Tamara Aleksic, Andrew Ross Worrall, Clare Verrill, Helen Turley, Leticia Campo and Valentine M Macaulay
Background: Insulin-like growth factors (IGFs) are known to play important roles in cancer biology, prompting evaluation of drugs targeting type 1 IGF receptor (IGF-1R). However, there is considerable lack of consensus in immunohistochemical (IHC) studies of IGF-1R in human tumors, confounding attempts to assess the predictive and prognostic significance of IGF-1R expression and subcellular localization. Likely sources of variation include use of different IGF-1R polyclonal antibodies and methods for IHC. Here, we aimed to develop a robust IGF-1R IHC protocol using a monoclonal antibody, suitable for use in formalin-fixed paraffin-embedded (FFPE) tissues.
Methods: Using controls including samples of FFPE tissues and tumor cells of defined IGF-1R expression, we used IHC and western blotting to compare polyclonal antibody #3027 with monoclonals #9750 and #14534 (Cell Signaling Technology).
Results: Compared with #3027, the monoclonals exhibited superior discrimination between IGF-1R-high and IGF-1R-deficient cells in manual IHC, signal generated by #9750 reflecting differences in IGF-1R expression detected by western blotting. In tissues, IGF-1R detected by #14534 was predominantly plasma membrane-associated, while #9750 detected IGF-1R in the plasma membranes, cytoplasm and nucleus of prostate and renal cancers, recapitulating appearances we described using previous lots of #3027, and reflecting subcellular localizations reported using other techniques. Use of #9750 and #14534 in an autostainer showed adequate differentiation of high vs low IGF-1R cells, but did not recapitulate appearances of manually-stained tissues. We provide a detailed protocol for the preferred manual method using #9750.
Conclusion: Standardization of IGF-1R IHC will promote understanding of the role of IGF-1R in tumor biology, and its potential as a candidate prognostic and predictive biomarker.
Share this article
Immunochemistry & Immunopathology received 174 citations as per Google Scholar report
