Background
Cancer is a severe health problem and is the leading cause of death worldwide, with annually increasing incidence and mortality rates. According to the latest statistics reported in CA cancer journals, 1,806,590 new cancer cases and 606,520 cancer deaths are expected to occur in the United States in 2020 [
1]. Although multidisciplinary treatments, such as surgery, chemotherapy, radiotherapy, targeted therapy, and immunotherapy, of malignancies have improved greatly in recent years, prognosis and early diagnosis remain extremely challenging [
2]. As such, there is an urgent need to identify innovative and effective targets for investigating the signalling pathways in tumours, which may ultimately play an indispensable role in therapeutic decision-making for cancer patients.
Long non-coding RNAs (lncRNAs), which were initially speculated to be transcriptional noise with no specific biological function, have emerged as a novel category of non-coding RNAs (ncRNAs) exceeding 200 nucleotides in length that are transcribed by RNA polymerase II but do not encode proteins due to the lack of an open reading frame [
3]. Nonetheless, a growing body of work has demonstrated that aberrant expression of lncRNAs is correlated with biological processes, including tumour progression, angiogenesis, metastasis, and invasion, indicating that lncRNAs can serve as tumour suppressors or oncogenes for cancer control [
4,
5]. Recently, small nucleolar RNA host gene 6 (SNHG6), linc00152, and opa-interacting protein 5 antisense RNA 1(OIP5-AS1) have been identified as potential prognostic biomarkers involved in the modulation of tumour-related genes and specific molecular mechanisms in human cancers [
6‐
8].
Small nucleolar RNA host gene 15 (SNHG15), which is located at 7p13 and is 860 base pairs long, was initially reported as a lncRNA with a short half-life [
9]. As a tumour oncogene, lncRNA SNHG15 functions as a competing endogenous RNA (ceRNA) to sponge miR-153, miR-38, miR-141, and miR-141-3p, which consequently promotes cell proliferation, migration, invasion, autophagy, and cisplatin resistance in glioma, breast cancer, osteosarcoma, and hepatocellular carcinoma [
10‐
13]. Furthermore, SNHG15 enhances tumour development or drug resistance in glioblastoma multiforme, colorectal carcinoma, and prostate cancer through the SNHG15/CDK6/miR-627, SNHG15/miR-141/SIRT1/Wnt/β-catenin, SNHG15/miR-338-3p/FKBP1A, and SNHG15/miR-338-3p/FOS-RAB14 axes [
14‐
17]. Additionally, it was found that SNHG15 could facilitate cell proliferation, invasion, and drug resistance in colorectal cancer by acting as a bifunctional MYC-regulated noncoding locus encoding an lncRNA that interacts with AIF. Similarly, it was demonstrated that SNHG15 promoted tumour progression in colon cancer by stabilising the transcription factor Slug [
18,
19]. However, only one report has found SNHG15 to be downregulated in thyroid cancer tissue samples and cells, suggesting its role as a tumor suppressor and the reduced expression of SNHG15 enhanced cell proliferation, migration, and invasion in vitro [
20].
Collectively, most studies have demonstrated that SNHG15 is involved in gene regulation by acting as an oncogene in various malignancies, and its elevated expression might be associated with the prognosis and clinicopathological parameters of gastric cancer, hepatocellular carcinoma, lung cancer, non-small cell lung cancer, renal cell carcinoma, pancreatic ductal adenocarcinoma, breast cancer, papillary thyroid carcinoma, colorectal cancer, and epithelial ovarian cancer [
21‐
31].
However, given the discrepancies between published studies, the small number of patient samples, and the different detection methods used, the prognostic value of SNHG15 remains unclear at this time. Therefore, we conducted this meta-analysis and bioinformatic validation to determine whether SNHG15 could be used as a non-invasive prognostic marker of tumours and attempted to reach a consensus regarding the prognostic value of this gene.
Methods
Search strategies for eligible literature
Relevant articles that investigated the association between SNHG15 expression and the clinical outcomes of cancer patients were searched using PubMed, Web of Science, Embase, and the Cochrane Library through February 26, 2020. Three domains of keywords in multiple combinations were utilised as search subjects as follows: (“long noncoding RNA” OR “lncRNA”) AND (“SNHG15” OR “small nucleolar RNA host gene 15”) AND (“Cancer” OR “Cancers” OR “Tumors” OR “Tumor” OR “Malignancy” OR “Malignancies” OR “Neoplasia” OR “Neoplasias” OR “Neoplasm” OR “Malignant Neoplasms” OR “Malignant Neoplasm” OR “Neoplasm, Malignant” OR “Neoplasms, Benign” OR “Benign Neoplasm” OR “Neoplasms, Malignant” OR “Benign Neoplasms” OR “Neoplasm, Benign”). Further, a manual search was conducted to avoid overlooking eligible papers by screening the title and abstracts of papers from the references lists of pertinent articles.
