RESEARCH ARTICLETranscription Factors and microRNA-Co-Regulated Genes in Gastric Cancer Invasionin Ex VivoYue Shi1, Jihan Wang1, Zhuoyuan Xin1, Zipeng Duan1, Guoqing Wang1,2*, Fan Li1,2*1 Department of Pathogenobiology, The Key Laboratory of Zoonosis, Chinese Ministry of Education, Collegeof Basic Medicine, Jilin University, Changchun, Jilin, China, 2 The Key Laboratory for Bionics Engineering,Ministry of Education, China, Jilin University, Changchun, China* qing8110@gmail.com (GQW); lifan@jlu.edu.cn (FL)AbstractAberrant miRNA expression abnormally modulates gene expression in cells and can contributeto tumorigenesis in humans. This study identified functionally relevant differentiallyexpressed genes using the transcription factors and miRNA-co-regulated network analysisfor gastric cancer. The TF-miRNA co-regulatory network was constructed based on data obtainedfrom cDNA microarray and miRNA expression profiling of gastric cancer tissues. Thenetwork along with their co-regulated genes was analyzed using Database for Annotation,Visualization and Integrated Discovery (DAVID) and Transcriptional Regulatory ElementDatabase (TRED). We found eighteen (17 up-regulated and 1 down-regulated) differentiallyexpressed genes that were co-regulated by transcription factors and miRNAs. KEGG pathwayanalysis revealed that these genes were part of the extracellular matrix-receptor interactionand focal adhesion signaling pathways. In addition, qRT- PCR and Western blot datashowed an increase in COL1A1 and decrease in NCAM1 mRNA and protein levels in gastriccancer tissues. Thus, these data provided the first evidence to illustrate that alteredgene network was associated with gastric cancer invasion. Further study with a large samplesize and more functional experiments is needed to confirm these data and contribute todiagnostic and treatment strategies for gastric cancer.IntroductionGastric cancer is one of the most common form of malignancies in the world, contributing to athird of cancer-related deaths in men and a fifth among women [1]. Approximately, two-thirdsof gastric cancer cases occur in the developing countries. In China, the incidence and mortalityrelated to gastric cancer ranks third among other forms of malignancies [2] and it was reportedthat gastric cancer occurs more frequently in rural areas and with a trend of younger peoplebeing affected by it in recent years [3]. Environmental (such as Helicobacter pylori infection orconsumption of smoked foods) and genetic factors (E-cadherin mutation) increases the susceptibilityto gastric cancer by inducing alterations in oncogenes/tumor suppressor genes and/orPLOS ONE | DOI:10.1371/journal.pone.0122882 April 10, 2015 1 / 13OPEN ACCESSCitation: Shi Y, Wang J, Xin Z, Duan Z, Wang G, Li F(2015) Transcription Factors and microRNA-Co-Regulated Genes in Gastric Cancer Invasion in ExVivo. PLoS ONE 10(4): e0122882. doi:10.1371/journal.pone.0122882Academic Editor: Jian-Jun Zhao, Dana-FarberCancer Institute, UNITED STATESReceived: November 8, 2014Accepted: February 24, 2015Published: April 10, 2015Copyright: © 2015 Shi et al. This is an open accessarticle distributed under the terms of the CreativeCommons Attribution License, which permitsunrestricted use, distribution, and reproduction in anymedium, provided the original author and source arecredited.Data Availability Statement: All relevant data arewithin the paper and its Supporting Information files.Funding: This work was supported by grants fromNational Natural Science Foundation of China(#81320108025 and #81472662). It is also supportedin part by National Natural Science Foundation ofChina (#81271897 and #81401712), Jilin KeyLaboratory of Biomedical Materials, Foundation ofJilin Province Science and Technology Department(#20130522013JH and #20140414048GH) and theNorman Bethune Program of Jilin University(#2012219).epigenetic profile [4]. Alteration in these critical factors results in abnormal regulation of cellgrowth, apoptosis, and differentiation thus promoting carcinogenesis. Multiple gene regulatorynetworks co-ordinate the transformation of normal cell to a tumor cell and drive tumor progression.However, to date, the detailed understanding of the underlying multiple gene regulatorynetworks in pathogenesis of gastric cancer is yet to be defined. Determining the detailedmolecular mechanistic network associated with gastric cancer development and progressioncould improve the understanding of carcinogenesis in gastric tissues, thus paving way for noveland effective strategies in the prevention, diagnosis and treatment of gastric cancer.Gene expression in cells is controlled both at transcription and post-transcriptional levels.Transcription factors (TFs) coordinate gene transcription, while miRNAs regulates gene expressionby mediating post-transcriptional events, such as mRNA degradation and proteintranslation [5]. Therefore, any alterations in miRNA function can result in the development ofcancer in