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01-04-2017 | Original Article

Combined Analysis of ChIP Sequencing and Gene Expression Dataset in Breast Cancer

Authors: Pengfei Liu, Wenhua Jiang, Shiyong Zhou, Jun Gao, Huilai Zhang

Published in: Pathology & Oncology Research | Issue 2/2017

Abstract

Breast cancer is a common malignancy in women and contribute largely to the cancer related death. The purpose of this study is to confirm the roles of GATA3 and identify potential biomarkers of breast cancer. Chromatin Immunoprecipitation combined with high-throughput sequencing (ChIP-Seq) (GSM1642515) and gene expression profiles (GSE24249) were downloaded from the Gene Expression Omnibus (GEO) database. Bowtie2 and MACS2 were used for the mapping and peak calling of the ChIP-Seq data respectively. ChIPseeker, a R bioconductor package was adopted for the annotation of the enriched peaks. For the gene expression profiles, we used affy and limma package to do normalization and differential expression analysis. The genes with fold change >2 and adjusted P-Value <0.05 were screened out. Besides, BETA (Binding and Expression Target Analysis) was used to do the combined analysis of ChIP-Seq and gene expression profiles. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for the functional enrichment analysis of overlapping genes between the target genes and differential expression genes (DEGs). What’s more, the protein-protein interaction (PPI) network of the overlapping genes was obtained through the Human Protein Reference Database (HPRD). A total of 46,487 peaks were identified for GATA3 and out of which, 3256 ones were found to located at −3000 ~ 0 bp from the transcription start sites (TSS) of their nearby gene. A total of 236 down- and 343 up-regulated genes were screened out in GATA3 overexpression breast cancer samples compared with those in control. The combined analysis of ChIP-Seq and gene expression dataset showed GATA3 act as a repressor in breast cancer. Besides, 68 overlaps were obtained between the DEGs and genes included in peaks located at −3000 ~ 0 bp from TSS. Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to cancer progression and gene regulation were found to be enriched in those overlaps. In the PPI network, NDRG1, JUP and etc. were found to directly interact with large number of genes, which might indicate their important roles in the progression of breast cancer.

Gradishar WJ, Anderson BO, Balassanian R, Blair SL, Burstein HJ, Cyr A, Elias AD, Farrar WB, Forero A, Giordano SH, Goetz M, Goldstein LJ, Hudis CA, Isakoff SJ, Marcom PK, Mayer IA, McCormick B, Moran M, Patel SA, Pierce LJ, Reed EC, Salerno KE, Schwartzberg LS, Smith KL, Smith ML, Soliman H, Somlo G, Telli M, Ward JH, Shead DA, Kumar R (2016) Invasive breast cancer version 1.2016, NCCN clinical practice guidelines in oncology. Journal of the National Comprehensive Cancer Network. JNCCN 14(3):324–354PubMed

Pusztai L, Ladanyi A, Szekely B, Dank M (2016) Immunotherapy opportunities in breast cancer. Magyar onkologia 60(1):34–40PubMed

Liu D (2016) Tumor necrosis factor-alpha, a regulator and therapeutic agent on breast cancer. Curr Pharm Biotechnol 17(6):486–494CrossRefPubMed

Maximiano S, Magalhaes P, Guerreiro MP, Morgado M (2016) Trastuzumab in the Treatment of Breast Cancer. BioDrugs: clinical immunotherapeutics, biopharmaceuticals and gene therapy doi:10.1007/s40259–016–0162-9

Kober KM, Dunn L, Mastick J, Cooper B, Langford D, Melisko M, Venook A, Chen LM, Wright F, Hammer M, Schmidt BL, Levine J, Miaskowski C, Aouizerat BE (2016) Gene Expression Profiling of Evening Fatigue in Women Undergoing Chemotherapy for Breast Cancer. Biological research for nursing doi:10.1177/1099800416629209

Cao ZG, Qin XB, Liu FF, Zhou LL (2015) Tryptophan-induced pathogenesis of breast cancer. Afr Health Sci 15(3):982–985. doi:10.4314/ahs.v15i3.36 CrossRefPubMedPubMedCentral

