Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis
2011

Studying the EGF Dependent Transcriptome in HeLa Cells

Sample size: 3 publication Evidence: high

Author Information

Author(s): Llorens Franc, Hummel Manuela, Pastor Xavier, Ferrer Anna, Pluvinet Raquel, Vivancos Ana, Castillo Ester, Iraola Susana, Mosquera Ana M, González Eva, Lozano Juanjo, Ingham Matthew, Dohm Juliane C, Noguera Marc, Kofler Robert, del Río Jose Antonio, Bayés Mònica, Himmelbauer Heinz, Sumoy Lauro

Primary Institution: Center for Genomic Regulation (CRG) - Universitat Pompeu Fabra (UPF), Barcelona, Spain

Hypothesis

Can a combined approach using microarrays and deep sequencing provide a comprehensive understanding of the EGF dependent transcriptome?

Conclusion

The study successfully identifies a robust set of EGF-regulated genes and their interactions, enhancing the understanding of EGF signaling in cancer.

Supporting Evidence

  • The study established a well-validated gene set with transcript levels altered after EGF treatment.
  • New genes previously unrelated to EGF functions were identified.
  • Cross-platform data meta-analysis was applied to enhance reliability.

Takeaway

Researchers looked at how a growth factor called EGF affects genes in cancer cells, finding many important connections and new genes involved.

Methodology

The study used multiple microarray platforms and digital gene expression profiling to analyze gene expression in HeLa cells treated with EGF.

Potential Biases

Potential cross-hybridization artifacts and discrepancies between platforms could affect results.

Limitations

The study may have biases due to the different platforms used and the inherent noise in microarray data.

Participant Demographics

HeLa cells, a human cervical cancer cell line.

Statistical Information

P-Value

p<0.05

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1186/1471-2164-12-326

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