/miRNA-151a-3p/RAB22A axis [12]; in hepatocellular carcinoma, by modulating the miR-128/CD151

Corresponding author.Department of Pharmacology, Xi'an Jiaotong University School of Medicine, 76 West Yanta Road, Xi'an, 710061, China. E-mail address: [email protected] (J. Liu).

https://doi.org/10.1016/j.yexcr.2019.111595 Received 8 May 2019; Received in revised form 30 August 2019; Accepted 31 August 2019 Available online 07 September 2019 0014-4827/ © 2019 Elsevier Inc. All rights reserved.

Experimental Cell Research 384 (2019) 111595

C. Zhang, et al.

Fig. 1. SNHG3 is upregulated and associated with various clinicopathological parameters in ccRCC (A) The expression of SNHG3 in 524 ccRCC tissues and 72 normal tissues based on data from the TCGA database. (B)The expression level of SNHG3 based on data from GEO dataset (GSE53757) (n = 72). (C) Relative expression of SNHG3 in 36 pairs ccRCC tumor tissues and adjacent normal tissues. (D, E, F) The expression level of SNHG3 was positively correlated with different clinicopathological features: distant metastasis, T stage, pathological TNM stage and histologic grade in ccRCC. (G, H) The Kaplan–Meier curves of SNHG3 in ccRCC for both OS and DFS. **P < 0.01, ***P < 0.001, ****P < 0.0001.

that upregulared SNHG3 correlated with the TNM stage and distant metastasis. The Kaplan–Meier method analysis which was used to evaluate the prognostic value of SNHG3 for ccRCC patients showed that higher expression of SNHG3 suggested worse overall survival (OS) and disease-free survival (DFS). Functionally, SNHG3 knockdown inhibited ccRCC proliferation, migration, invasion and promoted cell apoptosis in vitro and in vivo. Mechanistically, SNHG3 sponged miR-139-5p and hence increased the TOP2A expression in ccRCC. Our results suggested that SNHG3 might be an oncogene in ccRCC and could be considered as a potential diagnostic and therapeutic target for ccRCC.

Table 1 The characteristic of SNHG3 in clear cell renal cell carcinoma. Characteristic

Gender Age T N M Stage Grade

Total (n = 524)

Male Female ≤60 > 60 T1&T2 T3&T4 N0,Nx N1 M0,Mx M1 1,2 3,4 1,2, X 3,4

339 185 262 262 337 187 509 15 445 79 319 205 244 280

LncRNA-SNHG3 Low(262)

High(262)

165 97 129 133 181 81 257 5 233 29 173 89 137 125

174 88 133 129 156 106 252 10 212 50 146 116 107 155

p Value

0.411 0.727 0.023

2. Materials and methods

0.190 0.010

2.1. Cell culture

0.016

The human renal cancer cell lines ACHN, A498, Caki-1, and immortalized renal tubular epithelial cell HK-2 were cultured in DMEM high glucose medium supplemented with 10% fetal bovine serum and 1% penicillin–streptomycin, in a humidified atmosphere of 5% CO2 maintained at 37 °C.

0.009

pathway, SNHG3 can induces EMT and sorafenib resistance [10]. However, there are not any reports on the function and mechanism of SNHG3 in RCC up to now. In this work, we identified the increased expression of SNHG3 in renal cell cancer lines and tissues. Bioinformatics analysis demonstrated

2.2. Clinical sample preparation Altogether 36 paired ccRCC and adjacent tissue samples were 2

Experimental Cell Research 384 (2019) 111595

C. Zhang, et al.

Table 2 Univariate and multivariate analyses of clinicopathological factors for overall surviva. Risk factors

SNHG3 expression Age Gender Grade T N M Stage

Univariate analysis

Multivariate analysis

HR

P-value

95% CI

HR

P-value

95% CI

1.805 1.681 0.921 1.641 1.063 1.718 2.330 1.866

0.000 0.001 0.619 0.008 0.849 0.109 0.000 0.093

1.311–2.286 1.228–2.301 0.667–1.273 1.138–2.365 0.567–1.993 0.886–3.253 1.310–2.872 1.204–5.064

1.850 1.690

0.000 0.001

1.349–2.537 1.239–2.306

1.644

0.007

1.142–2.365

2.320 2.046

0.000 0.000

1.594–3.376 1.381–3.030

2.6. Luciferase assays

collected from patients who undergoing radical nephrectomy in Union Hospital, Wuhan, China, during the period of 2013–2017. Corresponding adjacent noncancerous tissues were acquired at least 5 cm away from the cancerous site. The study protocol was approved by the ethics committee of Xi'an Jiaotong University, and written informed consent was obtained from all subjects.

In brief, ACHN and HEK-293T cells were co-transfected with psicheck2 luciferase vectors containing the 3′ untranslated region of target genes with miR-139-5p mimic or mutant mimic or NC. Forty-eight hours after transfection, luciferase activity was measured using a DualLuciferase Reporter Assay (Promega, Madison, USA) according to the manufacturer's instructions.

2.3. Bioinformatics analysis

2.7. Cell proliferation, colony formation, EdU analysis, and transwell assays

RNA sequencing data and clinical data about gender, age, metastasis, TNM stages, OS, DFS of ccRCC patients were downloaded from The Cancer Genome Atlas (TCGA) database (genome-cancer.ucsc.edu/). In this study, OS standed for the time between disease diagnosis and death for any reason, while DFS was defined as the time from disease diagnosis or surgery to recurrence. In addition, raw gene expression profile was obtained from Gene Expression Omnibus (GEO53757) database (http://www.ncbi.nlm.nih.gov/geo/) for further validation. Candidate mirRNA interacting with SNHG3 and its target genes were searched through three publicly available algorithms, starBase (http:// starbase.sysu.edu.cn/), miRcode (http://www.mircode.org/) and LncRNASNP2 (bioinfo.life.hust.edu.cn/lncRNASNP2). The gene set enrichment analysis (GSEA) was used to assess the SNHG3 pathways and gene sets enriched in the ccRCC pathogenesis in patients from TCGA database.

