+ Site Statistics
References:
54,258,434
Abstracts:
29,560,870
PMIDs:
28,072,757
+ Search Articles
+ PDF Full Text Service
How our service works
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ Translate
+ Recently Requested

Microarray-based identification of differentially expressed genes in extramammary Paget's disease



Microarray-based identification of differentially expressed genes in extramammary Paget's disease



International Journal of Clinical and Experimental Medicine 8(5): 7251-7260



Extramammary Paget's disease (EMPD) is a rare cutaneous malignancy accounting for approximately 1-2% of vulvar cancers. The rarity of this disease has caused difficulties in characterization and the molecular mechanism underlying EMPD development remains largely unclear. Here we used microarray analysis to identify differentially expressed genes in EMPD of the scrotum comparing with normal epithelium from healthy donors. Agilent single-channel microarray was used to compare the gene expression between 6 EMPD specimens and 6 normal scrotum epithelium samples. A total of 799 up-regulated genes and 723 down-regulated genes were identified in EMPD tissues. Real-time PCR was conducted to verify the differential expression of some representative genes, including ERBB4, TCF3, PAPSS2, PIK3R3, PRLR, SULT1A1, TCF7L1, and CREB3L4. Generally, the real-time PCR results were consistent with microarray data, and the expression of ERBB4, PRLR, TCF3, PIK3R3, SULT1A1, and TCF7L1 was significantly overexpressed in EMPD (P<0.05). Moreover, the overexpression of PRLR in EMPD, a receptor for the anterior pituitary hormone prolactin (PRL), was confirmed by immunohistochemistry. These data demonstrate that the differentially expressed genes from the microarray-based identification are tightly associated with EMPD occurrence.

Please choose payment method:






(PDF emailed within 1 workday: $29.90)

Accession: 058310940

Download citation: RISBibTeXText

PMID: 26221264


Related references

Density based pruning for identification of differentially expressed genes from microarray data. Bmc Genomics 11 Suppl 2: S3, 2011

Identification of differentially expressed genes for time-course microarray data based on modified RM ANOVA. Ieee/Acm Transactions on Computational Biology and Bioinformatics 9(2): 451-466, 2014

Microarray-based identification of differentially expressed growth- and metastasis-associated genes in pancreatic cancer. Cellular and Molecular Life Sciences 60(6): 1180-1199, 2003

Microarray-based identification of differentially expressed genes in intracellular Brucella abortus within RAW264.7 cells. Plos One 8(8): E67014, 2014

Identification of differentially expressed genes in benign and malignant thyroid disease by DDRT-PCR and microarray. Endocrine Journal 47(Suppl August): 215, 2000

Identification of differentially expressed genes by cDNA microarray for end-stage renal disease in the fawn-hooded rat. Journal of the American Society of Nephrology 11(Program and Abstract Issue): 629A-630A, 2000

Microarray-based identification of differentially expressed genes in families of turbot (Scophthalmus maximus) after infection with viral haemorrhagic septicaemia virus (VHSV). Marine Biotechnology 14(5): 515-529, 2013

Microarray-based identification of differentially expressed genes in hypoxic term human trophoblasts and in placental villi of pregnancies with growth restricted fetuses. Placenta 26(4): 319-328, 2005

Mixture-model based estimation of gene expression variance from public database improves identification of differentially expressed genes in small sized microarray data. Bioinformatics 26(4): 486-492, 2010

Matrilysin-1 (MMP-7) and MMP-19 are expressed by Paget's cells in extramammary Paget's disease. Journal of Cutaneous Pathology 31(7): 483-491, 2004

Microarray analysis of Fusarium graminearum-induced wheat genes: identification of organ-specific and differentially expressed genes. Plant Biotechnology Journal 5(1): 38-49, 2007

Identification of differentially expressed genes associated with burn sepsis using microarray. International Journal of Molecular Medicine 36(6): 1623-1629, 2016

CIT: identification of differentially expressed clusters of genes from microarray data. Bioinformatics 18(1): 205-206, 2002

A regression-based method to identify differentially expressed genes in microarray time course studies and its application in an inducible Huntington's disease transgenic model. Human Molecular Genetics 11(17): 1977-1985, 2002

Identification of differentially expressed genes in human cancer using subtraction and microarray. International Journal of Molecular Medicine 8(Supplement 1): S68, 2001