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  5. Data from Long Noncoding RNA MIR17HG Promotes Colorectal Cancer Progression via miR-17-5p

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Preprint
en
2023

Data from Long Noncoding RNA MIR17HG Promotes Colorectal Cancer Progression via miR-17-5p

0 Datasets

0 Files

en
2023
DOI: 10.1158/0008-5472.c.6510741

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Michela Relucenti
Michela Relucenti

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Jie Xu
Qingtao Meng
Xiaobo Li
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Abstract

<div>Abstract<p>Immune dysregulation plays a vital role in colorectal cancer initiation and progression. Long noncoding RNAs (lncRNA) exhibit multiple functions including regulation of gene expression. Here, we identified an immune-related lncRNA, MIR17HG, whose expression was gradually upregulated in adjacent, adenoma, and colorectal cancer tissue. MIR17HG promoted tumorigenesis and metastasis in colorectal cancer cells both <i>in vitro</i> and <i>in vivo</i>. Mechanistically, MIR17HG increased the expression of NF-κB/RELA by competitively sponging the microRNA miR-375. In addition, RELA transcriptionally activated MIR17HG in a positive feedback loop by directly binding to its promoter region. Moreover, miR-17-5p, one of the transcribed miRNAs from MIR17HG, reduced the expression of the tumor suppressor B-cell linker (BLNK), resulting in increased migration and invasion of colorectal cancer cells. MIR17HG also upregulated PD-L1, indicating its potential role in immunotherapy. Overall, these findings demonstrate that MIR17HG plays an oncogenic role in colorectal cancer and may serve as a promising therapeutic target.</p>Significance:<p>These findings provide mechanistic insight into the role of the lncRNA MIR17HG and its miRNA members in regulating colorectal cancer carcinogenesis and progression.</p></div>

How to cite this publication

Jie Xu, Qingtao Meng, Xiaobo Li, Hongbao Yang, Jin Xu, Na Gao, Hao Sun, Shenshen Wu, Giuseppe Familiari, Michela Relucenti, Haitao Zhu, Jiong Wu, Rui Chen (2023). Data from Long Noncoding RNA MIR17HG Promotes Colorectal Cancer Progression via miR-17-5p. , DOI: https://doi.org/10.1158/0008-5472.c.6510741.

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Publication Details

Type

Preprint

Year

2023

Authors

13

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1158/0008-5472.c.6510741

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