After counting, the corresponding ACHN and Caki-1 cells were plated in 96-well plates and detected cell viability using the CCK8 assays (Dojindo Molecular Technologies, Inc, Rockville, MD, USA). For the colony formation assay, two weeks after 1000 cell seeding into sixwell plates, surviving colonies(> 50 cells per colony) were visualized, stained and photographed. The EdU assay kit was purchased from RiboBio (Guangzhou, China) and conducted based on the manufacturer's instructions. Migration and invasion assays were performed as previously described [15]. 2.8. Flow cytometry After the transfected cells were harvested, fluorescein isothiocyanate (FITC) and Annexin V were used to stain cells according to the manufacturer's protocol (FITC Annexin V Apoptosis Detection Kit, BD Biosciences) and a flow cytometric analysis was performed.

2.4. Oligonucleotide, lentivirus, plasmid, and shRNA The small hairpin RNA (shRNA) of SNHG3 was synthesized and cloned into the plko. l plasmid (Addgene, Cambridge, USA). Primers were listed as follows: sh-SNHG3-1 5′- CCGGGCACTGGCTGCCAACAT AAATCTCGAGATTTATGTTGGCAGCCAGTGCTTTTTG -3′, 3′-AATTCA AAAAGCACTGGCTGCCAACATAAATCTCGAGATTTATGTTGGCAGCCA GTGC -5′; sh-SNHG3-2 5′- CCGGGCTAGGAATGCACATTCTTTCCTCGA GGAAAGAATGTGCATTCCTAGCTTTTTG-3′, 3′-AATTCAAAAAGCTAGG AATGCACATTCTTTCCTCGAGGAAAGAATGTGCATTCCTAGC-5′. MicroRNA mimics, inhibitors and negative control were synthesized by RiboBio (Guangzhou, China). TOP2A overexpression plasmid was purchased from Vigene (Shandong, China).

2.9. Western blot assay Proteins were extracted by RIPA (Beyotime Institute of Biotechnology) lysis buffer adding with PMSF and protease inhibitor cocktail. Forty micrograms protein lysates were separated using SDSPAGE gel and transferred to a PVDF membrane (Roche). After an hour of skimmed milk block, the membrane was incubated with specific primary antibodies overnight. The membranes were then washed and incubated with secondary antibodies (Proteintech, Wuhan) at room temperature for 2 h. Antibodies against CDK-6 (1:1000; #13331), Ccaspase-3(1:1000; #9662), N-cadherin (1:1000; #13116), E-cadherin (1:1000; #3195), and Vimentin (1:1000; #5741) were purchased from Cell Signaling Technology. Antibodies against Bcl-2(1:500; PAA778Hu01), Bax (1:500; PAB343Hu01) were purchased from CloudClone (Wuhan). Antibodies against TOP2A (1:500; CY5008) were purchased from Abways (Shanghai). Antibodies against β-actin (1:10000; 60008-1) were purchased from Proteintech (Wuhan).

2.5. Quantitative real-time PCR The extraction of all RNA from tissues and cells were conducted with the TRIzol reagent (Invitrogen, Carlsbad, CA) according to the manufacturer's instructions. The purity and concentration of the RNA solution was measured with the NanoDrop 2000 spectrophotometer (NanoDrop Technologies, Wilmington, USA). Real-time PCR using SYBR Green Real-Time PCR Master Mix (Roche, Basel, Switzerland) was conducted using the LightCycler 480II qPCR System (Roche, Basel, Switzerland). Primers were listed as follows: SNHG3 5′-AATCGATGGT AGCAACGGGA-3′, 3′-CACCTCCCCTATGCCAGTAG-5′; TOP2A 5′-TGGT GGCAAGGATTCTGCTA-3′, 3′-TCACGCACATCAAAGTTGGG-5′; GAPDH 5′- CCTTCATTGACCTCAACTACA-3′, 3′-GCTCCTGGAAGATGGTGAT-5′.

2.10. Xenograft subcutaneously and tail intravenous injection Male BALB/C nude mice between four and five weeks old purchased from Beijing Vital River Laboratory Animal Technology Co. Ltd. were injected subcutaneously with a total of 2 × 106 prepared cells. And 3

Experimental Cell Research 384 (2019) 111595

C. Zhang, et al.

Fig. 2. Knockdown of SNHG3 inhibits ccRCC cell proliferation in vitro (A) GSEA assays for the correlation of proliferation, DNA replication and the expression of SNHG3 according to the TCGA database. NES, normalized enrichment score. FDR < 25%, P < 0.05 was considered statistically significant. (B) The expression of SNHG3 in three ccRCC cell lines (ACHN, A498 and Caki-1) and normal renal tubular epithelial cell line (HK-2). (C) Relative SNHG3 expression following SNHG3 knockdown in ACHN and Caki-1 cells by qRT-PCR assay. (D) CCK-8 assays in ACHN and Caki-1 cells after knockdown of SNHG3. (E, F) EdU (Scale bars: 50 μm) and colony formation assays in ACHN and Caki-1 cell after knockdown of SNHG3. (G) GSEA assays for the correlation of DNA repair, apoptosis and the expression of SNHG3 according to the TCGA database. (H) Flow cytometry assays for the apoptosis rates of ACHN and Caki-1 cells after knockdown of SNHG3. (I) Western blot results for the protein levels of indicated molecules in the SNHG3-knockdown cells. *P < 0.05, **P < 0.01.

2.11. Statistical analysis

nude mouse were injected by tail vein to construct metastasis model. Tumor weight and volume was measured, and H&E staining and immunohistochemical staining were performed on tumor and liver tissues of mice. All animal experiments were performed in accordance with animal protocols approved by the Institutional Animal Use and Care Committee of Xi'an Jiaotong University.

