The prognostic value of lncRNA SNHG4 and its potential mechanism in liver cancer

Functional role of lncRNAs in gastrointestinal malignancies: the peculiar case of small nucleolar RNA host gene family

Long noncoding RNAs (lncRNAs) play crucial roles in normal physiology and are often de-regulated in disease states such as cancer. Recently, a class of lncRNAs referred to as the small nucleolar RNA host gene (SNHG) family have emerged as important players in tumourigenesis. Here, we discuss new findings describing the role of SNHGs in gastrointestinal tumours and summarize the three main functions by which these lncRNAs promote carcinogenesis, namely: competing with endogenous RNAs, modulating protein function, and regulating epigenetic marking. Furthermore, we discuss how SNHGs participate in different hallmarks of cancer, and how this class of lncRNAs may serve as potential biomarkers in cancer diagnosis and therapy.

Prognostic value of circulating long non-coding RNAs in colorectal cancer patients: a meta-analysis

OBJECTIVES

This meta-analysis aimed to evaluate the prognostic significance of circulating long non-coding RNAs (lncRNAs) in colorectal cancer (CRC).

METHODS

A comprehensive literature search was conducted in databases (Embase, Web of Science, PubMed, and Cochrane Library) up to July 2022. The quality of included studies was assessed using the Newcastle-Ottawa Scale (NOS). Statistical analysis was performed with Review Manager 5.4 and Stata 17.0. Publication bias was assessed using Begg's test, and sensitivity analysis was conducted to validate the meta-analysis results.

RESULTS

Ten articles, comprising 1,473 CRC patients and 18 different circulating lncRNAs, were included. Thirteen circulating lncRNAs were found to be up-regulated in CRC patients, while five were down-regulated. High expression of circulating lncRNAs up-regulated in CRC patients was associated with shorter CRC OS (HR = 2.91, 95% CI: 1.17, 7.22; P = 0.02, I2 = 86%). Conversely, high expression of circulating lncRNAs down-regulated in CRC patients was linked to longer CRC OS (HR = 0.16, 95% CI: 0.07, 0.40; P < 0.0001, I2 = 0%) and improved DFS (HR = 0.52, 95% CI: 0.37, 0.74; P = 0.0002, I2 = 0%). Additionally, circulating lncRNA levels correlated with TNM staging, tumor location, and lymph node metastasis.

CONCLUSION

Circulating lncRNAs show promise as prognostic markers for CRC patients, but further studies are warranted to validate these findings.

The siRNA-mediated knockdown of SNHG4 efficiently induced pro-apoptotic signaling and suppressed metastasis in SW1116 colorectal cancer cell line

BACKGROUND

Long non-coding RNAs are broadly dysregulated in disease conditions, especially cancer, and are associated with tumor initiation, invasion, and overall survival. This study aimed to elucidate the expression level of Small Nucleolar RNA Host Gene 4 (SNHG4) lncRNA in colorectal cancer (CRC) and its effect on cell cycle progression, invasion, and death.

METHODS AND RESULTS

We evaluated the expression level of SNHG4 in clinical samples, including CRC tissues, adenomatous colorectal polyps (ACP), and their marginals. SNHG4-silenced SW1116 cells were used to evaluate the cell viability, cycle arrest, invasion, and apoptosis using MTT assay, scratching, flow cytometry, and immunoblotting. We also predicted molecular networks related to the SNHG4 involvement in CRC development. Results showed that SNHG4 expresses in cancerous tissues significantly higher than in polyps and marginals. This overexpression discriminated CRC from marginals and ACP with a suitable prognostic potential. Silencing of SNHG4 arrested the cell cycle at S and G2 phases and promoted early apoptosis in SW1116. It affected the active form of MMP2 and prevented cell invasion. Sponging of miRNAs which promotes the choline metabolism is the probable mechanism of SNHG4 involvement in CRC.

CONCLUSIONS

In conclusion, SNHG4 promotes CRC by dysregulating apoptosis and cell migration, and shows significant prognostic potential for CRC.

