Comprehensive analysis of differentially expressed profiles of lncRNAs, mRNAs, and miRNAs in laryngeal squamous cell carcinoma in order to construct a ceRNA network and identify potential biomarkers

Bioinformatics analysis proposes a possible role for long noncoding RNA MIR17HG in retinoblastoma

BACKGROUND

Retinoblastoma (RB) is the most common prevalent intraocular malignancy among infants and children, particularly in underdeveloped countries. With advancements in genomics and transcriptomics, noncoding RNAs have been increasingly utilized to investigate the molecular pathology of diverse diseases.

AIMS

This study aims to establish the competing endogenous RNAs network associated with RB, analyse the function of mRNAs and lncRNAs, and finds the relevant regulatory network.

METHODS AND RESULTS

This study establishes a network of competing endogenous RNAs by Spearman correlation analysis and prediction based on RB patients and healthy children. Enrichment analyzes based on Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes are conducted to analyze the potential biological functions of lncRNA and mRNA networks. Weighted gene co-expression network analysis (WGCNA) is employed to identify gene cluster modules exhibiting the strongest correlation with RB. The results indicate a significant correlation between the lncRNA MIR17HG (R = .73, p = .02) and the RB phenotype. ceRNA networks reveal downstream miRNAs (hsa-mir-425-5p and hsa-mir455-5p) and mRNAs (MDM2, IPO11, and ITGA1) associated with MIR17Hg. As an inhibitor of the p53 signaling pathway, MDM2 can suppress the development of RB.

CONCLUSION

In conclusion, lncRNAs play a role in RB, and the MIR17HG/hsa-mir-425-5p/MDM2 pathway may contribute to RB development by inhibiting the p53 signaling pathway.

Accurate prognostic prediction for patients with clear cell renal cell carcinoma using a ferroptosis-related long non-coding RNA risk model

INTRODUCTION

Ferroptosis is a recently discovered type of programmed cell death that plays a crucial role in tumor occurrence and progression. However, no prognostic model has been established yet for clear cell renal cell carcinoma (ccRCC) using ferroptosis-related long non-coding RNAs (lncRNAs).

METHODS

In the present study, lncRNA expression profiles, sex, age, TMN stage, and other clinical data of ccRCC samples were extracted from The Cancer Genome Atlas database. In addition, ferroptosis-related lncRNAs were identified using co-expression analysis, and the risk model was established using Cox regression and least absolute shrinkage and selection operator regression analyses. Log-rank test and Kaplan-Meier analysis were performed to evaluate the predictive accuracy of the risk model for the overall survival (OS) of patients with ccRCC. Moreover, the functional enrichment of ferroptosis-related lncRNAs was performed and visualized using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes.

RESULTS

Eight prognostic ferroptosis-related lncRNAs were identified, such as LINC01615, AC026401.3, LINC00944, AL590094.1, DLGAP1-AS2, AC016773.1, AC147651.1, and AP000439.2, making up the ferroptosis-related lncRNA risk model. The risk model effectively divided patients with ccRCC into high- and low-risk groups, and their survival time was calculated. The high-risk group showed significantly shorter OS compared to the low-risk group. The nomogram to predict the survival rate of the patients revealed that the risk score was the most critical factor affecting OS in patients with ccRCC. The ferroptosis-related lncRNA risk model was an independent predictor of prognostic risk assessment in patients with ccRCC.

CONCLUSION

The ferroptosis-related lncRNAs risk model and genomic clinicopathological nomogram have the potential to accurately predict the prognosis of patients with ccRCC and could serve as potential therapeutic targets in the future.

miRNAs as potential game-changers in head and neck cancer: Future clinical and medicinal uses

Head and neck cancers (HNCs) are a group of heterogeneous tumors formed most frequently from epithelial cells of the larynx, lips, oropharynx, nasopharynx, and mouth. Numerous epigenetic components, including miRNAs, have been demonstrated to have an impact on HNCs characteristics like progression, angiogenesis, initiation, and resistance to therapeutic interventions. The miRNAs may control the production of numerous genes linked to HNCs pathogenesis. The roles that miRNAs play in angiogenesis, invasion, metastasis, cell cycle, proliferation, and apoptosis are responsible for this impact. The miRNAs also have an impact on crucial HNCs-related mechanistic networks like the WNT/β-catenin signaling, PTEN/Akt/mTOR pathway, TGFβ, and KRAS mutations. miRNAs may affect how the HNCs respond to treatments like radiation and chemotherapy in addition to pathophysiology. This review aims to demonstrate the relationship between miRNAs and HNCs with a particular emphasis on how miRNAs impact HNCs signaling networks.

