Genome-Wide Identification of a Novel Eight-lncRNA Signature to Improve Prognostic Prediction in Head and Neck Squamous Cell Carcinoma

Identification of a disulfidptosis-related lncRNA signature for the prognostic and immune landscape prediction in head and neck squamous cell carcinoma

PURPOSE

Disulfidptosis, a newly identified form of cell death, is triggered by disulfide stress. Herein, a unique signature was developed based on disulfidptosis-related lncRNAs (DRlncRNAs) for the prognostic and immune landscape prediction of head and neck squamous cell carcinoma (HNSCC).

METHODS

Transcriptome, somatic mutation, and clinical data were acquired at The Cancer Genome Atlas database. Individuals were partitioned into training and test cohorts at a 1:1 ratio to facilitate the development of a DRlncRNA signature using the least absolute shrinkage and selection operation method. Based on the median risk score, all HNSCC individuals were stratified into the high-risk group (HRG) and low-risk group (LRG). Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) analyses were used to estimate the prognostic value, and a nomogram was generated for survival prediction. To provide a more comprehensive assessment, the tumor microenvironment, functional enrichment, immune cell infiltration, and immunotherapeutic sensitivity were explored between LRG and HRG.

RESULTS

A DRlncRNA signature was established with 10 DRlncRNAs. The corresponding values of areas under the ROC curves for 1-, 3-, and 5-year overall survival were 0.710, 0.692, and 0.640. A more favorable prognosis was noted in the patients with lower risk, along with higher immune scores, increased immune-related functions, and immune cell infiltration, as well as improved response to the immunotherapeutic intervention in comparison with individuals at higher risk.

CONCLUSION

These findings demonstrate that the developed DRlncRNA signature holds promise as a reliable prognostic marker and predictor of immunotherapy response in HNSCC patients.

Cuproptosis-related risk score based on machine learning algorithm predicts prognosis and characterizes tumor microenvironment in head and neck squamous carcinomas

Cuproptosis is a recently discovered type of programmed cell death that shows significant potential in the diagnosis and treatment of cancer. It has important significance in the prognosis of HSNC. This study aims to construct a cuproptosis-related prognostic model and risk score through new data analysis methods such as machine learning algorithms for the prognosis analysis of HSNC. Protein-protein interaction network and machine learning methods were employed to identify hub genes that were used to construct a TreeGradientBoosting model for predicting overall survival. The relationship between the risk scores obtained from the model and features such as tumor microenvironment (TME) and tumor immunity was explored. The C-indexes of the TreeGradientBoosting model in the training and validation cohorts were 0.776 and 0.848, respectively. The nomogram based on risk scores and clinical features showed good performance, and distinguished the TME and immunity between high-risk and low-risk groups. The cuproptosis-associated risk score can be used to predict prognoses, TME, and tumor immunity of HNSC patients.

Identification of a novel MSI-related ceRNA network for predicting the prognosis and immunotherapy response of gastric cancer

BACKGROUND

Mounting evidence has underscored the pivotal role of the competitive endogenous RNA (ceRNA) regulatory networks among various cancers. However, the behavior characteristics and complexity of the ceRNA network in Gastric cancer (GC) remains unclear. In this study, we aimed to clarify a Microsatellite instability (MSI)-related ceRNA regulatory network and identify potential prognostic markers associated with GC.

METHODS AND RESULTS

We extracted transcriptome data of GC patients from The Cancer Genome Atlas (TCGA) and identified differentially expressed lncRNAs, miRNAs and mRNAs based on MSI status. A hub ceRNA network including 1 lncRNAs (MIR99AHG), 2 miRNAs and 26 mRNAs specific to MSI was established in GC. We further constructed a prognostic model with seven target mRNAs by Lasso Cox regression, which yielded AUC values of 0.76. The prognostic model was further validated in an external independent dataset that integrated three GEO datasets. The characterization of immune cell infiltration and immunotherapy effects between high-risk and low-risk groups were then analyzed. Immune cell infiltration was significantly different between high- and low-risk groups based on risk scores. GC patients with lower risk scores correlated with better immune checkpoint inhibitor therapy (ICI) response. We further validated the expression and regulatory relationship of the ceRNA network in vitro experiments, and also confirmed the relationship between MIR99AHG and PD-L1.

CONCLUSIONS

Our research provides in-depth insights on the role of MSI-related ceRNA in GC and the prognosis and ICIs therapy response of GC patients can be assessed by the risk model based on MSI-related ceRNA network.

Integrated analysis of competitive endogenous RNA networks in elder patients with non-small cell lung cancer

BACKGROUND

Lung cancer is one of the most prevalent cancers and the leading cause of cancer-related deaths worldwide; non-small cell lung cancer (NSCLC) comprises approximately 80% of all lung cancer cases. This study aimed to construct a competing endogenous RNA (ceRNA) network and identify prognostic signatures in elderly patients with NSCLC.

