Deregulation of long noncoding RNA SNHG17 and TTC28-AS1 is associated with type 2 diabetes mellitus

Resistance and aerobic training increases genome-wide DNA methylation in women with polycystic ovary syndrome

Physical activity is a first-line treatment for polycystic ovary syndrome (PCOS). Resistance or aerobic exercise improves metabolic complications, reproductive outcomes, and quality of life in PCOS. DNA methylation reprogramming during exercise may be the major modifier behind these changes. We sought to evaluate genome-wide DNA methylation changes after supervised resistance and aerobic exercise in women with PCOS. Exercises were performed in 56 women with PCOS (resistance, n = 30; aerobic, n = 26), for 16 weeks (wks), three times per week, in 50-minute to one-hour sessions. Anthropometric indices and hormonal and metabolic parameters were measured before and after training. Genome-wide leukocyte DNA methylation was analysed by Infinium Human MethylationEPIC 850K BeadChip microarrays (Illumina). Both resistance and aerobic exercise improved anthropometric indices, metabolic dysfunction, and hyperandrogenism in PCOS after the training programme, but no differences were observed between the two exercises. Resistance and aerobic exercise increased genome-wide DNA methylation, although resistance changed every category in the CpG island context (islands, shores, shelve, and open sea), whereas aerobic exercise altered CpG shores and the open sea. Using a stringent FDR (>40), 6 significantly differentially methylated regions (DMRs) were observed in the resistance exercise cohort and 14 DRMs in the aerobic cohort, all of which were hypermethylated. The increase in genome-wide DNA methylation may be related to the metabolic and hormonal changes observed in PCOS after resistance and aerobic exercise. Since the mammalian genome is hypermethylated globally to prevent genomic instability and ageing, resistance and aerobic exercise may promote health and longevity through environmentally induced epigenetic changes.

Whole transcriptome sequencing analyses of islets reveal ncRNA regulatory networks underlying impaired insulin secretion and increased β-cell mass in high fat diet-induced diabetes mellitus

AIM

Our study aims to identify novel non-coding RNA-mRNA regulatory networks associated with β-cell dysfunction and compensatory responses in obesity-related diabetes.

METHODS

Glucose metabolism, islet architecture and secretion, and insulin sensitivity were characterized in C57BL/6J mice fed on a 60% high-fat diet (HFD) or control for 24 weeks. Islets were isolated for whole transcriptome sequencing to identify differentially expressed (DE) mRNAs, miRNAs, IncRNAs, and circRNAs. Regulatory networks involving miRNA-mRNA, lncRNA-mRNA, and lncRNA-miRNA-mRNA were constructed and functions were assessed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses.

RESULTS

Despite compensatory hyperinsulinemia and a significant increase in β-cell mass with a slow rate of proliferation, HFD mice exhibited impaired glucose tolerance. In isolated islets, insulin secretion in response to glucose and palmitic acid deteriorated after 24 weeks of HFD. Whole transcriptomic sequencing identified a total of 1324 DE mRNAs, 14 DE miRNAs, 179 DE lncRNAs, and 680 DE circRNAs. Our transcriptomic dataset unveiled several core regulatory axes involved in the impaired insulin secretion in HFD mice, such as miR-6948-5p/Cacna1c, miR-6964-3p/Cacna1b, miR-3572-5p/Hk2, miR-3572-5p/Cckar and miR-677-5p/Camk2d. Additionally, proliferative and apoptotic targets, including miR-216a-3p/FKBP5, miR-670-3p/Foxo3, miR-677-5p/RIPK1, miR-802-3p/Smad2 and ENSMUST00000176781/Caspase9 possibly contribute to the increased β-cell mass in HFD islets. Furthermore, competing endogenous RNAs (ceRNA) regulatory network involving 7 DE miRNAs, 15 DE lncRNAs and 38 DE mRNAs might also participate in the development of HFD-induced diabetes.

CONCLUSIONS

The comprehensive whole transcriptomic sequencing revealed novel non-coding RNA-mRNA regulatory networks associated with impaired insulin secretion and increased β-cell mass in obesity-related diabetes.