Screening and analysis of differentially expressed circRNAs and miRNAs in chronic diabetic extremity wounds

Increasing studies have shown that circular RNAs (circRNAs) and microRNAs (miRNAs) are related to the development of endocrine and metabolic diseases. However, there are few reports on the expression of circRNAs and miRNAs and their related co-expression and the expression of competitive endogenous RNA (ceRNA) in diabetic chronic refractory wounds. In this study, we compared the differential expression of circRNAs and miRNAs in diabetes chronic refractory wounds and normal skin tissues by high-throughput gene sequencing, and screened the differentially expressed circRNAs and miRNAs. Five abnormally expressed circRNAs and seven abnormally expressed miRNAs were detected by reverse transcription quantitative polymerase chain reaction PCR (RT-qPCR)to verify the results of RNA sequencing. We applied gene ontology (GO) to enrich and analyze dysregulated genes and elucidated their main functions via the Kyoto encyclopedia of genes and genomes analysis (KEGG). We constructed coding noncoding gene co-expression networks and ceRNA networks based on significantly abnormally expressed genes. According to the results of coding noncoding gene co-expression network analysis, hsa_circRNA_104175, hsa_circRNA_ 001588, hsa_circRNA_104330, hsa_circRNA_ 100141, hsa_circRNA_103107, and hsa_ circRNA_102044 may be involved in the regulation of the chronic intractable wound healing process in diabetes mellitus. This is particularly true in the regulation of vascular smooth muscle contraction-related pathways and the actin cytoskeleton, which affect the healing of chronic intractable wounds in diabetes. MiR-223-5p, miR-514a-3p, miR-205-5p, and miR-203-3p, which each have a targeting relationship with the above circRNAs, regulate the metabolism of nitrogen compounds in wound tissue by regulating NOD-like receptor signaling pathways, signaling pathways regulating the pluripotency of stem cells, microRNAs in cancer, and ECM-receptor interaction. This study showed circRNAs, miRNAs, and their network are associated with the development of chronic intractable wounds in diabetes, and our research identified the goals for new molecular biomarkers and gene therapy.

The analysis of tumor-infiltrating immune cell and ceRNA networks in laryngeal squamous cell carcinoma

BACKGROUND

Laryngeal squamous cell carcinoma (LSCC) is one of the most common forms of head and neck cancers. However, few studies have focused on the correlation between competing endogenous RNA (ceRNAs) and immune cells in LSCC.

METHODS

RNAseq expression of LSCC and adjacent tissues were downloaded from The Cancer Genome Atlas to establish a ceRNA network. The key gene in ceRNA was screened by the cox regression analysis to establish a prognostic risk assessment model. The CIBERSORT algorithm was then used to screen important tumor-infiltrating cells related to LSCC. Finally, co-expression analysis was applied to explore the relationship between key genes in the ceRNA network and tumor-infiltrating cells. The external datasets were used to validate critical biomarkers.

RESULTS

We constructed a prognostic risk assessment model of key genes in the ceRNA network. As it turned out, Kaplan-Meier survival analysis showed significant differences in overall survival rates between high-risk and low-risk groups (P < .001). The survival rate of the high-risk group was drastically lower than that of the low-risk group, and the AUC of 1 year, 3 years, and 5 years were all above 0.7. In addition, some immune infiltrating cells were also found to be related to LSCC. In the co-expression analysis, there is a negative correlation between plasma cells and TUBB3 (r = -0.33, P = .0013). External dataset validation also supports this result.

CONCLUSION

In this study, we found that some key genes (SLC35C1, CLDN23, HOXB7, STC2, TMEM158, TNFRSF4, TUBB3) and immune cells (plasma cells) may correspond to the prognosis of LSCC.

Stanniocalcin 2 (STC2): a universal tumour biomarker and a potential therapeutical target

Stanniocalcin 2 (STC2) is a glycoprotein which is expressed in a broad spectrum of tumour cells and tumour tissues derived from human breast, colorectum, stomach, esophagus, prostate, kidney, liver, bone, ovary, lung and so forth. The expression of STC2 is regulated at both transcriptional and post-transcriptional levels; particularly, STC2 is significantly stimulated under various stress conditions like ER stress, hypoxia and nutrient deprivation. Biologically, STC2 facilitates cells dealing with stress conditions and prevents apoptosis. Importantly, STC2 also promotes the development of acquired resistance to chemo- and radio- therapies. In addition, multiple groups have reported that STC2 overexpression promotes cell proliferation, migration and immune response. Therefore, the overexpression of STC2 is positively correlated with tumour growth, invasion, metastasis and patients' prognosis, highlighting its potential as a biomarker and a therapeutic target. This review focuses on discussing the regulation, biological functions and clinical importance of STC2 in human cancers. Future perspectives in this field will also be discussed.