Construction and systematic evaluation of a machine learning-based cuproptosis-related lncRNA score signature to predict the response to immunotherapy in hepatocellular carcinoma

Introduction

Hepatocellular carcinoma (HCC) is a common malignant cancer with a poor prognosis. Cuproptosis and associated lncRNAs are connected with cancer progression. However, the information on the prognostic value of cuproptosis-related lncRNAs is still limited in HCC.

Methods

We isolated the transcriptome and clinical information of HCC from TCGA and ICGC databases. Ten cuproptosis-related genes were obtained and related lncRNAs were correlated by Pearson's correlation. By performing lasso regression, we created a cuproptosis-related lncRNA prognostic model based on the cuproptosis-related lncRNA score (CLS). Comprehensive analyses were performed, including the fields of function, immunity, mutation and clinical application, by various R packages.

Results

Ten cuproptosis-related genes were selected, and 13 correlated prognostic lncRNAs were collected for model construction. CLS was positively or negatively correlated with cancer-related pathways. In addition, cell cycle and immune related pathways were enriched. By performing tumor microenvironment (TME) analysis, we determined that T-cells were activated. High CLS had more tumor characteristics and may lead to higher invasiveness and treatment resistance. Three genes (TP53, CSMD1 and RB1) were found in high CLS samples with more mutational frequency. More amplification and deletion were detected in high CLS samples. In clinical application, a CLS-based nomogram was constructed. 5-Fluorouracil, gemcitabine and doxorubicin had better sensitivity in patients with high CLS. However, patients with low CLS had better immunotherapeutic sensitivity.

Conclusion

We created a prognostic CLS signature by machine learning, and we comprehensively analyzed the signature in the fields of function, immunity, mutation and clinical application.

Long non-coding RNA SNHG4 enhances RNF14 mRNA stability to promote the progression of colorectal cancer by recruiting TAF15 protein

SNHG4 is a lncRNA that was previously reported to promote colorectal cancer (CRC) progression via molecular sponge mechanism. Bioinformatic analysis suggested SNHG4 might scaffold TAF15 protein-RNF14 mRNA interaction. We aimed to investigate the mechanisms of potential SNHG4/TAF15/RNF14 axis in promoting CRC malignant phenotypes. Protein-RNA interaction was determined using RNA immunoprecipitation, pull-down and fluorescence in situ hybridization (FISH) combined immunofluorescence assays. Cell apoptosis rates were quantified using flow cytometry. CCK-8 and colony formation were adopted to determine cell proliferation. Wound healing and transwell assays were employed to assess cell migration and invasion, respectively. Xenograft tumor model was applied to assess the effects of SNHG4 on CRC tumorigenesis in vivo. SNHG4, TAF15 and RNF14 were up-regulated in CRC tissues. SNHG4 overexpression promoted cell proliferation, migration, invasion, and Wnt/β-catenin pathway activation in vitro, as well as tumor growth in vivo. The inhibited malignant phenotypes caused by SNHG4 knockdown were impeded by TAF15 or RNF14 overexpression. Mechanistically, SNHG4 recruited TAF15 protein and thus promoted the interaction between TAF15 protein and RNF14 mRNA, leading to the increased RNF14 mRNA stability. This in turn facilitated the Wnt/β-catenin signal transduction. SNHG4 enhanced RNF14 mRNA stability and activated the Wnt/β-catenin pathway to promote the progression of colorectal cancer by recruiting TAF15 protein.

The Regulatory Mechanisms and Clinical Significance of Lnc SNHG4 in Cancer

BACKGROUND

LncRNAs have been reported to be involved in a variety of biological functions, including gene expression, cell growth, and differentiation. They may also serve as oncogenes or tumor suppressor genes in diseases. lncRNAs that can encode small nucleolar RNAs (snoRNAs) have been named small nucleolar RNA host genes (SNHGs).

OBJECTIVE

In this review article, we readily review the regulatory mechanisms and clinical significance of Lnc SNHG4 in cancer.

