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Identification of Differentially Expressed Genes in Pancreatic Ductal Adenocarcinoma and Normal Pancreatic Tissues Based on Microarray Datasets

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Identification of Differentially Expressed Genes in Pancreatic Ductal Adenocarcinoma and Normal Pancreatic Tissues Based on Microarray Datasets MOLECULAR MEDICINE REPORTS 20: 1901-1914, 2019 Identification of differentially expressed genes in pancreatic ductal adenocarcinoma and normal pancreatic tissues based on microarray datasets LIYING LIU1,2*, SIQI WANG1,2*, CHUNYUAN CEN1,2, SHUYI PENG1,2, YAN CHEN1,2, XIN LI1,2, NAN DIAO1,2, QIAN LI1,2, LING MA3 and PING HAN1,2 1Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology; 2Hubei Province Key Laboratory of Molecular Imaging, Wuhan, Hubei 430022; 3Advanced Application Team, GE Healthcare, Shanghai 201203, P.R. China Received August 15, 2018; Accepted May 1, 2019 DOI: 10.3892/mmr.2019.10414 Abstract. Pancreatic ductal adenocarcinoma (PDAC) is a downregulated genes. Reverse transcription-quantitative PCR highly aggressive malignant tumor with rapid progression was performed to examine the expression levels of S100A6, and poor prognosis. In the present study, 11 high-quality KRT19 and GNG7, and the results suggested that S100A6 was microarray datasets, comprising 334 tumor samples and 151 significantly upregulated in PDAC compared with normal non-tumor samples from the Gene Expression Omnibus, pancreatic tissues. ITGA2 overexpression was significantly were screened, and integrative meta-analysis of expression associated with shorter overall survival times, whereas family data was used to identify gene signatures that differentiate with sequence similarity 46 member C overexpression was between PDAC and normal pancreatic tissues. Following strongly associated with longer overall survival times. In the identification of differentially expressed genes (DEGs), addition, network-based meta-analysis confirmed growth two-way hierarchical clustering analysis was performed for factor receptor-bound protein 2 and histone deacetylase 5 as all DEGs using the gplots package in R software. Hub genes pivotal hub genes in PDAC compared with normal tissue. In were then determined through protein-protein interaction conclusion, the results of the present meta‑analysis identified network analysis using NetworkAnalyst. In addition, functional PDAC‑related gene signatures, providing new perspectives and annotation and pathway enrichment analyses of all DEGs were potential targets for PDAC diagnosis and treatment. conducted in the Database for Annotation, Visualization, and Integrated Discovery. The expression levels and Kaplan-Meier Introduction analysis of the top 10 upregulated and downregulated genes were verified in The Cancer Genome Atlas. A total of 1,587 Pancreatic ductal adenocarcinoma (PDAC) is one of the DEGs, including 1,004 upregulated and 583 downregulated most aggressive malignant tumors worldwide; it has a poor genes, were obtained by comparing PDAC with normal tissues. prognosis and a 5‑year survival rate of ~8% in the USA (1). Of these, hematological and neurological expressed 1, integrin The median survival time for patients with advanced PDAC subunit α2 (ITGA2) and S100 calcium-binding protein A6 is <7 months, even with active treatment (2). Statistics from (S100A6) were the top upregulated genes, and kinesin family the National Cancer Institute Surveillance, Epidemiology and member 1A, Dymeclin and β-secretase 1 were the top End Results database (https://seer.cancer.gov) indicate that PDAC is the fourth leading cause of cancer-related mortality, accounting for ~7% of all cancer deaths in the United States. The mortality rate of men with pancreatic cancer increased slightly from 2005 to 2014, at a rate of 0.3% per year (1). Based Correspondence to: Professor Ping Han, Department of on this trend, Hezel et al predicted that pancreatic cancer would Radiology, Union Hospital, Tongji Medical College, Huazhong become the second most common cause of cancer-related University of Science and Technology, 1277 Jiefang Avenue, death by 2030 (3). Resection of pancreatic tumor tissue during Wuhan, Hubei 430022, P.R. China the early stage is currently the only curative treatment method. E‑mail: [email protected] However, as symptoms and biomarkers for early diagnosis *Contributed equally are lacking, >80% of patients with PDAC are not diagnosed until they are in the advanced stage, thereby missing the best Key words: pancreatic ductal adenocarcinoma, differentially timeframe for curative treatment (4). Additionally, the lack of expressed genes, functional annotation, pathway enrichment effective and credible interventions is another key cause of analysis, protein-protein interaction the high mortality rate in patients with PDAC (3). Thus, new targets for PDAC diagnosis and better therapeutics for PDAC treatment are urgently needed. 