YY1-induced lncRNA DSCR8 promotes the progression of ovarian cancer via miR-3192-5p/YY1 axis

Long Non-Coding RNA Small Nucleolar RNA Host Gene 4 Induced by Transcription Factor SP1 Promoted the Progression of Nasopharyngeal Carcinoma Through Modulating microRNA-510-5p/Centromere Protein F Axis

Long non-coding RNAs (LncRNAs) are implicated with tumorigenesis and the development of nasopharyngeal carcinoma (NPC). Previous studies suggested that long non-coding RNA small nucleolar RNA host gene 4 (SNHG4) exerted oncogenic roles in various cancers. However, the function and molecular mechanism of SNHG4 in NPC have not been investigated. In our study, it was confirmed that the SNHG4 level was enriched in NPC tissues and cells. Functional assays indicated that SNHG4 depletion inhibited the proliferation and metastasis but promoted apoptosis of NPC cells. Furthermore, we identified miR-510-5p as a downstream gene of SNHG4 in NPC cells and SNHG4 upregulated CENPF expression by binding to miR-510-5p. Moreover, there was a positive (or negative) association between CENPF and SNHG4 (or miR-510-5p) expression in NPC. In addition, rescue experiments verified that CENPF overexpression or miR-510-5p silencing abrogated inhibitory effects on NPC tumorigenesis caused by SNHG4 deficiency. The study demonstrated that SNHG4 promoted NPC progression via miR-510-5p/CENPF axis, providing a novel potential therapeutic target for NPC treatments.

PGC-1α promotes colorectal carcinoma metastasis through regulating ABCA1 transcription

Colorectal cancer (CRC) is a highly aggressive cancer in which metastasis plays a key role. However, the mechanisms underlying metastasis have not been fully elucidated. Peroxisome proliferator-activated receptor gamma coactivator 1α (PGC-1α), a regulator of mitochondrial function, has been reported as a complicated factor in cancer. In this study, we found that PGC-1α was highly expressed in CRC tissues and was positively correlated with lymph node and liver metastasis. Subsequently, PGC-1α knockdown was shown to inhibit CRC growth and metastasis in both in vitro and in vivo studies. Transcriptomic analysis revealed that PGC-1α regulated ATP-binding cassette transporter 1 (ABCA1) mediated cholesterol efflux. Mechanistically, PGC-1α interacted with YY1 to promote ABCA1 transcription, resulting in cholesterol efflux, which subsequently promoted CRC metastasis through epithelial-to-mesenchymal transition (EMT). In addition, the study identified the natural compound isoliquiritigenin (ISL) as an inhibitor that targeted ABCA1 and significantly reduced CRC metastasis induced by PGC-1α. Overall, this study sheds light on how PGC-1α promotes CRC metastasis by regulating ABCA1-mediated cholesterol efflux, providing a basis for further research to inhibit CRC metastasis.

LncNAP1L6 activates MMP pathway by stabilizing the m6A-modified NAP1L2 to promote malignant progression in prostate cancer

Malignant progression such as bone metastasis, which is associated with pathologic fractures, pain and reduced survival frequently occurs in prostate cancer (PCa) patients at advanced stages. Accumulating evidence has supported that long non-coding RNAs (lncRNAs) participate in multiple biological processes. Nevertheless, the functions of most lncRNAs in PCa malignant progression remain largely unclear. Our current study is to elucidate the influence of lncRNA lncNAP1L6 on PCa malignant progression and uncover the possible regulatory mechanism. Firstly, RT-qPCR analysis was to detect lncNAP1L6 expression and suggested that lncNAP1L6 was markedly upregulated in PCa cells. Functional assays manifested that silencing of lncNAP1L6 hampered cell migration, invasion, and epithelial-mesenchymal transition (EMT) while overexpression of lncNAP1L6 exacerbated cell migration, invasion and EMT. In addition, mechanism assays were to determine the latent regulatory mechanism of lncNAP1L6. It turned out that METTL14/METTL3 complex mediated m6A methylation of NAP1L2 mRNA. Besides, lncNAP1L6 recruited HNRNPC to m6A-modified NAP1L2, leading to stabilization of NAP1L2 mRNA. Moreover, NAP1L6 interacted with YY1 to promote the transcription of MMP2 and MMP9 and activate MMP signaling pathway. In summary, lncNAP1L6 was identified as an oncogene in PCa, which revealed that lncNAP1L6 might be used as potential therapeutic target in PCa.