Identifying prognostic lncRNAs based on a ceRNA regulatory network in laryngeal squamous cell carcinoma

Purpose

Growing evidence demonstrates that long non-coding RNAs (lncRNAs) play a crucial role as competing endogenous RNAs (ceRNAs) in tumor occurrence. The lncRNAs’ functions and clinical significance in laryngeal squamous cell carcinoma (LSCC) remain unclear. The study aims to reveal the lncRNA-associated ceRNA regulatory network of LSCC and clarify its clinical relevance.

Methods

Here, we obtained LSCC transcriptome data from The Cancer Genome Atlas (TCGA) database and identified the differential expression profile of lncRNAs, miRNAs, and mRNAs by the EdgeR R package. The function enrichment analysis of mRNAs was performed using clusterProfiler R package and GSEA3.0. Then, we constructed a ceRNA network and prognosis model based on lncRNAs through bioinformatic methods. Moreover, we explored the functions of prognosis-related lncRNA in LSCC by CCK-8 and transwell assay.

Results

1961 lncRNAs, 69 miRNAs, and 2224 mRNAs were identified as differentially expressed genes in LSCC tissues. According to the transcriptome differential expression profile, a ceRNA network containing 61 lncRNAs, 21 miRNAs, and 77 mRNAs was established. Then, four lncRNAs (AC011933.2, FAM30A, LINC02086, LINC02575) were identified from the ceRNA network to build a prognosis model for LSCC patients. And we found that LINC02086 and LINC02575 promoted the proliferation, migration, and invasion of LSCC cells while AC011933.2 and FAM30A inhibited these biological functions in vitro. Furthermore, we validated that LINc02086/miR-770-5p/SLC26A2 axis promoted migration in LSCC.

Conclusion

Four lncRNAs of the ceRNA network were abnormally expressed and related to patient prognosis in LSCC. They played a significant role in the progress of LSCC via affecting the proliferation and metastasis of tumor cells.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08422-2.

miRNA biomarkers for predicting overall survival outcomes for head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a malignant tumor of the upper aerodigestive tract. The loss and gain of miRNA function promote cancer development through various mechanisms. RNA sequencing (RNA-seq) and miRNAs sequencing data from the Cancer Genome Atlas (TCGA) was used to show the dysfunctional miRNAs microenvironment and to provide useful biomarkers for miRNAs therapy. Seven miRNAs were found to be independent prognostic factors of HNSCC patients in the training cohort. A total of 60 target genes for these miRNAs were predicted. Nine target genes (CDCA4, CXCL14, FLNC, KLF7, NBEAL2, P4HA1, PFKM, PFN2 and SEPPINE1) were correlated with patient's overall survival (OS) outcomes. We identified novel miRNAs markers for the prognosis of head and neck squamous cell carcinoma.

Long non-coding RNA DSCAM-AS1 contributes to the tumorigenesis of cervical cancer by targeting miR-877-5p/ATXN7L3 axis

Cervical cancer (CC) is ranked as the fourth most common cancer that occurs in women universally, which normally causes pain in the lower belly. Plenty of studies have stated that the expression of long non-coding RNAs (lncRNAs) is linked to the cellular development of many kinds of cancers. DSCAM-AS1 has been reported to act as an oncogene in other cancer types and the aim of our study was to uncover the function and regulatory mechanism of DSCAM-AS1 in CC. In this research, our findings presented that DSCAM-AS1 expression was up-regulated in CC cells. DSCAM-AS1 led to the development of CC by enhancing cell proliferation, migration and invasion ability. DSCAM-AS1 was verified to combine with miR-877-5p and down-regulate the expression of miR-877-5p. Results also showed that ATXN7L3 was a downstream target gene of miR-877-5p and it was unfavorably modulated by miR-877-5p. Enhanced expression of ATXN7L3 counterbalanced the DSCAM-AS1 knockdown effect on the progression of CC. This was the first time to analyze the underlying regulatory mechanism of the oncogenic DSCAM-AS1. Our findings clarified that DSCAM-AS1 played as an oncogenic lncRNA by targeting miR-877-5p/ATXN7L3 axis to promote CC progression, which may provide insights into the prevention of CC.

