Comprehensive analysis of the lncRNA‑associated competing endogenous RNA network in breast cancer

LncRNA LINC00466 Promotes the Progression of Breast Cancer via miR-4731-5p/EPHA2 Pathway

BACKGROUND

Breast Cancer (BC) is a female malignancy with a high mortality rate. Novel diagnostic and prognostic biomarkers are valuable for reducing BC mortality. Our study is designed to undrape the precise role of the LINC00466/miR-4731-5p/EPHA2 axis in BC.

METHODS

The Cancer Genome Atlas (TCGA) sequencing dataset was utilized to compare the levels of LINC00466. The levels of LINC00466, miR-4731-5p, and EPHA2 were tested by qRTPCR. Cell proliferation and cycle were detected by CCK-8 assay and flow cytometer. In vivo role of LINC00466 was tested by Xenograft nude models. Binding sites were predicted by TargetScan and Starbase. The binding relationship was employed by Dual-luciferase reporter gene assay and RNA pull-down assay.

RESULTS

LINC00466 was increased in human breast cancer tissues. LINC00466 was negatively associated with miR-4731-5p and positively correlated with EPHA2 in human breast cancer tissues. Down-regulation of LINC00466 suppressed the proliferation and arrested the cell cycle of breast cancer cells, and inhibited tumor growth in vivo.

CONCLUSION

LINC00466 promoted BC development via mediating the miR-4731-5p/EPHA2 axis, which has the potential value as a promising therapeutic target in BC.

Integration analysis of cis- and trans-regulatory long non-coding RNAs associated with immune-related pathways in non-small cell lung cancer

Background

Long non-coding RNAs (lncRNAs) are importantly involved in the initiation and progression of non-small cell lung cancer (NSCLC). However, the classification and mechanisms of lncRNAs remain largely elusive.

Aim

Hence, we addressed this through bioinformatics analysis.

Methods and results

We utilized microarray technology to analyze lncRNAs and mRNAs in twenty paired NSCLC tumor tissues and adjacent normal tissues. Gene set enrichment analysis, Kyoto Encyclopedia of Genes and Genomes, and Gene Ontology were conducted to discern the biological functions of identified differentially expressed transcripts. Additionally, networks of lncRNA-mRNA co-expression, including cis-regulation, lncRNA-transcription factor (TF)-mRNA, trans-regulation, and lncRNA-miRNA-mRNA interactions were explored. Furthermore, the study examined differentially expressed transcripts and their prognostic values in a large RNA-seq dataset of 1016 NSCLC tumors and normal tissues extracted from the Cancer Genome Atlas (TCGA). The analysis revealed 391 lncRNAs and 344 mRNAs with differential expression in NSCLC tumor tissues compared to adjacent normal tissues. Subsequently, 43,557 co-expressed lncRNA-mRNA pairs were identified, including 27 lncRNA-mRNA pairs in cis, 9 lncRNA-TF-mRNA networks, 34 lncRNA-mRNA pairs in trans, and 8701 lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) networks. Notably, these lncRNAs were found to be involved in immune-related pathways. Six significant transcripts, including NTF4, PTPRD-AS, ITGA11, HID1-AS1, RASGRF2-AS1, and TBX2-AS1, were identified within the ceRNA network and trans-regulation.

Conclusion

This study brings important insights into the regulatory roles of lncRNAs in NSCLC, providing a fresh perspective on lncRNA research in tumor biology.

Exploring the multifaceted role of RASGRP1 in disease: immune, neural, metabolic, and oncogenic perspectives

RAS guanyl releasing protein 1 (RASGRP1) is a guanine nucleotide exchange factor (GEF) characterized by the presence of a RAS superfamily GEF domain. It functions as a diacylglycerol (DAG)-regulated nucleotide exchange factor, specifically activating RAS through the exchange of bound GDP for GTP. Activation of RAS by RASGRP1 has a wide range of downstream effects at the cellular level. Thus, it is not surprising that many diseases are associated with RASGRP1 disorders. Here, we present an overview of the structure and function of RASGRP1, its crucial role in the development, expression, and regulation of immune cells, and its involvement in various signaling pathways. This review comprehensively explores the relationship between RASGRP1 and various diseases, elucidates the underlying molecular mechanisms of RASGRP1 in each disease, and identifies potential therapeutic targets. This study provides novel insights into the role of RASGRP1 in insulin secretion and highlights its potential as a therapeutic target for diabetes. The limitations and challenges associated with studying RASGRP1 in disease are also discussed.

Long non-coding RNA MEG3 acts as a suppressor in breast cancer by regulating miR-330/CNN1

BACKGROUND

The current study aimed to investigate the molecular mechanism of long non-coding RNA (lncRNA) MEG3 in the development of breast cancer.

