Analysis of lncRNA-Mediated ceRNA Crosstalk and Identification of Prognostic Signature in Head and Neck Squamous Cell Carcinoma

Genetic associations between gene polymorphisms on 3p25 and oral squamous cell carcinoma

OBJECTIVES

To evaluate the association of SYN2, PPARG, RAF1, TIMP4, and IQSEC1 polymorphisms in 3p25 with oral squamous cell carcinoma (OSCC) in the Chinese Han population.

SUBJECTS AND METHODS

Genomic DNA was extracted from 494 subjects with or without OSCC. Basic information on the subjects, clinical data, and prognoses were collected. Fifteen candidate single nucleotide polymorphisms (SNPs) were selected and genotyped. The statistical analyses included descriptive statistics, logistic regression, survival, and functional annotation was performed.

RESULTS

IQSEC1-rs2686742 correlated with OSCC occurrence. In addition, RAF1-rs1051208, PPARG-rs10865710, PPARG-rs3856806, IQSEC1-rs2686742, PPARG-rs1175544, IQSEC1-rs9211, and IQSEC1-rs2600322 were significantly associated with the clinical characteristics of patients with OSCC. The log-rank test showed that IQSEC1-rs2600322 may play an important role in the survival of patients with OSCC. The Cox regression analysis suggested that PPARG-rs10865710, PPARG-rs7649970, IQSEC1-rs9211, IQSEC1-rs2600322, and IQSEC1-rs12487715 influenced survival outcomes. The functional annotation indicated that the transcript levels of IQSEC1 were upregulated in head and neck squamous cell carcinoma tissues, whereas PPARG gene transcription was downregulated.

CONCLUSIONS

IQSEC1-rs2686742 may be closely associated with OSCC onset. Multiple SNPs in IQSEC1 and PPARG genes correlated with the clinical characteristics of OSCC, among which PPARG-rs10865710, IQSEC1-rs9211, and IQSEC1-rs2600322 were associated with cancer prognosis.

DDIT4 promotes malignancy of head and neck squamous cell carcinoma

This study investigated the cancer-promoting effect of ferroptosis regulator DNA damage-inducible transcript 4 (DDIT4) and its relevant mechanisms. Vital ferroptosis-related genes were identified using bioinformatic methods on the basis of data collected from TCGA and seven other online databases. Cell Counting Kit-8 (CCK8), colony formation, wound-healing and transwell assays, and western blot analysis were conducted for verifying the biological role of DDIT4 in vitro. The immune score and tumor purity were calculated using R package "estimate." The relationship was identified between DDIT4 expression and immune cell infiltration using ssGSEA and CIBERSORT algorithms. R package "Seurat" was used to perform unsupervised clustering of the single cells, and "SingleR" was utilized for annotation. R package "STUtility" was employed to plot the spatial expression of DDIT4. For trajectory analysis, monocle was used to predict cell differentiation and demonstrate the expression of DDIT4 at each state. Here, DDIT4 overexpression was observed in Head and Neck Squamous Cell Carcinoma (HNSCC) cohort, and DDIT4 upregulation showed a positive correlation with larger tumor size, lymph node metastasis, more advanced TNM stage and higher tumor mutational burden (TMB). Moreover, DDIT4 knockdown could markedly inhibit the proliferation, colony formation, invasion and migration of HNSCC cells, as well as suppress the expression of HIF-1a, VEGF and vimentin. In comparison, DDIT4 overexpression showed a negative correlation with immune score and infiltrations of several immune cells. DDIT4 played crucial roles in the differentiation of CAFs and T cells. Collectively, this study demonstrates that DDIT4 contributes a critical role in HNSCC progression. The positive feedback regulation between DDIT4 and HIF-1a may be a potential target for HNSCC treatment.

Identification of circRNA-lncRNA-miRNA-mRNA competitive endogenous RNA networks as prognostic bio-markers in head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is one of the most prevalent neoplasms of malignancy. The pathogenesis of HNSCC is involved in the change of gene expression and the abnormal interaction between genes.

OBJECTIVE

The purpose of our research is to find genes that affect the survival time of patients and construct circRNA-lncRNA-miRNA-mRNA network. This paper aims to reveal the development mechanism of HNSCC and provide new ideas for clinical prognosis prediction.

METHODS

Transcriptome data were obtained from TCGA and GEO databases. A total of 556 samples were included. We screened the differentially expressed lncRNAs, circRNAs and mRNAs to predict interactions between lncRNA-miRNA, circRNA-miRNA and miRNA-mRNA. Then, we selected the hub mRNAs to predict the prognosis of patients.

RESULTS

We identified 8 hub prognostic mRNAs (FAM111A, IFIT2, CAV1, KLF9, OCIAD2, SLCO3A1, S100A16 and APOL3) by a series of bioinformatics analyses and established the prognostic ceRNA network of 8 mRNAs, 3 miRNAs, 2 circRNAs and 1 lncRNAs according to the targeting relationship by using databases.

CONCLUSION

We established the circRNA-lncRNA-miRNA-mRNA gene interaction network in HNSCC. We illuminated the molecular mechanism underlying the gene regulation associated with the pathogenesis of HNSCC and predicted the biomarkers related to prognosis.

