Characterization of the expression and activation of the epidermal growth factor receptor in squamous cell carcinoma of the skin

Authors


  • Conflicts of interest
    None declared.

Gerald Fogarty, Radiation Oncology Associates, PO Box 1003, Crows Nest 1585, NSW, Australia.
E-mail: gerald.fogarty@mia.net.au

Summary

Background  Locally advanced skin cancers including squamous cell carcinoma (SCC) of the skin are increasing in incidence. Patients are often elderly with significant comorbidities and therapy can be difficult. New targeted therapies, such as treatment directed at the epidermal growth factor receptor (EGFR), may be effective and less toxic in these patients. However, before designing appropriate clinical trials it is necessary to characterize the expression and activation of targets such as the EGFR to evaluate the rationale of using EGFR inhibitors (EGFRIs) in the treatment of this type of cancer.

Objectives  To characterize the expression and activation by phosphorylation of EGFR in SCC of the skin by quantitative Western blotting using the LiCor immunofluorescence detection system with validation by immunohistochemistry. Secondary objectives were to evaluate downstream targets of EGFR expression and activation in SCC of the skin and to examine the associations between EGFR, pathological features and clinical behaviour of these tumours.

Methods  Twenty-one mainly locally advanced skin SCCs collected in our institution and stored in our tissue bank over a 4-year period were used for the study.

Results  Nine of 21 (43%) tumours expressed EGFR above background. Of those nine, five expressed phosphorylated EGFR. There was no correlation with downstream activation of canonical signalling pathways, pathological features or clinical behaviour.

Conclusions  EGFR is expressed in a minority of tumours and then is not always activated. These results show that, before designing a trial with a targeted agent such as an EGFRI in SCC of the skin, it is important to verify the presence of the appropriate target to maximize the best outcome.

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