All statistical analyses were carried out using SPSS 22.0 (IBM SPSS, Chicago, IL) and Graphpad Prism 6.0 (GraphPad Software, San Diego, California, USA). Data are presented as mean ± SEM. All experiments were repeated three times. Student's two-tailed t-test was used to analysis the significant differences. Pearson's correlation coefficient was used to measure the linear relationship, log-rank test was used to

4

Experimental Cell Research 384 (2019) 111595

C. Zhang, et al.

Fig. 3. Knockdown of SNHG3 inhibits ccRCC cell migration and invasion in vitro (A) GSEA assays for the correlation of metastasis, epithelial mesenchymal transition and the expression of SNHG3 according to the TCGA database. (B, C) Migration and invasion assays in ACHN and Caki-1 cells after knockdown of SNHG3. (D) Wound-healing assays in ACHN and Caki-1 cells after knockdown of SNHG3. (E) Western blot results for the protein levels of indicated molecules in the SNHG3knockdown cells. **P < 0.01, ***P < 0.001.

GEO dataset (GSE53757). According to the microarray results of 72 pairs of RCC specimens [16], the expression of SNHG3 were also upregulated in RCC (P < 0.001; Fig. 1B). To verify SNHG3 expression in ccRCC, we extracted the RNA from 36 pairs ccRCC tissues and adjacent normal tissue specimens, and quantitatively analyzed the SNHG3 expression level using qRT-PCR assay. Our results also demonstrated that the relative expression of SNHG3 were elevated in ccRCC tissues (Fig. 1C). We further evaluated the relevance between SNHG3 expression and clinicopathological parameters in ccRCC. By analyzing the TCGA-KIRC database, the expression level of SNHG3 was positively correlated with distant metastasis, T stage, pathological TNM stage, and histologic grade in ccRCC (Fig. 1D and E). Furthermore, higher SNHG3

analyze the SNHG3 expression and OS or DFS. In all results, P < 0.05 was considered statistically significant.

3. Results 3.1. SNHG3 is upregulated and associated with various clinicopathological parameters in ccRCC The analysis of RNA-sequence data of 72 normal tissue and 524 ccRCC specimens in TCGA database indicated that the expression of SNHG3 was elevated in ccRCC tissues compared with in the normal tissues (Fig. 1A). Subsequently, we analyzed SNHG3 expression using a 5

Experimental Cell Research 384 (2019) 111595

C. Zhang, et al.

Fig. 4. Knockdown of SNHG3 inhibits ccRCC cell growth and metastasis in vivo (A) Photographs of tumors excised six weeks after subcutaneously injected with shLacz/sh-SNHG3 stably transfected ACHN cells (n = 6). (B, C) Tumor weight and mean tumor volume were measured on the indicated days. (D) Relative SNHG3 expression were detected in tumor xenografts formed with indicated cells. (E) Representative images of H&E and IHC analysis of Ki-67 in tumor xenografts formed with indicated cells. Ki-67 index calculated as the percentage of Ki-67 positive cells. Scale bars: 50 μm. (F) Representative images of H&E staining of metastatic nodules in the livers in the tail vein metastasis model with indicated cells. Scale bars: 1000 μm and 100 μm *P < 0.05, **P < 0.01, ***P < 0.001.

expression was found in T stage IV and III, when contrasted to T stage I and II, and the same results were showed in pathological TNM stage and the histologic grade (Fig. 1F). However, the SNHG3 expression was not significantly associated with gender, age and the N stage in ccRCC (Table 1). To determine whether SNHG3 expression was associated with ccRCC patients' survival, we employed Kaplan-Meier method to analyze the association of SNHG3 expression with ccRCC patients OS and DFS from TCGA-KIRC database. The results indicated that the OS and DFS time of ccRCC patients with higher SNHG3 expression were significantly shorter than those with lower SNHG3 expression. (Fig. 1G and H). We then evaluated whether SNHG3 expression was independent of other clinicopathological parameters in predicting ccRCC patients’ OS. Univariate and multivariate COX hazard regression models were employed using SNHG3 expression, age, gender, T stage, N stage, M stage, G stage, TNM stage as risk factors, and the results made clearly that SNHG3 expression could serve as an independent prognostic factor for ccRCC (Table 2). These results reveal that the upregulation of SNHG3 may play a critical part in the progression of ccRCC.

control nonspecific shRNA (Lacz) were prepared to stably inhibit SNHG3 expression in two ccRCC cell lines ACHN and Caki-1 (Fig. 2C). Then, CCK-8 assays revealed that knockdown SNHG3 inhibited ACHN and Caki-1 cell growth (Fig. 2D), and the Ethynyl deoxy Uridine (EdU) dye assays exhibited a reduced proliferation rate in the SNHG3 silenced RCC cells (Fig. 2E). Similarly, colony formation assays demonstrated that silencing SNHG3 decreased the clone forming ability of RCC cells (Fig. 2F). Additionally, GSEA results also indicated that high SNHG3 expression exhibited significant relations with the expression of DNA repair and apoptosis-related genes in ccRCC (Fig. 2G). We then adopted flow cytometry cell apoptosis analysis to assess the apoptotic rates of SNHG3 knockdown cells. As speculated, SNHG3 knockdown significantly increased the proportion of apoptotic cells (Fig. 2H). Moreover, western blotting results indicated that the expression levels of proliferation related protein CDK6 was decreased and the apoptosisrelated proteins Bax was increased, while Bcl-2 decreased in SNHG3 silenced RCC cells (Fig. 2I). Overall, the above results demonstrate that SNHG3 can influence ccRCC cell growth in vitro.

