Using Insulin-like growth factor genes to predict outcome in breast and lung cancer patients

As the era of personalised medicine and genomics evolves and the potential for better targeted treatments becomes a reality, the need to identify which individual treatments will benefit each individual patient is becoming imperative. One way to do this is to try and identify predictive gene signatures.  This is what Rajski and colleagues have done in the article published this week in BMC Medicine; “IGF-I induced genes in stromal fibroblasts predict the clinical outcome of breast and lung cancer patients”, using cell lines to first develop the signature, and later validating their data in clinical patient samples.

In the accompanying commentary, Werner and Bruchim nicely outline the broader background to the article and explain the way in which Rajski and colleagues’ findings contribute not only to insulin-growth factor-targeted therapies for breast and lung cancer, but also more generally to the development of gene signatures for prediction of treatment response.

Why not visit the BMC Medicine webpage and check out the full story?

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