METHODS

We extracted data from elderly patients with NSCLC from The Cancer Genome Atlas and identified differentially expressed (DE) messenger RNAs (mRNAs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to investigate the functions of DEmRNAs. The interactions between RNAs were predicted using starBase, TargetScan, miRTarBase, and miRanda. Cytoscape version 3.0 was used to construct and visualize the lncRNA-miRNA-mRNA ceRNA network. The association between the expression levels of DERNAs in the constructed ceRNA network and overall survival was determined using the survival package in R software. Furthermore, another Gene Expression Omnibus cohort was studied to externally validate the ceRNA network.

RESULTS

In total, 2865 DEmRNAs, 62 DEmiRNAs, and 131 DElncRNAs were identified. Dysregulated mRNAs are enriched in cancer-related processes and pathways. A ceRNA network was constructed using 38 miRNAs, 61 lncRNAs, and 164 mRNAs. Of these, 3 lncRNAs, 3 miRNAs, and 16 mRNAs were closely related to overall survival. The MIR99AHG-hsa-miR-31-5p-PRKCE axis has been identified as a potential ceRNA network involved in the development of NSCLC in elderly individuals. External validation of the MIR99AHG-hsa-miR-31-5p-PRKCE axis in the GSE19804 cohort showed that PRKCE was downregulated and that MIR99AHG was upregulated in the tumor tissues of elderly patients with NSCLC compared with normal lung tissues.

CONCLUSIONS

This study provides novel insights into the lncRNA-miRNA-mRNA ceRNA network and reveals potential biomarkers for the diagnosis and prognosis of elderly patients with NSCLC.

METTL3-mediated long non-coding RNA MIR99AHG methylation targets miR-4660 to promote bone marrow mesenchymal stem cell osteogenic differentiation

Whether long non-coding RNA Mir-99a-Let-7c Cluster Host Gene (LncRNA MIR99AHG) is involved in osteoporosis (OP) remains vague, so we hereby center on its implication. Old C57BL/6J mice were injected with the silencing lentivirus of MIR99AHG and subjected to microCT analysis and immunohistochemistry on osteogenic cells. The osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) with or without transfection was determined by alkaline phosphatase (ALP) and Alizarin Red S staining. Total N(6)-methyladenosine (m6A) on the bone marrow mesenchymal stem cells (BMSCs) was quantified. The potential methylation site and the complementary binding sites with candidate microRNA (miR) were predicted via bioinformatic analyses, with the latter being confirmed via dual-luciferase reporter, RNA immunoprecipitation and RNA pull-down assays. Quantitative real-time PCR and Western blot were used for quantification assays. MIR99AHG was decreased during the osteogenic differentiation of BMSCs, where increased Osterix (OSX), Collagen, Type I, Alpha 1 (Col1A1), Osteocalcin (OCN) and RUNX Family Transcription Factor 2 (RUNX2) as well as more color-stained areas were found. Also, silencing MIR99AHG relieved the OP in mice and reduced the loss of osteogenic cells. M6A methylation in undifferentiated BMSCs was low and MIR99AHG overexpression abolished the effects of overexpressed METTL3 on promoting osteogenic differentiation. MiR-4660, which was downregulated in BMSCs without differentiation but increased during osteogenic differentiation, could bind with MIR99AHG. Furthermore, miR-4660 promoted osteogenic differentiation and reversed the effects of overexpressed MIR99AHG. The present study demonstrated that METTL3-mediated LncRNA MIR99AHG methylation enhanced the osteogenic differentiation of BMSCs via targeting miR-4660.

IGF2BP2 serves as a core m6A regulator in head and neck squamous cell carcinoma

Methylation of N6 adenosine (m6A) plays a crucial role in the development and progression of cancers. Its modification is regulated by three types of m6A-related regulators (methyltransferases (writers), demethylases (erasers), and RNA-binding proteins (readers)). Till now, the functions and roles of these regulators in head and neck squamous cell carcinoma (HNSC) remain largely unexplored. Therefore, we utilized the open HNSC dataset in The Cancer Genome Atlas (TCGA), four different cell lines, and our HNSC patient samples (n=40) to explore the clinical significance of 19 m6A regulators, and selected the most significant prognosis-related regulator. Authentic analyses based on online websites were also used in the study (Oncomine, UALCAN, Kaplan-Meier plotter, Human Protein Atlas (HPA), cBioPortal, LinkedOmics, String, etc.). From the results, general overexpression of m6A regulators was observed in pan-cancer, especially in HNSC. IGF2BP2 was recognized as the hub m6A regulator, which was an independent, unfavorable prognostic factor in HNSC. Its mRNA and protein expression in HNSC were significantly up-regulated. Gene mutation types of IGF2BP2 in HNSC (32%) were mainly mRNA High or Amplification, which represented the high expression of IGF2BP2. And these mutations were associated with a poor prognosis. In functional analysis, IGF2BP2 was negatively correlated to tumor immune infiltration in HNSC. Finally, HMGA2 might interact with the IGF2BP2 in HNSC. In conclusion, IGF2BP2 serves as a core m6A regulator among all regulators in HNSC, which has a high expression and predicts the poor prognosis of HNSC patients independently. IGF2BP2 might bring a new direction for HNSC treatment in the future.