humans [6,7]. Transcription factors are proteins that bind to specific DNA sequencesto control the rate of transcription of genetic information from DNA to mRNA [8,9], whilemiRNAs are a group of a small non-coding RNA in cells and function in RNA silencing andpost-transcriptional regulation of gene expression [10,11]. The TF-miRNA gene regulatorynetwork determines the overall gene expression profile in cells to some extent. Therefore, analysisof the TF-miRNA co-regulatory networks in gastric cancer tissues could help us to furtherour understanding on how TFs and miRNAs coordinate the regulation of gene expression contributingto gastric carcinogenesis [12]. In our previous study, we profiled differentially expressedgenes in eighty pairs of gastric carcinoma-adjacent normal tissues using cDNAmicroarrays [13] and found a number of genes with altered expression, including TFs. Based
on the information from Transcriptional Regulatory Element Database (TRED) [14], we built
and consolidated a TF-gene regulatory network. In this study, we profiled differentially expressed
miRNAs in five pairs of gastric carcinoma-adjacent normal tissues and constructed a
miRNA-target regulatory network for gastric cancer by integrating the miRNA targeting gene
databases, including Targetscan, miRanda, miRDB, and miRWalk [15]. We then constructed
the TF-miRNA co-regulatory network using our previous data and then performed GO and
KEGG pathway analyses and performed real time PCR and western blot analysis to validate
these data. Thus, both of the methods and analyses could provide important clues for future
studies on miRNA and TFs functions in gastric cancer.
Materials and Methods
Tissue samples
A total of 25 gastric carcinoma patients were recruited for this study from The First Hospital of
Jilin University, Changchun, China. Gastric cancer tissues and the matching distant noncancerous
tissues were surgically resected and stored in liquid nitrogen within 10 min after the
resection. Written informed consents were obtained from all the subjects and the data were analyzed
anonymously. The TNM and histological classification were according to World Health
Organization (WHO) criteria. This study was approved by the Ethics Committee of College of
Basic Medical Sciences, Jilin University.
Profiling of differentially expressed mRNA and microRNA in gastric
cancer tissues
The differentially expressed mRNA data between gastric cancer and normal tissues was conducted
from 80 patients and reported previously [13]. We used 2-fold change to profile the
differentially expressed genes for this study.
TF/miRNA Co-Regulated Networks in Gastric Cancer
PLOS ONE | DOI:10.1371/journal.pone.0122882 April 10, 2015 2 / 13
Competing Interests: The authors have declared
that no competing interests exist.
In this study, differentially expressed miRNAs in 5 pairs of gastric cancer–adjacent normal
tissues (see patients’ data in S2 Table) were profiled using Affymetrix miRNA microarray chips
according to the manufacturer’s protocols. Briefly, total RNA from tissue samples was isolated
using the Trizol (Invitrogen, Carlsbad, CA, USA) and miRNA was isolated and purified using
the mirVana miRNA Isolation Kit (Ambion, Austin, TX, USA) and then subjected to Gene
Chip microRNA array analysis. The data were scanned using GeneChip Scanner3000 with
GeneChip Operating Software (GCOS) and analyzed.
Construction of TF-gene, miRNA-targeting gene, and TF-miRNA coregulatory
networks
Based on the GeneChip Human Exon 1.0 ST microarray data (Affymetrix, CA, USA), we constructed
the TF-gene network by integrating gene expression profiles and transcriptional regulatory
element database (TRED). Regulatory interactions between microRNA and their target
genes were established based on information from Targetscan, miRanda, miRDB and miRWalk
database. The TF-miRNA co-regulatory networks were constructed by overlapping these two
sections. Hub-genes that co-regulated by TFs and miRNAs were also identified. The networks
were constructed using Cytoscape software (Institute of Systems Biology, USA, http://www.
cytoscape.org).
Functional annotations of selected genes
Online analytical tools such as Database for Annotation, Visualization and Integrated Discovery
(DAVID) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were applied to explore
the functional pathway associated with differentially expressed genes. Significantly enriched
KEGG pathways with p < 0.01 were identified and analyzed further.
Quantitative RT-PCR (qRT-PCR)
For detect mRNA level, we utilized 5 μg total RNA samples of each sample to reversely transcribe
into cDNA with the first strand cDNA Synthesis Kit (Takara, Dalian, China) and then
amplified using qPCR for expression of COL1A1, and NCAM1 mRNA with SYBR Premix Ex
Taq (Takara) in Applied Biosystems 7300 Fast Real-Time PCR System according to the manufacturers’
instructions. The relative expression of
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