LncRNA TM4SF19-AS1 exacerbates cell proliferation, migration, invasion, and EMT in head and neck squamous cell carcinoma via enhancing LAMC1 expression

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous and aggressive tumor with high mortality and unfavorable prognosis. Numerous long non-coding RNAs (lncRNAs) have been confirmed to exert pivotal parts in cancers. Nevertheless, the functions of most lncRNAs in HNSCC need deeper exploration. Our present research tried to clarify the biological role of TM4SF19 antisense RNA 1 (TM4SF19-AS1) and investigate its regulatory mechanism in HNSCC. RT-qPCR analysis was done to test TM4SF19-AS1 expression and identify the up-regulation of TM4SF19-AS1 in HNSCC cells. Loss-of-function assays were also involved, and the data implied that TM4SF19-AS1 knockdown hampered the proliferation, migration, invasion, along with epithelial-mesenchymal transition (EMT) of HNSCC cells. In vivo assays revealed TM4SF19-AS1 depletion restrained HNSCC tumor growth. Additionally, mechanism experiments were implemented to uncover the underlying regulatory mechanism of TM4SF19-AS1 in HNSCC cells. It turned out that TM4SF19-AS1 modulated laminin subunit gamma 1 (LAMC1) expression via sequestering microRNA-153-3p (miR-153-3p) and recruiting heterogeneous nuclear ribonucleoprotein C (HNRNPC) protein. Rescue assays confirmed that TM4SF19-AS1 contributed to HNSCC cell malignant behaviors via up-regulating LAMC1. To summarize, TM4SF19-AS1 played an oncogenic role in HNSCC cells, signifying TM4SF19-AS1 may have the potential to be used as a novel molecular target for HNSCC diagnosis.

Identification of a novel ceRNA network related to prognosis and immunity in HNSCC based on integrated bioinformatic investigation

Head and neck squamous cell carcinoma (HNSCC) is characterized by an immunosuppression environment and necessitates the development of new immunotherapy response predictors. The study aimed to build a prognosis-related competing endogenous RNA (ceRNA) network based on immune-related genes (IRGs) and analyze its immunological signatures. Differentially expressed IRGs were identified by bioinformatics analysis with Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and ImmPort databases. Finally, via upstream prognosis-related microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) prediction and co-expression analysis, we built an immune-related ceRNA network (LINC00052/hsa-miR-148a-3p/PLAU) related to HNSCC patient prognosis. CIBERSORT analysis demonstrated that there were substantial differences in 11 infiltrating immune cells in HNSCC, and PLAU was closely correlated with 10 type cells, including T cells CD8+ (R =  - 0.329), T cells follicular helper (R = - 0.342) and macrophage M0 (R = 0.278). Methylation and Tumor Immune Dysfunction and Exclusion (TIDE) analyses revealed that PLAU upregulation was most likely caused by hypomethylation and that high PLAU expression may be associated with tumor immune evasion in HNSCC, respectively.

Immune Infiltration-Related ceRNA Network Revealing Potential Biomarkers for Prognosis of Head and Neck Squamous Cell Carcinoma

Background

Head and neck squamous cell carcinoma (HNSCC) is a frequently lethal malignancy, and the mortality is considerably high. The tumor microenvironment (TME) has been identified as a critical participation in cancer development, treatment, and prognosis. However, competing endogenous RNA (ceRNA) networks grouping with immune/stromal scores of HNSCC patients need to be further illustrated. Therefore, our study aimed to provide clues for searching promising prognostic markers of TME in HNSCC.

Materials and Methods

ESTIMATE algorithm was used to calculate immune scores and stromal scores of the enrolled HNSCC patients. Differentially expressed genes (DEGs), lncRNAs (DELs), and miRNAs (DEMs) were identified by comparing the expression difference between high and low immune/stromal scores. Then, a ceRNA network and protein-protein interaction (PPI) network were constructed for selecting hub regulators. In addition, survival analysis was performed to access the association between immune scores, stromal scores, and differentially expressed RNAs in the ceRNA network and the overall survival (OS) of HNSCC patients. Then, the GSE65858 datasets from Gene Expression Omnibus (GEO) database was used for verification. At last, the difference between the clinical characteristics and immune cell infiltration in different expression groups of IL10RA, PRF1, and IL2RA was analyzed.

Results

Survival analysis showed a better OS in the high immune score group, and then we constructed a ceRNA network composed of 97 DEGs, 79 DELs and 22 DEMs. Within the ceRNA network, FOXP3, IL10RA, STAT5A, PRF1, IL2RA, miR-148a-3p, miR-3065-3p, and lncRNAs, including CXCR2P1, HNRNPA1P21, CTA-384D8.36, and IGHV1OR15-2, were closely correlated with the OS of HNSCC patients. Especially, using the data from GSE65858, we successfully verified that IL10RA, PRF1, and IL2RA were not only significantly upregulated in patients high immune scores, but also their high expressions were associated with longer survival time. In addition, stratified analysis showed that PRF1 and IL2RA might be involved in the mechanism of tumor progress.

Conclusion

In conclusion, we constructed a ceRNA network related to the TME of HNSCC, which provides candidates for therapeutic intervention and prognosis evaluation.

