Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis.

Due to the large number of putative microRNA gene targets predicted by sequence-alignment databases and the relative low accuracy of such predictions which are conducted independently of biological context by design, systematic experimental identification and validation of every functional microRNA...

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Autores principales: Younghee Lee, Xinan Yang, Yong Huang, Hanli Fan, Qingbei Zhang, Youngfei Wu, Jianrong Li, Rifat Hasina, Chao Cheng, Mark W Lingen, Mark B Gerstein, Ralph R Weichselbaum, H Rosie Xing, Yves A Lussier
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Publicado: Public Library of Science (PLoS) 2010
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spelling oai:doaj.org-article:1f3f6d79c24448c498154cf3417eabdd2021-11-25T05:42:34ZNetwork modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis.1553-734X1553-735810.1371/journal.pcbi.1000730https://doaj.org/article/1f3f6d79c24448c498154cf3417eabdd2010-04-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20369013/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Due to the large number of putative microRNA gene targets predicted by sequence-alignment databases and the relative low accuracy of such predictions which are conducted independently of biological context by design, systematic experimental identification and validation of every functional microRNA target is currently challenging. Consequently, biological studies have yet to identify, on a genome scale, key regulatory networks perturbed by altered microRNA functions in the context of cancer. In this report, we demonstrate for the first time how phenotypic knowledge of inheritable cancer traits and of risk factor loci can be utilized jointly with gene expression analysis to efficiently prioritize deregulated microRNAs for biological characterization. Using this approach we characterize miR-204 as a tumor suppressor microRNA and uncover previously unknown connections between microRNA regulation, network topology, and expression dynamics. Specifically, we validate 18 gene targets of miR-204 that show elevated mRNA expression and are enriched in biological processes associated with tumor progression in squamous cell carcinoma of the head and neck (HNSCC). We further demonstrate the enrichment of bottleneckness, a key molecular network topology, among miR-204 gene targets. Restoration of miR-204 function in HNSCC cell lines inhibits the expression of its functionally related gene targets, leads to the reduced adhesion, migration and invasion in vitro and attenuates experimental lung metastasis in vivo. As importantly, our investigation also provides experimental evidence linking the function of microRNAs that are located in the cancer-associated genomic regions (CAGRs) to the observed predisposition to human cancers. Specifically, we show miR-204 may serve as a tumor suppressor gene at the 9q21.1-22.3 CAGR locus, a well established risk factor locus in head and neck cancers for which tumor suppressor genes have not been identified. This new strategy that integrates expression profiling, genetics and novel computational biology approaches provides for improved efficiency in characterization and modeling of microRNA functions in cancer as compared to the state of art and is applicable to the investigation of microRNA functions in other biological processes and diseases.Younghee LeeXinan YangYong HuangHanli FanQingbei ZhangYoungfei WuJianrong LiRifat HasinaChao ChengMark W LingenMark B GersteinRalph R WeichselbaumH Rosie XingYves A LussierPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 6, Iss 4, p e1000730 (2010)
institution DOAJ
collection DOAJ
language EN
topic Biology (General)
QH301-705.5
spellingShingle Biology (General)
QH301-705.5
Younghee Lee
Xinan Yang
Yong Huang
Hanli Fan
Qingbei Zhang
Youngfei Wu
Jianrong Li
Rifat Hasina
Chao Cheng
Mark W Lingen
Mark B Gerstein
Ralph R Weichselbaum
H Rosie Xing
Yves A Lussier
Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis.
description Due to the large number of putative microRNA gene targets predicted by sequence-alignment databases and the relative low accuracy of such predictions which are conducted independently of biological context by design, systematic experimental identification and validation of every functional microRNA target is currently challenging. Consequently, biological studies have yet to identify, on a genome scale, key regulatory networks perturbed by altered microRNA functions in the context of cancer. In this report, we demonstrate for the first time how phenotypic knowledge of inheritable cancer traits and of risk factor loci can be utilized jointly with gene expression analysis to efficiently prioritize deregulated microRNAs for biological characterization. Using this approach we characterize miR-204 as a tumor suppressor microRNA and uncover previously unknown connections between microRNA regulation, network topology, and expression dynamics. Specifically, we validate 18 gene targets of miR-204 that show elevated mRNA expression and are enriched in biological processes associated with tumor progression in squamous cell carcinoma of the head and neck (HNSCC). We further demonstrate the enrichment of bottleneckness, a key molecular network topology, among miR-204 gene targets. Restoration of miR-204 function in HNSCC cell lines inhibits the expression of its functionally related gene targets, leads to the reduced adhesion, migration and invasion in vitro and attenuates experimental lung metastasis in vivo. As importantly, our investigation also provides experimental evidence linking the function of microRNAs that are located in the cancer-associated genomic regions (CAGRs) to the observed predisposition to human cancers. Specifically, we show miR-204 may serve as a tumor suppressor gene at the 9q21.1-22.3 CAGR locus, a well established risk factor locus in head and neck cancers for which tumor suppressor genes have not been identified. This new strategy that integrates expression profiling, genetics and novel computational biology approaches provides for improved efficiency in characterization and modeling of microRNA functions in cancer as compared to the state of art and is applicable to the investigation of microRNA functions in other biological processes and diseases.
format article
author Younghee Lee
Xinan Yang
Yong Huang
Hanli Fan
Qingbei Zhang
Youngfei Wu
Jianrong Li
Rifat Hasina
Chao Cheng
Mark W Lingen
Mark B Gerstein
Ralph R Weichselbaum
H Rosie Xing
Yves A Lussier
author_facet Younghee Lee
Xinan Yang
Yong Huang
Hanli Fan
Qingbei Zhang
Youngfei Wu
Jianrong Li
Rifat Hasina
Chao Cheng
Mark W Lingen
Mark B Gerstein
Ralph R Weichselbaum
H Rosie Xing
Yves A Lussier
author_sort Younghee Lee
title Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis.
title_short Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis.
title_full Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis.
title_fullStr Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis.
title_full_unstemmed Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis.
title_sort network modeling identifies molecular functions targeted by mir-204 to suppress head and neck tumor metastasis.
publisher Public Library of Science (PLoS)
publishDate 2010
url https://doaj.org/article/1f3f6d79c24448c498154cf3417eabdd
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