Identification of Prognostic Factors in Cholangiocarcinoma Based on Integrated ceRNA Network Analysis

This study is aimed at screening prognostic biomarkers in cholangiocarcinoma (CHOL) based on competitive endogenous RNA (ceRNA) regulatory network analysis. Microarray data for lncRNAs, mRNA, and miRNAs were downloaded from the GEO and TCGA databases. Differentially expressed RNAs (DERs) were identified in CHOL and normal liver tissue samples. WGCNA was used to identify disease-related gene modules. By integrating the information from the starBase and DIANA-LncBasev2 databases, we constructed a ceRNA network. Survival analysis was performed, and a prognostic gene-based prognostic score (PS) model was generated. The correlation between gene expression and immune cell infiltration or immune-related feature genes was analyzed using TIMER. Finally, real-time quantitative PCR (RT-qPCR) was used to verify the expression of the 10 DERs with independent prognosis. A large cohort of DERs was identified in the CHOL and control samples. The ceRNA network consisted of 6 lncRNAs, 2 miRNAs, 90 mRNAs, and 98 nodes. Ten genes were identified as prognosis-related genes, and a ten-gene signature PS model was constructed, which exhibited a good prognosis predictive ability for risk assessment of CHOL patients (AUC value = 0.975). Four genes, ELF4, AGXT, ABCG2, and LDHD, were associated with immune cell infiltration and closely correlated with immune-related feature genes (CD14, CD163, CD33, etc.) in CHOL. Additionally, the consistency rate of the RT-qPCR results and bioinformatics analysis was 80%, implying a relatively high reliability of the bioinformatic analysis results. Our findings suggest that the ten-signature gene PS model has significant prognostic predictive value for patients with CHOL. These four immune-related DERs are involved in the progression of CHOL and may be useful prognostic biomarkers for CHOLs.

Risk stratification of acute myeloid leukemia: Assessment using a novel prediction model based on ferroptosis-immune related genes

In acute myeloid leukemia (AML), the link between ferroptosis and the immune microenvironment has profound clinical significance. The objective of this study was to investigate the role of ferroptosis-immune related genes (FIRGs) in predicting the prognosis and therapeutic sensitivity in patients with AML. Using The Cancer Genome Atlas dataset, single sample gene set enrichment analysis was performed to calculate the ferroptosis score of AML samples. To search for FIRGs, differentially expressed genes between the high- and low-ferroptosis score groups were identified and then cross-screened with immune related genes. Univariate Cox and LASSO regression analyses were performed on the FIRGs to establish a prognostic risk score model with five signature FIRGs (BMP2, CCL3, EBI3, ELANE, and S100A6). The prognostic risk score model was then used to divide the patients into high- and low-risk groups. For external validation, two Gene Expression Omnibus cohorts were employed. Overall survival was poorer in the high-risk group than in the low-risk group. The novel risk score model was an independent prognostic factor for overall survival in patients with AML. Infiltrating immune cells were also linked to high-risk scores. Treatment targeting programmed cell death protein 1 may be more effective in high-risk patients. This FIRG-based prognostic risk model may aid in optimizing prognostic risk stratification and treatment of AML.

MIR99AHG/miR-204-5p/TXNIP/Nrf2/ARE Signaling Pathway Decreases Glioblastoma Temozolomide Sensitivity

Glioblastoma (GBM) is the most prevalent primary cerebral tumor in adults with high aggressiveness. Temozolomide (TMZ) is considered as the most widely used chemotherapy for GBM patients. Accumulating studies have proved that long non-coding RNAs (lncRNAs) participate in the pathogenesis of tumors. The aim of our study is to disclose the role of mir-99a-let-7c cluster host gene (MIR99AHG) in GBM. MIR99AHG expression was discovered to be elevated in GBM cells through quantitative real-time polymerase chain reaction (RT-qPCR) analysis. Loss-of-function experiments demonstrated that MIR99AHG silencing enhanced TMZ sensitivity of GBM both in vitro and in vivo. RNA pull down, RNA-binding protein immunoprecipitation (RIP), and luciferase reporter assays were implemented to unveil the underlying mechanism of MIR99AHG in GBM. The results of the mechanism assays implied that MIR99AHG interacted with microRNA-204-5p (miR-204-5p) and enhanced thioredoxin interacting protein (TXNIP) expression to inactivate the Nrf2/ARE signaling pathway. MIR99AHG/miR-204-5p/TXNIP regulatory axis was verified by rescue experiments in GBM. To summarize, MIR99AHG plays a promoting role in the TMZ resistance of GBM cells. The findings in this study might provide novel sight for the treatment for GBM.