Evaluated expression of CELSR3 in oral squamous cell carcinoma is associated with perineural invasion and poor prognosis

OBJECTIVE

The objective of this study was to evaluate CELSR3 expression and explore its potential mechanism in oral squamous cell carcinoma.

STUDY DESIGN

CELSR3 mRNA expression was analyzed using The Cancer Genome Atlas (TCGA) database. CELSR3 protein expression in 135 surgical oral squamous cell carcinoma specimens was observed by immunohistochemical staining. Staining results were used to investigate the association between CELSR3 expression and clinicopathologic characteristics and prognosis. Bioinformatics analyses were used to explore the potential mechanism of CELSR3 in head and neck squamous cell carcinoma.

RESULTS

CELSR3 mRNA expression was upregulated in patients with head and neck squamous cell carcinoma in the TCGA head and neck squamous cell carcinoma data set. Increased CELSR3 protein expression was associated with perineural invasion and poor clinical outcomes in patients with oral squamous cell carcinoma. Bioinformatics analyses revealed that CELSR3 is involvement in axonogenesis, neuron migration, and cell-cell adhesion, all of which are involved in the process of perineural invasion.

CONCLUSION

CELSR3 may play a pro-oncogenic role in oral squamous cell carcinoma and can predict perineural invasion and poor survival. CELSR3 may be involved in oral squamous cell carcinoma progression by modulating perineural invasion.

The role of long non-coding RNAs in the pathogenesis of head and neck squamous cell carcinoma

Head and neck cancers are a heterogeneous collection of malignancies of the upper aerodigestive tract, salivary glands, and thyroid. However, the molecular mechanisms underlying the carcinogenesis of head and neck squamous cell carcinomas (HNSCCs) remain poorly understood. Over the past decades, overwhelming evidence has demonstrated the regulatory roles of long non-coding RNAs (lncRNAs) in tumorigenesis, including HNSCC. Notably, these lncRNAs have vital roles in gene regulation and affect various aspects of cellular homeostasis, including proliferation, survival, and metastasis. They exert regulating functions by interacting with nucleic acids or proteins and affecting cancer cell signaling. LncRNAs represent a burgeoning field of cancer research, and we are only beginning to understand the importance and complicity of lncRNAs in HNSCC. In this review, we summarize the deregulation and function of lncRNAs in human HNSCC. We also review the working mechanism of lncRNAs in HNSCC pathogenesis and discuss the potential application of lncRNAs as diagnostic/prognostic tools and therapeutic targets in human HNSCC.

Tracking the Molecular Fingerprint of Head and Neck Cancer for Recurrence Detection in Liquid Biopsies

The 5-year relative survival for patients with head and neck cancer, the seventh most common form of cancer worldwide, was reported as 67% in developed countries in the second decade of the new millennium. Although surgery, radiotherapy, chemotherapy, or combined treatment often elicits an initial satisfactory response, relapses are frequently observed within two years. Current surveillance methods, including clinical exams and imaging evaluations, have not unambiguously demonstrated a survival benefit, most probably due to a lack of sensitivity in detecting very early recurrence. Recently, liquid biopsy monitoring of the molecular fingerprint of head and neck squamous cell carcinoma has been proposed and investigated as a strategy for longitudinal patient care. These innovative methods offer rapid, safe, and highly informative genetic analysis that can identify small tumors not yet visible by advanced imaging techniques, thus potentially shortening the time to treatment and improving survival outcomes. In this review, we provide insights into the available evidence that the molecular tumor fingerprint can be used in the surveillance of head and neck squamous cell carcinoma. Challenges to overcome, prior to clinical implementation, are also discussed.

Salivary Metabolomics for Prognosis of Oral Squamous Cell Carcinoma

This study aimed to identify salivary metabolomic biomarkers for predicting the prognosis of oral squamous cell carcinoma (OSCC) based on comprehensive metabolomic analyses. Quantified metabolomics data of unstimulated saliva samples collected from patients with OSCC (n = 72) were randomly divided into the training (n = 35) and validation groups (n = 37). The training data were used to develop a Cox proportional hazards regression model for identifying significant metabolites as prognostic factors for overall survival (OS) and disease-free survival. Moreover, the validation group was used to develop another Cox proportional hazards regression model using the previously identified metabolites. There were no significant between-group differences in the participants’ characteristics, including age, sex, and the median follow-up periods (55 months [range: 3–100] vs. 43 months [range: 0–97]). The concentrations of 5-hydroxylysine (p = 0.009) and 3-methylhistidine (p = 0.012) were identified as significant prognostic factors for OS in the training group. Among them, the concentration of 3-methylhistidine was a significant prognostic factor for OS in the validation group (p = 0.048). Our findings revealed that salivary 3-methylhistidine is a prognostic factor for OS in patients with OSCC.

The association of long non-coding RNA in the prognosis of oral squamous cell carcinoma

BACKGROUND

Oral cancer is considered one of the most prevalent cancers in India. This is mainly because India suffers from high usage of tobacco, which is one of the main causative agents of oral cancer, and lacks proper health and sexual hygiene in rural areas.

