Bioinformatic analysis of the prognostic value of the lncRNAs encoding snoRNAs in hepatocellular carcinoma

Construction of CDKN2A-related competitive endogenous RNA network and identification of GAS5 as a prognostic indicator for hepatocellular carcinoma

BACKGROUND

Competitive endogenous RNA (ceRNA) is an innovative way of gene expression modulation, which plays a crucial part in neoplasia. However, the intricacy and behavioral characteristics of the ceRNA network in hepatocellular carcinoma (HCC) remain dismal.

AIM

To establish a cyclin dependent kinase inhibitor 2A (CDKN2A)-related ceRNA network and recognize potential prognostic indicators for HCC.

METHODS

The mutation landscape of CDKN2A in HCC was first explored using the cBioPortal database. Differential expression analysis was implemented between CDKN2Ahigh and CDKN2Alow expression HCC samples. The targeted microRNAs were predicted by lncBasev3.0, and the targeted mRNAs were predicted by miRDB, and Targetscan database. The univariate and multivariate analysis were utilized to identify independent prognostic indicators.

RESULTS

CDKN2A was frequently mutated and deleted in HCC. The single-cell RNA-sequencing analysis revealed that CDKN2A participated in cell cycle pathways. The CDKN2A-related ceRNA network-growth arrest specific 5 (GAS5)/miR-25-3p/SRY-box transcription factor 11 (SOX11) was successfully established. GAS5 was recognized as an independent prognostic biomarker, whose overexpression was correlated with a poor prognosis in HCC patients. The association between GAS5 expression and methylation, immune infiltration was explored. Besides, traditional Chinese medicine effective components targeting GAS5 were obtained.

CONCLUSION

This CDKN2A-related ceRNA network provides innovative insights into the molecular mechanism of HCC formation and progression. Moreover, GAS5 might be a significant prognostic biomarker and therapeutic target in HCC.

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.

Comprehensive analysis of cuproptosis-related long non-coding RNAs in prognosis, immune microenvironment infiltration and chemotherapy response of hepatocellular carcinoma

The objective of this study is to explore the relationship between cuproptosis-related long noncoding RNAs (lncRNAs) in hepatocellular carcinoma (HCC). RNA-seq data, including lncRNAs and related clinical information of HCC patients, were downloaded from The Cancer Genome Atlas database. A signature composed 3 cuproptosis-related lncRNAs was constructed by LASSO analysis, and HCC patients were classified into high- and low-risk groups. Patients in the high-risk group had a poorer prognosis compared with the low-risk group. Univariate Cox and multivariate Cox regression analyses confirmed that the signature model was an independent risk factor compared to other clinical biomarkers. Furthermore, gene set enrichment analysis indicated that metabolism-related pathways were enriched in low-risk group, including drug metabolism, and fatty acid metabolism. Further research demonstrated that there were markedly differences in drug response between the high- and low-risk group. Immune related analysis showed that the most type of immune cells and immunological function in the high-risk group were different with the risk-group. Finally, TP53 mutation rate and the tumor mutational burden in the high-risk group were higher compared with the low-risk group. In conclusion, we constructed a prognostic signature based on the expression of cuproptosis-related lncRNAs to predict HCC patients' prognosis, drug response and immune microenvironment, and further research will be conducted to uncover the mechanisms.

Unlocking the predictive potential of long non-coding RNAs: a machine learning approach for precise cancer patient prognosis

The intricate web of cancer biology is governed by the active participation of long non-coding RNAs (lncRNAs), playing crucial roles in cancer cells' proliferation, migration, and drug resistance. Pioneering research driven by machine learning algorithms has unveiled the profound ability of specific combinations of lncRNAs to predict the prognosis of cancer patients. These findings highlight the transformative potential of lncRNAs as powerful therapeutic targets and prognostic markers. In this comprehensive review, we meticulously examined the landscape of lncRNAs in predicting the prognosis of the top five cancers and other malignancies, aiming to provide a compelling reference for future research endeavours. Leveraging the power of machine learning techniques, we explored the predictive capabilities of diverse lncRNA combinations, revealing their unprecedented potential to accurately determine patient outcomes.

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.

Overall Survival Signature of 5-Methylcytosine Regulators Related Long Non-Coding RNA in Hepatocellular Carcinoma

Purpose

Studies reported that 5-methylcytosine (m5C) RNA transferase alters tumor progression; however, studies of m5C-related lncRNA remain lacking. This article intends to study the lncRNA modified by m5C RNA transferase in hepatocellular carcinoma using a combination of computational biology and basic experiments.

Method

We identified 13 m5C RNA transferase-related genes and selected long non-coding RNAs with a Pearson correlation coefficient greater than 0.4. Univariate Cox regression analysis was used to screen m5C RNA transferase lncRNA related to survival phenotype. We divided TCGA-LIHC into two types of m5C RNA using non-negative matrix decomposition. According to WGCNA, the co-expression models of two lncRNA regulation modes were constructed to analyze the characteristic biological processes of the two m5C RNA transferase-related lncRNA gene models. Then, a predictive model of m5C RNA transferase lncRNA was using LASSO regression. Finally, we used cell experiments, transwell experiments, and clone formation experiments to test the relationship between SNHG4 and tumor cell proliferation in Hep-G2 and Hep-3b cells line.

