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Agrawal A, Vindal V. Competing endogenous RNAs in head and neck squamous cell carcinoma: a review. Brief Funct Genomics 2024; 23:335-348. [PMID: 37941447 DOI: 10.1093/bfgp/elad049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 10/19/2023] [Accepted: 10/20/2023] [Indexed: 11/10/2023] Open
Abstract
Our understanding of RNA biology has evolved with recent advances in research from it being a non-functional product to molecules of the genome with specific regulatory functions. Competitive endogenous RNA (ceRNA), which has gained prominence over time as an essential part of post-transcriptional regulatory mechanism, is one such example. The ceRNA biology hypothesis states that coding RNA and non-coding RNA co-regulate each other using microRNA (miRNA) response elements. The ceRNA components include long non-coding RNAs, pseudogene and circular RNAs that exert their effect by interacting with miRNA and regulate the expression level of its target genes. Emerging evidence has revealed that the dysregulation of the ceRNA network is attributed to the pathogenesis of various cancers, including the head and neck squamous cell carcinoma (HNSCC). This is the most prevalent cancer developed from the mucosal epithelium in the lip, oral cavity, larynx and pharynx. Although many efforts have been made to comprehend the cause and subsequent treatment of HNSCC, the morbidity and mortality rate remains high. Hence, there is an urgent need to understand the holistic progression of HNSCC, mediated by ceRNA, that can have immense relevance in identifying novel biomarkers with a defined therapeutic intervention. In this review, we have made an effort to highlight the ceRNA biology hypothesis with a focus on its involvement in the progression of HNSCC. For the identification of such ceRNAs, we have additionally highlighted a number of databases and tools.
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Affiliation(s)
- Avantika Agrawal
- Department of Biotechnology & Bioinformatics, School of Life Sciences, University of Hyderabad, Hyderabad, Telangana 500046, India
| | - Vaibhav Vindal
- Department of Biotechnology & Bioinformatics, School of Life Sciences, University of Hyderabad, Hyderabad, Telangana 500046, India
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2
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Qi D, Li H, Wang S, Wang S, Zheng R, Liu N, Han B, Liu L. Construction of ceRNA network and key gene screening in cervical squamous intraepithelial lesions. Medicine (Baltimore) 2022; 101:e31928. [PMID: 36482542 PMCID: PMC9726336 DOI: 10.1097/md.0000000000031928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND This study aimed to construct an endogenous competition network for cervical squamous intraepithelial lesions using differential gene screening. METHODS GSE149763 was used to screen differentially expressed long non-coding RNAs (lncRNAs) and mRNAs to predict correlated microRNAs (miRNAs). The correlated miRNAs and GSE105409 were used to screen differentially expressed miRNAs for differential co-expression analysis, and the co-expressed differentially expressed miRNAs were used to predict correlated mRNAs. Differentially expressed mRNAs, miRNAs, and lncRNAs were visualized, and differential gene screening, enrichment, and pathway analysis were performed. RESULTS The ceRNA network of cervical squamous intraepithelial was successfully established and a potential differentially expressed network was identified. The key genes were VEGFA and FOS, and the key pathway was the MAPK signaling pathway. CONCLUSIONS The differential expression and potential effects of the lncRNA BACH1-IT1/miR-140-5p/VEGFA axis, key genes, VEGFA and FOS, and MAPK signaling in CIN were clarified, and the occurrence and potential effects of CIN were further clarified. The underlying molecular mechanism provides a certain degree of reference for subsequent treatments and experimental research.