DISCUSSION

Non-coding RNAs are reported to be involved in the various mechanism and causality of cancer. Numerous reports have identified viable prospects connecting non-coding RNA (ncRNA) with cancer. Specific ncRNAs like long non-coding RNA or lncRNAs are recently being prioritized as potential associations in the cause of cancer.

CONCLUSION

This review aims at presenting a concise perspective on the basics and the recent advancements of the lncRNA research pertaining specifically to oral cancer, its recurrence, and the future possibilities of knowledge it might possess.

Identification of Novel Biomarkers for Predicting Prognosis and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma Based on ceRNA Network and Immune Infiltration Analysis

Objectives

Patients with head and neck squamous cell carcinoma (HNSCC) have poor prognosis and show poor responses to immune checkpoint (IC) inhibitor (ICI) therapy. Competing endogenous RNA (ceRNA) networks, tumor-infiltrating immune cells (TIICs), and ICIs may influence tumor prognosis and response rates to ICI therapy. This study is aimed at identifying prognostic and IC-related biomarkers and key TIIC signatures to improve prognosis and ICI therapy response in HNSCC patients.

Methods and Results

Ninety-five long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and 1746 mRNAs were identified using three independent methods. We constructed a ceRNA network and estimated the proportions of 22 immune cell subtypes. Ten ceRNAs were related to prognosis according to Kaplan–Meier analysis. Two risk signatures based, respectively, on nine ceRNAs (ANLN, CFL2, ITGA5, KDELC1, KIF23, NFIA, PTX3, RELT, and TMC7) and three immune cell types (naïve B cells, neutrophils, and regulatory T cells) via univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression analyses could accurately and independently predict the prognosis of HNSCC patients. Key mRNAs in the ceRNA network were significantly correlated with naïve B cells and regulatory T cells and with stage, grade, and immune and molecular subtype. Eight IC genes exhibited higher expression in tumor tissues and were correlated with eight key mRNAs in the ceRNA network in HNSCC patients with different HPV statuses according to coexpression and TIMER 2.0 analyses. Most drugs were effective in association with expression of these key signatures (ANLN, CFL2, ITGA5, KIF23, NFIA, PTX3, RELT, and TMC7) based on GSCALite analysis. The prognostic value of key biomarkers and associations between key ceRNAs and IC genes were validated using online databases. Eight key ceRNAs were confirmed to predict response to ICI in other cancers based on TIDE analysis.

Conclusions

We constructed two risk signatures to accurately predict prognosis in HNSCC. Key IC-related signatures may be associated with response to ICI therapy. Combinations of ICIs with inhibitors of eight key mRNAs may improve survival outcomes of HNSCC patients.

A ceRNA-associated risk model predicts the poor prognosis for head and neck squamous cell carcinoma patients

Head and neck squamous cell carcinoma (HNSCC) is one of the most malignant cancers with poor prognosis worldwide. Emerging evidence indicates that competing endogenous RNAs (ceRNAs) are involved in various diseases, however, the regulatory mechanisms of ceRNAs underlying HNSCC remain unclear. In this study, we retrieved differentially expressed long non-coding RNAs (DElncRNAs), messenger RNAs (DEmRNAs) and microRANs (DEmiRNAs) from The Cancer Genome Atlas database and constructed a ceRNA-based risk model in HNSCC by integrated bioinformatics approaches. Functional enrichment analyses showed that DEmRNAs might be involved in extracellular matrix related biological processes, and protein–protein interaction network further selected out prognostic genes, including MYL1 and ACTN2. Importantly, co-expressed RNAs identified by weighted co-expression gene network analysis constructed the ceRNA networks. Moreover, AC114730.3, AC136375.3, LAT and RYR3 were highly correlated to overall survival of HNSCC by Kaplan–Meier method and univariate Cox regression analysis, which were subsequently implemented multivariate Cox regression analysis to build the risk model. Our study provides a deeper understanding of ceRNAs on the regulatory mechanisms, which will facilitate the expansion of the roles on the ceRNAs in the tumorigenesis, development and treatment of HNSCC.

Distinguishable Prognostic miRNA Signatures of Head and Neck Squamous Cell Cancer With or Without HPV Infection

Since their discovery in the 1990’s, microRNAs (miRNA) have opened up new vistas in the field of cancer biology and are found to have fundamental roles in tumorigenesis and progression. As head and neck squamous cell carcinoma (HNSCC) with positive human papillomavirus (HPV+) is significantly distinct from its HPV negative (HPV−) counterpart in terms of both molecular mechanisms and clinical prognosis, the current study aimed to separately develop miRNA signatures for HPV+ and HPV− HNSCC as well as to explore the potential functions. Both signatures were reliable for the prediction of prognosis in their respective groups. Then Enrichment analysis was performed to predict the potential biological functions of the signatures. Importantly, combining previous studies and our results, we speculated that HPV+ HNSCC patients with low signature score had better immunity against the tumors and enhanced the sensitivity of therapies leading to improved prognosis, while HPV− HNSCC patients with high signature score acquired resistance to therapeutic approaches as well as dysregulation of cell metabolism leading to poor prognosis. Hence, we believe that the identified signatures respectively for HPV+ and HPV− HNSCC, are of great significance in accessing patient outcomes as well as uncovering new biomarkers and therapeutic targets, which are worth further investigation through molecular biology experiments.