Inhibitory role of LINC00332 in gastric cancer progression through regulating cell EMT and stemness

OBJECTIVE

Gastric cancer (GC) is one of the most common lethal malignancies worldwide. The molecular mechanisms underlying GC early detection are poorly understood. Identifying potential coding and non-coding markers and related pathways in the GC progression is essential. Some Long non-coding RNAs (lncRNAs) reportedly play vital roles during gastric GC development. However, the clinical significance and biological function of LINC00332 in GC remain largely unclear.

METHODS

The gene expression patterns of GC from an RNAseq dataset (GSE122401) were retrieved from the Gene Expression Omnibus (GEO) database to recognize differentially expressed genes (DEGs) and lncRNAs (DELs) between normal and GC samples through several bioinformatic analysis. The expression of LINC00332 and MMP-13 as a target gene was quantified in fresh frozen tissues obtained from GC patients. In addition, we investigated the potential function of LINC00332 in silico and in vitro.

RESULTS

The expressions of LINC00332 and MMP-13 were significantly downregulated and upregulated in GC tissues, respectively. A significant inverse correlation between LINC00332 and MMP-13 mRNA expression was observed in tumor samples. The mRNA expression level of mesenchymal markers, stem cell factors, and MMP genes were significantly decreased after the LINC00332 ectopic expression, while epithelial markers expression was significantly increased. The LINC00332 overexpression markedly repressed proliferation, migration, and invasion and did not induce apoptosis in AGS cells. In addition, LINC00332 overexpression notably promoted the E-cadherin protein expression. Moreover, LINC00332 significantly decreased the cisplatin resistance.

CONCLUSION

Our findings indicated that LINC00332 may be a critical anti-EMT factor and provided a new efficient therapeutic strategy for GC treatment.

Skin cutaneous melanoma properties of immune-related lncRNAs identifying potential prognostic biomarkers

Skin cutaneous melanoma (SKCM) is one of the most aggressive and life-threatening cancers with high incidence rate, metastasis rate and mortality. Early detection and stratification of risk assessment are essential to treat SKCM and to improve survival rate. The aim of this study is to construct an immune-related lncRNAs (immlncRNAs) prognosis risk model to identify immune biomarkers for early diagnosis, prognosis assessment and target immunotherapy of SKCM. For this purpose, we identified 46 immlncRNAs significantly correlated with SKCM prognosis to construct the prognostic risk model and patients were stratified into the high- and low-risk subgroups according to the developed model. The predictive efficiency of this model has been proved by K-M survival analysis and receiver operating characteristic curve. Moreover, CIBERSORT algorithms confirmed that there were differences in immune cell infiltration between the high- and low-risk groups. Functional enrichment analysis further indicated that immlncRNAs were related to a variety of immune response process signaling pathways, suggesting that relevant immlncRNAs could play an important role in the immune regulation of SKCM. Finally, subgroup analysis and multiple Cox regression analysis further proved the stability of the model. In summary, we successfully constructed a 46 immlncRNA-related prognostic risk score model with excellent predictive efficacy and provided more possibilities to investigate the immune regulation mechanisms and to develop immunotherapy of SKCM.

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.

Development of a prognostic nomogram based on an eight-gene signature for esophageal squamous cell carcinoma by weighted gene co-expression network analysis (WGCNA)

Background

Esophageal squamous cell carcinoma (ESCC) is a highly aggressive malignant tumor. This study aims to develop a robust prognostic model for ESCC.

Methods

Expression profiles of ESCC were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Co-expressed modules were constructed by weighted gene co-expression network analysis (WGCNA). Differentially expressed genes (DEGs) between ESCC and normal samples were identified with the screening criteria of adjusted P value <0.05 and log |fold change (FC)| >1. After univariate and multivariate Cox regression analysis, an 8-gene module was constructed. A receiver operating characteristic (ROC) curve for overall survival (OS) was used to assess the prediction efficacy of the risk score. A nomogram was developed based on the risk score, age, gender, and stage for 1-, 2- and 3-year survival. The potential biological functions and pathways of the 8 genes were predicted using the Metascape database.