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Affiliation(s)
- Ding Qi
- Heilongjiang University of Traditional Chinese Medicine, Heilongjiang, China
| | - Hongmei Li
- The 2nd Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, Heilongjiang, China
| | - Shuoqi Wang
- Heilongjiang University of Traditional Chinese Medicine, Heilongjiang, China
| | - Shimeng Wang
- Heilongjiang University of Traditional Chinese Medicine, Heilongjiang, China
| | - Rui Zheng
- Heilongjiang University of Traditional Chinese Medicine, Heilongjiang, China
| | - Ning Liu
- Heilongjiang University of Traditional Chinese Medicine, Heilongjiang, China
| | - Buwei Han
- Heilongjiang University of Traditional Chinese Medicine, Heilongjiang, China
| | - Li Liu
- The 1st Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, Heilongjiang, China
- * Correspondence: Li Liu, Department of Gynecology, The 1st Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, Harbin, Heilongjiang 150036, China (e-mail: )
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Construction of lncRNA TYMSOS/hsa-miR-101-3p/CEP55 and TYMSOS/hsa-miR-195-5p/CHEK1 Axis in Non-small Cell Lung Cancer. Biochem Genet 2022; 61:995-1014. [DOI: 10.1007/s10528-022-10299-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 10/21/2022] [Indexed: 11/10/2022]
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4
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Zhang J, Liu L, Zhang W, Li X, Zhao C, Li S, Li J, Le TD. miRspongeR 2.0: an enhanced R package for exploring miRNA sponge regulation. BIOINFORMATICS ADVANCES 2022; 2:vbac063. [PMID: 36699386 PMCID: PMC9710667 DOI: 10.1093/bioadv/vbac063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 08/24/2022] [Accepted: 09/01/2022] [Indexed: 02/01/2023]
Abstract
Summary MicroRNA (miRNA) sponges influence the capability of miRNA-mediated gene silencing by competing for shared miRNA response elements and play significant roles in many physiological and pathological processes. It has been proved that computational or dry-lab approaches are useful to guide wet-lab experiments for uncovering miRNA sponge regulation. However, all of the existing tools only allow the analysis of miRNA sponge regulation regarding a group of samples, rather than the miRNA sponge regulation unique to individual samples. Furthermore, most existing tools do not allow parallel computing for the fast identification of miRNA sponge regulation. Here, we present an enhanced version of our R/Bioconductor package, miRspongeR 2.0. Compared with the original version introduced in 2019, this package extends the resolution of miRNA sponge regulation from the multi-sample level to the single-sample level. Moreover, it supports the identification of miRNA sponge networks using parallel computing, and the construction of sample-sample correlation networks. It also provides more computational methods to infer miRNA sponge regulation and expands the ground truth for validation. With these new features, we anticipate that miRspongeR 2.0 will further accelerate the research on miRNA sponges with higher resolution and more utilities. Availability and implementation http://bioconductor.org/packages/miRspongeR/. Supplementary information Supplementary data are available at Bioinformatics Advances online.
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Affiliation(s)
| | - Lin Liu
- UniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia
| | - Wu Zhang
- Department of Molecular Biology, School of Agriculture and Biological Sciences, Dali University, Dali 671003, China
| | - Xiaomei Li
- UniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia
| | - Chunwen Zhao
- Department of Information and Electronic Engineering, School of Engineering, Dali University, Dali 671003, China
| | - Sijing Li
- Department of Information and Electronic Engineering, School of Engineering, Dali University, Dali 671003, China
| | - Jiuyong Li
- UniSA STEM, University of South Australia, Mawson Lakes, SA 5095, Australia
| | - Thuc Duy Le
- To whom correspondence should be addressed. or
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5
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Tanuj GN, Khan O, Malla WA, Rajak KK, Chandrashekar S, Kumar A, Dhara S, Gupta PK, Mishra BP, Dutt T, Gandham R, Sajjanar B. Integrated analysis of long-noncoding RNA and circular RNA expression in Peste-des-Petits-Ruminants Virus (PPRV) infected marmoset B lymphocyte (B95a) cells. Microb Pathog 2022; 170:105702. [DOI: 10.1016/j.micpath.2022.105702] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 06/26/2022] [Accepted: 07/31/2022] [Indexed: 10/15/2022]
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6
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Song Y, Li J, Mao Y, Zhang X. ceRNAshiny: An Interactive R/Shiny App for Identification and Analysis of ceRNA Regulation. Front Mol Biosci 2022; 9:865408. [PMID: 35647026 PMCID: PMC9136144 DOI: 10.3389/fmolb.2022.865408] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 04/13/2022] [Indexed: 12/13/2022] Open
Abstract
The competing endogenous RNA (ceRNA) network is a newly discovered post-transcriptional regulation that controls both physiological and pathological progresses. Increasing research studies have been pivoted on this theory to explore the function of novel non-coding RNAs, pseudogenes, circular RNAs, and messenger RNAs. Although there are several R packages or computational tools to analyze ceRNA networks, an urgent need for easy-to-use computational tools still remains to identify ceRNA regulation. Besides, the conventional tools were mainly devoted to investigating ceRNAs in malignancies instead of those in neurodegenerative diseases. To fill this gap, we developed ceRNAshiny, an interactive R/Shiny application, which integrates widely used computational methods and databases to provide and visualize the construction and analysis of the ceRNA network, including differential gene analysis and functional annotation. In addition, demo data in ceRNAshiny could provide ceRNA network analyses about neurodegenerative diseases such as Parkinson's disease. Overall, ceRNAshiny is a user-friendly application that benefits all researchers, especially those who lack an established bioinformatic pipeline and are interested in studying ceRNA networks.