METHODS

The regulating relationships among lncRNA MEG3, miRNA-330 and CNN1 were predicted by bioinformatics analysis of breast cancer samples in the Cancer Genome Atlas database. The differential expression of lncRNA MEG3, miRNA-330 and CNN1 was first validated in breast cancer tissues and cells. The effects of lncRNA MEG3 on breast cancer malignant properties were evaluated by manipulating its expression in MCF-7 and BT-474 cells. Rescue experiments, dual-luciferase assays, and RNA immunoprecipitation (RIP) experiments were further used to validate the relationships among lncRNA MEG3, miRNA-330 and CNN1.

RESULTS

Bioinformatics analysis showed that lncRNA MEGs and CNN1 were significantly downregulated in breast cancer tissues, while miR-330 was upregulated. These differential expressions were further validated in our cohort of breast cancer samples. High expression levels of lncRNA MEG3 and CNN1 as well as low expression of miR-330 were significantly associated with favorable overall survival. Overexpression of lncRNA MEG3 significantly inhibited cell viability, migration and invasion, decreased cells in S stage and promoted cell apoptosis. Dual-luciferase reporter gene assay and RIP experiments showed that lncRNA MEG3 could directly bind to miR-330. Moreover, miR-330 mimics on the basis of lncRNA MEG3 overexpression ameliorated the tumor-suppressing effects of lncRNA MEG3 in breast cancer malignant properties by decreasing CNN1 expression.

CONCLUSION

Our study indicated lncRNA MEG3 is a breast cancer suppressor by regulating miR-330/CNN1 axis.

lncRNA-microRNA axis in cancer drug resistance: particular focus on signaling pathways

Cancer drug resistance remains a formidable challenge in modern oncology, necessitating innovative therapeutic strategies. The convergence of intricate regulatory networks involving long non-coding RNAs, microRNAs, and pivotal signaling pathways has emerged as a crucial determinant of drug resistance. This review underscores the multifaceted roles of lncRNAs and miRNAs in orchestrating gene expression and cellular processes, mainly focusing on their interactions with specific signaling pathways. Dysregulation of these networks leads to the acquisition of drug resistance, dampening the efficacy of conventional treatments. The review highlights the potential therapeutic avenues unlocked by targeting these non-coding RNAs. Developing specific inhibitors or mimics for lncRNAs and miRNAs, alone or in combination with conventional chemotherapy, emerges as a promising strategy. In addition, epigenetic modulators, immunotherapies, and personalized medicine present exciting prospects in tackling drug resistance. While substantial progress has been made, challenges, including target validation and safety assessment, remain. The review emphasizes the need for continued research to overcome these hurdles and underscores the transformative potential of lncRNA-miRNA interplay in revolutionizing cancer therapy.

Optimized cell type signatures revealed from single-cell data by combining principal feature analysis, mutual information, and machine learning

Machine learning techniques are excellent to analyze expression data from single cells. These techniques impact all fields ranging from cell annotation and clustering to signature identification. The presented framework evaluates gene selection sets how far they optimally separate defined phenotypes or cell groups. This innovation overcomes the present limitation to objectively and correctly identify a small gene set of high information content regarding separating phenotypes for which corresponding code scripts are provided. The small but meaningful subset of the original genes (or feature space) facilitates human interpretability of the differences of the phenotypes including those found by machine learning results and may even turn correlations between genes and phenotypes into a causal explanation. For the feature selection task, the principal feature analysis is utilized which reduces redundant information while selecting genes that carry the information for separating the phenotypes. In this context, the presented framework shows explainability of unsupervised learning as it reveals cell-type specific signatures. Apart from a Seurat preprocessing tool and the PFA script, the pipeline uses mutual information to balance accuracy and size of the gene set if desired. A validation part to evaluate the gene selection for their information content regarding the separation of the phenotypes is provided as well, binary and multiclass classification of 3 or 4 groups are studied. Results from different single-cell data are presented. In each, only about ten out of more than 30000 genes are identified as carrying the relevant information. The code is provided in a GitHub repository at https://github.com/AC-PHD/Seurat_PFA_pipeline.

A Novel Inflammatory Response-Related Gene Signature Predicts Immune Status and Prognosis of Breast Cancer

PURPOSE

Breast cancer is the most common type of cancer and the leading cause of cancer-related death in women worldwide. In this study, we aimed to construct an inflammatory response-related gene model for predicting the immune status and prognosis of breast cancer patients.