Results

The 2 ESCC-related co-expression modules were built via WGCNA. Among all DEGs, 55 survival-related genes were identified for ESCC. Based on these genes, an 8-gene module was constructed, composed of CFAP53, FCGR2A, FCGR3A, GNGT1, IGF2, LINC01524, MAGEA3, and MAGEA6. The area under the curve (AUC) was 0.961, suggesting that the risk score could effectively predict the OS of patients with ESCC. Furthermore, the nomogram exhibited high accuracy in predicting the survival rate of ESCC patients at 1, 2, and 3 years. These genes were mainly involved in ESCC-related pathways such as extracellular matrix organization, collagen formation, and blood vessel development.

Conclusions

Our nomogram based on the 8-gene risk score could be a reliable prognostic tool for ESCC.

LncRNA MIR99AHG mediated by FOXA1 modulates NOTCH2/Notch signaling pathway to accelerate pancreatic cancer through sponging miR-3129-5p and recruiting ELAVL1

Background

Pancreatic cancer (PCa) is a fatal malignancy with poor prognosis, high recurrence and mortality. Substantial reports have suggested long non-coding RNAs (lncRNAs) are implicated in development of numerous malignant tumors, and PCa is included. However, the correlation between novel lncRNA mir-99a-let-7c cluster host gene (MIR99AHG) and PCa remains elusive and needs to be deeply investigated.

Methods

In this study, we firstly used RT-qPCR to examine MIR99AHG expression. Functional assays were implemented for determination of the role of MIR99AHG in PCa cells. Mechanism experiments were designed and carried out for exploring the regulatory mechanism involving MIR99AHG.

Results

MIR99AHG was distinctly overexpressed in PCa cell lines. MIR99AHG deficiency abrogated PCa cell proliferation, migration and invasion. Moreover, MIR99AHG up-regulation was induced by transcription factor forkhead box A1 (FOXA1). Furthermore, MIR99AHG modulated notch receptor 2 (NOTCH2) expression and stimulated Notch signaling pathway through sequestering microRNA-3129-5p (miR-3129-5p) and recruiting ELAV like RNA binding protein 1 (ELAVL1).

Conclusions

Altogether, the exploration of FOXA1/MIR99AHG/miR-3129-5p/ELAVL1/NOTCH2 axis in the progression of PCa might provide a meaningful revelation for PCa diagnosis and treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02189-z.

N6-Methyladenosine-Related Long Noncoding RNAs as Potential Prognosis Biomarkers for Endometrial Cancer

Purpose

Endometrial cancer (EC) is a common gynaecologic malignancy with an increasing incidence rate and mortality in recent years. N6-methylandenosine (m6A)-related long noncoding RNA (lncRNA) plays a vital role in EC, emerging as one of the most abundant RNA modifications.

Materials and Methods

The Cancer Genome Atlas (TCGA) database and UCSC Xena were used to download data related to EC. Survival and univariate and multifactorial prognostic analyses were performed for m6A-related lncRNAs. The expression levels of the three lncRNAs were verified using q-PCR. A nomogram was used to create a clinical tool to assess overall survival. To investigate the relationship between m6A-related lncRNA and EC, we downloaded differential genes related to EC from the TCGA database and mined three m6A-related lncRNAs, namely SCARNA9, TRAF3IP2-AS1, and AL133243.2. The data were categorized into high- and low-risk groups based on m6A-associated lncRNA.

Results

Survival analysis revealed that the high-risk group had a lower survival rate. Survival analysis of three m6A-associated lncRNAs revealed that cases with high expression of SCARNA9 tended to have a poorer prognosis, whereas the opposite was true for TRAF3IP2-AS1, AL133243.2. Univariate and multifactorial prognostic analyses suggested statistical differences in patients’ age, FIGO stage, pathological grade, risk score, and prognosis of EC, which was confirmed by results of the separate prognostic factor analysis for the three lncRNAs. Risk status was validated as an independent prognostic indicator, and the prognostic nomogram combined patient age, pathological stage, and FIGO classification to assess 3–5-year survival. Cases from high- and low-risk groups were analysed for the tumour microenvironment and immune cell scores, and stromal cell scores were found to be lower in the high-risk group. Correlations were analysed using different databases for immune cell classification.

Conclusion

m6A-related lncRNAs may play a key role in the diagnosis and treatment of EC as targets of prognosis and the immune microenvironment.

Recent development of machine learning methods in sumoylation sites prediction

Sumoylation of proteins is an important reversible post-translational modification of proteins and mediates a variety of cellular processes. Sumo-modified proteins can change their subcellular localization, activity and stability. In addition, it also plays an important role in various cellular processes such as transcriptional regulation and signal transduction. The abnormal sumoylation is involved in many diseases, including neurodegeneration and immune-related diseases, as well as the development of cancer. Therefore, identification of the sumoylation site (SUMO site) is fundamental to understanding their molecular mechanisms and regulatory roles. In contrast to labor-intensive and costly experimental approaches, computational prediction of sumoylation sites in silico also attracted much attention for its accuracy, convenience and speed. At present, many computational prediction models have been used to identify SUMO sites, but these contents have not been comprehensively summarized and reviewed. Therefore, the research progress of relevant models is summarized and discussed in this paper. We will briefly summarize the development of bioinformatics methods on sumoylation site prediction. We will mainly focus on the benchmark dataset construction, feature extraction, machine learning method, published results and online tools. We hope the review will provide more help for wet-experimental scholars.