Park E (2016) Data on cell cycle in breast cancer cell line, MDA-MB-231 with ferulic acid treatment. Data in brief 7:107–110. doi:10.1016/j.dib.2016.02.001 CrossRefPubMedPubMedCentral

Asch-Kendrick R, Cimino-Mathews A (2016) The role of GATA3 in breast carcinomas: a review. Hum Pathol 48:37–47. doi:10.1016/j.humpath.2015.09.035 CrossRefPubMed

Si W, Huang W, Zheng Y, Yang Y, Liu X, Shan L, Zhou X, Wang Y, Su D, Gao J, Yan R, Han X, Li W, He L, Shi L, Xuan C, Liang J, Sun L, Wang Y, Shang Y (2015) Dysfunction of the Reciprocal Feedback Loop between GATA3- and ZEB2-Nucleated Repression Programs Contributes to Breast Cancer Metastasis. Cancer Cell 27(6):822–836. doi:10.1016/j.ccell.2015.04.011 CrossRefPubMed

10.

McCleskey BC, Penedo TL, Zhang K, Hameed O, Siegal GP, Wei S (2015) GATA3 expression in advanced breast cancer: prognostic value and organ-specific relapse. Am J Clin Pathol 144(5):756–763. doi:10.1309/AJCP5MMR1FJVVTPK CrossRefPubMed

11.

Dieci MV, Smutna V, Scott V, Yin G, Xu R, Vielh P, Mathieu MC, Vicier C, Laporte M, Drusch F, Guarneri V, Conte P, Delaloge S, Lacroix L, Fromigue O, Andre F, Lefebvre C (2016) Whole exome sequencing of rare aggressive breast cancer histologies. Breast Cancer Res Treat 156(1):21–32. doi:10.1007/s10549–016-3718-y CrossRefPubMed

12.

Chu IM, Michalowski AM, Hoenerhoff M, Szauter KM, Luger D, Sato M, Flanders K, Oshima A, Csiszar K, Green JE (2012) GATA3 inhibits lysyl oxidase-mediated metastases of human basal triple-negative breast cancer cells. Oncogene 31(16):2017–2027. doi:10.1038/onc.2011.382 CrossRefPubMed

13.

Gautier L, Cope L, Bolstad BM, Irizarry RA (2004) Affy--analysis of Affymetrix GeneChip data at the probe level. Bioinformatics 20(3):307–315. doi:10.1093/bioinformatics/btg405 CrossRefPubMed

14.

Langmead B (2010) Aligning short sequencing reads with Bowtie. Current protocols in bioinformatics / editoral board, Andreas D Baxevanis [et al] Chapter 11:Unit 11 17. doi:10.1002/0471250953.bi1107s32

15.

Feng J, Liu T, Qin B, Zhang Y, Liu XS (2012) Identifying ChIP-seq enrichment using MACS. Nat Protoc 7(9):1728–1740. doi:10.1038/nprot.2012.101 CrossRefPubMed

16.

Yu G, Wang LG, He QY (2015) ChIPseeker: an R/bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics 31(14):2382–2383. doi:10.1093/bioinformatics/btv145 CrossRefPubMed

17.

Wang S, Sun H, Ma J, Zang C, Wang C, Wang J, Tang Q, Meyer CA, Zhang Y, Liu XS (2013) Target analysis by integration of transcriptome and ChIP-seq data with BETA. Nat Protoc 8(12):2502–2515. doi:10.1038/nprot.2013.150 CrossRefPubMedPubMedCentral

18.

Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA (2003) DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol 4(5):P3

19.

Keshava Prasad TS, Goel R, Kandasamy K, Keerthikumar S, Kumar S, Mathivanan S, Telikicherla D, Raju R, Shafreen B, Venugopal A, Balakrishnan L, Marimuthu A, Banerjee S, Somanathan DS, Sebastian A, Rani S, Ray S, Harrys Kishore CJ, Kanth S, Ahmed M, Kashyap MK, Mohmood R, Ramachandra YL, Krishna V, Rahiman BA, Mohan S, Ranganathan P, Ramabadran S, Chaerkady R, Pandey A (2009) Human Protein Reference Database--2009 update. Nucleic Acids Res 37(Database issue):D767–D772. doi:10.1093/nar/gkn892 CrossRefPubMed

20.

Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13(11):2498–2504. doi:10.1101/gr.1239303 CrossRefPubMedPubMedCentral

21.

Lin Y, Zhao J, Hu X, Wang L, Liang L, Chen W (2016) Transcription factor CCAAT/enhancer binding protein alpha up-regulates microRNA let-7a-1 in lung cancer cells by direct binding. Cancer Cell Int 16:17. doi:10.1186/s12935–016–0294-5 CrossRefPubMedPubMedCentral

22.

Li C, Deng L, Zhi Q, Meng Q, Qian A, Sang H, Li X, Xia J (2016) MicroRNA-183 Functions As an Oncogene by Regulating PDCD4 in Gastric Cancer. Anti Cancer Agents Med Chem 16(4):447–455CrossRef

23.

Mitxelena J, Apraiz A, Vallejo-Rodriguez J, Malumbres M, Zubiaga AM (2016) E2F7 regulates transcription and maturation of multiple microRNAs to restrain cell proliferation. Nucleic Acids Res. doi:10.1093/nar/gkw146 PubMedPubMedCentral

24.

Takaku M, Grimm SA, Wade PA (2015) GATA3 in Breast Cancer: Tumor Suppressor or Oncogene? Gene Expr 16(4):163–168. doi:10.3727/105221615X14399878166113 CrossRefPubMedPubMedCentral

25.

Tkocz D, Crawford NT, Buckley NE, Berry FB, Kennedy RD, Gorski JJ, Harkin DP, Mullan PB (2012) BRCA1 and GATA3 corepress FOXC1 to inhibit the pathogenesis of basal-like breast cancers. Oncogene 31(32):3667–3678. doi:10.1038/onc.2011.531 CrossRefPubMed

26.

Xiong Y, Castro E, Yagi R, Zhu J, Lesourne R, Love PE, Feigenbaum L, Bosselut R (2013) Thpok-independent repression of Runx3 by Gata3 during CD4+ T-cell differentiation in the thymus. Eur J Immunol 43(4):918–928. doi:10.1002/eji.201242944 CrossRefPubMed

27.

Liu W, Yue F, Zheng M, Merlot A, Bae DH, Huang M, Lane D, Jansson P, Lui GY, Richardson V, Sahni S, Kalinowski D, Kovacevic Z, Richardson DR (2015) The proto-oncogene c-Src and its downstream signaling pathways are inhibited by the metastasis suppressor, NDRG1. Oncotarget 6(11):8851–8874. doi:10.18632/oncotarget.3316 CrossRefPubMedPubMedCentral

28.

Salis O, Bedir A, Kilinc V, Alacam H, Gulten S, Okuyucu A (2014) The anticancer effects of desferrioxamine on human breast adenocarcinoma and hepatocellular carcinoma cells. Cancer biomarkers: section A of Disease markers 14(6):419–426. doi:10.3233/CBM-140422 CrossRef

29.

Song JY, Lee JK, Lee NW, Jung HH, Kim SH, Lee KW (2008) Microarray analysis of normal cervix, carcinoma in situ, and invasive cervical cancer: identification of candidate genes in pathogenesis of invasion in cervical cancer. International journal of gynecological cancer: official journal of the international gynecological cancer. Society 18(5):1051–1059. doi:10.1111/j.1525-1438.2007.01164.x

30.

Wang Y, Zheng T (2014) Screening of hub genes and pathways in colorectal cancer with microarray technology. Pathol Oncol Res: POR 20(3):611–618. doi:10.1007/s12253–013–9739-5 CrossRefPubMed

Title: Combined Analysis of ChIP Sequencing and Gene Expression Dataset in Breast Cancer
Authors: Pengfei Liu
Wenhua Jiang
Shiyong Zhou
Jun Gao
Huilai Zhang
Publication date: 01-04-2017
Publisher: Springer Netherlands
Published in: Pathology & Oncology Research / Issue 2/2017
Print ISSN: 1219-4956
Electronic ISSN: 1532-2807
DOI: https://doi.org/10.1007/s12253-016-0116-z

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