Promises and caveats of in silico biomarker discovery
Author Information
Author(s): Pusztai L, Leyland-Jones B
Primary Institution: The University of Texas, M.D. Anderson Cancer Center
Conclusion
In silico analysis of gene expression data can help identify potential biomarkers for breast cancer, but results may not be clinically reliable without further validation.
Supporting Evidence
- Several biomarkers have been reported to be associated with survival in breast cancer.
- Many past trials lack tumor banks, making it hard to obtain specimens.
- High-throughput genomic tools are increasingly applied to discover predictors of clinical outcomes.
Takeaway
Scientists are using computer data to find clues about breast cancer markers, but they need to be careful because the data might not always be accurate.
Methodology
The study involved in silico analysis of publicly available gene expression data.
Potential Biases
Technical noise and differences in analytical methods can affect the reliability of the findings.
Limitations
Results from in silico analysis depend on the quality of the source data and may not be clinically accepted without further validation.
Digital Object Identifier (DOI)
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