METHODS

We obtained the inflammatory response-related genes from the Molecular Signatures Database. Furthermore, we used univariate Cox regression analysis, the least absolute shrinkage and selection operator (LASSO) regression analysis, and multivariate Cox regression to construct an inflammatory response-related gene signature (IRGS) model based on dataset obtained from The Cancer Genome Atlas (TCGA). Patients were consequently categorized into high-risk and low-risk groups. Kaplan-Meier analysis was used to compare the overall survival (OS) of high-risk and low-risk groups. Following that, we validated the model using a dataset (GSE96058) acquired from Gene Expression Omnibus (GEO) database. Univariate and multivariate Cox analyses were used to determine the independent prognostic value of the IRGS in the TCGA and GSE96058 cohorts. A nomogram was constructed to predict the OS in the TCGA cohort. Further, we used Gene Set Enrichment Analysis (GSEA), CIBERSORT, and single-sample Gene Set Enrichment Analysis (ssGSEA) to evaluate the associations of IRGS with immune-associated pathways and immune infiltration. Finally, the relationship between the expression of the signature genes and drug sensitivity was conducted using Pearson correlation analysis.

RESULTS

We established an IRGS to stratify breast cancer patients into the low-risk and high-risk groups. In both the training and validation sets, patients in the high-risk group had significantly shorter OS than those in the low-risk group. The risk score was significantly correlated with the clinical characteristics and could be used as a tool to predict the prognosis of breast cancer. Moreover, we found that the IRGS risk score was an independent predictor of OS in breast cancer patients, and a nomogram model based on IRGS risk score and other clinical factors could effectively predict the prognosis of breast cancer patients. Furthermore, the IRGS risk score was correlated with immune characteristics and was inversely associated with the abundance of immune cell infiltration. Patients with a low IRGS risk score had higher expression levels of immune checkpoint genes, suggesting that IRGS can be used as a potential indicator for immunotherapy. Finally, we found that the expression levels of prognostic genes were significantly correlated with tumor cell sensitivity to chemotherapeutic drugs.

CONCLUSION

Overall, these findings suggest that the IRGS can be used to predict the prognosis and immune status of breast cancer patients and provide new therapeutic targets for the treatment of these patients.

Comprehensive analysis of lncRNA-mRNAs co-expression network identifies potential lncRNA biomarkers in cutaneous squamous cell carcinoma

Background

Cutaneous squamous cell carcinoma (cSCC) is the second most common type of skin cancer, the prognosis for patients with metastatic cSCC remains relatively poor. Thus, there is an urgent need to identify new diagnostic, prognostic, and therapeutic targets and pathways in cSCC.

Results

It detected a total of 37,507 lncRNA probes and 32,825 mRNA probes and found 3593 differentially expressed lncRNAs and 3236 differentially expressed mRNAs. It has been found that mRNAs ACY3, NR1D1, MZB1 has co-expression relationship with six lncRNAs, GXYLT1P3, LINC00348, LOC101928131, A-33-p3340852, A-21-p0003442 and LOC644838.

Conclusions

The aim of this study is to identify cSCC-specific lncRNAs and indicated that six unstudied lncRNAs may serve an important role in endoplasmic reticulum stress apoptosis, autophagy and the progression of cSCC by modulating ACY3, NR1D1 and MZB1.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08481-0.

What is beyond LncRNAs in breast cancer: A special focus on colon cancer-associated Transcript-1 (CCAT-1)

Long non-coding RNAs (LncRNAs) play a vital role in the process of malignant transformation. In breast cancer (BC), lncRNAs field is currently under intensive investigations. Yet, the role of lncRNAs as promising diagnostic and/or prognostic biomarkers and as therapeutic target/tool among BC patients still needs a special focus from the biomedical scientists. In BC, triple negative breast cancer patients (TNBC) are the unlucky group as they are always represented with the worst prognosis and the highest mortality rates. For that reason, a special focus on TNBC and associated lncRNAs was addressed in this review. Colon cancer-associated transcript 1 (CCAT-1) is a newly discovered oncogenic lncRNA that has been emerged as a vital biomarker for diagnosis, prognosis and therapeutic interventions in multiple malignancies and showed differential expression among TNBC patients. In this review, the authors shed the light onto the general role of lncRNAs in BC and the specific functional activities, molecular mechanisms, competing endogenous ncRNA role of CCAT-1 in TNBC.

Uncovering the roles of microRNAs/lncRNAs in characterising breast cancer subtypes and prognosis

Background

Accurate prognosis and identification of cancer subtypes at molecular level are important steps towards effective and personalised treatments of breast cancer. To this end, many computational methods have been developed to use gene (mRNA) expression data for breast cancer subtyping and prognosis. Meanwhile, microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) have been extensively studied in the last 2 decades and their associations with breast cancer subtypes and prognosis have been evidenced. However, it is not clear whether using miRNA and/or lncRNA expression data helps improve the performance of gene expression based subtyping and prognosis methods, and this raises challenges as to how and when to use these data and methods in practice.

