Long non-coding RNA (lncRNA) and epithelial-mesenchymal transition (EMT) in colorectal cancer: a systematic review

O’Brien, Stephen J.; Bishop, Campbell; Hallion, Jacob; Fiechter, Casey; Scheurlen, Katharina M.; Paas, Mason; Burton, James F.; Galandiuk, Susan

doi:10.1080/15384047.2020.1794239

Cited by 32 publications

(26 citation statements)

References 107 publications

(286 reference statements)

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“…3e, f ). Although ZFAS1 does not inversely correlate with miR-200b, lncRNA and miRNA expression are dependent on a number of different upstream regulatory molecules 21 . We have previously reported the adverse role of low miR-200b and miR-200c expression with overall survival 22 .…”

Section: Resultsmentioning

confidence: 84%

Long non-coding RNA ZFAS1 is a major regulator of epithelial-mesenchymal transition through miR-200/ZEB1/E-cadherin, vimentin signaling in colon adenocarcinoma

et al. 2021

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Colon adenocarcinoma is a common cause of cancer-related deaths worldwide. Epithelial-mesenchymal transition is a major regulator of cancer metastasis, and increased understanding of this process is essential to improve patient outcomes. Long non-coding RNA (lncRNA) are important regulators of carcinogenesis. To identify lncRNAs associated with colon carcinogenesis, we performed an exploratory differential gene expression analysis comparing paired colon adenocarcinoma and normal colon epithelium using an RNA-sequencing data set. This analysis identified lncRNA ZFAS1 as significantly increased in colon cancer compared to normal colon epithelium. This finding was validated in an institutional cohort using laser capture microdissection. ZFAS1 was also found to be principally located in the cellular cytoplasm. ZFAS1 knockdown was associated with decreased cellular proliferation, migration, and invasion in two colon cancer cell lines (HT29 and SW480). MicroRNA-200b and microRNA-200c (miR-200b and miR-200c) are experimentally validated targets of ZFAS1, and this interaction was confirmed using reciprocal gene knockdown. ZFAS1 knockdown regulated ZEB1 gene expression and downstream targets E-cadherin and vimentin. Knockdown of miR-200b or miR-200c reversed the effect of ZFAS1 knockdown in the ZEB1/E-cadherin, vimentin signaling cascade, and the effects of cellular migration and invasion, but not cellular proliferation. ZFAS1 knockdown was also associated with decreased tumor growth in an in vivo mouse model. These results demonstrate the critical importance of ZFAS1 as a regulator of the miR-200/ZEB1/E-cadherin, vimentin signaling cascade.

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Section: Resultsmentioning

confidence: 84%

Long non-coding RNA ZFAS1 is a major regulator of epithelial-mesenchymal transition through miR-200/ZEB1/E-cadherin, vimentin signaling in colon adenocarcinoma

et al. 2021

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“…LncRNA XIST, expressed in differentiating ESCs (F1 2-1 ESC line), promotes metastasis and EMT in colorectal cancer, sponging miR-125b-2-3p [236,237]. Likewise, many lncRNAs involved in colorectal cancer act as ceRNAs and regulate the expression of the EMT transcription factors such as ZEB1, 2/E-Cadherin, and Wnt/β-Catenin signaling [238]. CeRNAs have been described as critical components of the TGFβ-induced EMT pathway, and they represent potential targets to disrupt EMT during tumorigenesis [226].…”