LncRNA RHPN1-AS1 inhibition induces autophagy and apoptosis in prostate cancer cells via the miR-7-5p/EGFR/PI3K/AKT/mTOR signaling pathway

LncRNA RHPN1-AS1 (RHPN1-AS1) has been confirmed to promote tumor progression in multiple cancers and is upregulated in prostate cancer (PCa), but whether it has an effect on PCa progression remains unclear. In this study, we found that PCa patients with high RHPN1-AS1 expression had a shorter survival time, and RHPN1-AS1 was significantly upregulated in PCa tissues and cells. Based on informatics analysis we predicted that miR-7-5p binds to 3'UTR of RHPN1-AS1 and epidermal growth factor receptor (EGFR) and verified it by luciferase reporter gene assay. Subsequently, we transfected PCa cells with RHPN1-AS1 overexpression vector (RHPN1-AS1), knockdown plasmids (sh-RHPN1-AS1) and/or miR-7-5p mimics or inhibitor and/or overexpression vector (EGFR) or small interfering RNA of EGFR (si-EGFR) or its control, and found that overexpression of RHPN1-AS1 inhibited miR-7-5p expression and promoted EGFR expression, silencing RHPN1-AS1 inhibited proliferation and invasion, and induced G2/M arrest, apoptosis and autophagy in PCa cells. 3MA (an inhibitor of autophagy)-mediated autophagy inhibition attenuated RHPN1-AS1 inhibition-induced apoptosis. Overexpression miR-7-5p or silencing EGFR promoted LC3-I to LC3-II conversion, enhanced autophagy activity, induced cleaved-caspase-3 expression and apoptosis in PCa cells. Furthermore, overexpression of RHPN1-AS1 promoted phosphorylation of phosphatidylinositol 3-kinase (PI3K), AKT and mTOR, inhibited LC3-I to LC3-II conversion and reduced apoptosis in PCa cells, while GSK2126458 (an inhibitor of PI3K) reversed the effect of RHPN1-AS1 on PCa cells. In summary, RHPN1-AS1 acted as a ceRNA of miR-7-5p to upregulate EGFR expression, silencing RHPN1-AS1 suppressed PCa tumor progression by inducing autophagy and apoptosis in PCa cells through the miR-7-5p/EGFR/PI3K/AKT/mTOR pathway.

LncRNA FOXP4-AS1 Promotes the Progression of Esophageal Squamous Cell Carcinoma by Interacting With MLL2/H3K4me3 to Upregulate FOXP4

Malignant tumors are a grave threat to human health. Esophageal squamous cell carcinoma (ESCC) is a common gastrointestinal malignant tumor. China has a high incidence of ESCC, and its morbidity and mortality are higher than the global average. Increasingly, studies have shown that long noncoding RNAs (lncRNAs) play a vital function in the occurrence and development of tumors. Although the biological function of FOXP4-AS1 has been demonstrated in various tumors, the potential molecular mechanism of FOXP4-AS1 in ESCC is still poorly understood. The expression of FOXP4 and FOXP4-AS1 was detected in ESCC by quantitative real-time PCR (qRT–PCR) or SP immunohistochemistry (IHC). shRNA was used to silence gene expression. Apoptosis, cell cycle, MTS, colony formation, invasion and migration assays were employed to explore the biological functions of FOXP4 and FOXP4-AS1. The potential molecular mechanism of FOXP4-AS1 in ESCC was determined by dual-luciferase reporter, RNA immunoprecipitation (RIP) and chromatin immunoprecipitation (ChIP). Here, we demonstrated that FOXP4-AS1 was significantly increased in ESCC tissues and cell lines, associated with lymph node metastasis and TNM staging. Cell function experiments showed that FOXP4-AS1 promoted the proliferation, invasion and migration ability of ESCC cells. The expression of FOXP4-AS1 and FOXP4 in ESCC tissues was positively correlated. Further research found that FOXP4-AS1, upregulated in ESCC, promotes FOXP4 expression by enriching MLL2 and H3K4me3 in the FOXP4 promoter through a “molecular scaffold”. Moreover, FOXP4, a transcription factor of β-catenin, promotes the transcription of β-catenin and ultimately leads to the malignant progression of ESCC. Finally, FOXP4-AS1 may be a new therapeutic target for ESCC.