3.2. Knockdown of SNHG3 inhibits ccRCC cell proliferation in vitro

3.3. Knockdown of SNHG3 inhibits ccRCC cell migration and invasion in vitro

To further explore the role of SNHG3 in ccRCC, Gene Set Enrichment Analysis (GSEA) was employed in the TCGA database to identify SNHG3-associated biological signaling pathways in ccRCC on an unbiased basis, and the result indicated that DNA replication which was a proliferation-associated indexes, and the proliferation gene signatures were most correlated with the high SNHG3 expression group compared with patients with low SNHG3 expression (Fig. 2A). Subsequently, we measured the SNHG3 expression in RCC cell lines: ACHN, A498, Caki-1 and in the human immortalized renal tubular epithelial cell line HK-2. qRT-PCR result demonstrated a significant increase in the SNHG3 expression in RCC cell lines compared with in the HK-2 cell, and the ACHN and Caki-1 cell lines exhibited the higher expression (Fig. 2B). Two lenti-viruses carrying shRNA against SNHG3 and a

Subsequently, the effects of SNHG3 on ccRCC metastasis were explored. The GSEA analysis demonstrated that high SNHG3 expression was positively correlated with the expression of metastasis-related genes and epithelial mesenchymal transition gene signatures (Fig. 3A). Transwell assays indicated that SNHG3 silenced ccRCC cells owned the less migration and invasion abilities compared with the control ccRCC cells (Fig. 3B and C). Similarly, the wound-healing assays revealed that ccRCC cells transfected with SNHG3 shRNAs could suppress the scratch wound closure capacity than the negative control (Lacz) cells (Fig. 3D). In addition, western blotting results indicated that the protein level of the mesenchymal markers Vimentin and N-cadherin were decreased, while the epithelial marker E-cadherin was significantly increased in 6

Experimental Cell Research 384 (2019) 111595

C. Zhang, et al.

Fig. 5. SNHG3 acts as a molecular sponge for miR-139-5p in ccRCC (A) Three prediction software programs (starBase, miRcode and LncRNASNP2) were used to screen of candidate miRNAs molecules that could potentially target SNHG3. (B) Schematic of predicted binding sites between miR-139-5p and SNHG3 and the mutant sequence of miR-139-5p. (C) Relative expression of SNHG3 was detected after transfection with miR-139-5p mimics or its inhibitor in ACHN cells. (D) Luciferase reporter assays of psi-SNHG3 co-transfected with miR-139-5p mimics, its mutant or inhibitor in HEK293T and ACHN cells. (E, F, G) CCK-8 assays, EdU assays and transwell assays for the indicated cells. (H) The correlation between the expression of SNHG3 and miR-139-5p in ccRCC. (I, J) The expression level of miR139-5p in ccRCC tissues (Tumor vs Normal) and the paired tissues based on data from the TCGA database. (K, L) The Kaplan–Meier curves of miR-139-5p in ccRCC for both OS and DFS. *P < 0.05, **P < 0.01, ****P < 0.0001.

SNHG3 knockdown ccRCC cells (Fig. 3E). Taken together, these results reveal that SNHG3 can affect ccRCC cell migration and invasion in vitro.

group (Fig. 4F). These findings suggest that knockdown SNHG3 expression inhibits tumor growth and metastasis in vivo, which is consistent with its biological functions in vitro.

3.4. Knockdown of SNHG3 inhibits ccRCC cell growth and metastasis in vivo

3.5. SNHG3 acts as a molecular sponge for miR-139- 5p in ccRCC In order to investigate the potential mechanism of SNHG3 in ccRCC, we used three prediction software programs (starBase, miRcode and LncRNASNP2 tools) to screen of candidate miRNAs molecules that could potentially target SNHG3. As a result, we only found miR-139- 5p predicted by all the three tools that could bind to SNHG3 (Fig. 5A and B). After transfection with miR-139-5p in ACHN cells, the expression of SNHG3 was decreased significantly, while increased after inhibiting miR-139-5p with its inhibitor (Fig. 5C). Then, we constructed a luciferase reporter vectors (psi-SNHG3) of wild-type SNHG3 to psicheck2 vector, and also designed a miR-139-5p mutant that wouldn't bound with SNHG3. Dual-luciferase reporter assays in HEK293T and ACHN cells indicated that co-transfection of psi-SNHG3 together with miR139-5p mimics, but not the mutant significantly decreased the

To further explore whether SNHG3 affects tumorigenesis and metastasis in vivo, ACHN cells stably transfected with sh-Lacz/sh-SNHG3 were injected into nude mice subcutaneously or intravenously. We identified that there was a dramatic decrease in tumor weight and volume in the sh-SNHG3 group compared with sh-Lacz group (Fig. 4A, B and 4C). And after the mice were sacrificed at the end of the experiment, the SNHG3 expression measured in the sh-Lacz group was higher than that in the SNHG3 knockdown group (Fig. 4D). What's more, IHC analysis revealed that the tumors developed from sh-SNHG3 cells showed less Ki-67 expression than tumors formed from sh-Lacz cells (Fig. 4E). Besides, the number of liver metastatic nodules formed from sh-SNHG3 group was smaller compared with that in the sh-Lacz 7

Experimental Cell Research 384 (2019) 111595

C. Zhang, et al.

Fig. 6. TOP2A directly binds to miR-139-5p and associated with a poor prognosis with significantly upregulated in ccRCC (A) Schematic of predicted binding sites between miR-139-5p and TOP2A and the mutant sequence of miR-139-5p. (B) The relative expression of TOP2A was detected after transfection with miR-139-5p mimics or its inhibitor in ACHN cells. (C) Luciferase reporter assays of psi-TOP2A co-transfected with miR-139-5p mimics, its mutant or inhibitor in HEK293T and ACHN cells. (D, E) The mRNA and protein expression of TOP2A was measured for the indicated cells. (F) The correlation between the expression levels of TOP2A, miR-139-5p and SNHG3 (G, H) The expression level of TOP2A in ccRCC tissues compared with in adjacent normal tissues in GEO cohort GSE53757 and TCGA database. (I)The ROC curves of TOP2A (AUC = 0.9290 95% CI: 0.8840 to 0.9941; p < 0.001) in ccRCC. (J) The expression level of TOP2A was positively correlated with distant metastasis in ccRCC. (K) The Kaplan–Meier curves of TOP2A in ccRCC for both OS and DFS. *P < 0.05, **P < 0.01, ****P < 0.0001.