Multifaceted Roles of Long Non-coding RNAs in Head and Neck Cancer

The majority of RNA transcripts are non-coding RNA (ncRNA) transcripts with lengths exceeding 200 nucleotides that are not translated into protein. Unlike microRNAs (miRNAs), long ncRNAs (lncRNAs) are not confined to a single mechanism of action but have a large and diverse role in biological processes as they can function as transcription regulators, decoys, scaffolds, and enhancer RNAs. Currently, many lncRNA molecules are under investigation for their role in tumorigenesis, metastasis, and prognosis in different types of cancer. This review not only summarizes the characteristics and functions of lncRNAs but also discusses the therapeutic implications and applications of lncRNAs with roles associated with head and neck cancer. Our aim is to pinpoint the potential way to perturb specific lncRNAs for future therapeutic use.

Increased expression of CELSR3 indicates a poor prognostic factor for Prostate Cancer

Background: Cadherin EGF LAG Seven-Pass G-Type Receptor 3 (CELSR3) gene was reported to be overexpressed in various human cancers and involved in the regulation of neurite-dependent neurite outgrowth and may play a role in tumor formation. However, the clinical significance of CELSR3 in prostate cancer (PCa) has not been fully studied. Methods: The expression of CELSR3 was detected by crossover analysis of the public datasets and cell lines. MTT assay and migration assay were performed to evaluate the cells' physiological functioning. Co-expressed genes and enrichment analysis was performed to investigate the biological significance of CELSR3 in PCa. Quantitative real-time polymerase chain reaction was used to detect the expression levels of hub genes (CENPE, CENPA, CDC20, NUF2, ESPL1, PLK1) related to CELSR3. Results: We found a significant increase in CELSR3 expression in PCa patients and cell lines. Furthermore, immunohistochemical analysis showed that CELSR3 protein expression was significantly more highly expressed in the PCa tissues compared to the non-cancerous PCa tissues. CELSR3 downregulation significantly suppressed cell proliferation and migration potential. CELSR3-related hub genes (CENPE, CENPA, CDC20, NUF2, ESPL1, PLK1) were selected and the functions of these hub genes showed that the function of CELSR3 was closely related to the cell cycle-related signaling pathways. The upregulation of CELSR3 mRNA expression in the PCa tissues significantly correlated with the presence of high serum PSA levels, high pathological stage, high Gleason score, short overall survival time and short disease-free survival time. Conclusion: Our data suggest that CELSR3 may play an important role in the progression of PCa. More importantly, an increase in CELSR3 expression may be indicative of poor disease-free survival and poor prognosis in PCa patients.

LncRNA MIR194-2HG Promotes Cell Proliferation and Metastasis via Regulation of miR-1207-5p/TCF19/Wnt/β-Catenin Signaling in Liver Cancer

Purpose

LncRNAs play an important role in tumorigenesis and cancer progression in liver cancer. Although many lncRNAs have been reported, the role of MIR194-2HG and the underlying mechanism mediated by it are still largely unknown in HCC. This study aimed to investigate the biological role and mechanism of MIR194-2HG in liver cancer.

Materials and Methods

The expression of MIR194-2HG was determined in liver cancer tissues and cells by RT-qPCR. The overall survival rate of MIR194-2HG was analyzed by Kaplan–Meier survival analysis. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), colony formation, and Transwell assays were carried out to detect cell migration and invasion. Western blotting was used to quantify the levels of all proteins. The regulatory mechanism of the MIR194-2HG/miR-1207-5p/TCF19 axis in liver cancer was investigated by dual-luciferase activity reporter assay, Kaplan-Meier survival analysis, and Western blotting.

Results

MIR194-2HG was upregulated in liver cancer tissues and cell lines. Liver cancer patients with higher expression of MIR194-2HG revealed poor overall survival compared with those who had lower expression of MIR194-2HG. MIR194-2HG promoted the proliferation, migration, and invasion of HepG2 and Huh7 cells by acting as a ceRNA mechanism for the miR-1207-5p/TCF19 axis to activate the Wnt/β-catenin signaling pathway.

Conclusion

MIR194-2HG acts in an oncogenic role and activates the Wnt/β-catenin signaling pathway via a miR-1207-5p/TCF19 axis-mediated mechanism, which provides a novel avenue for diagnostic or therapeutic interventions in liver cancer.

Screening lncRNAs with diagnostic and prognostic value for human stomach adenocarcinoma based on machine learning and mRNA-lncRNA co-expression network analysis

BACKGROUND

Stomach adenocarcinoma (STAD), is one of the most lethal malignancies around the world. The aim of this study was to find the long noncoding RNAs (lncRNAs) acting as diagnostic and prognostic biomarker of STAD.

METHODS

Base on TCGA dataset, the differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified between STAD and normal tissue. The machine learning and survival analysis were performed to evaluate the potential diagnostic and prognostic value of lncRNAs for STAD. We also build the co-expression network and functional annotation. The expression of selected candidate mRNAs and lncRNAs were validated by Quantitative real-time polymerase chain reaction (qRT-PCR) and GSE27342 dataset. GSE27342 dataset were also to perform gene set enrichment analysis.