Results

We identified 436 m5C RNA transferase-related lncRNAs. Using univariate Cox regression analysis, 43 prognostic-related lncRNAs were determined according to P < 0.001. We divided TCGA-LIHC into two regulation modes of m5C RNA transferase using non-negative matrix factorization. The two regulation modes showed significant differences in overall and disease-free survival. We used LASSO to construct m5c-related lncRNA prognostic signature. Thus, a predictive m5C-lncRNA model was established using four lncRNAs: AC026412.3, AC010969.2, SNHG4, and AP003392.5. The score calculated by the m5C-lncRNA model significantly correlated with the overall survival of hepatocellular carcinoma. The receiver operating characteristic curve and decision curve analysis verified the accuracy of the predictive model. We observed a more robust immune response in the high-risk score group. The transwell experiments and clone formation experiments suggested that m5C RNA transferase-related lncRNA SNHG4 promotes the proliferation and migration of Hep-G2 and Hep-3b cells line.

Conclusion

Two lncRNA expression patterns regulated by m5C RNA transferase were identified. The difference between the two expression patterns and the survival phenotype in the biological process was pointed out. A 5-methylcytosine RNA methyltransferases-related lncRNA overall survival signature was constructed. These results provide some understanding of the influence of m5C transferase on hepatocellular carcinoma. The prediction model of m5C transferase lncRNA has potential clinical value in managing hepatocellular carcinoma.

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.

Bioinformatic Analyses of the Ferroptosis-Related lncRNAs Signature for Ovarian Cancer

Both ferroptosis and lncRNAs are significant for ovarian cancer (OC). Whereas, the study of ferroptosis-related lncRNAs (FRLs) still few in ovarian cancer. We first constructed an FRL-signature for patients with OC in the study. A total of 548 FRLs were identified for univariate Cox regression analysis, and 21 FRLs with significant prognosis were identified. The prognostic characteristics of nine FRLs was constructed and validated, showing opposite prognosis in two subgroups based on risk scores. The multivariate Cox regression analysis and nomogram further verified the prognostic value of the risk model. By calculating ferroptosis score through ssGSEA, we found that patients with higher risk scores exhibited higher ferroptosis scores, and high ferroptosis score was a risk factor. There were 40 microenvironment cells with significant differences in the two groups, and the difference of Stromal score between the two groups was statistically significant. Six immune checkpoint genes were expressed at different levels in the two groups. In addition, five m6A regulators (FMR1, HNRNPC, METTL16, METTL3, and METTL5) were higher expressed in the low-risk group. GSEA revealed that the risk model was associated with tumor-related pathways and immune-associated pathway. We compared the sensitivity of chemotherapy drugs between the two risk groups. We also explored the co-expression, ceRNA relation, cis and trans interaction of ferroptosis-related genes and lncRNAs, providing a new idea for the regulatory mechanisms of FRLs. Moreover, the nine FRLs were selected for detecting their expression levels in OC cells and tissues.

Emerging role of long noncoding RNAs in recurrent hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains one of the most frequent types of liver cancer and is characterized by a high recurrence rate. Recent studies have proposed that long non-coding RNAs (lncRNAs) are potential biomarkers in several recurrent tumor types. It is now well understood that invasion, migration, and metastasis are important factors for tumor recurrence. Moreover, some of the known risk factors for HCC may affect the expression levels of several types of lncRNAs and thus affect the recurrence of liver cancer through lncRNA regulation. In this paper, we review the biological functions, molecular mechanisms, and roles of lncRNAs in HCC and summarize current knowledge about lncRNAs as potential biomarkers in recurrent HCC.

The role of ceRNA-mediated diagnosis and therapy in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide due to its high degree of malignancy, high incidence, and low survival rate. However, the underlying mechanisms of hepatocarcinogenesis remain unclear. Long non coding RNA (lncRNA) has been shown as a novel type of RNA. lncRNA by acting as ceRNA can participate in various biological processes of HCC cells, such as tumor cell proliferation, migration, invasion, apoptosis and drug resistance by regulating downstream target gene expression and cancer-related signaling pathways. Meanwhile, lncRNA can predict the efficacy of treatment strategies for HCC and serve as a potential target for the diagnosis and treatment of HCC. Therefore, lncRNA serving as ceRNA may become a vital candidate biomarker for clinical diagnosis and treatment. In this review, the epidemiology of HCC, including morbidity, mortality, regional distribution, risk factors, and current treatment advances, was briefly discussed, and some biological functions of lncRNA in HCC were summarized with emphasis on the molecular mechanism and clinical application of lncRNA-mediated ceRNA regulatory network in HCC. This paper can contribute to the better understanding of the mechanism of the influence of lncRNA-mediated ceRNA networks (ceRNETs) on HCC and provide directions and strategies for future studies.

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.