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Affiliation(s)
- Yueqiang Song
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Jia Li
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Yiming Mao
- Department of Thoracic Surgery, Suzhou Kowloon Hospital, School of Medicine, Shanghai Jiao Tong University, Suzhou, China
| | - Xi Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
- Department of Rehabilitation, Huashan Hospital, Fudan University, Shanghai, China
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Abstract
Most of the transcribed human genome codes for noncoding RNAs (ncRNAs), and long noncoding RNAs (lncRNAs) make for the lion's share of the human ncRNA space. Despite growing interest in lncRNAs, because there are so many of them, and because of their tissue specialization and, often, lower abundance, their catalog remains incomplete and there are multiple ongoing efforts to improve it. Consequently, the number of human lncRNA genes may be lower than 10,000 or higher than 200,000. A key open challenge for lncRNA research, now that so many lncRNA species have been identified, is the characterization of lncRNA function and the interpretation of the roles of genetic and epigenetic alterations at their loci. After all, the most important human genes to catalog and study are those that contribute to important cellular functions-that affect development or cell differentiation and whose dysregulation may play a role in the genesis and progression of human diseases. Multiple efforts have used screens based on RNA-mediated interference (RNAi), antisense oligonucleotide (ASO), and CRISPR screens to identify the consequences of lncRNA dysregulation and predict lncRNA function in select contexts, but these approaches have unresolved scalability and accuracy challenges. Instead-as was the case for better-studied ncRNAs in the past-researchers often focus on characterizing lncRNA interactions and investigating their effects on genes and pathways with known functions. Here, we focus most of our review on computational methods to identify lncRNA interactions and to predict the effects of their alterations and dysregulation on human disease pathways.
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Wang Y, Wei J, Chen T, Yang X, Zhao L, Wang M, Dou Y, Du Y, Ni R, Li T, Ma X. A Whole Transcriptome Analysis in Peripheral Blood Suggests That Energy Metabolism and Inflammation Are Involved in Major Depressive Disorder. Front Psychiatry 2022; 13:907034. [PMID: 35633815 PMCID: PMC9136012 DOI: 10.3389/fpsyt.2022.907034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 04/27/2022] [Indexed: 11/13/2022] Open
Abstract
INTRODUCTION Previous studies on transcriptional profiles suggested dysregulation of multiple RNA species in major depressive disorder (MDD). However, the interaction between different types of RNA was neglected. Therefore, integration of different RNA species in transcriptome analysis would be helpful for interpreting the functional readout of the transcriptome in MDD. METHODS A whole transcriptome sequencing were performed on the peripheral blood of 15 patients with MDD and 15 matched healthy controls (HCs). The differential expression of miRNAs, lncRNAs, circRNAs, and mRNAs was examined between MDD and HCs using empirical analysis of digital gene expression data in R (edgeR). Weighted correlation network analysis (WGCNA) was used to identify RNA co-expression modules associated with MDD. A ceRNA network was constructed for interpretation of interactions between different RNA species. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to explore potential biological mechanisms associated with MDD. RESULTS Multiple RNAs and co-expression modules were identified to be significantly dysregulated in MDD compared to HCs. Based on the differential RNAs, a ceRNA network that were dysregulated in MDD were constructed. The pathway networks that related to oxidative phosphorylation and the chemokine signaling were found to be associated with MDD. CONCLUSION Our results suggested that the processes of energy metabolism and inflammation may be involved in the pathophysiology of MDD.
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Affiliation(s)
- Yu Wang
- Psychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Jinxue Wei
- Psychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, China.,Sichuan Clinical Medical Research Center for Mental Disorders, Chengdu, China
| | - Ting Chen
- Psychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Xiao Yang
- Psychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Liansheng Zhao
- Psychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, China.,Sichuan Clinical Medical Research Center for Mental Disorders, Chengdu, China
| | - Min Wang
- Psychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Yikai Dou
- Psychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Yue Du
- Psychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Rongjun Ni
- Psychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Tao Li
- Psychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaohong Ma
- Psychiatric Laboratory and Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.,West China Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
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Liu TT, Li R, Huo C, Li JP, Yao J, Ji XL, Qu YQ. Identification of CDK2-Related Immune Forecast Model and ceRNA in Lung Adenocarcinoma, a Pan-Cancer Analysis. Front Cell Dev Biol 2021; 9:682002. [PMID: 34409029 PMCID: PMC8366777 DOI: 10.3389/fcell.2021.682002] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 07/06/2021] [Indexed: 12/12/2022] Open
Abstract
Background Tumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD). Methods “GEO2R,” “limma” R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. “Survival,” “survminer,” “rms” R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs. Results A total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = –0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By “survival ROC” R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05. Conclusion In conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.