METHODS

We systematically investigated databases, like Scopus, PubMed, Embase, Google Scholar, and Cochrane Library database for all research articles, and have provided an overview regarding the biological functions and mechanisms of lncRNA SNHG4 in tumorigenesis.

RESULTS

Compared to neighboring normal tissues, SNHG4 is significantly dysregulated in various tumor tissues. SNHG4 upregulation is mainly associated with advanced tumor stage, tumor size, TNM stage, and decreased overall survival. In addition, aberrant SNHG4 expression promotes cell proliferation, metastasis, migration, and invasion of cancer cells.

CONCLUSION

SNHG4 may serve as a new therapeutic target and prognostic biomarker in patients with cancer.

Comprehensive analysis of nine m7G-related lncRNAs as prognosis factors in tumor immune microenvironment of hepatocellular carcinoma and experimental validation

Background: Hepatocellular carcinoma (HCC) remains the most prevalent gastrointestinal malignancy worldwide, with robust drug resistance to therapy. N7-methylguanosine (m7G) mRNA modification has been significantly related to massive human diseases. Considering the effect of m7G-modified long non-coding RNAs (lncRNAs) in HCC progression is unknown, the study aims at investigating a prognostic signature to improve clinical outcomes for patients with HCC.

Methods: Two independent databases (TCGA and ICGC) were used to analyze RNAseq data of HCC patients. First, co-expression analysis was applied to obtain the m7G-related lncRNAs. Moreover, consensus clustering analysis was employed to divide HCC patients into clusters. Then, using least absolute shrinkage and selection operator-Cox regression analysis, the m7G-related lncRNA prognostic signature (m7G-LPS) was first tested in the training set and then confirmed in both the testing and ICGC sets. The expression levels of the nine lncRNAs were further confirmed via real-time PCR in cell lines, principal component analysis, and receiver operating characteristic curve. The m7G-LPS could divide HCC patients into two different risk groups with the optimal risk score. Then, Kaplan–Meier curves, tumor mutation burden (TMB), therapeutic effects of chemotherapy agents, and expressions of immune checkpoints were performed to further enhance the availability of immunotherapeutic treatments for HCC patients.

Results: A total of 1465 lncRNAs associated with the m7G genes were finally selected from the TCGA database, and through the univariate Cox regression, the expression levels of 22 m7G-related lncRNAs were concerning HCC patients’ overall survival (OS). Then, the whole patients were grouped into two subgroups, and the OS in Cluster 1 was longer than that of patients in Cluster 2. Furthermore, nine prognostic m7G-related lncRNAs were identified to conduct the m7G-LPS, which were further verified. A prognostic nomogram combined age, gender, HCC grade, stage, and m7G-LPS showed strong reliability and accuracy in predicting OS in HCC patients. Finally, immune checkpoint expression, TMB, and several chemotherapy agents were remarkably associated with risk scores. More importantly, the OS of the TMB-high patients was the worst among the four groups.

Conclusion: The prognostic model we established was validated by abundant algorithms, which provided a new perspective on HCC tumorigenesis and thus improved individualized treatments for patients.

Identification and Validation of Necroptosis-Related LncRNA Signature in Hepatocellular Carcinoma for Prognosis Estimation and Microenvironment Status