Long noncoding RNA SNHG10 promotes colorectal cancer cells malignant progression by targeting miR-3690

Long noncoding RNA small nucleolar RNA host gene 10 (SNHG10) has been suggested to function as tumor promoter in various human cancer types. Herein, the role of SNHG10 in colorectal cancer (CRC) was explored. Expression levels of genes in colorectal cancer tissues and cell lines were detected by Starbase and reverse transcription quantitative PCR (RT-qPCR) Cell Counting Kit-8 (CCK-8), the BrdU incorporation assay and Transwell assays were explored to study the function of SNHG10 in HCT116 and DXH-1 cells. In addition, the interaction of SNHG10 and miR-3690 was analyzed by dual-luciferase reporter assays. SNHG10 had a high expression level in CRC tissues and cell lines. Meanwhile, knockdown of SNHG10 reduced cell viability, inhibited cell proliferation and decreased cell migration and invasion. Moreover, bioinformatics analysis revealed that one potential target gene of SNHG10 was miR-3690. Dual-luciferase reporter assay confirmed that miR-3690 directly targeted SNHG10. Importantly, SNHG10 could decrease the expression of miR-3690 in HCT116 and DXH-1 cells. More importantly, the silencing of miR-3690 reversed the effect of the SNHG10 knockdown on the cell viability, proliferation, migration and invasion of HCT116 and DXH-1 cells. The present results demonstrated that SNHG10 promotes colorectal cancer cells the malignant progression by targeting miR-3690.Abbreviations: CRC: Colorectal cancer; Lnc RNA: Long noncoding RNA; microRNAs: miRNAs/miRs; RT-qPCR: reverse transcription quantitative polymerase chain reaction; CCK-8: Cell Counting Kit-8.

A innovative prognostic symbol based on neutrophil extracellular traps (NETs)-related lncRNA signature in non-small-cell lung cancer

Neutrophil extracellular traps (NETs) are closely related to cancer progression. NETs-related lncRNAs play crucial roles in non-small-cell lung cancer (NSCLC) but there have been no systematic studies regarding NETs-related long noncoding RNA (lncRNA) signatures to forecast the prognosis of NSCLC patients. It’s essential to build commensurate NETs-related lncRNA signatures. The expression profiles of prognostic mRNAs and lncRNAs and relevant clinical data of NSCLC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The NETs-related genes came from the results of our transcriptome RNA microarray data. The co-expression network of lncRNAs and NETs-related genes was structured to confirm NETs-related lncRNAs. The 19 lncRNAs correlated with overall survival (OS) were selected by exploiting univariate Cox regression (P < 0.05). Lasso regression and multivariate Cox regression (P < 0.05) were utilized to develop a 12-NETs-related lncRNA signature. We established a risk score based on the signature, which suggested that patients in the high-risk group displayed significantly shorter OS than patients in the low-risk group (P < 0.0001, P = 0.0023 respectively in the two cohorts). The risk score worked as an independent predictive factor for OS in both univariate and multivariate Cox regression analyses (HR> 1, P< 0.001). Additionally, by RT-qPCR, we confirmed that NSCLC cell lines have higher levels of the three adverse prognostic NETs-related lncRNAs than normal lung cells. The expression of lncRNAs significantly increases after NETs stimulation. In short, the 12 NETs-related lncRNAs and their model could play effective roles as molecular markers in predicting survival for NSCLC patients.

Identification of Cancer Cell Stemness-Associated Long Noncoding RNAs for Predicting Prognosis of Patients with Hepatocellular Carcinoma

Long noncoding RNAs (lncRNAs) are emerging as crucial contributors to the development of hepatocellular carcinoma (HCC) and are involved in the stemness regulation of liver cancer stem cells (LCSCs). However, cancer cell stemness-associated lncRNAs and their relevance in prediction of clinical prognosis remain largely unexplored. In this study, through the transcriptome-wide screen, we identified a total of 136 LCSC-associated lncRNAs. We evaluated the prognostic value of these lncRNAs and optimally established an 11-lncRNA (including AC008622.2, AC015908.3, AC020915.2, AC025176.1, AC026356.2, AC099850.3, CYTOR, DDX11-AS1, HTR2A-AS1, LINC02870, and SNHG3) prognostic risk model. Multivariate analysis revealed that the risk score is an independent prognostic predictor for HCC patients, which outperforms the traditional clinical pathological factors. Gene set enrichment analysis suggested that the high-risk score reflects the alteration of pathways involved in cell cycle, oxidative phosphorylation, and metabolism. Furthermore, functional studies on SNHG12, the leading candidate of the risk lncRNAs, revealed that knockdown of SNHG12 reduces the abilities of HCC cells stemness, proliferation, migration, and invasion. In summary, we constructed a prognostic risk model based on 11 LCSC-associated lncRNAs, which might be a promising prognostic predictor for HCC patients and highlight the involvement of lncRNAs in LCSC-associated treatment strategy in clinical practice.

lncRNA SNHG4 modulates colorectal cancer cell cycle and cell proliferation through regulating miR-590-3p/CDK1 axis

