SNHG20 serves as a predictor for prognosis and promotes cell growth in oral squamous cell carcinoma

Noncoding RNAs in oral cancer

Oral cancer (OC) is the most prevalent subtype of cancer arising in the head and neck region. OC risk is mainly attributed to behavioral risk factors such as exposure to tobacco and excessive alcohol consumption, and a lesser extent to viral infections such as human papillomaviruses and Epstein-Barr viruses. In addition to these acquired risk factors, heritable genetic factors have shown to be associated with OC risk. Despite the high incidence, biomarkers for OC diagnosis are lacking and consequently, patients are often diagnosed in advanced stages. This delay in diagnosis is reflected by poor overall outcomes of OC patients, where 5-year overall survival is around 50%. Among the biomarkers proposed for cancer detection, noncoding RNA (ncRNA) can be considered as one of the most promising categories of biomarkers due to their role in virtually all cellular processes. Similar to other cancer types, changes in expressions of ncRNAs have been reported in OC and a number of ncRNAs have diagnostic, prognostic, and therapeutic potential. Moreover, some ncRNAs are capable of regulating gene expression by various mechanisms. Therefore, elucidating the current literature on the four main types of ncRNAs namely, microRNA, lncRNA, snoRNA, piwi-RNA, and circular RNA in the context of OC pathogenesis is timely and would enable further improvements and innovations in diagnosis, prognosis, and treatment of OC. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development.

Expression and mechanism of long non-coding RNA HCG22 in oral squamous cell carcinoma

OBJECTIVES

To investigate the expression and mechanism of the long non-coding RNA (lncRNA) HCG22 in oral squamous cell carcinoma (OSCC).

METHODS

HCG22 levels were detected in the OSCC and adjacent tissues, OSCC cells, and normal oral keratinocytes. HCG22 expression in SCC-25 and HSC-3 cells was upregulated by transfection of the overexpressing plasmi dvector. Methyl thiazolyl tetrazolium (MTT) assay, flow cytometry, and Transwell assay were employed to detect changes in cell proliferation, apoptosis, migration, and invasion ability, while Western blotting was used to detect the expression of epithelial-mesenchymal transformation-related proteins. The expression level of miR-650 in the cells was detected by real-time quantitative polymerase chain reaction (RT-qPCR), and dual-luciferase reporter gene assay was applied to assess the targeting relationship between HCG22 and miR-650.

RESULTS

Compared with that in adjacent tissues, the expression of HCG22 significantly decreased in OSCC tissues (P<0.05). Moreover, the prognostic survival of patients in the low-HCG22 expression group was significantly lower than that in the high-expression group (P<0.05). Compared with that in HOK cells, the expression of HCG22 was significantly lower in SCC-25, HN13, HSC-3, and CAL-27 cells (P<0.05). Upregulation of HCG22 expression could inhibit the proliferation, migration, invasion, and apoptosis of SCC-25 and HSC-3 cells, upregulatethe expression of E-cadherin, and downregulate the expression of N-cadherin and vimentin (P<0.05). miR-650 mimics could reduce the luciferase activity of HCG22 wild-type plasmid cells (P<0.05), and the expression of miR-650 in SCC-25 and HSC-3 cells decreased after upregulation of HCG22 expression (P<0.05).

CONCLUSIONS

HCG22 is expressed at low levels in OSCC. Upregulation of the expression of this lncRNA can inhibit the proliferation, migration, invasion, and epithelial-mesenchymal transition of OSCC cells. The mechanism of action of HCG22 may be related to its targeted regulation of miR-650.

The Use of Machine Learning to Create a Risk Score to Predict Survival in Patients with Hepatocellular Carcinoma: A TCGA Cohort Analysis

INTRODUCTION

Hepatocellular carcinoma (HCC) accounts for approximately 90% of primary liver malignancies and is currently the fourth most common cause of cancer-related death worldwide. Due to varying underlying etiologies, the prognosis of HCC differs greatly among patients. It is important to develop ways to help stratify patients upon initial diagnosis to provide optimal treatment modalities and follow-up plans. The current study uses Artificial Neural Network (ANN) and Classification Tree Analysis (CTA) to create a gene signature score that can help predict survival in patients with HCC.

METHODS

The Cancer Genome Atlas (TCGA-LIHC) was analyzed for differentially expressed genes. Clinicopathological data were obtained from cBioPortal. ANN analysis of the 75 most significant genes predicting disease-free survival (DFS) was performed. Next, CTA results were used for creation of the scoring system. Cox regression was performed to identify the prognostic value of the scoring system.