Results

In this paper, we conduct a comparative study of 35 methods, including 12 breast cancer subtyping methods and 23 breast cancer prognosis methods, on a collection of 19 independent breast cancer datasets. We aim to uncover the roles of miRNAs and lncRNAs in breast cancer subtyping and prognosis from the systematic comparison. In addition, we created an R package, CancerSubtypesPrognosis, including all the 35 methods to facilitate the reproducibility of the methods and streamline the evaluation.

Conclusions

The experimental results show that integrating miRNA expression data helps improve the performance of the mRNA-based cancer subtyping methods. However, miRNA signatures are not as good as mRNA signatures for breast cancer prognosis. In general, lncRNA expression data does not help improve the mRNA-based methods in both cancer subtyping and cancer prognosis. These results suggest that the prognostic roles of miRNA/lncRNA signatures in the improvement of breast cancer prognosis needs to be further verified.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04215-3.

Identification of Prognostic Biomarkers and Correlation With Immune Infiltrates in Hepatocellular Carcinoma Based on a Competing Endogenous RNA Network

Background

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Recently, competing endogenous RNAs (ceRNA) have revealed a significant role in the progression of HCC. Herein, we aimed to construct a ceRNA network to identify potential biomarkers and illustrate its correlation with immune infiltration in HCC.

Methods

RNA sequencing data and clinical traits of HCC patients were downloaded from TCGA. The limma R package was used to identify differentially expressed (DE) RNAs. The predicted prognostic model was established using univariate and multivariate Cox regression. A K-M curve, TISIDB and GEPIA website were utilized for survival analysis. Functional annotation was determined using Enrichr and Reactome. Protein-to-protein network analysis was implemented using SRTNG and Cytoscape. Hub gene expression was validated by quantitative polymerase chain reaction, Oncomine and the Hunan Protein Atlas database. Immune infiltration was analyzed by TIMMER, and Drugbank was exploited to identify bioactive compounds.

Results

The predicted model that was established revealed significant efficacy with 3- and 5-years of the area under ROC at 0.804 and 0.744, respectively. Eleven DEmiRNAs were screened out by a K-M survival analysis. Then, we constructed a ceRNA network, including 56 DElncRNAs, 6 DEmiRNAs, and 28 DEmRNAs. The 28 DEmRNAs were enriched in cancer-related pathways, for example, the TNF signaling pathway. Moreover, six hub genes, CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1, were all overexpressed in HCC tissues and independently correlated with survival rate. Furthermore, expression of hub genes was related to immune cell infiltration in HCC, including B cells, CD8⁺ T cells, CD4⁺ T cells, monocytes, macrophages, neutrophils, and dendritic cells.

Conclusion

The findings from this study demonstrate that CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1 are closely associated with prognosis and immune infiltration, representing potential therapeutic targets or prognostic biomarkers in HCC.

Identification of crucial long non-coding RNAs and mRNAs along with related regulatory networks through microarray analysis in esophageal carcinoma

Esophageal carcinoma (EC) is a tremendous threat to human health and life worldwide. Long non-coding RNAs (lncRNAs) have been identified as crucial players in carcinomas including EC. An in-depth understanding on regulatory networks of lncRNAs contributes to the better management of EC. In this text, 2052 lncRNAs and 3240 mRNAs were found to be differentially expressed in 5 EC tumor tissues versus adjacent normal tissues by microarray analysis. Moreover, 297 carcinoma-related genes were screened out according to pathway and disease annotation analyses. In addition, 410 potential lncRNA-mRNA cis-regulation pairs and 395 lncRNA-mRNA trans-regulation pairs were screened out. Among these genes, 14 trans-regulated and 19 cis-regulated genes were found to be related with carcinomas. Additionally, 42 possible lncRNA-mRNA trans-regulation pairs and 26 cis-regulation pairs were found to be related with carcinomas. Also, 4 differentially expressed transcription factors in EC and lncRNAs possibly regulated by these transcription factors were screened out. Moreover, plenty of common upregulated or downregulated lncRNAs and mRNAs in EC were identified by comparative analysis for our microarray outcomes and previous high-throughput data. Furthermore, we demonstrated that ENST00000437781.1 knockdown inhibited cell proliferation and facilitated cell apoptosis by downregulating SIX homeobox 4 (SIX4) and ENST00000524987.1 knockdown had no influence on anoctamin 1 calcium activated chloride channel (ANO1) expression in EC cells. In conclusion, we identified some crucial lncRNAs and genes along with potential regulatory networks of lncRNAs/genes, deepening our understanding on pathogenesis of EC.

Integrated analysis of lncRNA-miRNA-mRNA ceRNA network and the potential prognosis indicators in sarcomas

BACKGROUND

Competitive endogenous RNA (ceRNA) networks have revealed a new mechanism of interaction between RNAs, and play crucial roles in multiple biological processes and development of neoplasms. They might serve as diagnostic and prognosis markers as well as therapeutic targets.