Body mass index stratified meta-analysis of genome-wide association studies of polycystic ovary syndrome in women of European ancestry

BACKGROUND

Polycystic ovary syndrome (PCOS) is a complex multifactorial disorder with a substantial genetic component. However, the clinical manifestations of PCOS are heterogeneous with notable differences between lean and obese women, implying a different pathophysiology manifesting in differential body mass index (BMI). We performed a meta-analysis of genome-wide association study (GWAS) data from six well-characterised cohorts, using a case-control study design stratified by BMI, aiming to identify genetic variants associated with lean and overweight/obese PCOS subtypes.

RESULTS

The study comprised 254,588 women (5,937 cases and 248,651 controls) from individual studies performed in Australia, Estonia, Finland, the Netherlands and United States of America, and separated according to three BMI stratifications (lean, overweight and obese). Genome-wide association analyses were performed for each stratification within each cohort, with the data for each BMI group meta-analysed using METAL software. Almost half of the total study population (47%, n = 119,584) were of lean BMI (≤ 25 kg/m2). Two genome-wide significant loci were identified for lean PCOS, led by rs12000707 within DENND1A (P = 1.55 × 10-12) and rs2228260 within XBP1 (P = 3.68 × 10-8). One additional locus, LINC02905, was highlighted as significantly associated with lean PCOS through gene-based analyses (P = 1.76 × 10-6). There were no significant loci observed for the overweight or obese sub-strata when analysed separately, however, when these strata were combined, an association signal led by rs569675099 within DENND1A reached genome-wide significance (P = 3.22 × 10-9) and a gene-based association was identified with ERBB4 (P = 1.59 × 10-6). Nineteen of 28 signals identified in previous GWAS, were replicated with consistent allelic effect in the lean stratum. There were less replicated signals in the overweight and obese groups, and only 4 SNPs were replicated in each of the three BMI strata.

CONCLUSIONS

Genetic variation at the XBP1, LINC02905 and ERBB4 loci were associated with PCOS within unique BMI strata, while DENND1A demonstrated associations across multiple strata, providing evidence of both distinct and shared genetic features between lean and overweight/obese PCOS-affected women. This study demonstrated that PCOS-affected women with contrasting body weight are not only phenotypically distinct but also show variation in genetic architecture; lean PCOS women typically display elevated gonadotrophin ratios, lower insulin resistance, higher androgen levels, including adrenal androgens, and more favourable lipid profiles. Overall, these findings add to the growing body of evidence supporting a genetic basis for PCOS as well as differences in genetic patterns relevant to PCOS BMI-subtype.

Enabling factor for cancer hallmark acquisition: Small nucleolar RNA host gene 17

The role of long non-coding RNA (lncRNA) in human tumors has gradually received increasing attention in recent years. Particularly, the different functions of lncRNAs in different subcellular localizations have been widely investigated. The upregulation of lncRNA small nucleolar RNA host gene 17 (SNHG17) has been observed in various human tumors. Growing evidence has proved that SNHG17 plays a tumor-promoting role in tumorigenesis and development. This paper describes the molecular mechanisms by which SNHG17 contributes to tumor formation and development. The different functions of SNHG17 in various subcellular localizations are also emphasized: its function in the cytoplasm as a competing endogenous RNA (ceRNA), its action in the nucleus as a transcriptional coactivator, and its function through the polycomb repressive complex 2 (PRC2)-dependent epigenetic modifications that regulate transcriptional processes. Finally, the correlation between SNHG17 and human tumors is summarized. Its potential as a novel prognostic and diagnostic biomarker for cancer is explored especially.

Long non-coding RNAs: a valuable biomarker for metabolic syndrome

Long non-coding RNAs (lncRNAs) have become important regulators of gene expression because they affect a wide range of biological processes, such as cell growth, death, differentiation, and aging. More and more evidence suggests that lncRNAs play a role in maintaining metabolic homeostasis. When certain lncRNAs are out of balance, metabolic disorders like diabetes, obesity, and heart disease get worse. In this review, we talk about what we know about how lncRNAs control metabolism, with a focus on diseases caused by long-term inflammation and the characteristics of the metabolic syndrome. We looked at lncRNAs and their molecular targets in the pathogenesis of signaling pathways. We also talked about how lncRNAs are becoming more and more interesting as diagnostic and therapeutic targets for improving metabolic homeostasis.