Colorectal cancer (CRC) is a prevalent malignancy worldwide. The development of genome sequencing technology has allowed the discovery that epigenetic regulation might play a critical role in CRC tumorigenesis. In the present study, we found that the long noncoding RNA (lncRNA) SNHG4 was dramatically increased in CRC tissue samples and cell lines based on both publicly available and experimental data. SNHG4 knockdown suppressed the viability and colony formation capacity of CRC cells. The expression of CDK1 was considerably increased in CRC tissue samples and cells and had a positive correlation with the expression of SNHG4 in CRC. SNHG4 silencing not only caused S phase cell cycle arrest but also significantly downregulated the CDK1, cyclin B1, and cyclin A2 protein levels in CRC cells. miR-590-3p simultaneously bound to SNHG4 and CDK1. miR-590-3p functioned to inhibit CDK1 expression. miR-590-3p overexpression exerted the same effects on the CRC cell phenotype as SNHG4 knockdown. The effects of si-SNHG4 on CRC cells were significantly reversed by anti-miR-590-3p, indicating that SNHG4 relieved the miR-590-3p-induced inhibition of CDK1 by acting as a competing endogenous RNA (ceRNA). In vivo, SNHG4 silencing inhibited subcutaneously transplanted tumor growth and decreased cell cycle marker levels, whereas miR-590-3p inhibition exerted the opposite effects. The in vivo effects of SNHG4 silencing were also reversed by miR-590-3p inhibition. The SNHG4/miR-590-3p/CDK1 axis influences the cell cycle to modulate CRC cell proliferation and subcutaneously transplanted tumor growth. Further application of this axis still requires analysis using more animal models and clinical investigations.

SNHG1 knockdown upregulates miR-376a and downregulates FOXK1/Snail axis to prevent tumor growth and metastasis in HCC

Long non-coding RNAs (lncRNAs), microRNAs (miRNAs or miRs), and genes are emerging players in cancer progression. In the present study, we explored the roles and interactions of oncogenic lncRNA small nucleolar RNA host gene 1 (SNHG1), miR-376, forkhead box protein K1 (FOXK1), and Snail in hepatocellular carcinoma (HCC). Expression of SNHG1, miR-376, and FOXK1 in HCC was characterized in clinical HCC tissues of 75 patients with HCC. The interactions between SNHG1 and miR-376 and between miR-376 and FOXK1 were predicted and confirmed by dual-luciferase reporter gene and RNA immunoprecipitation assays. Overexpression and knockdown experiments were performed in HCC cells to examine the effects of the SNHG1/miR-376/FOXK1/Snail axis on viability, apoptosis, invasiveness, and migrating abilities. Their effects on tumor growth and metastasis were validated in nude mouse models. SNHG1 and FOXK1 were upregulated, and miR-376a was downregulated in HCC. SNHG1 knockdown contributed to suppression of HCC cell viability, invasion, and migration properties and promotion of apoptosis. SNHG1 could competitively bind to miR-376a to upregulate its target gene FOXK1, which upregulated Snail. SNHG1 knockdown delayed cancer progression both in vitro and in vivo by upregulating miR-376a and downregulating FOXK1 and Snail. SNHG1 knockdown exerts anti-tumor activity in HCC, suggesting a therapeutic target.

Crosstalk of long non-coding RNAs and EMT: Searching the missing pieces of an incomplete puzzle for lung cancer therapy

BACKGROUND

Lung cancer is considered to be the first place among the cancer-related deaths worldwide and demands novel strategies in the treatment of this life-threatening disorder. The aim of this review is to explore regulation of epithelial-to-mesenchymal transition (EMT) by long non-coding RNAs (lncRNAs) in lung cancer.

INTRODUCTION

LncRNAs can be considered as potential factors for targeting in cancer therapy, since they regulate a bunch of biological processes, e.g. cell proliferation, differentiation and apoptosis. The abnormal expression of lncRNAs occurs in different cancer cells. On the other hand, epithelial-to-mesenchymal transition (EMT) is a critical mechanism participating in migration and metastasis of cancer cells.

METHOD

Different databases including Googlescholar, Pubmed and Sciencedirect were used for collecting articles using keywords such as "LncRNA", "EMT", and "Lung cancer".

RESULT

There are tumor-suppressing lncRNAs that can suppress EMT and metastasis of lung cancer cells. Expression of such lncRNAs undergoes down-regulation in lung cancer progression and restoring their expression is of importance in suppressing lung cancer migration. There are tumor-promoting lncRNAs triggering EMT in lung cancer and enhancing their migration.

CONCLUSION

LncRNAs are potential regulators of EMT in lung cancer, and targeting them, both pharmacologically and genetically, can be of importance in controlling migration of lung cancer cells.

LncRNA SNHG9 is a prognostic biomarker and correlated with immune infiltrates in prostate cancer

Background

Expression of Long non-coding RNA (LncRNA) small nucleolar RNA host gene 9 (SNHG9) is observed in some cancer types, while its role in prostate cancer (PCa) is unclear. We aimed to demonstrate the relationship between SNHG9 and PCa based on The Cancer Genome Atlas (TCGA) database.

Methods

Kruskal-Wallis test, Wilcoxon signed-rank test, and logistic regression were used to evaluate relationships between clinical-pathologic features and SNHG9 expression. Receiver operating characteristic (ROC) curves were used to describe binary classifier value of SNHG9 using area under curve (AUC) score. Kaplan-Meier method and Cox regression analysis were used to evaluate factors contributing to prognosis. Gene set enrichment analysis (GSEA) and immune infiltration analysis were performed to identify the significantly involved functions of SNHG9.

Results

Increased SNHG9 expression in PCa was associated with N stage (P<0.001), Gleason score (P=0.002), primary therapy outcome (P=0.001), residual tumor (P<0.001) and prostate specific antigen (PSA) (P=0.007). ROC curve suggested the significant diagnostic and prognostic ability of SNHG9 (AUC =0.815). High SNHG9 expression predicted a poorer progression-free survival (PFS) (P=0.002), and SNHG9 expression (HR: 1.776; 95% CI: 1.067-2.955; P=0.027) was independently correlated with PFS in PCa patients. GSEA and immune infiltration analysis showed that SNHG9 expression was correlated with regulating the function of ribosome and some types of immune infiltrating cells.