METHODS

In this work, we identified differentially expressed mRNAs (DEGs), lncRNAs (DELs) and miRNAs (DEMs) in sarcomas by comparing the gene expression profiles between sarcoma and normal muscle samples in Gene Expression Omnibus (GEO) datasets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses were applied to investigate the primary functions of the overlapped DEGs. Then, lncRNA-miRNA and miRNA-mRNA interactions were predicted, and the ceRNA regulatory network was constructed using Cytoscape software. In addition, the protein-protein interaction (PPI) network and survival analysis were performed.

RESULTS

A total of 1296 DEGs were identified in sarcoma samples by combining the GO and KEGG enrichment analyses, 338 DELs were discovered after the probes were reannotated, and 36 DEMs were ascertained through intersecting two different expression miRNAs sets. Further, through target gene prediction, a lncRNA-miRNA-mRNA ceRNA network that contained 113 mRNAs, 69 lncRNAs and 29 miRNAs was constructed. The PPI network identified the six most significant hub proteins. Survival analysis revealed that seven mRNAs, four miRNAs and one lncRNA were associated with overall survival of sarcoma patients.

CONCLUSIONS

Overall, we constructed a ceRNA network in sarcomas, which might provide insights for further research on the molecular mechanism and potential prognosis biomarkers.

LINC00466 Impacts Cell Proliferation, Metastasis and Sensitivity to Temozolomide of Glioma by Sponging miR-137 to Regulate PPP1R14B Expression

Purpose

LINC00466 is a newfound long non-coding RNA (lncRNA) that has been rarely explored in cancers. However, the specific role and molecular mechanism of LINC00466 in glioma remain to be further elucidated.

Methods

Bioinformatic analysis was used to screen differentially expressed genes. Quantitative real-time PCR (qRT-PCR) was used to determine the expression of LINC00466, microRNA-137 (miR-137) and protein phosphatase 1 regulatory subunit 14B (PPP1R14B). Dual-luciferase reporter gene assay and RNA binding protein Immunoprecipitation (RIP) assays were employed to verify the binding relationship among LINC00466, miR-137 and PPP1R14B. The sensitivity of glioma cells to temozolomide (TMZ) was measured by cell counting kit-8 (CCK8) assay. The xenograft nude models were used to test the effects of LINC00466 on glioma tumor growth in vivo.

Results

Highly expressed LINC00466 and PPP1R14B and lowly expressed miR-137 were eventually revealed in glioma tissues. Overexpression of LINC00466 could promote proliferation, metastasis and drug sensitivity to TMZ of glioma cells. LINC00466 could bind to miR-137, and up-regulation of miR-137 could attenuate the enhancing effects caused by LINC00466 overexpression. We took a further step and found that miR-137 could bind to PPP1R14B. Besides, LINC00466 could function as a sponge to miR-137 to regulate PPP1R14B. In addition, overexpression of LINC00466 could promote tumor growth in vivo.

Conclusion

These findings validate LINC00466 could restrain the miR-137 expression to up-regulate PPP1R14B and therefore promote proliferation, metastasis and resistance to TMZ of glioma.

Comprehensive analysis of ceRNA network related to lincRNA in glioblastoma and prediction of clinical prognosis

BACKGROUND

Long intergenic non-coding RNAs (lincRNAs) are capable of regulating several tumours, while competitive endogenous RNA (ceRNA) networks are of great significance in revealing the biological mechanism of tumours. Here, we aimed to study the ceRNA network of lincRNA in glioblastoma (GBM).

METHODS

We obtained GBM and normal brain tissue samples from TCGA, GTEx, and GEO databases, and performed weighted gene co-expression network analysis and differential expression analysis on all lincRNA and mRNA data. Subsequently, we predicted the interaction between lincRNAs, miRNAs, and target mRNAs. Univariate and multivariate Cox regression analyses were performed on the mRNAs using CGGA data, and a Cox proportional hazards regression model was constructed. The ceRNA network was further screened by the DEmiRNA and mRNA of Cox model.

RESULTS

A prognostic prediction model was constructed for patients with GBM. We assembled a ceRNA network consisting of 18 lincRNAs, 6 miRNAs, and 8 mRNAs. Gene Set Enrichment Analysis was carried out on four lincRNAs with obvious differential expressions and relatively few studies in GBM.

CONCLUSION

We identified four lincRNAs that have research value for GBM and obtained the ceRNA network. Our research is expected to facilitate in-depth understanding and study of the molecular mechanism of GBM, and provide new insights into targeted therapy and prognosis of the tumour.