Long noncoding RNA SNHG17: a novel molecule in human cancers

Many studies in recent years have found that dysregulation of long non-coding RNAs (lncRNAs) can contribute to disease. Small nucleolar RNA host gene 17 (SNHG17) is a novel cancer-related lncRNA of the SNHG family which is highly expressed in various tumors and may exert oncogenic functions. Several studies have demonstrated that SNHG17 is closely related to the proliferation, migration, invasion, apoptosis, and chemical drug resistance of tumor cells, and clinical studies have found an association between high SNHG17 expression and poor prognosis. In this review, we summarize relevant studies investigating SNHG17, focusing on its biological function as well as its potential value for clinical applications.

Long non-coding RNA TTC28-AS1 attenuates high glucose-induced damage in HK-2 cells depending on the regulation of miR-320a/CD2AP axis

BACKGROUND

Diabetic nephropathy (DN) is the leading cause of end-stage renal disease (ESRD) worldwide. Emerging evidence suggests that long non-coding RNAs (lncRNAs) play crucial roles in DN pathogenesis.

OBJECTIVE

The purpose of the present study was to explore the role and mechanism of lncRNA tetratricopeptide repeat domain 2B antisense RNA 1 (TTC28-AS1) in DN.

METHODS

Cell viability and apoptosis were assessed by the Cell Counting-8 Kit (CCK-8) assay and flow cytometry, respectively. The levels of TTC28-AS1, miR-320a and CD2-associated protein (CD2AP) were determined by quantitative real-time polymerase chain reaction (qRT-PCR) or western blot. The levels of interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and IL-8 were gauged by enzyme-linked immunosorbent assay (ELISA). Targeted relationship between miR-320a and TTC28-AS1 or CD2AP was evaluated by dual-luciferase reporter and RNA immunoprecipitation (RIP) assays.

RESULTS

Our data indicated that high glucose (HG) induced HK-2 cell damage by the repression of cell viability and autophagy and the enhancement of cell apoptosis, fibrosis and pro-inflammatory cytokines production. TTC28-AS1 was down-regulated and miR-320a was up-regulated in HG-induced HK-2 cells. TTC28-AS1 overexpression or miR-320a knockdown alleviated HG-induced damage in HK-2 cells. MiR-320 was a molecular mediator of TTC28-AS1 in regulating HG-induced HK-2 cell damage. Moreover, TTC28-AS1 functioned as a post-transcriptional regulator of CD2AP expression by miR-320a. MiR-320a knockdown relieved HG-induced damage in HK-2 cells by up-regulating CD2AP.

CONCLUSIONS

Our findings suggest that TTC28-AS1 attenuates HG-induced damage in HK-2 cells at least partially by targeting the miR-320a/CD2AP axis, highlighting its role as a promising therapeutic approach for DN treatment.

Construction of a ceRNA network in glioma and analysis of its clinical significance

Background

Glioma is the most common central nervous system tumor with a poor survival rate and prognosis. Previous studies have found that long non-coding RNA (lncRNA) and competitive endogenous RNA (ceRNA) play important roles in regulating various tumor mechanisms. We obtained RNA-Seq data of glioma and normal brain tissue samples from TCGA and GTEx databases and extracted the lncRNA and mRNA expression data. Further, we analyzed these data using weighted gene co-expression network analysis and differential expression analysis, respectively. Differential expression analysis was also carried out on the mRNA data from the GEO database. Further, we predicted the interactions between lncRNA, miRNA, and targeted mRNA. Using the CGGA data to perform univariate and multivariate Cox regression analysis on mRNA.

Results

We constructed a Cox proportional hazard regression model containing four mRNAs and performed immune infiltration analysis. Moreover, we also constructed a ceRNA network including 21 lncRNAs, two miRNAs, and four mRNAs, and identified seven lncRNAs related to survival that have not been previously studied in gliomas. Through the gene set enrichment analysis, we found four lncRNAs that may have a significant role in tumors and should be explored further in the context of gliomas.

Conclusions

In short, we identified four lncRNAs with research value for gliomas, constructed a ceRNA network in gliomas, and developed a prognostic prediction model. Our research enhances our understanding of the molecular mechanisms underlying gliomas, providing new insights for developing targeted therapies and efficiently evaluating the prognosis of gliomas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08035-w.