Construction of a novel immune-related lncRNA signature and its potential to predict the immune status of patients with hepatocellular carcinoma

Background

The accuracy of existing biomarkers for predicting the prognosis of hepatocellular carcinoma (HCC) is not satisfactory. It is necessary to explore biomarkers that can accurately predict the prognosis of HCC.

Methods

In this study, original transcriptome data were downloaded from The Cancer Genome Atlas (TCGA) database. Immune-related long noncoding ribonucleic acids (irlncRNAs) were identified by coexpression analysis, and differentially expressed irlncRNA (DEirlncRNA) pairs were distinguished by univariate analysis. In addition, the least absolute shrinkage and selection operator (LASSO) penalized regression was modified. Next, the cutoff point was determined based on the area under the curve (AUC) and Akaike information criterion (AIC) values of the 5-year receiver operating characteristic (ROC) curve to establish an optimal model for identifying high-risk and low-risk groups of HCC patients. The model was then reassessed in terms of clinicopathological features, survival rate, tumor-infiltrating immune cells, immunosuppressive markers, and chemotherapy efficacy.

Results

A total of 1009 pairs of DEirlncRNAs were recognized in this study, 30 of these pairs were included in the Cox regression model for subsequent analysis. After regrouping according to the cutoff point, we could more effectively identify factors such as aggressive clinicopathological features, poor survival outcomes, specific immune cell infiltration status of tumors, high expression level of immunosuppressive biomarkers, and low sensitivity to chemotherapy drugs in HCC patients.

Conclusions

The nonspecific expression level signature involved with irlncRNAs shows promising clinical value in predicting the prognosis of HCC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09059-x.

LINC02532 Contributes to Radiosensitivity in Clear Cell Renal Cell Carcinoma through the miR-654-5p/YY1 Axis

Background: Studies have shown that long non-coding RNAs (lncRNAs) play essential roles in tumor progression and can affect the response to radiotherapy, including in clear cell renal cell carcinoma (ccRCC). LINC02532 has been found to be upregulated in ccRCC. However, not much is known about this lncRNA. Hence, this study aimed to investigate the role of LINC02532 in ccRCC, especially in terms of radioresistance. Methods: Quantitative real-time PCR was used to detect the expression of LINC02532, miR-654-5p, and YY1 in ccRCC cells. Protein levels of YY1, cleaved PARP, and cleaved-Caspase-3 were detected by Western blotting. Cell survival fractions, viability, and apoptosis were determined by clonogenic survival assays, CCK-8 assays, and flow cytometry, respectively. The interplay among LINC02532, miR-654-5p, and YY1 was detected by chromatin immunoprecipitation and dual-luciferase reporter assays. In addition, in vivo xenograft models were established to investigate the effect of LINC02532 on ccRCC radioresistance in 10 nude mice. Results: LINC02532 was highly expressed in ccRCC cells and was upregulated in the cells after irradiation. Moreover, LINC02532 knockdown enhanced cell radiosensitivity both in vitro and in vivo. Furthermore, YY1 activated LINC02532 in ccRCC cells, and LINC02532 acted as a competing endogenous RNA that sponged miR-654-5p to regulate YY1 expression. Rescue experiments indicated that miR-654-5p overexpression or YY1 inhibition recovered ccRCC cell functions that had been previously impaired by LINC02532 overexpression. Conclusions: Our results revealed a positive feedback loop of LINC02532/miR-654-5p/YY1 in regulating the radiosensitivity of ccRCC, suggesting that LINC02532 might be a potential target for ccRCC radiotherapy. This study could serve as a foundation for further research on the role of LINC02532 in ccRCC and other cancers.