promotes ccRCC proliferation and metastation by sponging miR-1395p.

luciferase activities, while miR-139-5p inhibitor promoted luciferase activities compared with the control group (Fig. 5D). To further explore whether the functions of SNHG3 were relied on sponging miR-139-5p in ccRCC, ACHN cells stably transfected with sh-SNHG3 or sh-Lacz were transfected with miR-139-5p inhibitor or a NC of the inhibitor. CCK-8 assays and EdU assays demonstrated that miR-139-5p downregulation could rescue the growth inhibition caused by SNHG3 knockdown (Fig. 5E and F). And the transwell assays showed that the decrease in migration and invasion abilities with sh-SNHG3 transfection could be partially attenuated by miR-139-5p inhibitor (Fig. 5G). Besides, we conducted a correlation analysis based the TCGA-KIRC database, and the results revealed that there was a negative correlation between the expression of SNHG3 and miR-139-5p in ccRCC (Fig. 5H). After that we examined the expression of miR-139-5p in TCGA and found that miR139-5p existed lower expression in ccRCC tissues (Tumor vs Normal, 506 vs 71) (Fig. 5I) and the paired tissues (paired tumor vs paired normal, 71 vs 71) (Fig. 5J). The Kaplan-Meier survival analysis indicated that the OS and DFS time of ccRCC patients with lower miR139-5p expression were significantly shorter than those with higher miR-139-5p expression (Fig. 5K, L). These results indicate that SNHG3

3.6. TOP2A directly binds to MiR-139-5p and associated with a poor prognosis with significantly upregulated in ccRCC The functions of microRNAs mostly depend on their downstream target genes. Using the online software including starbase and mirDB, we found that miR-139-5p could bind to the 3′UTR region of TOP2A by bioinformatics analysis (Fig. 6A). In addition, as previously reported, TOP2A was the target gene of miR-139-5p in pancreatic cancer [17]. Thus we transfected ACHN cells with miR-139-5p mimics or inhibitor and its negative control, respectively, the expression of TOP2A decreased or increased accordingly (Fig. 6B). And then, luciferase reporter vector psi-TOP2A containing the 3′UTR of TOP2A was constructed. Dual luciferase reporter assays in HEK-293T and ACHN cells showed that miR-139-5p decreased while its inhibitor increased the luciferase activities. We also noticed that mutations brought into the binding sequence of miR-139-5p with TOP2A (Fig. 6A) abolished its suppressive effects (Fig. 6C). Meanwhile, the effects of SNHG3/miR-139-5p axis on 8

Experimental Cell Research 384 (2019) 111595

C. Zhang, et al.

Fig. 7. SNHG3 positively regulated the miR-139-5p target gene TOP2A in ccRCC. (A) CCK-8 assays for the indicated ACHN cells. (B) EdU (Scale bars: 50 μm) assays for the proliferation of indicated ACHN cells. (C) Transwell assays for the migration and invasion abilities of indicated ACHN cells. (D) Western blot results for the protein levels of indicated molecules in ACHN cells. *P < 0.05, **P < 0.01.

Fig. 8. The connection between SNHG3, miR-139-5p, TOP2A and ccRCC. (A)The comparison between levels of TOP2A in tumors with high level of SNHG3 and tumors with low levels of SNHG3 based on data from the TCGA database. (B) The comparison between levels of TOP2A in tumors with high level of miR-139-5p and tumors with low levels of miR-139-5p based on data from the TCGA database. (C) The survival outcome of different SNHG3 expression level in the high TOP2A group in the TCGA-KIRC database. (D) The survival outcome of different SNHG3 expression level in the low TOP2A group in the TCGA-KIRC database. (E) The survival outcome of different miR-139-5p expression levels in the high TOP2A group in the TCGA-KIRC database. (F) The survival outcome of different miR-139-5p expression levels in the low TOP2A group in the TCGA-KIRC database. *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