Conclusions

SNHG9 expression was significantly correlated with poor survival and immune infiltrations in PCa, and it may be a promising prognostic biomarker in PCa.

Are spliced ncRNA host genes distinct classes of lncRNAs?

Many small nucleolar RNAs and many of the hairpin precursors of miRNAs are processed from long non-protein-coding host genes. In contrast to their highly conserved and heavily structured payload, the host genes feature poorly conserved sequences. Nevertheless, there is mounting evidence that the host genes have biological functions beyond their primary task of carrying a ncRNA as payload. So far, no connections between the function of the host genes and the function of their payloads have been reported. Here we investigate whether there is evidence for an association of host gene function or mechanisms with the type of payload. To assess this hypothesis we test whether the miRNA host genes (MIRHGs), snoRNA host genes (SNHGs), and other lncRNA host genes can be distinguished based on sequence and/or structure features unrelated to their payload. A positive answer would imply a functional and mechanistic correlation between host genes and their payload, provided the classification does not depend on the presence and type of the payload. A negative answer would indicate that to the extent that secondary functions are acquired, they are not strongly constrained by the prior, primary function of the payload. We find that the three classes can be distinguished reliably when the classifier is allowed to extract features from the payloads. They become virtually indistinguishable, however, as soon as only sequence and structure of parts of the host gene distal from the snoRNAs or miRNA payload is used for classification. This indicates that the functions of MIRHGs and SNHGs are largely independent of the functions of their payloads. Furthermore, there is no evidence that the MIRHGs and SNHGs form coherent classes of long non-coding RNAs distinguished by features other than their payloads.

Identification of grade-related genes and construction of a robust genomic-clinicopathologic nomogram for predicting recurrence of bladder cancer

BACKGROUND

Bladder cancer (BC) is a common tumor in the urinary system with a high recurrence rate. The individualized treatment and follow-up after surgery is the key to a successful outcome. Currently, the surveillance strategies are mainly depending on tumor stage and grade. Previous evidence has proved that tumor grade was a significant and independent risk factor of BC recurrence. Exploring the grade-related genes may provide us a new approach to predict prognosis and guide the post-operative treatment in BC patients.

METHODS

In this study, the weighted gene co-expression network analysis was applied to identify the hub gene module correlated with BC grade using GSE71576. After constructing a protein-protein interaction (PPI) network with the hub genes inside the hub gene module, we identified some potential core genes. TCGA and another independent dataset were used for further validation.

RESULTS

The results revealed that the expression of AURKA, CCNA2, CCNB1, KIF11, TTK, BUB1B, BUB1, and CDK1 were significantly higher in high-grade BC, showing a strong ability to distinguish BC grade. The expression levels of the 8 genes in normal, paracancerous, tumorous, and recurrent bladder tissues were progressively increased. By conducting survival analysis, we proved their prognostic value in predicting the recurrence of BC. Eventually, we constructed a prognostic nomogram by combining the 8-core-gene panel with clinicopathologic features, which had shown great performance in predicting the recurrence of BC.

CONCLUSION

We identified 8 core genes that revealed a significant correlation with the tumor grade as well as the recurrence of BC. Finally, we proved the value of a novel prognostic nomogram for predicting the relapse-free survival of BC patients after surgery, which could guide their treatment and follow-up.

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.

A prognostic model composed of four long noncoding RNAs predicts the overall survival of Asian patients with hepatocellular carcinoma

Based on accumulating evidence, long noncoding RNAs (lncRNAs) are potential biomarkers and therapeutic targets for many diseases, including tumors. In this study, we consulted The Cancer Genome Atlas (TCGA) database to explore the functions and modulatory mechanisms of lncRNAs as competing endogenous RNAs (ceRNAs) in hepatocellular carcinoma (HCC) in Asian patients and constructed a risk scoring system composed of four lncRNAs (SNHG1, STEAP3-AS1, RUSC1-AS1, and SNHG3) to predict the outcomes of Asian patients with HCC. The prognostic value of this risk model was validated in the internal validation cohort (n = 157). The stratified survival analysis revealed good performance for the risk model in stratifying clinical features. According to the Cox proportional hazard regression analysis, the four-lncRNA risk model is an independent prognostic model for Asian patients with HCC. Finally, we developed a nomogram that integrates prognostic signals and other clinical information to predict 1-, 3-, and 5-year overall survival rates. In conclusion, the prognostic lncRNAs identified in our study exerted potential biological effects on the development of HCC. The risk scoring model based on four lncRNAs may be an effective classification tool for assessing the prognosis of Asian patients with HCC.