KPNA2-Associated Immune Analyses Highlight the Dysregulation and Prognostic Effects of GRB2, NRAS, and Their RNA-Binding Proteins in Hepatocellular Carcinoma

Karyopherin α2 (KPNA2) was reported to be overexpressed and have unfavorable prognostic effects in many malignancies including hepatocellular carcinoma (HCC). Although its contributions to inflammatory response were reported in many studies, its specific associations with immune infiltrations and immune pathways during cancer progression were unclear. Here, we aimed to identify new markers for HCC diagnosis and prognosis through KPNA2-associated immune analyses. RNA-seq expression data of HCC datasets were downloaded from The Cancer Genome Atlas and International Cancer Genome Consortium. The gene expressions were counts per million normalized. The infiltrations of 24 kinds of immune cells in the samples were evaluated with ImmuCellAI (Immune Cell Abundance Identifier). The Spearman correlations of the immune infiltrations with KPNA2 expression were investigated, and the specific positive correlation of B-cell infiltration with KPNA2 expression in HCC tumors was identified. Fifteen genes in KEGG (Kyoto Encyclopedia of Genes and Genomes) B-cell receptor signaling pathway presented significant correlations with KPNA2 expression in HCC. Among them, GRB2 and NRAS were indicated to be independent unfavorable prognostic factors for HCC overall survival. Clinical Proteomic Tumor Analysis Consortium HCC dataset was investigated to validate the results at protein level. The upregulation and unfavorable prognostic effects of KPNA2 and GRB2 were confirmed, whereas, unlike its mRNA form, NRAS protein was presented to be downregulated and have favorable prognostic effects. Through receiver operating characteristic curve analysis, the diagnostic potential of the three proteins was shown. The RNA-binding proteins (RBPs) of KPNA2, NRAS, and GRB2, downloaded via The Encyclopedia of RNA Interactomes, were investigated for their clinical significance in HCC at protein level. An eight-RBP signature with independent prognostic value and dysregulations in HCC was identified. All the RBPs were significantly correlated with MKI67 expression and at least one of KPNA2, GRB2, and NRAS at protein level in HCC, indicating their roles in HCC progression and the regulation of the three proteins. We concluded that KPNA2, GRB2, NRAS, and their RBPs might have coordinating roles in HCC immunoregulation and progression. They might be new markers for HCC diagnosis and prognosis predication and new targets for HCC immunotherapy.

Long intergenic non‑coding RNA LINC01232 contributes to esophageal squamous cell carcinoma progression by sequestering microRNA‑654‑3p and consequently promoting hepatoma‑derived growth factor expression

Long intergenic non-coding RNA 01232 (LINC01232) was identified as a critical regulator of the development of pancreatic adenocarcinoma. The present study investigated the expression and regulatory roles of LINC01232 in esophageal squamous cell carcinoma (ESCC). The main aim of the present study was to elucidate the underlying mechanisms through which LINC01232 affects the malignancy of ESCC. Initially, LINC01232 expression in ESCC was analyzed using the TCGA and GTEx databases and was confirmed using reverse transcription-quantitative polymerase chain reaction. ESCC cell proliferation, apoptosis and migration and invasion were assessed using the Cell Counting kit-8 assay, flow cytometric analysis, and migration and invasion assays, respectively. ESCC tumor growth in vivo was examined using a xenograft mouse model. As shown by the results, a high LINC01232 expression was detected in ESCC tissues and cell lines. LINC01232 downregulation suppressed the proliferation, migration and invasion of ESCC cells, and promoted cell apoptosis in vitro. In addition, LINC01232 depletion restricted tumor growth in vivo. Mechanistically, LINC01232 was shown to function as an microRNA-654-3p (miR-654-3p) sponge in ESCC cells, and hepatoma-derived growth factor (HDGF) was identified as a direct target of miR-654-3p. LINC01232 could bind competitively to miR-654-3p and decrease its expression in ESCC cells, thereby promoting HDGF expression. Rescue experiments reconfirmed that the effects of LINC01232 deficiency in ESCC cells were restored by increasing the output of the miR-654-3p/HDGF axis. On the whole, the present study demonstrates that LINC01232 plays a tumor-promoting role during the progression of ESCC by regulating the miR-654-3p/HDGF axis. The LINC01232/miR-654-3p/HDGF pathway may thus provide a novel theoretical basis for the management of ESCC.

