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Identifying critical differentiation state of MCF-7 cells for breast cancer by dynamical network biomarkers.


ABSTRACT: Identifying the pre-transition state just before a critical transition during a complex biological process is a challenging task, because the state of the system may show neither apparent changes nor clear phenomena before this critical transition during the biological process. By exploring rich correlation information provided by high-throughput data, the dynamical network biomarker (DNB) can identify the pre-transition state. In this work, we apply DNB to detect an early-warning signal of breast cancer on the basis of gene expression data of MCF-7 cell differentiation. We find a number of the related modules and pathways in the samples, which can be used not only as the biomarkers of cancer cells but also as the drug targets. Both functional and pathway enrichment analyses validate the results.

SUBMITTER: Chen P 

PROVIDER: S-EPMC4516973 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Identifying critical differentiation state of MCF-7 cells for breast cancer by dynamical network biomarkers.

Chen Pei P   Liu Rui R   Chen Luonan L   Aihara Kazuyuki K  

Frontiers in genetics 20150728


Identifying the pre-transition state just before a critical transition during a complex biological process is a challenging task, because the state of the system may show neither apparent changes nor clear phenomena before this critical transition during the biological process. By exploring rich correlation information provided by high-throughput data, the dynamical network biomarker (DNB) can identify the pre-transition state. In this work, we apply DNB to detect an early-warning signal of brea  ...[more]

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