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Affiliation(s)
- Ting-Ting Liu
- Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.,Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, China
| | - Rui Li
- Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.,Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, China
| | - Chen Huo
- Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.,Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, China
| | - Jian-Ping Li
- Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.,Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, China
| | - Jie Yao
- Department of Pulmonary and Critical Care Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.,Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, China
| | - Xiu-Li Ji
- Department of Pulmonary Disease, Jinan Traditional Chinese Medicine Hospital, Jinan, China
| | - Yi-Qing Qu
- Shandong Key Laboratory of Infectious Respiratory Diseases, Jinan, China.,Department of Respiratory and Critical Care Medicine, Qilu Hospital of Shandong University, Jinan, China
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CeNet Omnibus: an R/Shiny application to the construction and analysis of competing endogenous RNA network. BMC Bioinformatics 2021; 22:75. [PMID: 33602117 PMCID: PMC7890952 DOI: 10.1186/s12859-021-04012-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 02/08/2021] [Indexed: 01/01/2023] Open
Abstract
Background The competing endogenous RNA (ceRNA) regulation is a newly discovered post-transcriptional regulation mechanism and plays significant roles in physiological and pathological progress. CeRNA networks provide global views to help understand the regulation of ceRNAs. CeRNA networks have been widely used to detect survival biomarkers, select candidate regulators of disease genes, and predict long noncoding RNA functions. However, there is no software platform to provide overall functions from the construction to analysis of ceRNA networks. Results To fill this gap, we introduce CeNet Omnibus, an R/Shiny application, which provides a unified framework for the construction and analysis of ceRNA network. CeNet Omnibus enables users to select multiple measurements, such as Pearson correlation coefficient (PCC), mutual information (MI), and liquid association (LA), to identify ceRNA pairs and construct ceRNA networks. Furthermore, CeNet Omnibus provides a one-stop solution to analyze the topological properties of ceRNA networks, detect modules, and perform gene enrichment analysis and survival analysis. CeNet Omnibus intends to cover comprehensiveness, high efficiency, high expandability, and user customizability, and it also offers a web-based user-friendly interface to users to obtain the output intuitionally. Conclusion CeNet Omnibus is a comprehensive platform for the construction and analysis of ceRNA networks. It is highly customizable and outputs the results in intuitive and interactive. We expect that CeNet Omnibus will assist researchers to understand the property of ceRNA networks and associated biological phenomena. CeNet Omnibus is an R/Shiny application based on the Shiny framework developed by RStudio. The R package and detailed tutorial are available on our GitHub page with the URL https://github.com/GaoLabXDU/CeNetOmnibus.
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Duan W, Kong X, Li J, Li P, Zhao Y, Liu T, Binang HB, Wang Y, Du L, Wang C. LncRNA AC010789.1 Promotes Colorectal Cancer Progression by Targeting MicroRNA-432-3p/ZEB1 Axis and the Wnt/β-Catenin Signaling Pathway. Front Cell Dev Biol 2020; 8:565355. [PMID: 33178684 PMCID: PMC7593606 DOI: 10.3389/fcell.2020.565355] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 09/24/2020] [Indexed: 12/12/2022] Open
Abstract
Accumulating literatures have indicated that long non-coding RNAs (lncRNAs) are crucial molecules in tumor progression in various human cancers, including colorectal cancer (CRC). However, the clinical significance and regulatory mechanism of a vast majority of lncRNAs in CRC remain to be determined. The current study aimed to explore the function and molecular mechanism of lncRNA AC010789.1 in CRC progression. AC010789.1 found to be overexpressed in CRC tissues and cells. High expression of AC010789.1 was associated with lymph node metastasis and poor prognosis. Moreover, AC010789.1 silencing inhibited proliferation, migration, invasion and epithelial-mesenchymal transition (EMT) in vitro as well as tumorigenesis and metastasis in vivo. Mechanistically, we demonstrated that repression of AC010789.1 promoted miR-432-3p expression, and miR-432-3p directly binds to ZEB1. We then proved the anti-tumor role of miR-432-3p in CRC, showing that the inhibitory effect of AC010789.1 knockdown on CRC cells was achieved by the upregulation of miR-432-3p but downregulation of ZEB1. We also established that silencing AC010789.1 suppressed the Wnt/β-catenin signaling pathway. However, this inhibitory effect was partially counteracted by inhibition of miR-432-3p. In summary, these results reveal that silencing AC010789.1 suppresses CRC progression via miR-432-3p-mediated ZEB1 downregulation and suppression of the Wnt/β-catenin signaling pathway, highlighting a potentially promising strategy for CRC treatment.
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Affiliation(s)
- Weili Duan
- Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Xue Kong
- Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Juan Li
- Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Peilong Li
- Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Yinghui Zhao
- Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Tong Liu
- Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Helen Barong Binang
- Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Yunshan Wang
- Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Lutao Du
- Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.,Tumor Marker Detection Engineering Technology Research Center of Shandong Province, Jinan, China
| | - Chuanxin Wang
- Department of Clinical Laboratory, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China.,Tumor Marker Detection Engineering Laboratory of Shandong Province, Jinan, China.,The Clinical Research Center of Shandong Province for Clinical Laboratory, Jinan, China
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