Clinicopathological association and prognostic value of long non-coding RNA CASC9 in patients with cancer: A meta-analysis

Several studies have reported a prognostic role of the long non-coding RNA (lncRNA) cancer susceptibility candidate 9 (CASC9) in various cancer types, but its clinical significance has remained inconclusive. The aim of the present meta-analysis was to evaluate the impact of CASC9 expression on the prognosis and clinicopathological features of patients with cancer patients. The PubMed, Embase, Cochrane Library and Web of Science databases were searched for relevant literature and eight studies, including 565 patients with cancer, were selected. The quality of these studies was appraised with the Newcastle-Ottawa Scale (NOS) and the association between CASC9 expression and prognosis or clinicopathological features was analyzed. Patients with high expression levels of CASC9 in their tumor tissues had a lower overall survival rate compared with those in the low CASC9 expression group (hazard ratio=2.25, 95% CI: 1.60-3.17, P<0.001). Furthermore, elevated CASC9 expression was significantly associated with deeper tumor invasion [odds ratio (OR)=2.66, 95% CI: 1.72-4.14, P<0.001], poor tumor differentiation (OR=2.44, 95% CI: 1.24-4.78, P=0.009), lymph node metastasis (OR=3.42, 95% CI: 1.98-5.92, P<0.001) and advanced clinical stage (OR=3.21, 95% CI: 2.21-4.66, P<0.001). In conclusion, CASC9 is a promising biomarker for predicting the prognosis of cancer patients and should be validated in the clinic.

lncRNA RASSF8‑AS1 suppresses the progression of laryngeal squamous cell carcinoma via targeting the miR‑664b‑3p/TLE1 axis

Long non‑coding (lnc)RNAs have been found to play a crucial role in tumor progression. The present study aimed to investigate the association between lncRNA RASSF8‑AS1 and laryngeal squamous cell carcinoma (LSCC) and the underlying mechanisms. Reverse transcription‑quantitative PCR was used to measure the mRNA expression level of RASSF8‑AS1, microRNA(miR)‑664b‑3p and transducin‑like enhancer of split 1 (TLE1) in LSCC. The associations between RASSF8‑AS1 and miR‑664b‑3p, and between miR‑664b‑3p and TLE1 were investigated using a dual luciferase reporter assay, while the former was further verified using an RNA immunoprecipitation (RIP) assay. The association between RASSF8‑AS1 and miR‑664b‑3p on cell biological functions was investigated in vitro using MTS, colony formation and Transwell assays. The RASSF8‑AS1 mRNA expression level was decreased in LSCC cell lines and carcinoma tissues, while overexpression of RASSF8‑AS1 reduced the migration, invasion and proliferation abilities of LSCC cells. Furthermore, luciferase and RIP assays confirmed that RASSF8‑AS1 was a competitive endogenous (ce)RNA by sponging miR‑664b‑3p to activate TLE1. miR‑664b‑3p was negatively modulated by RASSF8‑AS1; however, TLE1 was positively regulated by RASSF8‑AS1. Functionally, RASSF8‑AS1 acted as a ceRNA to upregulate TLE1 by sponging miR‑664b‑3p. In conclusion, the RASSF8‑AS1/miR‑664b‑3p/TLE1 axis acts by suppressing LSCC progression and may provide a novel insight for the molecular mechanism of LSCC.

Long non-coding RNA ADAMTS9-AS1 exacerbates cell proliferation, migration, and invasion via triggering of the PI3K/AKT/mTOR pathway in hepatocellular carcinoma cells

Although many long non-coding RNAs (lncRNAs) are modulators of biological events in hepatocellular carcinoma (HCC), the potential significance of most lncRNAs in HCC remains to be fully understood. The role of lncRNA ADAMTS9-AS1 in HCC was therefore determined. ADAMTS9-AS1 expression was higher in HCC cell lines compared to normal cells as determined by qPCR analyses. Furthermore, CCK-8, scratch wound healing, transwell migration, and invasion assays suggested that ADAMTS9-AS1 overexpression promoted the proliferation, migration, and invasion in MHCC97-H and HepG2 cells; ADAMTS9-AS1 knockdown showed the opposite results. Based on the results from GEO, the correlation between ADAMTS9-AS1 and PI3K/AKT/mTOR was identified. Thus, an association between ADAMTS9-AS1 and the PI3K/AKT/mTOR signaling pathway was further observed. To confirm the pathway protein levels, p-AKT, PIK3CB, and p-mTOR were selected. Western blot assays suggested that ADAMTS9-AS1 enhanced the expression levels of the three proteins. Because of their close relationship with PI3K/AKT/mTOR, apoptosis- or autophagy-related proteins were further investigated. ADAMTS9-AS1 expression was negatively related with LC3-II, BECN1, and pro-apoptotic Bax, whereas it was positively correlated SQSTM1 and anti-apoptotic Bcl-2 expression. Western blot results suggested that ADAMTS9-AS1 decreased ADAMTS9 expression. Our data revealed that ADAMTS9-AS1 contributed to proliferation, migration, and invasion in HCC cells, likely due to the activation of the PI3K/AKT/mTOR signaling pathway, to influence autophagy and apoptosis. These findings suggest that ADAMTS9-AS1 could serve as a molecular target in HCC treatment.

