Comparison of progestin transcriptional profiles in rat mammary gland using Laser Capture Microdissection and whole tissue-sampling.

Introduction: Investigation of molecular mechanisms by gene expression profiling gains increasingly importance in preclinical safety evaluation. However, assigning expressed genes to specific cell populations is nearly impossible if the investigated RNA originates from whole tissue extracts. In this regard, Laser Capture Microdissection (LCM) can be used to detect changes specific to individual cell types. The objective of this study was to investigate the use of LCM for characterisation of progestin-related gene expression changes in the mammary gland. Thus, transcriptional profiles of the mammary gland of rats treated with a non-steroidal progesterone-receptor ligand, promegestone, medroxyprogesterone acetate, progesterone or vehicle were compared using whole tissue homogenates or LCM-captured epithelial cells.

Methods: Total RNA from 30 mammary glands was isolated from snap-frozen specimen of the whole tissue and from approximately 25.000-30.000 cells of cresyl violet stained frozen sections employing LCM. After amplification of averaged 0.2μg total RNA of LCM-captured samples, RNA was labelled, hybridised to Affymetrix GeneChips and analysed.

Results: LCM-captured samples showed up to 3-fold more differentially expressed probe sets (progesterone) and up to 10-fold more downregulated (promegestone) probe sets than whole tissue samples implying high cell specificity. Moreover, mammary gland specific differentiation markers like whey acidic protein, alpha lactalbumin, casein alpha s1 and casein kappa showed up to 3.4-fold (alpha lactalbumin, vehicle) higher expression values. Multivariate data analyses revealed a clear separation of gene expression profiles according to the method used, suggesting an amplification dependent bias.

Discussion: LCM transcriptional profiling provides highly cell-specific information. An amplification dependent bias was observed. The technical variability was shown to be smaller than the biological variability. For progestin-related transcriptional profiling of the mammary gland, whole tissue-sampling proved to yield more informative results. Therefore LCM should only be considered when cell-type specific gene expression profiles are necessary for an in depth evaluation.