Background: Hepatocellular carcinoma (HCC) is among malignancies with the highest fatality toll globally and minimal therapeutic options. Necroptosis is a programmed form of necrosis or inflammatory cell death, which can affect prognosis and microenvironmental status of HCC. Therefore, we aimed to explore the prognostic value of necroptosis-related lncRNAs (NRLs) in HCC and the role of the tumor microenvironment (TME) in immunotherapy. Methods: The RNA-sequencing data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). NRLs were identified by Pearson correlation analysis. The signature was constructed using the LASSO-Cox regression analysis and evaluated using the receiver operating characteristic curve (ROC) and the area under the Kaplan-Meier curve. The nomogram was built based on clinical information and risk score. Gene set enrichment analysis (GSEA), immunoassay, half-maximum inhibitory concentration (IC₅₀) analysis of the risk group, and the HCC subtype identification based on NRLs were also carried out. Finally, we detected the expression of lncRNAs in HCC tissues and cell lines in vitro. Results: A total of 508 NRLs were screened out, and seven NRLs were constructed as a risk stratification system to classify patients into distinct low- and high-risk groups. Patients in the high-risk group had a significantly lower overall survival (OS) than those in the low-risk group. Using multivariate Cox regression analysis, we found that the risk score was an independent predictor of OS. Functional analysis showed that the immune status of different patients was different. The IC₅₀ analysis of chemotherapy demonstrated that patients in the high-risk group were more sensitive to commonly prescribed drugs. qRT-PCR showed that three high-risk lncRNAs were upregulated in drug-resistant cells, and the expression in HCC tissues was higher than that in adjacent tissues. Conclusion: The prediction signature developed in this study can be used to assess the prognosis and microenvironment of HCC patients, and serve as a new benchmark for HCC treatment selection.

Expression and Regulatory Network Analysis of Function of Small Nucleolar RNA Host Gene 4 in Hepatocellular Carcinoma

BACKGROUND AND AIMS

Long non-coding RNA small nucleolar RNA host genes (SNHGs) play a critical role in the occurrence and development of tumors. In this study, we aimed to investigate the role of SNHG4 in hepatocellular carcinoma (HCC) and its underlining mechanism.

METHODS

Datasets were acquired from The Cancer Genome Atlas (TCGA) database. lncLocator 2.0 was used to identify the distribution of SNHG4 in HCC cells. Gene expression, Kaplan-Meier survival, microRNA and transcription factor target analyses were performed with the University of Alabama Cancer (UALCAN) Database, Kaplan-Meier Plotter, LinkedOmics, WebGestalt and gene set enrichment analysis, respectively. Gene Ontology and pathway enrichment analyses and assessment of RNA binding proteins were performed by R software, circlncRNAnet and Encyclopedia of RNA Interactomes (ENCORI). In addition, CirclncRNAnet and ENCORI were used to find the correlation between SNHG4 and important proteins, while the prognostic value was assessed with the Human Protein Atlas database and Kaplan-Meier Plotter.

RESULTS

Expression of SNHG4 in HCC is higher in HCC tissue than in normal healthy liver tissues and is mainly distributed in the nucleus. SNHG4 positively correlated with poor prognosis (p<0.01 for overall survival and recurrence-free survival). Functional enrichment analysis revealed SNHG4 involvement with regulation of ribosomal RNA synthesis and the RNA processing and surveillance pathway. SNHG4 is closely associated with miR-154 and miR-206, transcription factor target E2F family and the signaling pathway for MAPK/ERK and mTOR. U2 auxiliary factor 2 (U2AF2) showed strong correlation with SNHG4, while low-expression of U2AF2 showed good prognosis.

CONCLUSIONS

Based on our findings, we infer SNHG4 may play a role in the formation of HCC via regulation of tumor-related pathways.

Long non-coding RNA small nucleolar RNA host genes: functions and mechanisms in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of the digestive system, with a high degree of malignancy. Although treatment methods are constantly improving, the mortality of patients is still very high, and the small nucleolar RNA host gene (SNHG) plays an important role in the occurrence and development of cancer. It can activate downstream signaling molecules by acting on microRNA and microRNA target genes, promote the proliferation, invasion, and migration of HCC cells, and provide a new molecular target for the treatment of HCC. At present, the molecular mechanisms of HCC remain unclear. In this study, the mechanism and signaling pathway of SNHG in HCC are reviewed, which provides a theoretical basis for the clinical treatment of HCC.

The Association between Long Noncoding RNA over Expression and Poor Prognosis of Liver Cancer: A Meta-Analysis

BACKGROUND

Long noncoding RNA (lncRNA) is considered to be a mediator of carcinogenesis, which may be associated with liver cancer survival. However, the relationship remains inconclusive. Meta-analysis was conducted to analytically review the association between the lncRNA expression level and clinicopathological characteristics and prognostic value of hepatic carcinoma.

