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

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

Research output: Contribution to journalArticle

117 Citations (Scopus)

Abstract

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 cancerassociated 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.

Original languageEnglish (US)
JournalPLoS Computational Biology
Volume6
Issue number4
DOIs
StatePublished - Apr 2010
Externally publishedYes

Fingerprint

MicroRNA
Metastasis
Network Modeling
MicroRNAs
microRNA
tumor
metastasis
neck
Tumors
Tumor
Neck
Genes
Head
cancer
Neoplasm Metastasis
neoplasms
gene
Cancer
modeling
Gene

ASJC Scopus subject areas

  • Cellular and Molecular Neuroscience
  • Ecology
  • Molecular Biology
  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Computational Theory and Mathematics

Cite this

Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis. / Lee, Younghee; Yang, Xinan; Huang, Yong; Fan, Hanli; Zhang, Qingbei; Wu, Youngfei; Li, Jianrong; Hasina, Rifat; Cheng, Chao; Lingen, Mark W.; Gerstein, Mark B.; Weichselbaum, Ralph R.; Xing, H. Rosie; Lussier, Yves A.

In: PLoS Computational Biology, Vol. 6, No. 4, 04.2010.

Research output: Contribution to journalArticle

Lee, Y, Yang, X, Huang, Y, Fan, H, Zhang, Q, Wu, Y, Li, J, Hasina, R, Cheng, C, Lingen, MW, Gerstein, MB, Weichselbaum, RR, Xing, HR & Lussier, YA 2010, 'Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis', PLoS Computational Biology, vol. 6, no. 4. https://doi.org/10.1371/journal.pcbi.1000730
Lee, Younghee ; Yang, Xinan ; Huang, Yong ; Fan, Hanli ; Zhang, Qingbei ; Wu, Youngfei ; Li, Jianrong ; Hasina, Rifat ; Cheng, Chao ; Lingen, Mark W. ; Gerstein, Mark B. ; Weichselbaum, Ralph R. ; Xing, H. Rosie ; Lussier, Yves A. / Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis. In: PLoS Computational Biology. 2010 ; Vol. 6, No. 4.
@article{d1c630a1a9c241429a121deb6c6b68d2,
title = "Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis",
abstract = "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 cancerassociated 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.",
author = "Younghee Lee and Xinan Yang and Yong Huang and Hanli Fan and Qingbei Zhang and Youngfei Wu and Jianrong Li and Rifat Hasina and Chao Cheng and Lingen, {Mark W.} and Gerstein, {Mark B.} and Weichselbaum, {Ralph R.} and Xing, {H. Rosie} and Lussier, {Yves A}",
year = "2010",
month = "4",
doi = "10.1371/journal.pcbi.1000730",
language = "English (US)",
volume = "6",
journal = "PLoS Computational Biology",
issn = "1553-734X",
publisher = "Public Library of Science",
number = "4",

}

TY - JOUR

T1 - Network modeling identifies molecular functions targeted by miR-204 to suppress head and neck tumor metastasis

AU - Lee, Younghee

AU - Yang, Xinan

AU - Huang, Yong

AU - Fan, Hanli

AU - Zhang, Qingbei

AU - Wu, Youngfei

AU - Li, Jianrong

AU - Hasina, Rifat

AU - Cheng, Chao

AU - Lingen, Mark W.

AU - Gerstein, Mark B.

AU - Weichselbaum, Ralph R.

AU - Xing, H. Rosie

AU - Lussier, Yves A

PY - 2010/4

Y1 - 2010/4

N2 - 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 cancerassociated 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.

AB - 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 cancerassociated 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.

UR - http://www.scopus.com/inward/record.url?scp=77952742610&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77952742610&partnerID=8YFLogxK

U2 - 10.1371/journal.pcbi.1000730

DO - 10.1371/journal.pcbi.1000730

M3 - Article

VL - 6

JO - PLoS Computational Biology

JF - PLoS Computational Biology

SN - 1553-734X

IS - 4

ER -