RESULTS

A total of 814 DEmRNAs and 106 DElncRNAs between STAD and normal tissue were obtained. FOXD2-AS1, LINC01235, and RP11-598F7.5 were defined as optimal diagnostic lncRNA biomarkers for STAD. The area under curve (AUC) of the decision tree model, random forests model, and support vector machine (SVM) model were 0.797, 0.981, and 0.983, and the specificity and sensitivity of the three model were 75.0% and 97.1%, 96.9% and 96%, and 96.9% and 97.1%, respectively. Among them, LINC01235 was not only an optimal diagnostic lncRNA biomarkers, but also related to survival time. The expression of three DEmRNAs (ESM1, WNT2, and COL10A1) and three optimal diagnostic lncRNAs biomarkers (FOXD2-AS1, RP11-598F7.5, and LINC01235) in qRT-PCR validation was were consistent with our integrated analysis. Except for FOXD2-AS1, ESM1, WNT2, COL10A1, and LINC01235 were upregulated in STAD, which was consistent with our integration results. Gene set enrichment analysis results indicated that DNA replication, Cell cycle, ECM-receptor interaction, and P53 signaling pathway were four significantly enriched pathways in STAD.

CONCLUSION

Our study identified three DElncRNAs as potential diagnostic biomarkers of STAD. Among them, LINC01235 also was a prognostic lncRNA biomarkers.

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.

Screening key lncRNAs with diagnostic and prognostic value for head and neck squamous cell carcinoma based on machine learning and mRNA-lncRNA co-expression network analysis

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is the seventh most common type of cancer around the world. The aim of this study was to seek the long non-coding RNAs (lncRNAs) acting as diagnostic and prognostic biomarker of HNSCC.

METHODS

Base on TCGA dataset, the differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified between HNSCC and normal tissue. The machine learning and survival analysis were performed to estimate the potential diagnostic and prognostic value of lncRNAs for HNSCC. We also build the co-expression network and functional annotation. The expression of selected candidate mRNAs and lncRNAs were validated by Quantitative real time polymerase chain reaction (qRT-PCR).

RESULTS

A total of 3363 DEmRNAs (1822 down-regulated and 1541 up-regulated mRNAs) and 32 DElncRNAs (13 down-regulated and 19 up-regulated lncRNAs) between HNSCC and normal tissue were obtained. A total of 13 lncRNAs (IL12A.AS1, RP11.159F24.6, RP11.863P13.3, LINC00941, FOXCUT, RNF144A.AS1, RP11.218E20.3, HCG22, HAGLROS, LINC01615, RP11.351J23.1, AC024592.9 and MIR9.3HG) were defined as optimal diagnostic lncRNAs biomarkers for HNSCC. The area under curve (AUC) of the support vector machine (SVM) model, decision tree model and random forests model and were 0.983, 0.842 and 0.983, and the specificity and sensitivity of the three model were 95.5% and 96.2%, 77.3% and 97.6% and 93.2% and 97.8%, respectively. Among them, AC024592.9, LINC00941, LINC01615 and MIR9-3HG was not only an optimal diagnostic lncRNAs biomarkers, but also related to survival time. The focal adhesion, ECM-receptor interaction, pathways in cancer and cytokine-cytokine receptor interaction were four significantly enriched pathways in DEmRNAs co-expressed with the identified optimal diagnostic lncRNAs. But for most of the selected DEmRNAs and DElncRNAs, the expression was consistent with our integrated analysis results, including LINC00941, LINC01615, FOXCUT, TGA6 and MMP13.

CONCLUSION

AC024592.9, LINC00941, LINC01615 and MIR9-3HG was not only an optimal diagnostic lncRNAs biomarkers, but also were a prognostic lncRNAs biomarkers.

CASC9 Facilitates Cell Proliferation in Bladder Cancer by Regulating CBX2 Expression

BACKGROUND

As the seventh most common urologic carcinoma worldwide, approximately 430,000 patients are diagnosed with bladder cancer (BC) every year. Increasing evidence indicates that long noncoding RNAs (lncRNAs) play crucial roles in the progression of BC.

OBJECTIVES

This study is aimed to explore the function and mechanism of CASC9 in BC.

METHODS

Bioinformatics analysis and experiments including RT-qPCR, luciferase reporter, Cell Counting Kit-8 assay, Western blot, RNA immunoprecipitation assay, and TUNEL staining were applied to explore the function and mechanism of CASC9 in BC tissues and cell lines.

RESULTS

Our study demonstrated that CASC9 was upregulated in BC tissues and cell lines. Moreover, we found that CASC9 knockdown notably decreased proliferation while increased apoptotic rate in BC cells. Mechanistically, bioinformatics prediction and following experiments indicated that CASC9 worked as a competing endogenous RNA (ceRNA) of CBX2 through sponging miR-497-5p. Meanwhile, we recognized that CASC9 and miR-497-5p negatively regulated each other in a mutual way. Furthermore, we found that miR-497-5p shared binding site with CBX2. In addition, miR-497-5p could negatively regulated CBX2, while CASC9 could positively regulated CBX2. Rescue assays reveled that CBX2 overexpression could reversed the reduction of cell proliferation or the enhancement of cell apoptosis induced by CASC9 suppression.