Inclusion and exclusion criteria
All enrolled studies were assessed by two independent investigators, and disagreements were resolved by reaching a consensus after discussion with the third author. Articles that met the following criteria were enrolled in our study: (1) original articles investigating the role of SNHG15 in cancers that were definitively diagnosed by histopathology; (2) samples were cancer tissue and adjacent normal tissue; (3) detection method was qRT-PCR; (4) clinical features, including age, gender, tumour size, TNM stage, lymph node metastasis or distant metastasis, and prognostic indicators, such as overall survival (OS), disease-free survival (DFS), or progression-free survival (PFS), were reported in the paper; (5) patients were categorised into increased and decreased SNHG15 expression groups based on a cut-off value, and the number of patients in these two groups was explicitly stated; (6) hazard ratios (HRs) and 95% confidence intervals (CIs) were reported by multivariate analysis from the articles or were available to be indirectly calculated via Kaplan-Meier (K-M) curves; and (7) the language of the article was English.
Exclusion criteria: (1) studies exploring other lncRNAs or those that were not related to cancers; (2) duplicate articles; (3) other literature types, such as reviews, letters, conference abstracts, meta-analyses, case reports, retractions, etc.; (4) articles focussed on biological functions; and (5) lack of sufficient data for HR and 95% CI extraction.
Data extraction and quality evaluation
The main information from eligible studies was extracted as follows: first author, publication year, country, cancer type, sample type, sample size (high/low), cut-off value for SNHG15 expression, assay method, survival (OS/RFS/PFS), HR availability, HR (95% CI) with its P value, follow-up months, and Newcastle-Ottawa Scale (NOS) scores. If survival rates were not obtained from multivariate analysis, the survival HR (95% CI) was indirectly retrieved from K-M curves by using Engauge Digitiser software. The quality of the enrolled studies was assessed using the NOS score with a range from 0 to 9, and a score greater than 6 was considered as qualified literature.
Gene Expression Profiling Interactive Analysis (GEPIA), which is based on The Cancer Genome Atlas (TCGA), was performed to further verify the abnormal expression of SNHG15 among cancer tissues and to match TCGA normal and GTEx data among various neoplasms with P < 0.01 as the cut-off value. Survival plots of the correlation between SNHG15 expression and OS and DFS were retrieved as K–M curves based on different cancer datasets online.
Functional prediction of SNHG15
We identified SNHG15 relevant ceRNA regulations by starBase, LncBase Predicted v.2, miRDB, TargetScan, miRTarBase, mirDIP and used Cytoscape to construct visualized ceRNA network.
Statistical analysis
Stata (Version 12.0) was used to analyse all the data extracted from the articles included in this study, and a P value < 0.05 indicated a significant difference. The HR and odds ratio (OR), with their corresponding 95% CIs, were utilised to analyse the association between SNHG15 expression and prognostic indicators (OS/DFS) and clinical features, respectively. When HR/OR > 1 and a 95% CI not including 1 were observed in the results, this implied that patients with SNHG15 overexpression had a worse prognosis and advanced clinicopathological parameters. Cochran’s Q and I2 statistics were determined to measure the heterogeneity across all enrolled studies. A random-effect model was applied with the existence of marked heterogeneity as I2 > 50% and P < 0.10, otherwise a fixed-effect model was used. Begg’s and Egger’s tests were quantitatively conducted to detect underlying publication bias. Accordingly, sensitivity analysis was used to evaluate the stability of the results.
Discussion
LncRNAs were initially thought to be “transcriptional noise” or “junk DNA” and received little attention in the previous few decades [
32]. However, as next-generation genome-wide sequencing and microarrays have been widely applied in clinical settings in recent years, new research has suggested that aberrant expression of lncRNAs may promote or suppress tumour growth, leading to carcinogenesis and cancer progression [
33,
34]. For example, some lncRNAs, such as NOC2L-4.1, TUG1, and MALAT1, are well established to promote tumour growth, while other lncRNAs, such as ASMTL-AS1, LINC02381, and LINC02499 have been found to inhibit tumour progression [
35‐
40].