MATERIALS AND METHODS

Four databases including Embase, PubMed, Web of Science, and the Cochrane Library were searched to collect studies about the relation between lncRNA overexpression and prognosis of liver cancer, dating from the earliest records of these databases to March 2021. Two researchers independently screened the data and literature to perform a stringent evaluation of the quality of material involved in the study. Meta-analysis was performed by Stata 16.0 software on 42 case-control studies with 6293 samples.

RESULTS

The outcomes of meta-analysis are presented as follows: lncRNA overexpression patients had later TNM stage (OR = 0.36, 95% CI (0.31, 0.41), P < 0.001), lower histological grade (OR = 0.56, 95%CI (0.49, 0.65), P < 0.001), more vascular invasion (OR = 2.02, 95% CI (1.74, 2.35), P < 0.001), bigger tumor size (OR = 2.28, 95% CI (2.00, 2.60), P < 0.001), more severe liver cirrhosis (OR = 1.39, 95% CI(0.1.16, 1.66), P < 0.001), more likely to metastasize (OR = 1.80, 95%CI(1.49, 2.18), P < 0.001), and more tumor numbers (OR = 0.72, 95% CI (0.62, 0.84), P < 0.05). lncRNA over expression patients had shorter OS (HR = 2.32, 95 CI% (2.08, 2.59), P < 0.01, RFS (HR = 2.19, 95 CI% (1.72, 2.78), P < 0.01), and DFS (HR = 2.01, 95 CI% (1.57, 2.57), P < 0.01).

CONCLUSIONS

Overexposure of lncRNA is a poor prognostic feature for patients with hepatic carcinoma. The scope of our study was limited because of a lack of relevant research and the poor representativeness and varying quality of the studies involved in the current meta-analysis. Our conclusion still requires higher studies for further validation. This trial is clinically registered with CRD4201920620.

The Association between Long Noncoding RNA over Expression and Poor Prognosis of Liver Cancer: A Meta-Analysis

Background

Long noncoding RNA (lncRNA) is considered to be a mediator of carcinogenesis, which may be associated with liver cancer survival. However, the relationship remains inconclusive. Meta-analysis was conducted to analytically review the association between the lncRNA expression level and clinicopathological characteristics and prognostic value of hepatic carcinoma.

Materials and Methods

Four databases including Embase, PubMed, Web of Science, and the Cochrane Library were searched to collect studies about the relation between lncRNA overexpression and prognosis of liver cancer, dating from the earliest records of these databases to March 2021. Two researchers independently screened the data and literature to perform a stringent evaluation of the quality of material involved in the study. Meta-analysis was performed by Stata 16.0 software on 42 case-control studies with 6293 samples.

Results

The outcomes of meta-analysis are presented as follows: lncRNA overexpression patients had later TNM stage (OR = 0.36, 95% CI (0.31, 0.41), P < 0.001), lower histological grade (OR = 0.56, 95%CI (0.49, 0.65), P < 0.001), more vascular invasion (OR = 2.02, 95% CI (1.74, 2.35), P < 0.001), bigger tumor size (OR = 2.28, 95% CI (2.00, 2.60), P < 0.001), more severe liver cirrhosis (OR = 1.39, 95% CI(0.1.16, 1.66), P < 0.001), more likely to metastasize (OR = 1.80, 95%CI(1.49, 2.18), P < 0.001), and more tumor numbers (OR = 0.72, 95% CI (0.62, 0.84), P < 0.05). lncRNA over expression patients had shorter OS (HR = 2.32, 95 CI% (2.08, 2.59), P < 0.01, RFS (HR = 2.19, 95 CI% (1.72, 2.78), P < 0.01), and DFS (HR = 2.01, 95 CI% (1.57, 2.57), P < 0.01).

Conclusions

Overexposure of lncRNA is a poor prognostic feature for patients with hepatic carcinoma. The scope of our study was limited because of a lack of relevant research and the poor representativeness and varying quality of the studies involved in the current meta-analysis. Our conclusion still requires higher studies for further validation. This trial is clinically registered with CRD4201920620.

