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In Silico discovery of transcription factors as potential diagnostic biomarkers of ovarian cancer.
- Source :
-
BMC systems biology [BMC Syst Biol] 2011 Sep 19; Vol. 5, pp. 144. Date of Electronic Publication: 2011 Sep 19. - Publication Year :
- 2011
-
Abstract
- Background: Our study focuses on identifying potential biomarkers for diagnosis and early detection of ovarian cancer (OC) through the study of transcription regulation of genes affected by estrogen hormone.<br />Results: The results are based on a set of 323 experimentally validated OC-associated genes compiled from several databases, and their subset controlled by estrogen. For these two gene sets we computationally determined transcription factors (TFs) that putatively regulate transcription initiation. We ranked these TFs based on the number of genes they are likely to control. In this way, we selected 17 top-ranked TFs as potential key regulators and thus possible biomarkers for a set of 323 OC-associated genes. For 77 estrogen controlled genes from this set we identified three unique TFs as potential biomarkers.<br />Conclusions: We introduced a new methodology to identify potential diagnostic biomarkers for OC. This report is the first bioinformatics study that explores multiple transcriptional regulators of OC-associated genes as potential diagnostic biomarkers in connection with estrogen responsiveness. We show that 64% of TF biomarkers identified in our study are validated based on real-time data from microarray expression studies. As an illustration, our method could identify CP2 that in combination with CA125 has been reported to be sensitive in diagnosing ovarian tumors.
- Subjects :
- Binding Sites genetics
Computational Biology methods
Female
Gene Expression Regulation, Neoplastic physiology
Humans
Promoter Regions, Genetic genetics
Biomarkers, Tumor metabolism
Estrogens pharmacology
Gene Expression Regulation, Neoplastic drug effects
Genes, Neoplasm genetics
Ovarian Neoplasms diagnosis
Transcription Factors genetics
Transcription Factors metabolism
Subjects
Details
- Language :
- English
- ISSN :
- 1752-0509
- Volume :
- 5
- Database :
- MEDLINE
- Journal :
- BMC systems biology
- Publication Type :
- Academic Journal
- Accession number :
- 21923952
- Full Text :
- https://doi.org/10.1186/1752-0509-5-144