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Our study demonstrates that (i) ErbB/HER ligands, including BTC and EREG, are expressed in most breast cancers; and (ii) TGFalpha, HB-EGF and NRG2 high expressions are related to the biological aggressiveness of the tumours.

The first step of the action of IGF1 and IGF2 (IGFs) is their binding to membrane receptors. IGF binding sites have been characterized by competitive binding and cross-linking techniques in human breast cancer cell lines as well as in human breast cancers and in human benign breast diseases. IGF2 is a good competitor of 125I-IGF1 binding to IGF1-R; insulin competes but with a potency 1/100 lower than the IGF1 potency. Chemical cross-linking experiments revealed that the apparent molecular weight of the IGF1-binding sites is 130,000. Alpha IR-3, a murine monoclonal antibody against the IGF1-R, blocks IGF1-binding to this receptor. This antibody inhibits the IGF1-stimulated growth of breast cancer cells. Therefore, the IGF1 specific binding sites correspond to the previously described type 1 IGF receptors (IGF1-R) in normal tissues. Cross-linking experiments with labeled IGF2 resulted in a major band of apparent Mr 260,000-270,000 that was inhibited by unlabeled IGF2 but not by insulin, and corresponds to the type 2 IGF receptor; a second band of apparent Mr 130,000 was inhibited by excess IGFs and insulin (Type I receptor). The alpha-IR3 inhibition of the IGF2 mitogenic activity suggest that IGF1-R partially mediates the growth effect of IGF2 in these cells. We and others have demonstrated that most breast cancer cell lines contain IGF1-R.(ABSTRACT TRUNCATED AT 250 WORDS)

In this report we present an extension of the pooled analysis of the prognostic impact of urokinase-type plasminogen activator (uPA) and its inhibitor PAI-I in breast cancer patients. We analyzed a different endpoint, metastasis-free survival (MFS). We checked the consistency of the estimates for uPA and PAI-1 for relapse-free survival (RFS) and MFS exploring possible sources of heterogeneity. Nodal status, the most important prognostic factor for breast cancer, introduced heterogeneity in the uPA/PAI-1 survival analyses, reflecting the interaction between nodal status and uPA/PAI-1. The estimates for uPA and PAI-1 were found to be consistent, even when a different transformation of their values was used. The heterogeneity of the separate data sets decreased if the levels of uPA and PAI-1 were ranked, data sets were pooled, and the analyses corrected for the base model that included all traditional prognostic factors, and stratified by data set. We conclude that uPA and PAI-1 are ready to be used in the clinic to help classify breast cancer patients into high and low risk groups.

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