In Silico discovery of transcription factors as potential diagnostic biomarkers of ovarian cancer
2011

Identifying Biomarkers for Ovarian Cancer

Sample size: 323 publication Evidence: moderate

Author Information

Author(s): Mandeep Kaur, Cameron R. MacPherson, Sebastian Schmeier, Kothandaraman Narasimhan, Mahesh Choolani, Vladimir B. Bajic

Primary Institution: King Abdullah University of Science and Technology

Hypothesis

Can transcription factors be identified as potential diagnostic biomarkers for ovarian cancer?

Conclusion

The study successfully identified 17 transcription factors as potential biomarkers for ovarian cancer, with 64% of them validated by real-time data.

Supporting Evidence

  • 64% of the identified transcription factor biomarkers were validated based on real-time data from microarray expression studies.
  • The study is the first bioinformatics analysis exploring multiple transcriptional regulators of ovarian cancer-associated genes.
  • Three unique transcription factors were identified as potential biomarkers for a subset of estrogen-controlled genes.

Takeaway

The researchers found some proteins that might help doctors detect ovarian cancer earlier by looking at how certain genes are controlled by hormones.

Methodology

The study used computational methods to analyze the promoters of 323 ovarian cancer-associated genes for estrogen response elements and transcription factor binding sites.

Potential Biases

The reliance on computational predictions may introduce biases if the underlying data is incomplete or inaccurate.

Limitations

The study's analysis was limited to a specific size of promoter regions and did not consider remote regulatory regions like enhancers.

Statistical Information

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1186/1752-0509-5-144

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