Analyses of DNA Methylation Involved in the Activation of Nuclear Karyopherin Alpha 2 Leading to Identify the Progression and Prognostic Significance Across Human Breast Cancer

Background

Karyopherin alpha 2 (KPNA2) is a nuclear import factor that plays a crucial role in nucleocytoplasmic transport, as well as cell proliferation, migration, and invasion in several cancers. However, the roles of KPNA2 in breast cancer as well as the underlying molecular mechanisms have not been elucidated.

Materials and Methods

To evaluate gene expression alterations during breast carcinogenesis, KPNA2 expression was analyzed using the Gene Expression Profiling Interactive Analysis and Oncomine analyses. The correlation between methylation and expression was analyzed using the MEXPRESS tool, UALCAN cancer database, and cBioPortal browser. Then, the expression and prognostic value of KPNA2 were investigated by our own breast cancer samples using RT-PCR. KPNA2 methylation level was detected by methylation-specific PCR.

Results

We obtained the following important results. (1) KPNA2 expression was significantly higher in breast cancer than normal samples and regulated by aberrant DNA hypomethylation of promoter region. (2) Among patients with breast cancer, those with higher KPNA2 expression had a lower survival rate. (3) The major mutation type of KPNA2 in breast cancer samples was missense mutation. (4) Homer1 was able to promote breast cancer progression may be through upregulating TPX2 expression.

Conclusion

Our findings suggest that aberrant DNA hypomethylation of promoter regions contributes to the aberrant expression of KPNA2 in breast cancer, which might be a potential indicator of poor prognosis.

Long noncoding RNA OSER1‑AS1 promotes the malignant properties of non‑small cell lung cancer by sponging microRNA‑433‑3p and thereby increasing Smad2 expression

OSER1 antisense RNA 1 (OSER1-AS1), a long noncoding RNA, has been well studied in the context of hepatocellular carcinoma. However, its expression status, specific functions, and tumorigenic mechanism in non-small cell lung cancer (NSCLC) remain uninvestigated. Hence, this study aimed to assess OSER1-AS1 expression, test the malignancy-related biological functions of OSER1-AS1, and illustrate how they affect NSCLC progression. OSER1-AS1 expression in NSCLC was measured by reverse transcription-quantitative polymerase chain reaction. Cell Counting Kit-8 assay, flow cytometry, cell migration and invasion assay, and tumor xenograft assay were performed to analyze the effects of OSER1-AS1 on the malignant phenotypes of NSCLC cells. Bioinformatics prediction with luciferase reporter and RNA immunoprecipitation assays were performed to determine the interaction between OSER1-AS1 and microRNA-433-3p (miR-433-3p). OSER1-AS1 was strongly expressed in NSCLC tissues and cell lines. Enhanced OSER1-AS1 expression was significantly correlated with tumor size, TNM stage, and lymph node metastasis in patients with NSCLC. Patients with NSCLC exhibiting high OSER1-AS1 expression had shorter overall survival than those exhibiting low OSER1-AS1 expression. Functionally, a reduction in OSER1-AS1 expression led to significant decreases in NSCLC cell proliferation, migration, and invasion as well as an increase in cell apoptosis in vivo. OSER1-AS1 knockdown suppressed the tumorigenic ability of NSCLC cells in vivo. Mechanistically, OSER1-AS1 acts as a competing endogenous RNA (ceRNA) in NSCLC cells by sponging miR-433-3p and thereby increasing the expression of mothers against decapentaplegic homolog 2 (Smad2). Finally, restoration experiments revealed that the suppression of miR-433-3p and restoration of Smad2 both counteracted the suppressive effects of OSER1-AS1 depletion in NSCLC cells. Our findings illustrate the biological importance of the OSER1-AS1/miR-433-3p/Smad2 pathway in NSCLC progression and offer a novel perspective regarding the identification of effective therapeutic and diagnostic targets.

Comprehensive biological function analysis of lncRNAs in hepatocellular carcinoma

Thousands of long non-coding RNAs (lncRNAs) have been discovered in human genomes by gene chip, next-generation sequencing, and/or other methods in recent years, which represent a significant subset of the universal genes involved in a wide range of biological functions. An abnormal expression of lncRNAs is associated with the growth, invasion, and metastasis of various types of human cancers, including hepatocellular carcinoma (HCC), which is an aggressive, highly malignant, and invasive tumor, and a poor prognosis in China. With a more in-depth understanding of lncRNA research for HCC and the emergence of new molecular-targeted therapies, the diagnosis, treatment, and prognosis of HCC will be considerably improved. Therefore, this review is expected to provide recommendations and directions for future lncRNA research for HCC.