Long noncoding RNA SNHG4: a novel target in human diseases

Recently, long noncoding RNAs (lncRNAs) have attracted great attention from researchers. LncRNAs are non-protein-coding RNAs of more than 200 nucleotides in length. Multiple studies have been published on the relationship between lncRNA expression and the progression of human diseases. LncRNA small nucleolar RNA host gene 4 (SNHG4), a member of the lncRNA SNHG family, is abnormally expressed in a variety of human diseases, including gastric cancer, renal cell carcinoma, glioblastoma, neuroblastoma, prostate cancer, colorectal cancer, osteosarcoma, cervical cancer, liver cancer, lung cancer, non-small-cell lung cancer, neonatal pneumonia, diabetic retinopathy, neuropathic pain, acute cerebral infarction, acute myeloid leukaemia, and endometriosis. In this paper, the structure of SNHG4 is first introduced, and then studies in humans, animal models and cells are summarized to highlight the expression and function of SNHG4 in the above diseases. In addition, the specific mechanism of SNHG4 as a competing endogenous RNA (ceRNA) is discussed. The findings indicate that SNHG4 can be used as a biomarker for disease prognosis evaluation and as a potential target for disease diagnosis and treatment.

Comprehensive Analysis of lncRNAs Related to the Prognosis of Esophageal Cancer Based on ceRNA Network and Cox Regression Model

Background

Esophageal cancer is one of the most deadly malignant tumors. Among the common malignant tumors in the world, esophageal cancer is ranked seventh, which has a high mortality rate. Long noncoding RNAs (lncRNAs) play an important role in the occurrence and development of various tumors. lncRNAs can competitively bind microRNAs (miRNAs) with mRNA, which can regulate the expression level of the encoded gene at the posttranscriptional level. This regulatory mechanism is called the competitive endogenous RNA (ceRNA) hypothesis, and ceRNA has important research value in tumor-related research. However, the regulation of lncRNAs is less studied in the study of esophageal cancer.

Methods

The Cancer Genome Atlas (TCGA) database was used to download transcriptome profiling data of esophageal cancer. Gene expression quantification data contains 160 cancer samples and 11 normal samples. These data were used to identify differentially expressed lncRNAs and mRNAs. miRNA expression data includes 185 cancer samples and 13 normal samples. The differentially expressed RNAs were identified using the edgeR package in R software. Then, the miRcode database was used to predict miRNAs that bind to lncRNAs. MiRTarBase, miRDB, and TargetScan databases were used to predict the target genes of miRNAs. Cytoscape software was used to draw ceRNA network. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using DAVID 6.8. Finally, multifactor cox regression was used to screen lncRNAs related to prognosis.

Results

We have screened 1331 DElncRNAs, 3193 DEmRNAs, and 162 DEmiRNAs. Among them, the ceRNA network contains 111 lncRNAs, 11 miRNAs, and 63 DEmRNAs. Finally, we established a prediction model containing three lncRNAs through multifactor Cox regression analysis.

Conclusions

Our research screened out three independent prognostic lncRNAs from the ceRNA network and constructed a risk assessment model. This is helpful to understand the regulatory role of lncRNAs in esophageal cancer.

Long noncoding RNA SNHG4 promotes renal cell carcinoma tumorigenesis and invasion by acting as ceRNA to sponge miR-204-5p and upregulate RUNX2

Background

Long noncoding RNAs (lncRNAs) are involved in the tumorigenesis and progression of human cancers, including renal cell carcinoma (RCC). Small nucleolar RNA host gene 4 (SNHG4) is reported to play an essential role in tumor growth and progression. However, the molecular mechanisms and function of SNHG4 in RCC remain undocumented.