Up-regulation of FOXN3-AS1 in invasive ductal carcinoma of breast cancer patients

Oncogenic and tumor-suppressive roles of long non-coding RNA make them an appropriate target for expression analysis in cancer studies. In this study, we selected two lncRNAs (EMX2OS and FOXN3-AS1) that are resided near the GWAS-identified SNPs for breast cancer (rs2901157 and rs141061110). These transcripts have been identified in different cancer types as either oncogenes or tumor suppressors. In the present investigation, we aimed to quantify the expression level of EMX2OS and FOXN3-AS1 in 44 breast cancer samples and normal adjacent tissues (ANCTs). The FOXN3-AS1 expression level was significantly increased in breast cancer samples compared with ANCTs (P value = 0.02), Also its amounts could distinguish two sets of samples with an accuracy of 70% (P value = 0.009). We have found an association between FOXN3-AS1 expression and tumor size (P value = 0.02). On the other hand, no significant differences were found in the EMX2OS expression level between two sets of samples (P value = 0.44); however, EMX2OS expression level has a significant association with the age of the patients (P value = 0.03). According to our result, FOXN3-AS1 can be demonstrated as a probable diagnostic marker in breast cancer so we suggest further functional studies to find the precise role of these lncRNAs in breast cancer progression.

Potential Therapeutic Targeting of lncRNAs in Cholesterol Homeostasis

Maintaining cholesterol homeostasis is essential for normal cellular and systemic functions. Long non-coding RNAs (lncRNAs) represent a mechanism to fine-tune numerous biological processes by controlling gene expression. LncRNAs have emerged as important regulators in cholesterol homeostasis. Dysregulation of lncRNAs expression is associated with lipid-related diseases, suggesting that manipulating the lncRNAs expression could be a promising therapeutic approach to ameliorate liver disease progression and cardiovascular disease (CVD). However, given the high-abundant lncRNAs and the poor genetic conservation between species, much work is required to elucidate the specific role of lncRNAs in regulating cholesterol homeostasis. In this review, we highlighted the latest advances in the pivotal role and mechanism of lncRNAs in regulating cholesterol homeostasis. These findings provide novel insights into the underlying mechanisms of lncRNAs in lipid-related diseases and may offer potential therapeutic targets for treating lipid-related diseases.

Deregulation of lncRNA HIST1H2AG-6 and AIM1-3 in peripheral blood mononuclear cells is associated with newly diagnosed type 2 diabetes

Background

Type 2 diabetes mellitus (T2DM) is mainly affected by genetic and environmental factors; however, the correlation of long noncoding RNAs (lncRNAs) with T2DM remains largely unknown.

Methods

Microarray analysis was performed to identify the differentially expressed lncRNAs and messenger RNAs (mRNAs) in patients with T2DM and healthy controls, and the expression of two candidate lncRNAs (lnc-HIST1H2AG-6 and lnc-AIM1-3) were further validated using quantitative real-time polymerase chain reaction (qRT-PCR). Spearman’s rank correlation coefficient was used to measure the degree of association between the two candidate lncRNAs and differentially expressed mRNAs. Furthermore, the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and GO (Gene Ontology) enrichment analysis were used to reveal the biological functions of the two candidate lncRNAs. Additionally, multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed.

Results

The microarray analysis revealed that there were 55 lncRNAs and 36 mRNAs differentially expressed in patients with T2DM compared with healthy controls. Notably, lnc-HIST1H2AG-6 was significantly upregulated and lnc-AIM1-3 was significantly downregulated in patients with T2DM, which was validated in a large-scale qRT-PCR examination (90 controls and 100 patients with T2DM). Spearman’s rank correlation coefficient revealed that both lncRNAs were correlated with 36 differentially expressed mRNAs. Furthermore, functional enrichment (KEGG and GO) analysis demonstrated that the two lncRNA-related mRNAs might be involved in multiple biological functions, including cell programmed death, negative regulation of insulin receptor signal, and starch and sucrose metabolism. Multivariate logistic regression analysis revealed that lnc-HIST1H2AG-6 and lnc-AIM1-3 were significantly correlated with T2DM (OR = 5.791 and 0.071, respectively, both P = 0.000). Furthermore, the ROC curve showed that the expression of lnc-HIST1H2AG-6 and lnc-AIM1-3 might be used to differentiate patients with T2DM from healthy controls (area under the ROC curve = 0.664 and 0.769, respectively).