9

Experimental Cell Research 384 (2019) 111595

C. Zhang, et al.

marker of cancer stem cells [26]. In colorectal cancer, the expression of MALAT1 is elevated, and it could interact with microRNA-218 to increase the expression level of EZH2, thus promoting its tolerance to oxaliplatin and epithelial-mesenchymal transformation [27]. In this study, we analyzed the TCGA database and found that SNHG3 was overexpressed in ccRCC, and the upregulation of SNHG3 in ccRCC was further confirmed in GEO database (GSE53757) and 36 pairs of ccRCC specimens. We also noticed that the expression of SNHG3 raised remarkably with the increase of grade and stage in ccRCC. Besides, higher SNHG3 expression indicated poorer prognosis and shorter survival of ccRCC. GSEA analysis indicated that high SNHG3 expression was highly correlated with proliferation, DNA replication, apoptosis, metastasis and epithelial-mesenchymal transition pathway in ccRCC based on the TCGA database. Functional experiments demonstrated that knockdown of SNHG3 significantly impaired ccRCC growth and metastasis both in vitro and in vivo. In addition, the silencing of SNHG3 could also promote ccRCC apoptosis. LncRNA could play a role through different mechanisms, among which competitive endogenous RNA (ceRNA) hypothesis was studied more extensively [15]. It has been proposed that: all RNA transcripts with binding sites of microRNAs can competently bind to the same microRNAs, and then regulate each other's expression at the posttranscriptional level, which was called ceRNA [28]. Recently, many LncRNA molecules have been reported to play a role through the ceRNA mechanism by competitively binding common miRNAs [29,30]. It has been reported that SNHG3 can competitively bind with miR-151a-3p and regulate RAB22A expression in osteosarcoma or with miR-128 and regulate CD151 in hepatocellular carcinoma [10,13]. To elucidate the possible molecular mechanism of SNHG3 in ccRCC progress, bioinformatics analysis was conducted to explore the potential target gene of SNHG3, and only the miR-139-5p were predicted by all three tools. MiR-139-5p expression levels had been found to be downregulation in different cancers such as hepatocellular carcinoma [31], colorectal cancer [32], prostate cancer [33], and to be involved in a variety of functions including metastasis, proliferation, drug resistance and so on. Through luciferase assays, qPCR analysis and rescue experiments, we found that SNHG3 could bind to miR-139-5p, and the expression of miR-139-5p was negatively correlated with the SNHG3 in ccRCC. The miR-139-5p expression in ccRCC was also decreased and was significantly correlated with poor prognosis. Topoisomerase II Alpha (TOP2A) localized on chromosome 17, is an enzyme that controls and alters the topological state of DNA. It had been reported that TOP2A functions as the target for several anticancer agents [34], and a variety of mutations in this gene had been associated with the development of drug resistance. It can also promote proliferation and epithelial–mesenchymal transition in cancers [35]. In pancreatic cancer, TOP2A was up-regulated and promoted tumor metastasis through activating β-catenin pathway and EMT process [17]. In colon cancer, TOP2A mediated T-cell factor dependent EMT transcription [35], and its overexpression not only associated with perineural invasion and poorer differentiation, but also an independent prognostic biomarker for patients with esophageal squamous cell [36]. Parker AS et al. reported that higher TOP2A expression was an independent marker of increased risk of cancer-specific death in ccRCC patients [37], and TOP2A was also a target gene of miR-139 that had been reported [17]. According to the databases of TCGA and GSE3757, TOP2A exhibited higher expression in ccRCC and was correlated with poorer prognosis, and it also had the ability to distinguish ccRCC patients from healthy individuals based the ROC curves analysis. And there was a significant positive correlation between TOP2A and SNHG3 expression, and a negative correlation between TOP2A and miR-139-5p expression. Our findings also demonstrated that TOP2A bound to miR-139-5p, thus mediating the roles of SNHG3 in promoting proliferation and metastasis of ccRCC. Besides, numerous studies have shown that over-expression of TOP2A is a factor of poor prognosis for many tumors, and according to our analysis of TCGA-KIRC database, whether in the high or low

TOP2A expression was further monitored. The qPCR and western blot results showed that SNHG3 knockdown could inhibit the expression of TOP2A, whereas miR-139-5p inhibitor could relieve the inhibition of TOP2A by SNHG3 knockdown (Fig. 6D and E). Furthermore, we observed that the expression of TOP2A was negatively correlated with miR-139-5p and positively correlated with SNHG3 remarkably in ccRCC in TCGA database (Fig. 6F). Besides, TOP2A was found significantly upregulated in ccRCC in GEO cohort GSE53757 and TCGA database (Fig. 6G and H), and TOP2A mRNA level could efficiently discriminate RCC tissues from normal tissues, yielding an AUC of 0.9290 (95% CI: 0.8840 to 0.9740; p < 0.0001) via the receiver operating characteristic (ROC) curves (Fig. 6I). Moreover, the expression level of TOP2A was positively correlated with distant metastasis (Fig. 6J), and higher TOP2A expression predicted shorter OS and DFS (Fig. 6K). 3.7. SNHG3 positively regulated the miR-139-5p target gene TOP2A in ccRCC To further explore whether oncogenic functions of SNHG3 were mostly dependent on TOP2A, we carried out a series of rescue experiments. The CCK-8 assays and EdU assays showed that TOP2A overexpression could promote ccRCC cells proliferation and relive the growth inhibition caused by SNHG3 knockdown (Fig. 7A and B). Moreover, transwell assays also indicated that TOP2A upregulation could increase the migration and invasion abilities of ccRCC cells, and this increase could be partially eliminated when SNHG3 was downregulated (Fig. 7C). We proceeded to examine whether upregulation of TOP2A influenced the expression of the proliferation and EMT related molecules. As revealed in Fig. 7D, western blotting assays showed that the overexpression of TOP2A could increase the protein levels of CDK6, Vimentin, N-cadherin, and decrease the protein levels of E-cadherin, and this effect could be rescued by SNHG3 knockdown. These data suggest that SNHG3 contributes to ccRCC proliferation and metastasis through regulating TOP2A. 3.8. The connection between SNHG3, miR-139-5p, TOP2A and ccRCC As TOP2A is a factor of poor prognosis for many tumors, we have made a comparison between levels of TOP2A in tumors with high level of miR-139-5p and tumors with low levels of miR-139-5p. The results showed that the expression level of TOP2A increased when SNHG3 was high, and decreased when SNHG3 was low (Fig. 8A). On the contrary, the expression level of TOP2A decreased when miR-139-5p was high and increased when miR-139-5p was low (Fig. 8B). And whether in the high or low group of TOP2A expression, the higher of SNHG3 level, the worse the survival outcome (Fig. 8C and D); similarly, the higher the expression level of TOP2A and the lower of miR-139-5p, the worse the survival outcome (Fig. 8E). However, when TOP2A was low, the expression level of miR-139-5p had no significant effect on survival (Fig. 8F). 4. Discussion There is increasing evidence that LncRNA plays an important role in the development of many types of diseases, such as hypertension [18], schizophrenia [19] and myocardial infarction [20]. Accumulating researches have also shown that LncRNA participates in numerous biological processes and plays crucial roles in the progress of cancer diseases [21–24]. For example, LncRNA MRCCAT1 is highly expressed in metastatic RCC. It could recruit PRC2 to NPR3 promoter region, so as to inhibit NPR3 expression, activate downstream p38-MAPK signaling pathway, and promote the proliferation and metastasis of RCC [25]. In breast cancer, the ribonucleoprotein complex composed of LncRNA MALAT1 and RNA-binding protein HuR bind to the promoter region of CD133 gene and down-regulated the expression of CD133, a surface 10