SNHG15, a promising new cancer-related lncRNA, has been found to be upregulated in a diverse array of malignant tumours. It has been demonstrated that elevated expression of SNHG15 is significantly related to tumour size, TNM stage, and lymph node metastasis in pancreatic cancer patients [
41]. However, the definitive prognostic role of this gene was previously unclear. In our meta-analysis, we investigated the potential association between SNHG15 expression and prognostic attributes and clinicopathological parameters by integrating data from 11 studies. We found that SNHG15 overexpression increased the risk of shorter OS and DFS with no conspicuous heterogeneity. Simultaneously, we demonstrated that patients with increased SNHG15 expression were more likely to develop advanced TNM stage and positive lymph node metastasis, while these effects were not associated with age, sex, or tumour size. Additionally, no evident publication bias in OS was identified throughout the study, and the robustness of the results was verified via sensitivity analysis. Furthermore, validating the TCGA datasets revealed that high SNHG15 expression levels were observed in COAD, DLBC, KIRC, PAAD, READ, TGCT, and THYM. We also evaluated the TCGA cohort to confirm the prognostic role of SNHG15 in various cancers, and the elevated expression of SNHG15 in 33 types of tumour tissues was associated with worse OS and DFS. In some cancers, including ACC, KIRC, MESO, and UVM, SNHG15 overexpression indicated shorter OS. Moreover, survival plots revealed that ACC, PRAD, and UVM patients with SNHG15 upregulation exhibited worse DFS. Taken together, these results indicate that SNHG15 could serve as a biological modulator and novel biomarker of poor prognosis in cancer patients.
LncRNAs can indirectly regulate the expression and function of target genes via ceRNA. Thus, we constructed a ceRNA network to assess the potential function and molecular mechanism of SNHG15 in cancers. The results of our functional analysis demonstrated that target genes indirectly affected by SNHG15 may be involved in some of these signaling pathways, and promoted the proliferation, invasion and metastasis of tumour cells. Accordingly, the potential molecular mechanism involved in tumour progression may be investigated in the future to better understand the association between altered SNHG15 expression and poor prognosis (Table
3). In gastric cancer, SNHG15 upregulation promotes cell proliferation and invasion by modulating the expression of MMP2/MMP9 [
21]. In lung cancer, it has been reported that SNHG15 overexpression enhances tumour occurrence and development by targeting miRNA-211-3p to regulate cell proliferation and migration in vitro [
23]. Similarly, in non-small cell lung cancer, two studies have demonstrated that SNHG15 knockdown suppresses tumorigenesis by inhibiting the expression of EMT, MMP2, and MMP9 and regulating the miR-486/CDK14 axis [
24,
25]. Meanwhile, another study has identified that SNHG15 facilitates renal cell carcinoma invasion and migration through the NF-κB signalling pathway and by inducing the EMT process [
26]. In breast cancer, it has been shown that SNHG15 functions as a ceRNA to sponge miR-211-3p, thereby promoting cell proliferation, migration, and invasion and inhibiting apoptosis [
28]. Additionally, SNHG15 has been reported to act as a ceRNA to modulate the miR-200a-3p/YAP1-Hippo axis in papillary thyroid carcinoma [
29]. Consistently, functional assays have revealed that upregulation of SNHG15 facilitates the migration, invasion, proliferation, and chemoresistance of epithelial ovarian cancer cells [
31]. However, the signalling pathways involved in in HCC, PDAC, and colorectal cancer remain unclear; therefore, additional studies are needed to explore the potential mechanisms by which SNHG15 expression predicts survival across diverse malignancies [
22,
27,
30].
Table 3
Summary of SNHG15 with their aberrant expression,biological functions, and related signaling pathways
| gastric cancer | upregulation | promote cell proliferation and invasion, inhibit apoptosis | MMP2/MMP9 |
| lung cancer | upregulation | promote cell proliferation,invasion | microRNA-211-3p |
| non-small cell lung cancer | upregulation | promote cell proliferation, invasion and metastasis, inhibit apoptosis. | EMT/MMP2/MMP9 |
| renal cell carcinoma | upregulation | promote cell proliferation, invasion and migration | EMT/NF-κB |
| non-small cell lung cancer | upregulation | promote cell proliferation, induce apoptosis and cycle arrest at G0/G1 phase | miR-486/CDK14 |
| breast cancer | upregulation | promote cell proliferation, migration,invasion and induce apoptosis | miR-211-3p/EMT |
| papillary thyroid cancer | upregulation | promote cell growth and migration | miR-200a-3p/YAP1-Hippo |
| epithelial ovarian cancer | upregulation | promote cell migration, invasion, proliferation and induce chemoresistance | – |
Several key points from our paper should be noted. First, our meta-analysis was the first study to exhaustively investigate the association between SNHG15 expression and clinical outcomes in cancer patients. In addition, only one random-effect model was employed in the analysis, indicating that the results are credible and accurate. Furthermore, we determined rigorous inclusion and exclusion criteria to enrol only high-quality studies.
Nonetheless, several limitations in our study should be considered. First, all the included subjects were from China, with small case numbers of certain cancer types and a small sample size, which led to our results being only applicable to Asia. To address this, we further validated these results using the GEPIA database to support our conclusion as broadly as possible. Further, HRs with 95% CIs were retrieved from K-M curves in six studies, which may inevitably exaggerate the prognostic value of SNGH15 and introduce bias. Moreover, the lack of articles with negative results may have caused an overestimation of the clinical value of this gene. Additionally, the inconsistent cut-off values may introduce heterogeneity among the studies.
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