LncRNA MONC suppresses the malignant phenotype of Endometrial Cancer Stem Cells and Endometrial Carcinoma Cells by regulating the MiR-636/GLCE axis

Background

Emerging evidence shows that abnormal expression of long non-coding RNA is involved in the occurrence and development of various tumors. LncRNA MONC is abnormally expressed in head and neck squamous cell carcinoma, lung cancer, colorectal cancer, and acute megakaryocytic leukemia, but the biological function and potential regulatory mechanism of MONC in endometrial cancer stem cells (ECSCs) and endometrial cancer cells (ECCs) have not been studied. In this study, we aimed to explore the tumor suppressive effect and mechanism of MONC in regulating ECSCs and ECCs.

Methods

We used qRT-PCR to detect the expression of MONC, miR-636 and GLCE in normal human endometrial tissues and endometrial carcinoma (EC) tissues. Luciferase assay was used to verify the binding sites between MONC and miR-636 and between miR-636 and GLCE. Double fluorescence in situ hybridization was used to locate MONC and miR-636 in cells. ECSCs were obtained by flow cytometry sorting assay. Sphere formation assay, CCK-8 assay, transwell invasion assay, cell cycle analysis and apoptosis assay were used to detect the effects of MONC/miR-636/GLCE axis on the malignant biological behavior of ECSCs and ECCs. The effect of MONC on the epithelial-to-mesenchymal transition (EMT) process was detected using western blot. Finally, we conducted in vivo verification through Tumor xenografts in BALB/C nude mice.

Results

In this study, we found MONC is low expression in endometrial carcinoma (EC) and patients in the MONC high-expression group had a better prognosis. MONC and miR-636 are relatively co-localized in the cytoplasm. MONC directly inhibits the malignant biological behavior of ECSCs and ECCs by directly inhibiting miR-636. Simultaneously, miR-636 may indirectly reduce the expression of MONC. Down-regulation of miR-636 may promote GLCE expression by targeting the 3′-untranslated region (UTR) of the downstream gene GLCE, thereby inhibiting the progression of ECSCs. MONC combined with miR-636 inhibited tumor epithelial-to-mesenchymal transition (EMT) process. In addition, we verified the tumor suppressive effect of MONC in nude mice, miR-636 can rescue the tumor suppressive effect of overexpressing MONC.

Conclusions

In conclusion, this study showed that MONC inhibits the malignant phenotypes of ECSCs and ECCs by regulating the miR-636/GLCE axis. Thus the MONC/miR-636/GLCE axis may provide novel treatment avenues for human EC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01911-1.

MIR99AHG is a noncoding tumor suppressor gene in lung adenocarcinoma

Little is known about noncoding tumor suppressor genes. An effective way to identify these genes is by analyzing somatic copy number variation (CNV)-related noncoding genes. By integrated bioinformatics analyses of differentially expressed long noncoding RNAs (lncRNAs) and arm-level CNVs in lung adenocarcinoma (LUAD), we identified a potential antitumor gene, MIR99AHG, encoding lncRNA MIR99AHG as well as a miR-99a/let-7c/miR-125b2 cluster on chromosome 21q. All four of these transcripts were downregulated in LUAD tissues partly due to the copy number deletion of the MIR99AHG gene. Both MIR99AHG and miR-99a expression was positively correlated with the survival of LUAD patients. MIR99AHG suppressed proliferation and metastasis and promoted autophagy both in vitro and in vivo. Mechanistically, the interaction between MIR99AHG and ANXA2 could accelerate the ANXA2-induced ATG16L+ vesicle biogenesis, thus promoting phagophore assembly. Additionally, miR-99a targeted a well-known autophagy suppressor, mammalian target of rapamycin (mTOR), thereby synergistically promoting autophagy and postponing LUAD progression with MIR99AHG. In summary, MIR99AHG emerges as a noncoding tumor suppressor gene in LUAD, providing a new strategy for antitumor therapy.