Experimental Cell Research 384 (2019) 111595

C. Zhang, et al.

group of TOP2A expression, the higher of SNHG3 level, the worse the survival outcome, this provided a more compelling link between the expression of SNHG3, TOP2A and poor tumor prognosis in ccRCC. In summary, our study identified that SNHG3 expression was upregulated in RCC cells and tissues. High expression of SNHG3 was associated with ccRCC progression and worse clinical prognosis. SNHG3 could promote ccRCC cell proliferation and metastasis through miR139-5p dependent TOP2A regulation. Besides, SNHG3 could accelerate the progression of ccRCC through other molecular mechanisms that have not yet been investigated, which need our further effort. However, these findings suggest that SNHG3 would provide a potential diagnostic and therapeutic target for ccRCC.

[14] W. Huang, Y. Tian, S. Dong, Y. Cha, J. Li, X. Guo, et al., The long non-coding RNA SNHG3 functions as a competing endogenous RNA to promote malignant development of colorectal cancer, Oncol. Rep. 38 (2017) 1402–1410. [15] Y. Qu, H. Xiao, W. Xiao, Z. Xiong, W. Hu, Y. Gao, et al., Upregulation of MIAT regulates LOXL2 expression by competitively binding MiR-29c in clear cell renal cell carcinoma, Cell. Physiol. Biochem. : Int. J. Exp. Cell. Physiol., Biochem., Pharmacol. 48 (2018) 1075–1087. [16] C.A. von Roemeling, D.C. Radisky, L.A. Marlow, S.J. Cooper, S.K. Grebe, P.Z. Anastasiadis, et al., Neuronal pentraxin 2 supports clear cell renal cell carcinoma by activating the AMPA-selective glutamate receptor-4, Cancer Res. 74 (2014) 4796–4810. [17] Y.F. Pei, X.M. Yin, X.Q. Liu, TOP2A induces malignant character of pancreatic cancer through activating beta-catenin signaling pathway, Biochim. Biophys. Acta (BBA) - Mol. Basis Dis. 1864 (2018) 197–207. [18] K. Jandl, H. Thekkekara Puthenparampil, L.M. Marsh, J. Hoffmann, J. Wilhelm, C. Veith, et al., Long non-coding RNAs influence the transcriptome in pulmonary arterial hypertension: the role of PAXIP1-AS1, J. Pathol. 247 (2019) 357–370. [19] G. Barry, J.A. Briggs, D.P. Vanichkina, E.M. Poth, N.J. Beveridge, V.S. Ratnu, et al., The long non-coding RNA Gomafu is acutely regulated in response to neuronal activation and involved in schizophrenia-associated alternative splicing, Mol. Psychiatry 19 (2014) 486–494. [20] M. Vausort, D.R. Wagner, Y. Devaux, Long noncoding RNAs in patients with acute myocardial infarction, Circ. Res. 115 (2014) 668–677. [21] P. Jia, H. Cai, X. Liu, J. Chen, J. Ma, P. Wang, et al., Long non-coding RNA H19 regulates glioma angiogenesis and the biological behavior of glioma-associated endothelial cells by inhibiting microRNA-29a, Cancer Lett. 381 (2016) 359–369. [22] Q. Chen, J. Cai, Q. Wang, Y. Wang, M. Liu, J. Yang, et al., Long noncoding RNA NEAT1, regulated by the EGFR pathway, contributes to glioblastoma progression through the WNT/beta-Catenin pathway by scaffolding EZH2, Clin. Cancer Res. : Off. J. Am. Assoc. Canc. Res. 24 (2018) 684–695. [23] D. Li, X. Wang, H. Mei, E. Fang, L. Ye, H. Song, et al., Long noncoding RNA pancEts1 promotes neuroblastoma progression through hnRNPK-mediated beta-catenin stabilization, Cancer Res. 78 (2018) 1169–1183. [24] L. Qu, J. Ding, C. Chen, Z.J. Wu, B. Liu, Y. Gao, et al., Exosome-transmitted lncARSR promotes sunitinib resistance in renal cancer by acting as a competing endogenous RNA, Cancer Cell 29 (2016) 653–668. [25] J.K. Li, C. Chen, J.Y. Liu, J.Z. Shi, S.P. Liu, B. Liu, et al., Long noncoding RNA MRCCAT1 promotes metastasis of clear cell renal cell carcinoma via inhibiting NPR3 and activating p38-MAPK signaling, Mol. Cancer 16 (2017) 111. [26] E. Latorre, S. Carelli, I. Raimondi, V. D'Agostino, I. Castiglioni, C. Zucal, et al., The ribonucleic complex HuR-MALAT1 represses CD133 expression and suppresses epithelial-mesenchymal transition in breast cancer, Cancer Res. 76 (2016) 2626–2636. [27] P. Li, X. Zhang, H. Wang, L. Wang, T. Liu, L. Du, et al., MALAT1 is associated with poor response to oxaliplatin-based chemotherapy in colorectal cancer patients and promotes chemoresistance through EZH2, Mol. Cancer Ther. 16 (2017) 739–751. [28] L. Salmena, L. Poliseno, Y. Tay, L. Kats, P.P. Pandolfi, A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language? Cell 146 (2011) 353–358. [29] Y. Tay, J. Rinn, P.P. Pandolfi, The multilayered complexity of ceRNA crosstalk and competition, Nature 505 (2014) 344–352. [30] G. Xiao, J. Yao, D. Kong, C. Ye, R. Chen, L. Li, et al., The Long Noncoding RNA TTTY15, Which Is Located on the Y Chromosome, Promotes Prostate Cancer Progression by Sponging Let-7, European urology, 2018. [31] P. Li, Z. Xiao, J. Luo, Y. Zhang, L. Lin, MiR-139-5p, miR-940 and miR-193a-5p inhibit the growth of hepatocellular carcinoma by targeting SPOCK1, J. Cell Mol. Med. 23 (2019) 2475–2488. [32] Q. Li, X. Liang, Y. Wang, X. Meng, Y. Xu, S. Cai, et al., miR-139-5p inhibits the epithelial-mesenchymal transition and enhances the chemotherapeutic sensitivity of colorectal cancer cells by downregulating BCL2, Sci. Rep. 6 (2016) 27157. [33] B. Yang, W. Zhang, D. Sun, X. Wei, Y. Ding, Y. Ma, et al., Downregulation of miR139-5p promotes prostate cancer progression through regulation of SOX5, Biomed Pharmacother. = Biomed. Pharmacother. 109 (2019) 2128–2135. [34] J.L. Delgado, C.M. Hsieh, N.L. Chan, H. Hiasa, Topoisomerases as anticancer targets, Biochem. J. 475 (2018) 373–398. [35] Q. Zhou, A.D. Abraham, L. Li, A. Babalmorad, S. Bagby, J.J. Arcaroli, et al., Topoisomerase IIalpha mediates TCF-dependent epithelial-mesenchymal transition in colon cancer, Oncogene 35 (2016) 4990–4999. [36] X.L. Xu, W.H. Zheng, Z.X. Fu, Z.P. Li, H.X. Xie, X.X. Li, et al., Topo2A as a prognostic biomarker for patients with resectable esophageal squamous cell carcinomas, Med. Oncol. 32 (2015) 396. [37] A.S. Parker, J.E. Eckel-Passow, D. Serie, T. Hilton, M. Parasramka, R.W. Joseph, et al., Higher expression of topoisomerase II alpha is an independent marker of increased risk of cancer-specific death in patients with clear cell renal cell carcinoma, Eur. Urol. 66 (2014) 929–935.