Long Non-Coding RNA TRPM2-AS Promotes Cell Migration and Invasion by Serving as a ceRNA of miR-138 and Inducing SOX4-Mediated EMT in Laryngeal Squamous Cell Carcinoma

Background

Laryngeal squamous cell carcinoma (LSCC) is a common type of malignant tumors of larynx, and in this study, we aimed to evaluate the functional role of long non-coding RNA TRPM2-AS in LSCC.

Methods

The expression levels of TRPM2-AS in LSCC tissues and cell lines were detected by RT-qPCR analysis. In vitro functional assays, including MTT assay and transwell assay, were performed to explore the biological effects of TRPM2-AS on LSCC cells. The expression levels of EMT-relevant proteins were detected by Western blot analysis. The interaction between TRPM2-AS and miR-138 in LSCC, predicted by bioinformatic method, was verified by dual-luciferase reporter assay.

Results

We observed that TRPM2-AS was highly expressed in human LSCC tissues and cell lines. LSCC patients with advanced clinical stage exhibited higher intratumoral TRPM2-AS expression. The results of functional assays demonstrated that TRPM2-AS knockdown remarkably inhibited the proliferation, migration and invasion of LSCC cells, whereas TRPM2-AS overexpression showed opposite effects. In mechanism, we further observed that TRPM2-AS directly bound to miR-138 and served as competing endogenous RNA (ceRNA), thereby increasing SOX4 expression and promoting EMT in LSCC. The oncogenic effects of TRPM2-AS in LSCC cells were partly diminished by miR-138 restoration.

Conclusion

In short, our findings provided first evidence that TRPM2-AS is highly expressed and exerts its oncogenic role in LSCC partly by miR-138/SOX4 axis.

Regulation of laryngeal squamous cell cancer progression by the lncRNA RP11-159K7.2/miR-206/DNMT3A axis

Long non‐coding RNAs (lncRNAs), which are longer than 200 nt, have been proved to play a role in promoting or inhibiting cancer progression. The following study investigated the role and underlying mechanisms of lncRNA RP11‐159K7.2 in laryngeal squamous cell carcinoma (LSCC) progression. Briefly, in situ hybridization (ISH) and real‐time quantitative PCR (RT‐qPCR) showed higher expression of RP11‐159K7.2 in LSCC tissues and cell lines. Patients with low expression level of RP11‐159K7.2 lived longer compared to those with high expression of RP11‐159K7.2 (χ² = 39.111, ***P < 0.001). Multivariate Cox regression analysis suggested that lncRNA RP11‐159K7.2 was an independent prognostic factor for LSCC patients (HR = 2.961, ***P < 0.001). Furthermore, to investigate the potential involvement of RP11‐159K7.2 in the development of LSCC, we knocked out the expression of endogenous RP11‐159K7.2 in TU‐212 cells and AMC‐HN‐8 cells via CRISPR/Cas9 double vector lentiviral system. RP11‐159K7.2 knockout decreased LSCC cell growth and invasion both in vitro and in vivo. Mechanically, we found that RP11‐159K7.2 could positively regulate the expression of DNMT3A by sponging miR‐206. In addition, a feedback loop was also discovered between DNMT3A and miR‐206. To sum up, these findings suggest that lncRNA RP11‐159K7.2 could be used as a potential biomarker for prognosis and treatment of LSCC.

LncRNA-Associated ceRNA Network Reveals Novel Potential Biomarkers of Laryngeal Squamous Cell Carcinoma

OBJECTIVE

This study aims to construct a systematic mRNA-miRNA-lncRNA network to identify novel lncRNAs and miRNAs biomarkers for laryngeal squamous cell carcinoma (LSCC).