1902 LIU et al: GENES AssOCIATED WIth PANCREATIC DUCTAL ADENOCARCINOMA Pancreatic cancer has many risk factors, including indi- Table I. Primer sequences. vidual, lifestyle-related, disease and drug-related factors, with PDAC being primarily caused by somatically acquired muta- Gene name Primer sequence (5'-3') tions (5). Jones et al investigated gene mutations involved in pancreatic cancer and found an average of 63 mutated genes (6). GAPDH F: ACTTTGGTATCGTGGAAGGACTCAT A number of previous studies have examined gene mutations R: GTTTTTCTAGACGGCAGGTCAGG in pancreatic cancer. For example, Nagata et al reported and S100A6 F: CCATCTTCCACAAGTACTCCGG validated that mucins, such as mucin (MUC) 1, MUC5 and R: GCAGCTTCGAGCCAATGGT MUC6, were overexpressed in invasive ductal carcinoma (IDC) GNG7 F: CGCATAGAAGCCGGGATTGA and in pancreatic intraepithelial neoplasia, which develops R: TTGTCCTTAAAGGGGTTCTCCG into IDC (7). Kirsten rat sarcoma viral oncogene homolog KRT19 F: AGAATTGAACCGGGAGGTCG (KRAS) has been confirmed as the driver gene in PDAC (6‑8). R: CCTGATTCTGCCGCTCACTA By establishing a genetically engineered mouse PDAC model, Rozenblum et al demonstrated that SMAD4 is inactivated S100A6, S100 calcium-binding protein; GNG7, G protein subunit 7; in most pancreatic cancers, which leads to inactivation of the KRT19, keratin-19. tumor suppressor gene cyclin-dependent kinase inhibitor 2A and activation of KRAS (9,10). p53, another tumor suppressor gene, has been found to be mutated in >50% of patients with PDAC (3,9). Fong and Winter systematically summarized the PDAC tissues were collected from 15 patients (female to male presence of various biomarkers in cancer cells and body fluids in ratio, 4:11) with PDAC who underwent surgical procedures patients with PDAC based on previous studies; these biomarkers at the Union Hospital of Tongji Medical College, Huazhong included the genes KRAS, Fanconi anemia complementation University of Science and Technology (Wuhan, China) group I (FANCI) and MUC1, and the proteins CA‑19-9, CA‑125 between July 2018 and September 2018. Human study proto- and CEA, as well as microRNA (miR)-21 and miR‑210 (11). cols were approved by the ethics committee of Tongji Medical Unexpectedly, although >2,000 studies have been conducted on College, Huazhong University of Science and Technology biomarkers for pancreatic cancer, the CA‑19-9 serum level is (Wuhan, China), and all patients in the study provided written the only widely used Food and Drug Administration-approved informed consent. The pathological diagnoses of the speci- tumor marker, albeit not for diagnosis. To date, no biomarkers mens were confirmed by two clinicopathological experts at the are sufficiently accurate for widespread diagnostic use (12). Department of Pathology, Union Hospital of Tongji Medical Since the emergence of high-throughput genomic technolo- College, Huazhong University of Science and Technology gies, including microarrays several decades ago, these techniques prior to RNA extraction. Specimens were snap frozen in liquid have been applied to study many diseases. For example, these nitrogen and stored at ‑80˚C. According to the American technologies are used to identify disease subtypes (13), explore Joint Commission on Cancer Staging System for patients with gene expression profiles of disease (14) and to identify poten- pancreatic adenocarcinoma (28), patients were divided into tial novel pathogenic genes and diseases (15). Additionally, three groups: i) Stage I (n=7); ii) stage II (n=7); and stage III molecular signatures discovered by microarrays have become (n=1). predictive biomarkers for certain diseases (16). An increasing number of studies have applied this technique to identify Identification of PDAC microarray datasets and validation in differentially expressed genes (DEGs) between tumor tissues The Cancer Genome Atlas (TCGA). The keywords ‘pancreatic and normal tissues (17). Although microarray technology has cancer’ were used to search for gene chips to study in the Gene enabled the discovery of biomarkers, study results vary owing Expression Omnibus (GEO) datasets of the National Center to inaccuracies or quality problems in microarray analyses and for Biotechnology Information database (http://www.ncbi. verification, and small sample sizes exacerbate this issue (18). nlm.nih.gov/geo). The inclusion criteria for the qualified chips A meta-analysis, as a large-sample study, has an advantage were as follows: i) The chip was a gene expression chip; ii) the in addressing this limitation due to its enhanced statistical genes were from normal pancreatic and/or PDAC tissues; iii) power (19). Prior meta-analyses have been applied to study the GEO series (GSE) dataset included >3 samples. Gene chips tumors to confirm DEGs between tumor tissue and normal that met any of the following criteria were excluded: i) Chips tissue in glioma (20,21), lung
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