Silicone gel breast implants.

While gonadotropin-releasing hormone (GnRH) or GnRH receptor (GnRHR) have been reported to exist in tissues other than brain and pituitary, there is no report concerning co-expression of GnRH and GnRHR in human breast tissues. To address this question, we have examined whether mRNA for GnRH as well as GnRHR was present in different human breast samples, by employing the reverse transcription-polymerase chain reaction (RT-PCR) protocol followed by Southern blotting of the PCR products. Coexpression of GnRH and GnRHR genes was further confirmed by dot blot hybridization using appropriate [32P]-labeled probes. We thus tested fibrocystic breast (4 cases), invasive ductal carcinomas (6 cases) and 1 adjacent non-neoplastic tissue. GnRHR and GnRH mRNAs were found in all actin-positive samples including malignant as well as nonmalignant tissues. Quantitative determinations of mRNA did not reveal significant differences between malignant and non-malignant breast samples for either GnRH or GnRHR gene expression. Our data show that neither gene was overexpressed in the breast cancer samples compared with normal breast tissue. Since GnRH agonists inhibit breast epithelial cell growth, the presence of GnRHR mRNA suggests that GnRH may specifically affect breast cell growth. Our data thus raise the possibility of an autocrine/paracrine role for GnRH in human mammary gland.

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PubMed1997

Discrimination of fibroblast subtypes by multivariate analysis of gene expression.

Fibroblasts and myofibroblasts from normal, fibrotic or tumoral breast tissues present multiple quantitative differences in gene expression even when grown in isolation. We were therefore prompted to investigate whether one could recognize various subtypes by their constitutive-gene expression profile. Quantitative autoradiographic data for 34 constitutively expressed transcripts were submitted to multivariate analysis of variance, followed by discriminant analysis and single linkage cluster analysis. Models assuming up to 8 putative fibroblast subtypes (among fibroblasts or myofibroblasts from breast skin, normal mammary stroma, tumor-adjacent "normal" stroma, post-radiation fibrosis lesions and benign or malignant tumors) and an epithelial-cell group used as an internal control resulted in 100% correct classification. Myofibroblasts from various origins clustered close to, although distinctly apart from, their corresponding alpha-smooth-muscle-actin-negative counterparts. Malignant tumor fibroblasts were phenotypically more distant from normal cells compared with other pathological types. Our results support the hypothesis of co-adaptive transformation of stromal and epithelial tissues during breast tumoral development and suggest that different types of fibroblasts give rise to different types of myofibroblasts. Discriminant analysis of quantitative molecular variation may be considered for the development of a powerful artificial-intelligence method for cell typing and should be particularly useful when no reliable discrete molecular markers are available.

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