A novel comprehensive immune-related gene signature as a promising survival predictor for the patients with head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC), the most frequent subtype of head and neck cancer, continues to have a poor prognosis with no improvement. The TNM stage is not satisfactory for individualized prognostic assessment and it does not predict response to therapy. In the present study, we downloaded the gene expression profiles from TCGA database to establish a training set and GEO database for a validation set. In the training set, we developed an 10 immune-related genes signature which had superior predictive value compared with TNM stage. A nomogram including clinical characteristics was also constructed for accurate prediction. Furthermore, it was determined that our prognostic signature might act as an independent factor for predicting the survival of HNSCC patients. As for the immune microenvironment, our results showed higher immune checkpoint expression (CLTA-4 and PD-1) in low-risk group which might reflect a positive immunotherapy response. Thus, our signature not only provided a promising biomarker for survival prediction, but might be evaluated as an indicator for personalized immunotherapy in patients with HNSCC.

Clinical Significance of a Novel Tumor Progression-Associated Immune Signature in Colorectal Adenocarcinoma

Background

Some colorectal adenocarcinoma (CRC) patients are susceptible to recurrence, and they rapidly progress to advanced cancer stages and have a poor prognosis. There is an urgent need for efficient screening criteria to identify patients who tend to relapse in order to treat them earlier and more systematically.

Methods

We identified two groups of patients with significantly different outcomes by unsupervised cluster analysis of GSE39582 based on 101 significantly differentially expressed immune genes. To develop an accurate and specific signature based on immune-related genes to predict the recurrence of CRC, a multivariate Cox risk regression model was constructed with a training cohort composed of 519 CRC samples. The model was then validated using 129, 292, and 446 samples in the real-time quantitative reverse transcription PCR (qRT-PCR), test, and validation cohorts, respectively.

Results

This classification system can also be used to predict the prognosis in clinical subgroups and patients with different mutation states. Four independent datasets, including qRT-PCR and The Cancer Genome Atlas (TCGA), demonstrated that they can also be used to accurately predict the overall survival of CRC patients. Further analysis suggested that high-risk patients were characterized by worse effects of chemotherapy and immunotherapy, as well as lower immune scores. Ultimately, the signature was identified as an independent prognostic factor.

Conclusion

The signature can accurately predict recurrence and overall survival in patients with CRC and may serve as a powerful prognostic tool to further optimize cancer immunotherapy.

A Five Immune-Related lncRNA Signature as a Prognostic Target for Glioblastoma

Background: A variety of regulatory approaches including immune modulation have been explored as approaches to either eradicate antitumor response or induce suppressive mechanism in the glioblastoma microenvironment. Thus, the study of immune-related long noncoding RNA (lncRNA) signature is of great value in the diagnosis, treatment, and prognosis of glioblastoma.

Methods: Glioblastoma samples with lncRNA sequencing and corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) database. Immune-lncRNAs co-expression networks were built to identify immune-related lncRNAs via Pearson correlation. Based on the median risk score acquired in the training set, we divided the samples into high- and low-risk groups and demonstrate the survival prediction ability of the immune-related lncRNA signature. Both principal component analysis (PCA) and gene set enrichment analysis (GSEA) were used for immune state analysis.

Results: A cohort of 151 glioblastoma samples and 730 immune-related genes were acquired in this study. A five immune-related lncRNA signature (AC046143.1, AC021054.1, AC080112.1, MIR222HG, and PRKCQ-AS1) was identified. Compared with patients in the high-risk group, patients in the low-risk group showed a longer overall survival (OS) in the training, validation, and entire TCGA set (p = 1.931e-05, p = 1.706e-02, and p = 3.397e-06, respectively). Additionally, the survival prediction ability of this lncRNA signature was independent of known clinical factors and molecular features. The area under the ROC curve (AUC) and stratified analyses were further performed to verify its optimal survival predictive potency. Of note, the high-and low-risk groups exhibited significantly distinct immune state according to the PCA and GSEA analyses.

Conclusions: Our study proposes that a five immune-related lncRNA signature can be utilized as a latent indicator of prognosis and potential therapeutic approach for glioblastoma.

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.

Head and Neck Squamous Cell Carcinoma: Epigenetic Landscape

Head and neck squamous carcinoma (HNSCC) constitutes the sixth most prevalent cancer worldwide. The molecular pathogenesis of HNSCC includes disorders in cell cycle, intercellular signaling, proliferation, squamous cell differentiation and apoptosis. In addition to the genetic mutations, changes in HNSCC are also characterized by the accumulation of epigenetic alterations such as DNA methylation, histone modifications, non-coding RNA activity and RNA methylation. In fact, some of them may promote cancer formation and progression by controlling the gene expression machinery, hence, they could be used as biomarkers in the clinical surveillance of HNSCC or as targets for therapeutic strategies. In this review, we focus on the current knowledge regarding epigenetic modifications observed in HNSCC and its predictive value for cancer development.

Tumor Suppressor LINC02487 Inhibits Oral Squamous Cell Carcinoma Cell Migration and Invasion Through the USP17-SNAI1 Axis

Purpose

The aim of this study was to explore the functions and associated mechanisms of long noncoding RNA LINC02487 in oral squamous cell carcinoma (OSCC).