YY1-induced long non-coding RNA PSMA3 antisense RNA 1 functions as a competing endogenous RNA for microRNA 214-5p to expedite the viability and restrict the apoptosis of bladder cancer cells via regulating programmed cell death-ligand 1

Bladder cancer (BC) is one of the most common malignant tumors in the urinary system. Our research aimed to explore the function and underlying mechanisms of long noncoding RNA (lncRNA) PSMA3-AS1 in BC. RT-qPCR was utilized to detect the levels of PSMA3-AS1, miR-214-5p, and PD-L1. ChIP assay was employed to confirm the transcription factor of PSMA3-AS1. Luciferase reporter assay was carried out to demonstrate the relationships between miR-214-5p and PSMA3-AS1 or PD-L1. The diagnostic value of PSMA3-AS1 was evaluated by the ROC curve. CCK-8, wound healing, transwell, and flow cytometry assays were applied to analyze cell viability, migration, invasion, and apoptosis. Western blotting was used to confirm the expression of cleaved caspase-3. The present study revealed that BC tissues and cells exhibited an increased expression in PSMA3-AS1. High expression of PSMA3-AS1 was related to poor prognosis in BC patients. Then, the area under the ROC curve for PSMA3-AS1 was up to 0.8954. Moreover, ChIP assay elaborated that YY1 could bind to the PSMA3-AS1 promoter region. Furthermore, it was found that that PSMA3-AS1 knockdown repressed BC cell viability and metastasis, and promoted apoptosis. In addition, miR-214-5p was inversely correlated with PSMA3-AS1 or PD-L1 levels. MiR-214-5p deletion reversed the impacts of PSMA3-AS1 deletion on BC progression, and PD-L1 inhibition also abrogated the influence of miR-214-5p deletion in BC development. In conclusion, YY1-induced PSMA3-AS1 exerted an oncogenic function in BC cells via targeting miR-214-5p and enhancing PD-L1, providing potential biomarkers for BC therapy.

LINC01224 promotes colorectal cancer progression through targeting miR-485-5p/MYO6 axis

Background

Long noncoding RNAs (lncRNAs) are related to colorectal cancer (CRC) development. However, the role and mechanism of lncRNA LINC01224 in CRC development are largely unknown.

Methods

LINC01224, Yin Yang 1 (YY1), microRNA (miR)-485-5p, and myosins of class VI (MYO6) levels were examined using quantitative reverse transcription polymerase chain reaction and western blotting. Functional analyses were processed through CCK-8, colony formation, flow cytometry, transwell, and xenograft analyses. Dual-luciferase reporter, chromatin immunoprecipitation (ChIP), RNA immunoprecipitation, and pull-down assays were conducted to analyze the binding interaction.

Results

LINC01224 abundance was elevated in CRC tissue samples and cell lines. Elevated LINC01224 might indicate the lower 5-year overall survival in 52 CRC patients. LINC01224 was upregulated via the transcription factor YY1. LINC01224 knockdown restrained CRC cell proliferation, migration, and invasion and increased apoptosis. MiR-485-5p was sponged by LINC01224, and miR-485-5p downregulation relieved the influence of LINC01224 interference on CRC progression. MYO6 was targeted via miR-485-5p and regulated via LINC01224/miR-485-5p axis. MiR-485-5p overexpression suppressed CRC cell proliferation, migration, and invasion and facilitated apoptosis. MYO6 upregulation mitigated the role of miR-485-5p. LINC01224 knockdown decreased xenograft tumor growth.

Conclusion

YY1-induced LINC01224 regulates CRC development via modulating miR-485-5p/MYO6 axis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02389-x.

Development of a Machine Learning-Based Autophagy-Related lncRNA Signature to Improve Prognosis Prediction in Osteosarcoma Patients

Background

Osteosarcoma is a frequent bone malignancy in children and young adults. Despite the availability of some prognostic biomarkers, most of them fail to accurately predict prognosis in osteosarcoma patients. In this study, we used bioinformatics tools and machine learning algorithms to establish an autophagy-related long non-coding RNA (lncRNA) signature to predict the prognosis of osteosarcoma patients.