METHODS

The mRNA, miRNA and lncRNA expression profiles of LSCC were obtained from Gene Expression Omnibus (GEO) database. The differentially expressed mRNAs, miRNAs and lncRNAs (DEmRNAs, DEmiRNAs and DElncRNAs) were screened between LSCC tissues and controls. Functional analysis of DEmRNAs, DEmRNAs targeted by DEmiRNAs and DEmRNAs targeted by DElncRNAs were respectively performed. The miRWalk, starbase and DIANA-LncBase were respectively used to predict DEmiRNAs-DEmRNAs, DElncRNAs-DEmRNAs and DElncRNAs-DEmiRNAs pairs. ceRNA network was built by DEmiRNAs-DEmRNAs and DElncRNAs-DEmiRNAs pairs. LncRNA subcellular localization was predicted using lncLocator. Using published The Cancer Genome Atlas (TCGA) and external datasets (GSE127165 and GSE133632), we also validated the expression of key DElncRNAs and DEmiRNAs in ceRNA network. The diagnostic and prognostic value of candidate genes was evaluated by ROC curve analysis and survival analysis, respectively.

RESULTS

There were 5 mRNA datasets, 3 miRNA datasets and 2 lncRNA datasets in this study. Totally, 2957 DEmRNAs, 61 DElncRNAs and 23 DEmiRNAs were identified. Functional analysis of DEmRNAs shows that they were significantly enriched in cancer-related pathways, such as DNA replication and extracellular matrix organization. There were 11 DEmiRNAs, 17 DElncRNAs and 967 DEmRNAs in the ceRNA network. Notably, up-regulated lncRNA DGCR5-down-regulated has-miR-338-3p/has-miR-139-5p pairs in this network were experimentally validated. Moreover, down-regulated AL121839.2, down-regulated LINC02147, up-regulated AC079328.2, up-regulated AC004943.2 and up-regulated HMGA2-AS1 were located in the cytoplasm. AL121839.2 and LINC02147 interacted with has-miR-1246. AC004943.2, AC079328.2 and HMGA2-AS1 targeted has-miR-3185, has-miR-3137 and has-miR-582-5p, respectively. Based on the TCGA and external datasets (GSE127165 and GSE133632), DGCR5 and AC004943.2 were significantly up-regulated while AL121839.2 and LINC02147, has-miR-338-3p, has-miR-139-5p and has-miR-582-5p were significantly down-regulated, which were consistent with our integration analysis. DGCR5, AL121839.2, LINC02147, AC004943.2, has-miR-338-3p, has-miR-139-5p and has-miR-582-5p could predict the occurrence of LSCC. Survival analysis suggested that only, AL121839.2 has potential prognostic value for LSCC.

CONCLUSION

This study provided novel insights into the ceRNA network and uncovered novel lncRNAs and miRNAs with diagnostic value in LSCC.

A prognostic long non-coding RNA-associated competing endogenous RNA network in head and neck squamous cell carcinoma

BACKGROUND

This study aimed to develop multi-RNA-based models using a competing endogenous RNA (ceRNA) regulatory network to provide survival risk prediction in head and neck squamous cell carcinoma (HNSCC).

METHODS

All long non-coding RNA (lncRNA), microRNA (miRNA), and mRNA expression data and clinicopathological features related to HNSCC were derived from The Cancer Genome Atlas. Differentially expressed RNAs were calculated using R. Prognostic factors were identified using univariate Cox regression analysis. Functional analysis was performed using GO, KEGG pathways, and PPI network. Based on the results, we derived a risk signature and compared high- and low-risk subgroups using LASSO regression analysis. Survival analysis and the relationship between risk signature and clinicopathological features were performed using log-rank tests and Cox regression analysis. A ceRNA regulatory network was constructed, and prognostic lncRNAs and miRNA expression levels were validated in vitro and in vivo.

RESULTS

A list of 207 lncRNAs, 18 miRNAs and 362 mRNAs related to overall survival was established. Five lncRNAs (HOTTIP, LINC00460, RMST, SFTA1P, and TM4SF19-AS1), one miRNA (hsa-miR-206), and one mRNA (STC2) were used to construct the ceRNA network. Three prognostic models contained 13 lncRNAs, eight miRNAs, and 17 mRNAs, which correlated with the patient status, disease-free survival (DFS), stage, grade, T stage, N stage, TP53 mutation status, angiolymphatic invasion, HPV status, and extracapsular spread. KEGG pathway analysis revealed significant enrichment of "Transcriptional misregulation in cancer" and "Neuroactive ligand-receptor interaction." In addition, HOTTIP, LINC00460, miR-206 and STC2 were validated in GTEx data, GEO microarrays and six HNSCC cell lines.

CONCLUSIONS

Our findings clarify the interaction of ceRNA regulatory networks and crucial clinicopathological features. These results show that prognostic biomarkers can be identified by constructing multi-RNA-based prognostic models, which can be used for survival risk prediction in patients with HNSCC.