RESULTS

363 patients diagnosed with HCC were analyzed in this study. ANN provided 15 genes with normalized importance >50%. CTA resulted in a set of three genes (NRM, STAG3, and SNHG20). Patients were then divided in to 4 groups based on the CTA tree cutoff values. The Kaplan-Meier analysis showed significantly reduced DFS in groups 1, 2, and 3 (median DFS: 29.7 months, 16.1 months, and 11.7 months, p < 0.01) compared to group 0 (median not reached). Similar results were observed when overall survival (OS) was analyzed. On multivariate Cox regression, higher scores were associated with significantly shorter DFS (1 point: HR 2.57 (1.38-4.80), 2 points: 3.91 (2.11-7.24), and 3 points: 5.09 (2.70-9.58), p < 0.01).

CONCLUSION

Long-term outcomes of patients with HCC can be predicted using a simplified scoring system based on tumor mRNA gene expression levels. This tool could assist clinicians and researchers in identifying patients at increased risks for recurrence to tailor specific treatment and follow-up strategies for individual patients.

Long Non-Coding RNAs as Functional Codes for Oral Cancer: Translational Potential, Progress and Promises

Oral cancer is one of the leading malignant tumors worldwide. Despite the advent of multidisciplinary approaches, the overall prognosis of patients with oral cancer is poor, mainly due to late diagnosis. There is an urgent need to develop valid biomarkers for early detection and effective therapies. Long non-coding RNAs (lncRNAs) are recognized as key elements of gene regulation, with pivotal roles in various physiological and pathological processes, including cancer. Over the past few years, an exponentially growing number of lncRNAs have been identified and linked to tumorigenesis and prognosis outcomes in oral cancer, illustrating their emerging roles in oral cancer progression and the associated signaling pathways. Herein, we aim to summarize the most recent advances made concerning oral cancer-associated lncRNA, and their expression, involvement, and potential clinical impact, reported to date, with a specific focus on the lncRNA-mediated molecular regulation in oncogenic signaling cascades and oral malignant progression, while exploring their potential, and challenges, for clinical applications as biomarkers or therapeutic targets for oral cancer.

Long Noncoding RNAs in Gastrointestinal Cancer: Tumor Suppression Versus Tumor Promotion

Approximately 80% of the human genome harbors biochemical marks of active transcription that its majority transcribes to noncoding RNAs, namely long noncoding RNAs (lncRNAs). LncRNAs are heterogeneous RNA transcripts that regulate critical biological processes such as cell survival and death. They involve in the progression of different cancers by affecting transcriptional and post-transcriptional modifications as well as epigenetic control of numerous tumor suppressors and oncogenes. Recent findings show that aberrant expression of lncRNAs is associated with tumor initiation, progression, invasion, and overall survival of patients with gastrointestinal (GI) cancers. Some lncRNAs play as tumor suppressors in all GI cancers, but others play as tumor promoters. However, some other lncRNAs might function as a tumor suppressor in one GI cancer, but as a tumor promoter in another GI cancer type. This fact highlights possible context dependency of the expression patterns and roles of at least some lncRNAs in GI cancer development and progression. Here, we review the functional relation of lncRNAs involved in the development and progression of GI cancer by focusing on their roles as tumor suppressor and tumor promoter genes.

Identification of long non-coding RNA signatures for squamous cell carcinomas and adenocarcinomas

Studies have demonstrated that both squamous cell carcinomas (SCCs) and adenocarcinomas (ACs) possess some common molecular characteristics. Evidence has accumulated to support the theory that long non-coding RNAs (lncRNAs) serve as novel biomarkers and therapeutic targets in complex diseases such as cancer.

In this study, we aimed to identify pan lncRNA signatures that are common to squamous cell carcinomas or adenocarcinomas with different tissues of origin. With the aid of elastic-net regularized regression models, a 35-lncRNA pan discriminative signature and an 11-lncRNA pan prognostic signature were identified for squamous cell carcinomas, whereas a 6-lncRNA pan discriminative signature and a 5-lncRNA pan prognostic signature were identified for adenocarcinomas. Among them, many well-known cancer relevant genes such as MALAT1 and PVT1 were included.

The identified pan lncRNA lists can help experimental biologists generate research hypotheses and adopt existing treatments for less prevalent cancers. Therefore, these signatures warrant further investigation.

Prognostic and clinicopathological significance of SNHG20 in human cancers: a meta-analysis

Background

It has been widely reported that the expression levels of SNHG20 are elevated in diverse types of cancers, indicating that SNHG20 may participate in cancer initiation and development. Besides, accumulating evidence reveals that SNHG20 overexpression is also connected with poor clinical outcomes among cancer patients. Herein, we carry out a systematic meta-analysis to further determine the prognostic and clinical significance of SNHG20 expression in various human cancers.