CONCLUSIONS

Our study manifests the first evidence that CASC9 serves as an oncogene in BC and accelerates cell proliferation by modulating miR-497-5p/CBX2 axis. The present study may provide a cogitable target for BC therapy.

A Key mRNA-miRNA-lncRNA Competing Endogenous RNA Triple Sub-network Linked to Diagnosis and Prognosis of Hepatocellular Carcinoma

Growing evidence has illustrated critical roles of competing endogenous RNA (ceRNA) regulatory network in human cancers including hepatocellular carcinoma. In this study, we aimed to find promising diagnostic and prognostic biomarkers for patients with hepatocellular carcinoma. Three novel unfavorable prognosis-associated genes (CELSR3, GPSM2, and CHEK1) was first identified. We also demonstrated that these genes were significantly upregulated in hepatocellular carcinoma cell lines and tissues. Next, 154 potential miRNAs of CELSR3, GPSM2, and CHEK1 were predicted. CHEK1-hsa-mir-195-5p/hsa-mir-497-5p and GPSM2-hsa-mir-122-5p axes were defined as two key pathways in carcinogenesis of hepatocellular carcinoma by combination of in silico analysis and experimental validation. Subsequently, lncRNAs binding to hsa-mir-195-5p, hsa-mir-497-5p, and hsa-mir-122-5p were predicted via starBase and miRNet databases. After performing expression analysis and survival analysis for these predicted lncRNAs, we showed that nine lncRNAs (SNHG1, SNHG12, LINC00511, HCG18, FGD5-AS1, CERS6-AS1, NUTM2A-AS1, SNHG16, and ASB16-AS1) were markedly increased in hepatocellular carcinoma and their upregulation indicated poor prognosis. Moreover, a similar mRNA-miRNA-lncRNA analysis for six “known” genes (CLEC3B, DNASE1L3, PTTG1, KIF2C, XPO5, and UBE2S) was performed. Subsequently, a comprehensive mRNA-miRNA-lncRNA triple ceRNA network linked to prognosis of patients with hepatocellular carcinoma was established. Moreover, all RNAs in this network exhibited significantly diagnostic values for patients with hepatocellular carcinoma. In summary, the current study constructed a mRNA-miRNA-lncRNA ceRNA network associated with diagnosis and prognosis of hepatocellular carcinoma.

The Emerging Role of Adhesion GPCRs in Cancer

Aberrant expression, function, and mutation of G protein-coupled receptors (GPCRs) and their signaling partners, G proteins, have been well documented in many forms of cancer. These cell surface receptors and their endogenous ligands are implicated in all aspects of cancer including proliferation, angiogenesis, invasion, and metastasis. Adhesion GPCRs (aGPCRs) form the second largest family of GPCRs, most of which are orphan receptors with unknown physiological functions. This is mainly due to our limited insight into their structure, natural ligands, signaling pathways, and tissue expression profiles. Nevertheless, recent studies show that aGPCRs play important roles in cell adhesion to the extracellular matrix and cell-cell communication, processes that are dysregulated in cancer. Emerging evidence suggests that aGPCRs are implicated in migration, proliferation, and survival of tumor cells. We here review the role of aGPCRs in the five most common types of cancer (lung, breast, colorectal, prostate, and gastric) and emphasize the importance of further translational studies in this field.

Identification and Validation of an Immune-Related RNA Signature to Predict Survival of Patients With Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous disease characterized by different molecular subgroups and clinical features. Therefore, it is important to uncover reliable molecular biomarkers for distinguishing different risk patient subgroup. Here, we conducted a multi-omics analysis to examine the joint predictive power of a multi-type RNA signature in the prognosis of HNSCC patients through integration analysis of mRNA, miRNA, and lncRNA expression profiles and clinical data in a large number of HNSCC patients. A multi-type RNA signature (15SigRS) was constructed which can classify patients into the high-risk group and low-risk group with the significantly different outcome [hazard ratio (HR) = 2.718, 95% confidence interval (CI), 2.258–3.272, p < 0.001] in the discovery data set, and subsequently validated in the Cancer Genome Atlas (TCGA) testing data set (HR = 1.299, 95% CI, 1.170–1.442, p < 0.001) and another independent GSE65858 data set (HR = 1.077, 95% CI, 1.016–1.143, p = 0.013). Further multivariate Cox regression analysis and stratification analysis demonstrated the independence of predictive performance of the 15SigRS relative to conventional clinicopathological factors. Furthermore, the 15SigRS has a prior performance in prognostic prediction than other single RNA type-based signatures. Functional analysis suggested that the 15SigRS are involved in immune- or metabolism-related KEGG pathways. In summary, our study demonstrated the potential application of mixed RNA types as molecular markers for predicting the outcome of cancer patients.

CELSR3 mRNA expression is increased in hepatocellular carcinoma and indicates poor prognosis

Objective

Hepatocellular carcinoma (HCC) is a disease that is associated with high mortality; currently, there is no curative and reliable treatment. Cadherin EGF LAG seven-pass G-type receptor 3 (CELSR3) is the key signaling molecule in the wingless and INT-1/planar cell polarity (WNT/PCP) pathway. This study aimed to elucidate the prognostic significance of CELSR3 in HCC patients.