Section: Regulation Of Mirnas Through Competitive Endogenous Rnas In mentioning

confidence: 99%

MicroRNAs and Stem-like Properties: The Complex Regulation Underlying Stemness Maintenance and Cancer Development

et al. 2021

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Embryonic stem cells (ESCs) have the extraordinary properties to indefinitely proliferate and self-renew in culture to produce different cell progeny through differentiation. This latter process recapitulates embryonic development and requires rounds of the epithelial–mesenchymal transition (EMT). EMT is characterized by the loss of the epithelial features and the acquisition of the typical phenotype of the mesenchymal cells. In pathological conditions, EMT can confer stemness or stem-like phenotypes, playing a role in the tumorigenic process. Cancer stem cells (CSCs) represent a subpopulation, found in the tumor tissues, with stem-like properties such as uncontrolled proliferation, self-renewal, and ability to differentiate into different cell types. ESCs and CSCs share numerous features (pluripotency, self-renewal, expression of stemness genes, and acquisition of epithelial–mesenchymal features), and most of them are under the control of microRNAs (miRNAs). These small molecules have relevant roles during both embryogenesis and cancer development. The aim of this review was to recapitulate molecular mechanisms shared by ESCs and CSCs, with a special focus on the recently identified classes of microRNAs (noncanonical miRNAs, mirtrons, isomiRs, and competitive endogenous miRNAs) and their complex functions during embryogenesis and cancer development.

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“…LncRNA plays an important role in the biological process of chromatin modification, transcription and post-transcription regulation and so on [4], and has a very important biological function. The variation or dysfunction of lncRNA can lead to the occurrence of many diseases, such as lung cancer [5][6][7][8]、breast cancer [9][10]、 prostate cancer [11][12] 、 osteosarcoma [13] 、 colorectal cancer [14] 、 gastric cancer [15] 、 bladder cancer [16] and cervical cancer [17], etc. Therefore, the research on lncRNA-disease association prediction can not only deepen the understanding of the pathogenic mechanism for complex diseases at the molecular level, but also use lncRNA as disease diagnosis, predicted biological target, drug target for treatment and prevention.…”

Section: Introductionmentioning

confidence: 99%

Principal Component Regression Analysis for lncRNA-Disease Association Prediction Based on Pathological Stage Data

Wang

Zhang

2021

IEEE Access

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Accumulating researches have found that lncRNAs play a key role in many important biological processes, such as chromatin modification, transcription, and post-transcription regulation. Because lncRNAs play an important role in the life process, many important complex diseases have been linked to the variation and dysfunction of lncRNAs. In current prediction researches on lncRNA-disease association, clinical prognosis information of the disease (such as pathological stage, clinical stage and so on) is rarely mentioned. In this manuscript, we apply the pathological stage data into the lncRNA-disease association prediction. Firstly, coordinates reverse rotation in circular (CRRC) is proposed. 6 clusters are calculated by the proposed cluster generating algorithm (ClGeA) based on CRRC. Secondly, harmonic importance ranking (HIR) is put forward. 28 core variables are obtained by the proposed selection algorithm of core variables for cancer pathological stage (SA-CV-CPS) based on HIR and cluster. Finally, on the basis of the above 28 core variables, pathological stage prediction algorithm for lncRNA-disease association based on principal component regression analysis (PSPA-LA-PCRA) is developed. Through PSPA-LA-PCRA, principal component set (including 20 PCs) and prediction model are gained. The proposed prediction model is based on unknown human lncRNA-disease association combining with the pathological stage data. Experimental results show that better results for AUC, precision rate, recall rate and F1-score of the prediction model are achieved by PSPA-LA-PCRA, which provides a favorable research premise for subsequent prediction studies of lncRNA-disease associations.

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Long non-coding RNA (lncRNA) and epithelial-mesenchymal transition (EMT) in colorectal cancer: a systematic review

Cited by 32 publications

References 107 publications

Long non-coding RNA ZFAS1 is a major regulator of epithelial-mesenchymal transition through miR-200/ZEB1/E-cadherin, vimentin signaling in colon adenocarcinoma

Long non-coding RNA ZFAS1 is a major regulator of epithelial-mesenchymal transition through miR-200/ZEB1/E-cadherin, vimentin signaling in colon adenocarcinoma

MicroRNAs and Stem-like Properties: The Complex Regulation Underlying Stemness Maintenance and Cancer Development

Principal Component Regression Analysis for lncRNA-Disease Association Prediction Based on Pathological Stage Data

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