Analysis of Gene Expression Using Gene Sets Discriminates Cancer Patients with and without Late Radiation Toxicity
2006

Gene Expression Profiling and Radiation Toxicity in Cancer Patients

Sample size: 38 publication 10 minutes Evidence: moderate

Author Information

Author(s): Svensson J. Peter, Stalpers Lukas J. A, Lange Rebecca E. E. Esveldt–van, Franken Nicolaas A. P, Haveman Jaap, Klein Binie, Turesson Ingela, Vrieling Harry, Giphart-Gassler Micheline

Primary Institution: Leiden University Medical Center

Hypothesis

The cellular response of normal tissue to X-rays could discriminate patients with and without late radiation toxicity.

Conclusion

Gene expression profiling can distinguish groups of patients with and without severe late radiotherapy toxicity, but predicting individual responses needs improvement.

Supporting Evidence

  • The gene set classifier improved correct classification to 86%.
  • The apoptotic response was more pronounced in patients that did not develop toxicity.
  • In an independent set of 12 patients, the toxicity status of eight was predicted correctly by the gene set classifier.

Takeaway

Scientists studied blood samples from cancer patients to see if their genes could help predict who would get sick from radiation treatment. They found some patterns that worked for groups of patients, but not for individuals yet.

Methodology

Blood samples from prostate cancer patients were analyzed for gene expression after X-ray irradiation to classify patients based on their response.

Potential Biases

Potential misclassification of patients based on clinical symptoms rather than genetic predisposition.

Limitations

The study focused on extreme responders, which may limit the generalizability of the findings.

Participant Demographics

Patients were prostate cancer survivors, with 21 having severe late radiation toxicity and 17 without.

Statistical Information

P-Value

p<0.001

Confidence Interval

95% confidence intervals for misclassification rates

Statistical Significance

p<0.001

Digital Object Identifier (DOI)

10.1371/journal.pmed.0030422

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