Methods

Qualifying publications were selected by searching for keywords in PubMed, Embase, Web of Science and Cochrane Library databases, up to September 1, 2019. Pooled hazard ratio (HR) or odds ratio (OR) with corresponding 95% confidence interval (CI) was computed to estimate the strength of association between SNHG20 and survival of cancer patients or clinicopathology using Stata 14.0 software.

Results

In total, 15 studies encompassing 1187 patients met the inclusion criteria were ultimately enrolled for analysis. According to the meta-analysis, patients with high SNHG20 expression were markedly linked to poorer overall survival (OS) (pooled HR = 2.47, 95% CI 2.05–2.98, P = 0.000) and disease-free survival/recurrence-free survival/progression-free survival (DFS/RFS/PFS) (pooled HR = 2.37, 95% CI 1.60–3.51, P = 0.000). Additionally, regarding clinicopathology of patients, enhanced SNHG20 was correlated with advanced tumour‐node‐metastasis (TNM) stage (OR = 2.80, 95% CI 2.00–3.93, P = 0.000), larger tumor size (OR = 3.08, 95% CI 2.11–4.51, P = 0.000), positive lymph nodes metastasis (OR = 2.99, 95% CI 2.08–4.31, P = 0.000), higher tumor stage (OR = 4.51, 95% CI 2.17–9.37, P = 0.000) and worse histological grade (OR = 1.95, 95% CI 1.44–2.63, P = 0.000), but not with gender, smoking status or distant metastasis.

Conclusions

Up-regulated SNHG20 expression is ubiquitous in different kinds of cancers. Moreover, up-regulated SNHG20 expression is capable of serving as an innovative predictive factor of inferior clinical outcomes in cancer patients. Nevertheless, higher-quality multicenter studies are required to corroborate our results.

An Emerging Class of Long Non-coding RNA With Oncogenic Role Arises From the snoRNA Host Genes

The small nucleolar RNA host genes (SNHGs) are a group of long non-coding RNAs, which are reported in many studies as being overexpressed in various cancers. With very few exceptions, the SNHGs (SNHG1, SNHG3, SNHG5, SNHG6, SNHG7, SNHG12, SNHG15, SNHG16, SNHG20) are recognized as inducing increased proliferation, cell cycle progression, invasion, and metastasis of cancer cells, which makes this class of transcripts a viable biomarker for cancer development and aggressiveness. Through our literature research, we also found that silencing of SNHGs through small interfering RNAs or short hairpin RNAs is very effective in both in vitro and in vivo experiments by lowering the aggressiveness of solid cancers. The knockdown of SNHG as a new cancer therapeutic option should be investigated more in the future.

Prognostic value of long non-coding RNA SNHG20 in cancer: A meta-analysis

BACKGROUND

Small nucleolar RNA host gene 20 (SNHG20) is a newly identified long non-coding RNA (lncRNA). Accumulative evidence suggest that SNHG20 is highly related to tumorigenesis. However, whether the levels of SNHG20 can be used for prognosis of patients with different cancer types was unclear. The present study aims to explore the role of SNHG20 in tumor prognosis and its clinical significance.

METHODS

Related articles published before March 14, 2019 were searched in PubMed, Excerpta Medica Database (EMBASE), ISI Web of Science, and China National Knowledge Infrastructure (CNKI). Hazard ratios (HRs) and their corresponding 95% confidence intervals (CIs) were obtained using Stata 11.0 software and used to for determination of the link between the levels of SNHG20 and overall survival (OS). Fixed or random model was chosen depending on the heterogeneity of the studies. A quality assessment of the included studies was performed according to the Newcastle-Ottawa scale. This study was approved by the Medical Ethics Committee of Xiangya Hospital of Central South University.

RESULTS

After a strict filtering process, a total of 1149 patients from 15 studies were enrolled in this study. Pooled data showed that elevated level of SNHG20 was correlated not only with poor overall survival (HR = 2.49, 95% confidence interval (CI): 2.05-2.98), but also with tumor-node-metastasis stage (TNM) (odds ratio (OR) = 3.32, 95% CI: 2.27-4.86), high histological grade (OR = 2.11, 95% CI: 1.55-2.87), tumor size (OR = 2.92, 95% CI: 2.17-3.91), and lymph node metastasis (OR = 4.48, 95% CI: 2.90-6.92). Of note, there is no significant heterogeneity difference among the studies.

CONCLUSION

Up-regulated SNHG20 predicts unfavorable prognosis for multiple kinds of cancers although further studies are in need to verify its clinical applications.