Disclosure statement The authors declare that they have no conflicts of interest. No conflict of interest exits in the submission of this manuscript, and manuscript is approved by all authors for publication. I would like to declare on behalf of my co-authors that the work described was original research that has not been published previously, and not under consideration for publication elsewhere, in whole or in part. All the authors listed have approved the manuscript that is enclosed. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.yexcr.2019.111595. References [1] R.L. Siegel, K.D. Miller, A. Jemal, Cancer statistics, CA: Canc. J. Clinicians 2019 69 (2019) 7–34. [2] W.M. Linehan, Genetic basis of kidney cancer: role of genomics for the development of disease-based therapeutics, Genome Res. 22 (2012) 2089–2100. [3] R. Adelaiye-Ogala, J. Budka, N.P. Damayanti, J. Arrington, M. Ferris, C.C. Hsu, et al., EZH2 modifies sunitinib resistance in renal cell carcinoma by kinome reprogramming, Cancer Res. 77 (2017) 6651–6666. [4] B. Beuselinck, S. Job, E. Becht, A. Karadimou, V. Verkarre, G. Couchy, et al., Molecular subtypes of clear cell renal cell carcinoma are associated with sunitinib response in the metastatic setting, Clin. Cancer Res. : Off. J. Am. Assoc. Canc. Res. 21 (2015) 1329–1339. [5] J.J. Quinn, H.Y. Chang, Unique features of long non-coding RNA biogenesis and function, Nat. Rev. Genet. 17 (2016) 47–62. [6] A.M. Schmitt, H.Y. Chang, Long noncoding RNAs in cancer pathways, Cancer Cell 29 (2016) 452–463. [7] D. Liu, Y. Li, G. Luo, X. Xiao, D. Tao, X. Wu, et al., LncRNA SPRY4-IT1 sponges miR101-3p to promote proliferation and metastasis of bladder cancer cells through upregulating EZH2, Cancer Lett. 388 (2017) 281–291. [8] Y. Han, Z. Wu, T. Wu, Y. Huang, Z. Cheng, X. Li, et al., Tumor-suppressive function of long noncoding RNA MALAT1 in glioma cells by downregulation of MMP2 and inactivation of ERK/MAPK signaling, Cell Death Dis. 7 (2016) e2123. [9] X. Wang, W. Sun, W. Shen, M. Xia, C. Chen, D. Xiang, et al., Long non-coding RNA DILC regulates liver cancer stem cells via IL-6/STAT3 axis, J. Hepatol. 64 (2016) 1283–1294. [10] P.F. Zhang, F. Wang, J. Wu, Y. Wu, W. Huang, D. Liu, et al., LncRNA SNHG3 induces EMT and sorafenib resistance by modulating the miR-128/CD151 pathway in hepatocellular carcinoma, J. Cell. Physiol. 234 (2019) 2788–2794. [11] L. Liu, J. Ni, X. He, Upregulation of the long noncoding RNA SNHG3 promotes lung adenocarcinoma proliferation, Dis. Markers 2018 (2018) 5736716. [12] N. Li, X. Zhan, X. Zhan, The lncRNA SNHG3 regulates energy metabolism of ovarian cancer by an analysis of mitochondrial proteomes, Gynecol. Oncol. 150 (2018) 343–354. [13] S. Zheng, F. Jiang, D. Ge, J. Tang, H. Chen, J. Yang, et al., LncRNA SNHG3/miRNA151a-3p/RAB22A axis regulates invasion and migration of osteosarcoma, Biomed Pharmacother. = Biomed. Pharmacother. 112 (2019) 108695.

11