Methods

Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to examine expression levels of SNHG4 in RCC tissue samples and cell lines. Cell counting kit-8, western blotting, activities of caspase-3, -8, and -9, wound-healing, and transwell invasion assays were performed to explore cell proliferation, apoptosis, migration, and invasion. The interaction among SNHG4, miR-204-5p, and RUNX2 was verified by bioinformatic analysis, a luciferase gene report, qRT-PCR, western blot analysis, and RNA immunoprecipitation assays. Xenograft mouse models were carried out to examine the role of SNHG4 in RCC in vivo.

Results

SNHG4 was highly expressed in RCC tissue samples and cell lines, and its upregulation was significantly involved in node involvement, distant metastasis, and reduced overall and relapse-free survival of patients with RCC. SNHG4 acted as an oncogenic lncRNA with promoted RCC cell proliferation, migration, invasion, and inhibited apoptosis. SNHG4 boosted tumor growth in xenograft mouse models. Mechanistically, SNHG4 functioned as a competing endogenous RNA (ceRNA) for sponging miR-204-5p, leading to the upregulation of its target RUNX2 to promote RCC cell proliferation and invasion.

Conclusion

SNHG4 and miR-204-5p might be indicated in RCC progression via RUNX2, suggesting the potential use of SNHG4/miR-204-5p/RUNX2 axis in RCC treatment.

Knockdown of lncRNA LINC01234 Suppresses the Tumorigenesis of Liver Cancer via Sponging miR-513a-5p

Background

Liver cancer is a frequent malignancy with poor prognosis and high mortality all over the world. It has been reported many lncRNAs could modulate the tumorigenesis of liver cancer. To identify novel potential targets for liver cancer, the differential expressed lncRNAs between liver cancer and adjacent normal tissues was analyzed with bioinformatics tool.

Methods

The differential expressed lncRNAs between liver cancer and adjacent normal tissues were analyzed with bioinformatics tool. Cell viability and proliferation was tested by CCK8 and Ki67, respectively. Apoptosis of liver cancer cells was tested by flow cytometry. Gene and protein expressions in liver cancer cells were measured by qRT-PCR and western blot, respectively. In vivo model of liver cancer was established to detect the effect of LINC01234 on liver cancer in vivo.

Results

LINC01234 was found to be negatively correlated with the survival rate of patients with liver cancer. Moreover, knockdown of LINC01234 significantly suppressed the proliferation and invasion of liver cancer cells via inducing the apoptosis. Meanwhile, miR-513a-5p was sponged by LINC01234, and USP4 was found to be a direct target of miR-513a-5p. In addition, LINC01234 knockdown inhibited the tumorigenesis of liver cancer via inactivating TGF-β signaling. Furthermore, silencing of LINC01234 notably inhibited the tumor growth of liver cancer in vivo.

Conclusion

Downregulation of LINC01234 could inhibit the tumorigenesis of liver cancer via mediation of miR-513a-5p/USP4/TGF-β axis. Thus, LINC01234 might serve as a new target for the treatment of liver cancer.

The Prediction and Prognostic Significance of INPP5K Expression in Patients with Liver Cancer

Liver cancer is a devastating disease for humans with poor prognosis. Although the survival rate of patients with liver cancer has improved in the past decades, the recurrence and metastasis of liver cancer are still obstacles for us. Inositol polyphosphate-5-phosphatase K (INPP5K) belongs to the family of phosphoinositide 5-phosphatases (PI 5-phosphatases), which have been reported to be associated with cell migration, polarity, adhesion, and cell invasion, especially in cancers. However, there have been few studies on the correlation of INPP5K and liver cancer. In this study, we explored the prognostic significance of INPP5K in liver cancer through bioinformatics analysis of data collected from The Cancer Genome Atlas (TCGA) database. Chi-square and Fisher exact tests were used to evaluate the relationship between INPP5K expression and clinical characteristics. Our results showed that low INPP5K expression was correlated with poor outcomes in liver cancer patients. Univariate and multivariate Cox analyses demonstrated that low INPP5K mRNA expression played a significant role in shortening overall survival (OS) and relapse-free survival (RFS), which might serve as the useful biomarker and prognostic factor for liver cancer. In conclusion, low INPP5K mRNA expression is an independent risk factor for poor prognosis in liver cancer.