A novel strategy for the diagnosis, prognosis, treatment, and chemoresistance of hepatocellular carcinoma: DNA methylation

The cancer mortality rate of hepatocellular carcinoma (HCC) is the second highest in the world and the therapeutic options are limited. The incidence of this deadly cancer is rising at an alarming rate because of the high degree of resistance to chemo- and radiotherapy, lack of proper, and adequate vaccination to hepatitis B, and lack of consciousness and knowledge about the disease itself and the lifestyle of the people. DNA methylation and DNA methylation-induced epigenetic alterations, due to their potential reversibility, open the access to develop novel biomarkers and therapeutics for HCC. The contribution to these epigenetic changes in HCC development still has not been thoroughly summarized. Thus, it is necessary to better understand the new molecular targets of HCC epigenetics in HCC diagnosis, prevention, and treatment. This review elaborates on recent key findings regarding molecular biomarkers for HCC early diagnosis, prognosis, and treatment. Currently emerging epigenetic drugs for the treatment of HCC are summarized. In addition, combining epigenetic drugs with nonepigenetic drugs for HCC treatment is also mentioned. The molecular mechanisms of DNA methylation-mediated HCC resistance are reviewed, providing some insights into the difficulty of treating liver cancer and anticancer drug development.

LINC01980 facilitates esophageal squamous cell carcinoma progression via regulation of miR-190a-5p/MYO5A pathway

Understanding the role of Long non-coding RNAs (lncRNAs) in tumorigenesis in diverse human malignancies would helpful for targeted therapies, containing esophageal squamous cell carcinoma (ESCC). However, the specific role and molecular mechanisms of LINC01980 in ESCC remain unclarified. In this study, we investigated the expression level, function role, and molecular mechanisms of LINC01980 in esophageal cancer cells and ESCC tissues. The high expression of LINC01980 was detected in ESCC tissues and cells, and predicted poor prognosis. LINC01980 promoted the cell proliferation, migration, invasion ability and epithelial-mesenchymal transition (EMT) progress in ESCC cells. In addition, a negative correlation between LINC01980 and miR-190a-5p or miR-190a-5p and MYO5A was observed in ESCC. We found that miR-190a-5p could directly bind with the mRNA of LINC01980 and MYO5A, and it was detected low expression in ESCC. We further demonstrated that the downregulation of MYO5A caused by overexpressing miR-190a-5p was released via upregulation of LINC01980. Functionally, LINC01980 acted as a competitively endogenous RNA (ceRNA) to impact the expression of MYO5A by sponging miR-190a-5p in ESCC. Therefore, these findings suggest that LINC01980 may act as an oncogenic lncRNA in ESCC and LINC01980/miR-190a-5p/MYO5A pathway contributes to the development of ESCC.

SP1-mediated upregulation of lncRNA SNHG4 functions as a ceRNA for miR-377 to facilitate prostate cancer progression through regulation of ZIC5

BACKGROUND/AIMS

Long noncoding RNAs (lncRNAs) have been demonstrated to serve distinct roles in human tumorigenesis. Previous studies have found that lncRNA small nucleolar RNA host gene 4 (SNHG4) was dysregulated in several tumors. However, the expression, clinical significances, and action mechanisms of SNHG4 in prostate cancer (PCa) are still unclear.

METHODS

Quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to detect SNHG4 expression in tissue samples and PCa cells. Cell counting kit-8, 5-ethynyl-2'-deoxyuridine, clonogenic formation, wound-healing, and transwell invasion assays were, respectively, used to evaluate cell proliferation, colony formation ability, migration, and invasion. Flow cytometric analysis was applied to assess cell apoptosis. Chromatin immunoprecipitation assays were conducted to determine the binding between SP1 and SNHG4 promoter. Luciferase reporter assay, qRT-PCR, and western blot analysis were carried out to explore and confirm the interaction among SNHG4, miR-377, and ZIC5.

RESULTS

SNHG4 was highly expressed in PCa and its upregulation was induced by transcription factor SP1. The high levels of SNHG4 were distinctly associated with tumor stage, lymph node metastasis, and reduced overall survival of patients with PCa. SNHG4 knockdown inhibited the growth, migration, and invasion of PCa cells. In addition, miR-377 was a target of SNHG4 and ZIC5 was a target gene of miR-377 in PCa. SNHG4 promoted ZIC5-mediated growth and metastasis through modulating miR-377.

CONCLUSION

Our findings illuminate how SNHG4 formed a regulatory network to display a tumor-promotive effect in PCa and revealed that SNHG4 may be a novel therapeutic target and prognostic marker for patients with PCa.

Development and validation of a prognostic classifier based on HIF-1 signaling for hepatocellular carcinoma

HIF-1 (hypoxia-inducible factor 1) signaling played a vital role in HCC (hepatocellular carcinoma) prognosis. We aimed to establish an accurate risk scoring system for HCC prognosis prediction and treatment guidance. 424 samples from TCGA (The Cancer Genome Atlas) and 445 samples from GSE14520 dataset were included as the derivation and validation cohort, respectively. In the derivation cohort, prognostic relevant signatures were selected from sixteen HIF-1 related genes and LASSO regression was adopted for model construction. Tumor-infiltrating immune cells were calculated using CIBERSORT algorithm. HIF-1 signaling significantly increased in HCC samples compared with normal tissues. Scoring system based on SLC2A1, ENO1, LDHA and GAPDH exhibited a continuous predictive ability for OS (overall survival) in HCC patients. PCA and t-SNE analysis confirmed a reliable clustering ability of risk score in both cohorts. Patients were classified into high-risk and low-risk groups and the survival outcomes between the two groups showed significant differences. In the derivation cohort, Cox regression indicated the scoring system was an independent predictor for OS, which was validated in the validation cohort. Different infiltrating immune cells fraction and immune scores were also observed in different groups. Herein, a novel integrated scoring system was developed based on HIF-1 related genes, which would be conducive to the precise treatment of patients.

