DUCTAL CARCINOMA IN SITU AND INVASIVE BREAST CANCER-BASED DIFFERENTIAL GENE EXPRESSION STUDY FOR THERAPEUTIC DEVELOPMENT
DOI:
https://doi.org/10.22159/ajpcr.2016.v9s3.14317Abstract
ABSTRACT
Objective: Breast cancer is the second most common cancer in women globally. Multiple inherited mutations in genes are predominantly associated
with breast cancer. The gene expression profiling of breast tumors generated by DNA microarray analysis provides molecular phenotyping that
determines and characterizes the classifications of these tumors.
Methods: In this work, we used gene expression profiling of breast cancer samples from Gene Expression Omnibus (GEO) database. The dataset
GSE41194, retrieved from GEO, was used to investigate differential gene expression in ductal carcinoma in situ (DCIS) and invasive breast cancer (IBC).
The dataset contains 26 DCIS and 24 IBC samples. The data were analyzed in R and Bioconductor. To normalize the data Robust Multiarray Average
(RMA) method was applied, limma software was used to identify the differentially expressed genes (DEGs) in DCIS and IBC; an adjusted p value ≤0.05
was used to filter differentially expressed probe sets, and a fold change (FC) ≥ 2 to identify upregulated and ≤−2 for downregulated genes. The DEGs
retrieved were clustered and annotated using Database for Annotation, Visualization and Integrated Discovery (DAVID) Bioinformatics Resources
with an EASE score ≤0.1 and count 2.
Results: The analysis obtained 72 DEGs with a p≤0.05. The FC≥2 identified 38 upregulated probesets and FC≤−2 identified 34 downregulated probe
sets. The up and downregulated genes obtained in various comparisons were characterized based on gene ontology (GO) and pathway analyses in
DAVID, which retrieved six genes that had principal pathways targeting breast cancer.
Conclusion: Identification of these genes and pathways enhances the knowledge and progression of DCIS to IBC; paving a novel way for developing
new therapies for treating patients with breast cancer.
Keywords: Molecular phenotyping, Gene Expression, Ductal carcinoma in situ, Invasive breast cancer.
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References
Youlden DR, Cramb SM, Dunn NA, Muller JM, Pyke CM, Baade PD. The descriptive epidemiology of female breast cancer: An international comparison of screening, incidence, survival and mortality. Cancer Epidemiol 2012;36(3):237-48.
Fitzmaurice C, Dicker D, Pain A, Hamavid H, Moradi-Lakeh M, MacIntyre MF, et al. The global burden of cancer 2013. JAMA Oncol 2015;1(4):505-27.
Smigal C, Jemal A, Ward E, Cokkinides V, Smith R, Howe HL, et al. Trends in breast cancer by race and ethnicity: Update 2006. CA Cancer J Clin 2006;56(3):168-83.
Kumar R, Sharma A, Tiwari RK. Application of microarray in breast cancer: An overview. J Pharm Bioallied Sci 2012;4(1):21-6.
Alteri R, Bandi P. Breast Cancer Facts & Figures 2011-2012. Atlanta: American Cancer Society, Inc.; 2011.
Cazzaniga M, Bonanni B. Breast cancer chemoprevention: Old and new approaches. J Biomed Biotechnol 2012;2012:985620.
Nevins JR, Potti A. Mining gene expression profiles: Expression signatures as cancer phenotypes. Nat Rev Genet 2007;8(8):601-9.
Kihara D, Yang YD, Hawkins T. Bioinformatics resources for cancer research with an emphasis on gene function and structure prediction tools. Cancer Inform 2007;2:25-35.
Slonim DK, Yanai I. Getting started in gene expression microarray analysis. PLoS Comput Biol 2009;5(10):e1000543.
Lee S, Stewart S, Nagtegaal I, Luo J, Wu Y, Colditz G, et al. Differentially expressed genes regulating the progression of ductal carcinoma in situ to invasive breast cancer. Cancer Res 2012;72(17):4574-86.
Barrett T, Wilhite SE, Ledoux P, Evangelista C, Kim IF, Tomashevsky M, et al. NCBI GEO: Archive for functional genomics data sets – update. Nucleic Acids Res 2013;41:D991-5.
R Development Core Team. R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria; 2012. Available from: https://www.r-project.org. [Last accessed on 2012 Jun 01].
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, et al. Bioconductor: Open software development for computational biology and bioinformatics. Genome Biol 2004;5(10):R80.
Irizarry RA, Hobbs B, Collin F, Beazerâ€Barclay YD, Antonellis KJ. Uwe Scherf, and Terence P. Speed. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 2003;4(2):249-64.
Ritchie ME, Phipson B, Wu D, Hu Y, Law CW, Shi W, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 2015;43(7):e47.
Huang da W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc 2009;4(1):44-57.
Gene Ontology Consortium. Gene ontology consortium: Going forward. Nucleic Acids Res 2015;43:D1049-56.
Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M. Data, information, knowledge and principle: Back to metabolism in KEGG. Nucleic Acids Res 2014;42:D199-205.
Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin 2011;61(2):69-90.
Appiah-Opong R, Asante IK, Safo DO, Tuffour I, Ofori-attah E, Uto T, et al. Cytotoxic effects of Albizia zygia (Dc) J.F. Macbr, a ghanaian medicinal plant, against human T-lymphoblast-like leukemia, prostate and breast cancer cell lines. Int J Pharm Pharm Sci [S.L.] 2016;8(5):392-6.
Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, et al. Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 2015;136(5):E359-86.
Ali I, Wani WA, Saleem K. Cancer scenario in India with future perspectives. Cancer Ther 2011;8(56):56-70.
Ismail MM, Soliman DH, Farrag AM, Sabour R. Synthesis, antitumor activity, pharmacophore modeling and Qsar studies of novel pyrazoles and pyrazolo [1, 5-A] pyrimidines against breast adenocarcinoma Mcf-7 cell line. Int J Pharm Pharm Sci [S.L.] 2016;8(7):434-42.
Dhillon AS, Hagan S, Rath O, Kolch W. MAP kinase signalling pathways in cancer. Oncogene 2007;26(22):3279-90.
Kumar P, Bolshette NB, Jamdade VS, Mundhe NA, Thakur KK, Saikia KK, et al. Breast cancer status in India: An overview. Biomed Prev Nutr 2013;3(2):177-83.
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