Methods

The Cancer Genome Atlas (TCGA) database, the Cancer Cell Line Encyclopedia (CCLE) database and the Gene Expression Omnibus (GEO) database were used to analyze the expression of CELSR3 mRNA in HCC samples and cells. The relationship between CELSR3 mRNA and clinical features was assessed by the chi-square test. the diagnostic and predictive value of CELSR3 mRNA expression were analyzed using the receiver operating characteristic (ROC) curve. Kaplan–Meier curve and Cox regression analyses were performed to assess the prognostic value of CELSR3 mRNA in HCC patients. Finally, all three cohorts database was used for gene set enrichment analysis(GSEA) and the identification of CELSR3-related signal transduction pathways.

Results

The expression of CELSR3 mRNA was upregulated in HCC, and its expression was correlated with age (P = 0.025), tumor status (P = 0.022), clinical stage (P = 0.003), T classification (P = 0.010), vital status (P = 0.001), and relapse (P = 0.005). The ROC curve assessment indicated that CELSR3 mRNA expression has high diagnostic value in HCC and in the subgroup analysis of stage. In addition, the Kaplan-Meier curve and Cox analyses suggested that patients with high CELSR3 mRNA expression have a poor prognosis, indicating that CELSR3 mRNA is an independent prognostic factor for the overall survival of HCC patients. GSEA showed that GO somatic diversification of immune receptors, GO endonuclease activity, GO DNA repair complex and GO somatic cell DNA recombination, were differentially enriched in the meta-GEO cohort, the HCC cell line cohort and the TCGA cohort of the high CELSR3 mRNA expression phenotype.

Conclusion

Our results indicate that CELSR3 mRNA is involved in the progression of cancer and can be used as a biomarker for the prognosis of HCC patients.

Comprehensive Analysis of a Competing Endogenous RNA Network Identifies Seven-lncRNA Signature as a Prognostic Biomarker for Melanoma

Long non-coding RNAs (LncRNAs) can act as competing endogenous RNA (ceRNA) involving in tumor initiation and progression. Nevertheless, the prognostic roles of lncRNAs in lncRNA-related ceRNA network of melanoma remain elusive. In this study, RNA sequence profiles were downloaded from The Cancer Genome Atlas (TCGA) database, and there were 2020 differentially expressed messenger RNAs (DEmRNAs), 438 differentially expressed lncRNAs (DElncRNAs) and 65 differentially expressed microRNAs (DEmiRNAs) between primary and metastasis melanoma patients. A ceRNA regulatory network was constructed based on the DElncRNAs-DEmiRNAs and DEmiRNAs-DEmRNAs interactions, which contained 39 lncRNAs, 10 miRNAs, and 16 mRNAs. Furthermore, univariate and multivariate Cox regression analysis were carried out to establish a 7-lncRNA prognostic signature. Subsequently, the area under the curve (AUC) value of the receiver operating characteristic (ROC) curve and the Kaplan-Meier risk survival analysis revealed the significant performance of this signature. Finally, pathway enrichment analyses implied that lncRNA MIR205HG and MIAT were associated with multiple cancer-related pathways, especially epidermis development and immune response. The current study provides novel insights into the lncRNA-related ceRNA network and the potential of lncRNAs to be candidate prognostic biomarkers and therapeutic targets in melanoma.

Exploring the role of Mir204/211 in HNSCC by the combination of bioinformatic analysis of ceRNA and transcription factor regulation

OBJECTIVES

This study aimed to reveal the regulatory roles of microRNAs in head and neck squamous cell carcinoma (HNSCC) through comprehensive ceRNA, miRNA-transcription factor (TF)-hub gene network and survival analysis.

MATERIALS AND METHODS

Expression analysis was performed using the 'edgeR' package based on The Cancer Genome Atlas database. The ceRNA network was screened by intersecting prediction results from miRcode, miRTarBase, miRDB and TargetScan. GSE30784, GSE59102 and GSE107591 from the Gene Expression Omnibus repository were chosen for cross-validation. Hub genes were identified using a protein-protein interaction network constructed by Search Tool for the Retrieval of Interacting Genes. The Transcriptional Regulatory Relationships Unraveled by Sentence-based Text mining (TTRUST) was utilized to map the miRNA-TF-Hub gene network. Patient overall survival was analyzed using the 'survival' package in R. Structural and functional analysis of miR-204/211 was based on miRbase and RNAstructure.

RESULTS

A ceRNA network of 178 lncRNAs, 19 miRNAs and 55 mRNAs was generated, and a TF regulatory network with 11 miRNAs, 11 TFs and 18 hub genes was constructed from the 52 hub genes identified through the protein-protein interaction (PPI) network. Survival analysis demonstrated that the dysregulated expression of 11 lncRNAs and 14 mRNAs was highly related to overall survival. Furthermore, miR-204 and miR-211 were significantly involved in the network with identical mature structures, indicating them as key miRNAs in HNSCC.

CONCLUSION

This study reveals the comprehensive molecular regulatory networks centralized by miRNAs in HNSCC and uncovers the crucial role of miR-204 and miR-211, which may become potential diagnostic and therapeutic targets.