Small Nucleolar RNA Host Gene 1 (SNHG1) and Chromosome 2 Open Reading Frame 48 (C2orf48) as Potential Prognostic Signatures for Liver Cancer by Constructing Regulatory Networks

Background

Liver cancer is a common malignant tumor with poor prognosis. The present study sought to identify potential signatures that can predict the prognosis of patients with liver cancer.

Material/Methods

The RNA sequencing (RNA-seq) and clinical information of liver cancer patients were obtained from the Cancer Genome Atlas (TCGA) database. Differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) were identified between liver cancer and adjacent normal tissues. After predicting lncRNA–miRNA and miRNA–mRNA pairs using online databases, the competing endogenous RNA (ceRNA) networks were constructed. Furthermore, the prognostic value of these differentially expressed genes was evaluated using univariate and multivariate Cox regression analyses.

Results

After constructing the ceRNA network, 2 lncRNAs small nucleolar RNA host gene 1 (SNHG1) and chromosome 2 open reading frame 48 (C2orf48) with the most nodes were identified. Correlation analysis revealed that SNHG1 was correlated with miR-195 and C2orf48 was correlated with miR-195 and miR-93. High expression of SNHG1, C2orf48, and miR-93 can contribute to poorer clinical outcomes compared to low expression. Furthermore, low miR-195 expression was correlated with shorter survival time than was high expression. SNHG1 and C2orf48 were closely associated with histology grade. Univariate and multivariate Cox regression analyses confirmed that SNHG1 and C2orf48 are risk factors for liver cancer.

Conclusions

Our findings revealed that SNHG1 and C2orf48 possess potential prognostic value and should be considered as possible biomarkers for predicting clinical outcomes for patients with liver cancer.

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

BACKGROUND AND OBJECT

Emerging evidence shows that non-coding RNA functions as new gene regulators and prognostic markers in several cancers, including liver cancer. Here, we focused on the small nucleolar RNA host gene 4 (SNHG4) in liver cancer prognosis based on The Cancer Genome Atlas (TCGA) data.

METHODS

The expression data and clinical information were downloaded from TCGA. Chi-square tests evaluated the correlation between SNHG4 expression and clinical parameters. Differences in survival between high and low expression groups (optic cutoff value determined by ROC) from Cox regression analysis were compared, and P-value was calculated by a log-rank test. Kaplan-Meier curves were compared with the log-rank test. GSEA and ceRNA network were conducted to explore the potential mechanism.

RESULTS

Data mining of lncRNA expression data for 371 patients with primary tumor revealed overexpression of SNHG4 in liver cancer. High SNHG4 expression was correlated with histological type (P = 0.01), histologic grade (P = 0.001), stage (P = 0.01), T classification (P = 0.004) and survival status (P = 0.013). Patients with high SNHG4 expression had poor overall survival and relapse-free survival compared with those with low SNHG4 expression. Multivariate analysis identified SNHG4 as an independent prognostic factor of poor survival in liver cancer. GSEA revealed related signaling pathway and ceRNA network explored the further mechanism.

CONCLUSION

High SNHG4 expression is an independent predictor of poor prognosis in liver cancer.

Can small nucleolar RNA be a novel molecular target for hepatocellular carcinoma?

BACKGROUND

Globally, hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death. Recently, many studies have demonstrated that small nucleolar RNA (snoRNA) was closely related to HCC.

OBJECTIVE

To explore whether snoRNA can be used as a molecular target for HCC.

METHODS

The PubMed, Embase, and Cochrane databases were searched for the published literatures related to snoRNA and HCC until August 12, 2019. After identification, screening, and verification, this study finally included 26 studies correlating small nucleolar RNA host gene (SNHG) and HCC, and 8 studies correlating snoRNA and HCC. Based on the collation of the relevant literature, the correlation network diagram between snoRNAs and HCC was constructed.

RESULTS

The SNHGs, such as SNHG1, SNHG6, SNHG16, and SNHG20 can play varied roles in HCC through different regulatory mechanisms. These SNHGs can promote and inhibit tumorigenesis. SNORD76 can promote the proliferation of tumor tissues and cells in vitro through different pathways. SnoU2_19 and SNORD76 can function through the same pathway. SNHG3, SNHG20, SNHG6, SNORD76, and snoRA47 can modulate epithelial-mesenchymal transition (EMT) to regulate the development of HCC cell or tissue. SNHG16, SNORD76, and SnoU2_19 can regulate the development of HCC through Wnt/β-catenin signaling pathway.

CONCLUSION

snoRNA can regulate the occurrence of HCC by modulating multiple molecular signaling pathways. Hence, snoRNA can be a potential molecular target for HCC.