Conclusion

The profiles of lncRNA and mRNA were significantly changed in patients with T2DM. The expression levels of lnc-HIST1H2AG-6 and lnc-AIM1-3 genes were significantly correlated with some features of T2DM, which may be used to distinguish patients with T2DM from healthy controls and may serve as potential novel biomarkers for diagnosis in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-00994-z.

Non-Coding RNAs Based Molecular Links in Type 2 Diabetes, Ischemic Stroke, and Vascular Dementia

This article reviews recent advances in the study of microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and their functions in type 2 diabetes mellitus (T2DM), ischemic stroke (IS), and vascular dementia (VaD). miRNAs and lncRNAs are gene regulation markers that both regulate translational aspects of a wide range of proteins and biological processes in healthy and disease states. Recent studies from our laboratory and others have revealed that miRNAs and lncRNAs expressed differently are potential therapeutic targets for neurological diseases, especially T2DM, IS, VaD, and Alzheimer's disease (AD). Currently, the effect of aging in T2DM, IS, and VaD and the cellular and molecular pathways are largely unknown. In this article, we highlight results from the works on the molecular connections between T2DM and IS, and IS and VaD. In each disease, we also summarize the pathophysiology and the differential expressions of miRNAs and lncRNAs. Based on current research findings, we hypothesize that 1) T2DM bi-directionally and age-dependently induces IS and VaD, and 2) these changes are precursors to the onset of dementia in elderly people. Research into these hypotheses is required to examine further whether research efforts on reducing T2DM, IS, and VaD may affect dementia and/or delay the AD disease process in the aged population.

Long Non-coding RNA SNHG17 Upregulates RFX1 by Sponging miR-3180-3p and Promotes Cellular Function in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common types of cancer that is associated with poor quality of life in patients and a global health burden. The mechanisms involved in the development and progression of HCC remain poorly understood.

Methods

Hepatocellular carcinoma human samples and cell lines were subjected to qRT-PCR for expression assessment. CCK-8 assay, Transwell migration and invasion assay, were applied for cell function detection. Animal experiment was used to measure the function of SNHG17 on cell growth in vivo. Western blot was conducted to evaluate the level of EMT in cells. RIP, RNA pull-down and luciferase reporter assays were performed to assess the correlation between SNHG17, miR-3180-3p and RFX1.

Results

Our study demonstrated that SNHG17 was upregulated in HCC human samples and involved cell proliferation, migration, invasion progress. SNHG17 promoted HCC cell growth and metastasis in vivo. Furthermore, we investigated the downstream factor of SNHG17, SNHG17 acted as a molecular sponge for miR-3180-3p, and SNHG17 regulated RFX1 expression via miR-3180-3p. SNHG17 promotes tumor-like behavior in HCC cells via miR-3180-3p/RFX1.

Conclusion

We determined RFX1 as the target of miR-3810-3p; SNHG17 enhanced the progression of HCC via the miR-3180-3p/RFX1 axis. Taken together, our findings may provide insight into the molecular mechanism involved in the progression of HCC and develop SNHG17 as a novel therapeutic target against HCC.

lncRNA SNHG17 is Downregulated in Gestational Diabetes Mellitus (GDM) and Has Predictive Values

AIM

Long non-coding RNA (lncRNA) SNHG17 has been shown to participate in type 2 diabetes mellitus, while its role in gestational diabetes mellitus (GDM) is unknown.

METHODS

Quantitative real-time PCR (qRT-PCR) assays were conducted to compare the differential expression of SNHG17 among 60 GDM patients and 60 healthy pregnant female controls. In addition, peripheral blood samples from 240 pregnant females were collected to evaluate the predictive value of SNHG17 for GDM patients. All females were followed-up until delivery to record the occurrence of GDM and perinatal outcomes. GDM-free curves were plotted to compare the occurrence of GDM between high- and low- SNHG17 expression groups. The diagnostic value of plasma SNHG17 for GDM was analyzed by ROC curve analysis. Moreover, the cell counting kit (CCK-8) assay was performed to evaluate the impact of SNHG17 on cell viability of INS-1, and the level of insulin secretion was detected by enzyme linked immunosorbent assay (ELISA) after overexpression or knockdown of SNHG17.

