Clinical radiobiologyImpact of supervised gene signatures of early hypoxia on patient survival
Section snippets
Data set
The starting material was the data set provided by the study of Chi et al., which represents, to our knowledge, the largest set of time series under hypoxia with 2.4 million of gene expression measurements. Four normal cell lines were used: human coronary artery endothelial cells (ECs), smooth muscle cells (SMCs), human mammary epithelial cells (HMECs), and renal proximal tubule epithelial cells (RPTECs 1 and 2) under two oxygen concentrations (less than 0.02% and 2%). Using cDNA microarrays of
Results
Correlating genes with a predefined pattern of interest was used to derive early hypoxia gene signatures from the HMEC cell lines under 0% and 2% oxygen. The genes reaching a correlation with the required temporal profile greater than 0.6 and a 2-fold induction or more were selected (Table 2). Results from log-rank tests on the Miller data set are reported in Table 3.
Early hypoxia
In this paper, we focus on the impact of the early response to hypoxia which with the exception of a few studies (e.g. [12]) is rarely investigated by means of microarrays. Due to potential differences arising for different oxygen concentrations, the two time series were treated independently. Both early hypoxia signatures were significant (p < 0.01 at 0%; p < 0.05 at 2%) whereas none of the late signatures were. A signature of the 15 common UniGenes (13 symbols) found in the two early signatures
Conclusions
This analysis shows that, consistent with our hypothesis, the early and late hypoxia responses are very different at the transcription level. In a relatively old cohort of patients with primary breast cancer treated by locoregional therapy and systemic adjuvant therapy, it was shown that early hypoxia signatures, but not late hypoxia responses, could correlate with survival differences. It suggests that gene signatures can provide a means to select patients for individualized therapy.
Acknowledgements
We acknowledge financial support from Siemens (to R.S. and M.H.W.S.), the Dutch Science Organization (ZonMW-NWO Top Grant 912-03-047 to B.W.), the Dutch Cancer Society (KWF Grant UM 2003-2821 to B.W.), and the EU 6th framework program (Euroxy program to B.W.).
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