Methods

We obtained expression and clinical data from osteosarcoma patients in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. We acquired an autophagy gene list from the Human Autophagy Database (HADb) and identified autophagy-related lncRNAs by co-expression analyses. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the autophagy-related lncRNAs were conducted. Univariate and multivariate Cox regression analyses were performed to assess the prognostic value of the autophagy-related lncRNA signature and validate the relationship between the signature and osteosarcoma patient survival in an independent cohort. We also investigated the relationship between the signature and immune cell infiltration.

Results

We initially identified 69 autophagy-related lncRNAs, 13 of which were significant predictors of overall survival in osteosarcoma patients. Kaplan-Meier analyses revealed that the 13 autophagy-related lncRNAs could stratify patients based on their outcomes. Receiver operating characteristic curve analyses confirmed the superior prognostic value of the lncRNA signature compared to clinically used prognostic biomarkers. Importantly, the autophagy-related lncRNA signature predicted patient prognosis independently of clinicopathological characteristics. Furthermore, we found that the expression levels of the autophagy-related lncRNA signature were significantly associated with the infiltration levels of different immune cell subsets, including T cells, NK cells, and dendritic cells.

Conclusion

The autophagy-related lncRNA signature established here is an independent and robust predictor of osteosarcoma patient survival. Our findings also suggest that the expression of these 13 autophagy-related lncRNAs may promote osteosarcoma progression by regulating immune cell infiltration in the tumor microenvironment.

Non-Coding RNAs as Biomarkers of Tumor Progression and Metastatic Spread in Epithelial Ovarian Cancer

Simple Summary

Despite advances in cancer research in recent years, efficient predictive biomarkers of tumor progression and metastatic spread for ovarian cancer are still missing. Therefore, we critically address recent findings in the field of non-coding RNAs (microRNAs and long non-coding RNAs) and DNA methylation in ovarian cancer patients as promising novel biomarkers of ovarian cancer progression.

Abstract

Ovarian cancer is one of the most common causes of death among gynecological malignancies. Molecular changes occurring in the primary tumor lead to metastatic spread into the peritoneum and the formation of distant metastases. Identification of these changes helps to reveal the nature of metastases development and decipher early biomarkers of prognosis and disease progression. Comparing differences in gene expression profiles between primary tumors and metastases, together with disclosing their epigenetic regulation, provides interesting associations with progression and metastasizing. Regulatory elements from the non-coding RNA families such as microRNAs and long non-coding RNAs seem to participate in these processes and represent potential molecular biomarkers of patient prognosis. Progress in therapy individualization and its proper targeting also rely upon a better understanding of interactions among the above-listed factors. This review aims to summarize currently available findings of microRNAs and long non-coding RNAs linked with tumor progression and metastatic process in ovarian cancer. These biomolecules provide promising tools for monitoring the patient’s response to treatment, and further they serve as potential therapeutic targets of this deadly disease.

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

Background

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

Methods

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

Results

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

Conclusions

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

Immune-Related lncRNA to Construct Novel Signature and Predict the Immune Landscape of Human Hepatocellular Carcinoma

The signature composed of immune-related long noncoding ribonucleic acids (irlncRNAs) with no requirement of specific expression level seems to be valuable in predicting the survival of patients with hepatocellular carcinoma (HCC). Here, we retrieved raw transcriptome data from The Cancer Genome Atlas (TCGA), identified irlncRNAs by co-expression analysis, and recognized differently expressed irlncRNA (DEirlncRNA) pairs using univariate analysis. In addition, we modified Lasso penalized regression. Then, we compared the areas under curve, counted the Akaike information criterion (AIC) values of 5-year receiver operating characteristic curve, and identified the cut-off point to set up an optimal model for distinguishing the high- or low-disease-risk groups among patients with HCC. We then reevaluated them from the viewpoints of survival, clinic-pathological characteristics, tumor-infiltrating immune cells, chemotherapeutics efficacy, and immunosuppressed biomarkers. 36 DEirlncRNA pairs were identified, 12 of which were included in a Cox regression model. After regrouping the patients by the cut-off point, we could more effectively differentiate between them based on unfavorable survival outcome, aggressive clinic-pathological characteristics, specific tumor immune infiltration status, low chemotherapeutics sensitivity, and highly expressed immunosuppressed biomarkers. The signature established by paring irlncRNA regardless of expression levels showed a promising clinical prediction value.