Upregulation of long noncoding RNA SNHG1 indicates a poor prognosis in patients with gastric cancer

It is indicated that the dysregulation of long noncoding RNAs (lncRNAs) is implicated in cancer progression. However, the clinical significance of lncRNA small nucleolar RNA host gene 1 (SNHG1) in gastric cancer remains elusive. The expression levels of SNHGs and the association of SNHG1/10/11 with the clinical characteristics in patients with gastric cancer were analyzed by The Cancer Genome Atlas RNA-seq data. A Cox proportional hazard regression model was used to evaluate the association of SNHG1/10/11 expression with the clinical outcomes in patients with gastric cancer. It was demonstrated that SNHG1/10/11 expression levels were dramatically elevated in gastric cancer tissue samples as compared with the adjacent normal tissues. Increased expression of SNHG1 had no correlation with the clinicopathological parameters, but acted as an independent prognostic factor of poor survival (hazard ration (HR) = 0.590, 95% confidence interval (CI) = 0.399–0.872, P = 0.008) and tumor recurrence (HR = 2.457, 95% CI = 1.442–4.186, P = 0.001) in patients with gastric cancer. In addition, knockdown of SNHG1 in vitro inhibited the proliferation and invasion of gastric cancer cells. Our findings showed that the upregulation of lncRNA SNHG1 indicated a poor prognosis in patients with gastric cancer and might offer a promising therapeutic target for gastric cancer.

LncRNA SNHG4 promotes the proliferation, migration, invasiveness, and epithelial–mesenchymal transition of lung cancer cells by regulating miR-98-5p

Long noncoding RNA small nucleolar RNA host gene 4 (SNHG4) is usually up-regulated in cancer and regulates the malignant behavior of cancer cells. However, its role in lung cancer remains elusive. In this study, we silenced the expression of SNHG4 in NCI-H1437 and SK-MES-1, two representative non-small-cell lung cancer cell lines, by transfecting them with siRNA (small interfering RNA) that specifically targets SNHG4. We observed significantly inhibited cell proliferation in vitro and reduced tumor growth in vivo after SNHG4 silencing. SNHG4 knockdown also led to cell cycle arrest at the G1 phase, accompanied with down-regulation of cyclin-dependent kinases CDK4 and CDK6. The migration and invasiveness of these two cell lines were remarkably inhibited after SNHG4 silencing. Moreover, our study revealed that the epithelial–mesenchymal transition (EMT) of lung cancer cells was suppressed by SNHG4 silencing, as evidenced by up-regulated E-cadherin and down-regulated SALL4, Twist, and vimentin. In addition, we found that SNHG4 silencing induced up-regulation of miR-98-5p. MiR-98-5p inhibition abrogated the effect of SNHG4 silencing on proliferation and invasion of lung cancer cells. In conclusion, our findings demonstrate that SNHG4 is required by lung cancer cells to maintain malignant phenotype. SNHG4 probably exerts its pro-survival and pro-metastatic effects by sponging anti-tumor miR-98-5p.

Low expression of long noncoding RNA CTC-297N7.9 predicts poor prognosis in patients with hepatocellular carcinoma

BACKGROUND

Long noncoding RNAs (lncRNAs) are reported to play important roles in tumorigenesis of various malignant tumors. However, the clinical significance of aberrant lncRNA expression in hepatocellular carcinoma (HCC) is still elusive.

METHODS

Firstly, a differentially expressed lncRNA CTC-297N7.9 in HCC was detected by analyzing the data from The Cancer Genome Atlas (TCGA). Secondly, the expression level of CTC-297N7.9 was examined in four HCC cell lines and 60 pairs of HCC tissues by polymerase chain reaction (PCR) assay at our center. Thirdly, receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic value of CTC-297N7.9 for HCC. Correlation and survival analysis of HCC patients from the TCGA and our center were also carried out to assess the predictive value of CTC-297N7.9. Finally, survival prognostic models were established combining lncRNA expression and other clinical parameters.

RESULTS

The expression of CTC-297N7.9 was downregulated in HCC cell lines and HCC tissues. ROC curve revealed its significant diagnostic value in HCC. CTC-297N7.9 expression correlated with serum alpha-fetal protein (AFP), tumor stage, and tumor differentiation. Survival analysis indicated that overall survival (OS) and disease-free survival (DFS) are all positively associated with CTC-297N7.9 expression, especially in patients without viral hepatitis or cirrhosis. Cox regression analysis showed that CTC-297N7.9 expression level is an independent prognostic factor for both OS and DFS in HCC patients. Based on the model, CTC-297N7.9 was observed to be negatively correlated to risk score, indicating its role as a protective factor for HCC.

CONCLUSION

Our study demonstrated that the low expression of CTC-297N7.9 is associated with poor prognosis in HCC patients, suggesting its possible role as a potential prognostic marker for HCC.

The characteristics of lung cancer in Xuanwei County: A review of differentially expressed genes and noncoding RNAs on cell proliferation and migration

The occurrence of lung cancers is the highest in Xuanwei County, Yunnan province, China, especially among nonsmoking women. Domestic combustion of smoky coal induces serious indoor air pollution and is considered to be the main cause of human lung cancers. The occurrence of lung cancer in Xuanwei County has unique characteristics, such as the high morbidity in nonsmoking women or people with no family history. In the present review, we summarize advances in identification of differentially expressed genes, regulatory lncRNAs and miRNAs in cell proliferation and migration of lung cancers in Xuanwei County. Moreover, several regulatory differentially expressed genes (DEGs) or noncoding RNAs have diagnostic and prognostic significance for lung cancers in Xuanwei County and have the potential to serve as biomarkers.