RESULTS

SNHG17 was downregulated in GDM patients compared to normal pregnant females. Low plasma expression levels of SNHG17 were closely correlated with the high incidence rate of GDM (GDM-free curve). Remarkably, plasma expression levels of SNHG17 at 4 weeks before the diagnosis of GDM (diagnosed by standard method) can be used to distinguish (ROC curve) GDM patients (diagnosed during follow-up) from normal pregnant females (GDM was not diagnosed during follow-up).

CONCLUSION

Plasma circulating SNHG17 is downregulated in GDM and has predictive values.

The Impact of lncRNAs in Diabetes Mellitus: A Systematic Review and In Silico Analyses

Long non-coding RNAs (lncRNAs) are non-coding transcripts that have emerged as one of the largest and diverse RNA families that regulate gene expression. Accumulating evidence has suggested a number of lncRNAs are involved in diabetes mellitus (DM) pathogenesis. However, results about lncRNA expressions in DM patients are still inconclusive. Thus, we performed a systematic review of the literature on the subject followed by bioinformatics analyses to better understand which lncRNAs are dysregulated in DM and in which pathways they act. Pubmed, Embase, and Gene Expression Omnibus (GEO) repositories were searched to identify studies that investigated lncRNA expression in cases with DM and non-diabetic controls. LncRNAs consistently dysregulated in DM patients were submitted to bioinformatics analysis to retrieve their target genes and identify potentially affected signaling pathways under their regulation. Fifty-three eligible articles were included in this review after the application of the inclusion and exclusion criteria. Six hundred and thirty-eight lncRNAs were differentially expressed between cases and controls in at least one study. Among them, six lncRNAs were consistently dysregulated in patients with DM (Anril, Hotair, Malat1, Miat, Kcnq1ot1, and Meg3) compared to controls. Moreover, these six lncRNAs participate in several metabolism-related pathways, evidencing their importance in DM. This systematic review suggests six lncRNAs are dysregulated in DM, constituting potential biomarkers of this disease.

Long noncoding RNAs as novel biomarkers for Type 2 diabetes

Type 2 diabetes (T2D) is a metabolic disease characterized by disordered glucagon secretion, insulin resistance in target tissues, and decreased islet β-cell mass and function. The routine diagnosis was based on measurements of metabolic markers, while genetic risk factors have been considered to increase the probability of predicting the development of the disease. Recent evidence suggests that long noncoding RNAs (lncRNAs) regulate gene expression in various physiological and pathological processes. As increasing lncRNAs are identified in β cells, understanding the regulatory roles of lncRNAs in T2D becomes indispensable. In this review, we discuss the potential role of lncRNAs contributing to β-cell identity and T2D susceptibility, which provide a perspective insight into the development of novel diagnosis biomarkers for T2D.

STAT3-Induced lncRNA SNHG17 Exerts Oncogenic Effects on Ovarian Cancer through Regulating CDK6

Emerging studies indicate that long noncoding RNAs (lncRNAs) play crucial roles in ovarian cancer (OC). By analyzing high-throughput data, we found that SNHG17 was highly expressed in multiple OC cohorts. However, its functions in OC were not explored. In this study, lncRNA expression in OC was analyzed by a series of microarray data. The functions of SNHG17 were investigated by various in vitro and in vivo assays. Fluorescence in situ hybridization (FISH), RNA pull-down, chromatin immunoprecipitation (ChIP), RNA immunoprecipitation (RIP), and luciferase reporter assays were used to reveal the potential mechanisms involved in the effects of SNHG17. We found that SNHG17 was overexpressed in OC and that the oncogenic transcription factor STAT3 was involved in promoting its expression. In addition, high SNHG17 expression was associated with a poor prognosis in OC. Functional analysis revealed that SNHG17 could promote OC cell growth. Mechanistically, SNHG17 was found to be located predominantly in the cytoplasm. It could regulate expression of CDK6, an important cell-cycle regulator, by acting as a molecular sponge for miR-214-3p. In summary, our study suggested that SNHG17 acted as an oncogene in OC, which might serve as a novel target for OC diagnosis and therapy.