Methods

The relative expression levels of LINC02487 in OSCC cell lines and tissue samples were examined by RT-qPCR. Intracellular localization was determined using RNA fluorescence in situ hybridization. LINC02487 was cloned into the pCMV-puro vector and then introduced into OSCC cells using lentiviral transfection. Cell processes, such as proliferation, apoptosis, migration, and invasion, were subsequently examined. LINC02487-binding proteins were identified by ChIRP-MS and confirmed by RNA immunoprecipitation. Protein expression was determined by western blotting assay.

Results

LINC02487 has been reported to be downregulated in OSCC. Here, we confirmed that the expression of LINC02487 was reduced in 6 OSCC cell lines compared with that in immortalized normal oral epithelial cells and in 50 OSCC samples compared with paired adjacent normal tissue in a Chinese population and that LINC02487 expression levels were associated with cancer metastasis. We further identified that LINC02487 was localized to the cytoplasm, aggregated around the nuclear membrane. Functional studies demonstrate that overexpression of LINC02487 significantly suppresses cell migration and invasion and also inhibits cell proliferation. For the mechanism, we reveal that LINC02487 directly binds to USP17, a deubiquitinating enzyme, and regulates cell migration and invasion through the USP17-SNAI1 axis in a process that involves epithelial-mesenchymal transition (EMT).

Conclusion

Our results confirm that long noncoding RNA LINC02487 is downregulated in OSCC tissue samples and cell lines. We also find that LINC02487 acts as a tumor suppressor through the USP17-SNAI1 axis.

Autophagy-Related Signature for Head and Neck Squamous Cell Carcinoma

Background

Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies in the world, with low survival and poor quality of life. Autophagy-associated genes (ATGs) have been reported to be involved in the initiation and progression of malignancies. Here, we aimed to investigate the association between autophagy-associated genes and the outcomes in HNSCC patients.

Methods

We obtained ATGs with prognostic values by analyzing the datasets from The Cancer Genome Atlas (TCGA) and Human Autophagy Database (HADb). The enrichment functions of autophagy differential genes were analyzed by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The Kaplan-Meier method was applied to the survival curve analysis. A prognostic autophagy-related gene signature was established, and its independence was verified.

Results

We acquired a total of 529 samples and 232 ATGs; further, we identified 45 genes associated with prognosis and built a prognosis autophagy signature based on risk score of 15 genes. Patients were divided into two groups based on risk scores. The Kaplan-Meier curve illustrated that the survival rate of the high-risk group was significantly lower than that of the low-risk group in both the training group and validation group. The ROC curve revealed that the risk score had the highest AUC value in the 3rd and 5th years, reaching 0.703 and 0.724, which are higher than other risk factors such as gender, age, and TNM stage. The nomogram further confirmed its weight in the prognosis of HNSCC patients. Through KEGG and GO enrichment analyses, we observed that ATGs were involved in the tumorigenesis and invasion of tumor by various mediating pathways. We gained 3 hub genes (MAP1LC3B, FADD, and LAMP1) and further analyzed the survival curves, mutations, differential expressions, and their roles in tumors on the online websites.

Conclusion

We identified a novel autophagy-related signature that may provide promising biomarker genes for the treatment and prognosis of HNSCC. We need to validate its prognostic value by applying it to the clinic.

Candidate lncRNA-microRNA-mRNA networks in predicting non-small cell lung cancer and related prognosis analysis

PURPOSE

The role of non-coding RNA, once thought to be dark matter, is increasingly prominent in cancer. Our article explores the effect of non-coding RNA in lung adenocarcinoma and lung squamous cell carcinoma by mining TCGA public database.

METHODS

Download the data by applying the official TCGA software. The data were analyzed by R data analysis packages, 'edgeR', 'gplots' and 'survival'. We better illustrate the potential networks of lung cancer genes by constructing ceRNAs, using Cytoscape software.

RESULTS

We obtained genes which were differentially expressed in lung adenocarcinoma and lung squamous cell carcinoma analysis. Within these differentially expressed genes, we also conducted a survival analysis to find differentially expressed genes associated with prognosis in both lung adenocarcinoma and lung squamous cell carcinoma. Based on genes differentially expressed of both lung adenocarcinoma and lung squamous cell carcinoma, we constructed a ceRNA network to illustrate the mechanism of lung adenocarcinoma and lung squamous cell carcinoma. Our study analyzed genes which were differentially expressed in lung adenocarcinoma and lung squamous cell carcinoma using the TCGA database.

CONCLUSION

Based on this, the prognosis in both lung squamous cell carcinoma and lung adenocarcinoma was analyzed. We have also constructed a ceRNA network to provide a basis for the study of ceRNA in lung adenocarcinoma and lung squamous cell carcinoma.