The current gold standard for diagnostic classification of many solid-tissue neoplasms is immunohistochemistry (IHC) performed on formalin-fixed, paraffin-embedded (FFPE) tissue. Although IHC is commonly used, there remain important issues related to preanalytic variability, nonstandard methods, and operator bias that may contribute to clinically significant error. To increase the quantitative accuracy and reliability of FFPE tissue-based diagnosis, we sought to develop a clinical proteomic method to characterize protein expression in pathologic tissue samples rapidly and quantitatively.We subclassified FFPE tissue from 136 clinical pituitary adenoma samples according to hormone translation with IHC and then extracted tissue proteins and quantified pituitary hormones with multiplex bead-based immunoassays. Hormone concentrations were normalized and compared across diagnostic groups. We developed a quantitative classification scheme for pituitary adenomas on archived samples and validated it on prospectively collected clinical samples.The most abundant relative hormone concentrations differentiated sensitively and specifically between IHC-classified hormone-expressing adenoma types, correctly predicting IHC-positive diagnoses in 85% of cases overall, with discrepancies found only in cases of clinically nonfunctioning adenomas. Several adenomas with clinically relevant hormone-expressing phenotypes were identified with this assay yet called "null" by IHC, suggesting that multiplex immunoassays may be more sensitive than IHC for detecting clinically meaningful protein expression.Multiplex immunoassays performed on FFPE tissue extracts can provide diagnostically relevant information and may exceed the performance of IHC in classifying some pituitary neoplasms. This technique is simple, largely amenable to automation, and likely applicable to other diagnostic problems in molecular pathology.
Techniques to evaluate gene expression profiling, including real-time quantitative PCR, TaqMan low-density arrays, and sufficiently sensitive cDNA microarrays, are efficient methods for monitoring human embryonic stem cell (hESC) cultures. However, most of these high-throughput tests have a limited use due to high cost, extended turnaround time, and the involvement of highly specialized technical expertise. Hence, there is a paucity of rapid, cost-effective, robust, yet sensitive methods for routine screening of hESCs. A critical requirement in hESC cultures is to maintain a uniform undifferentiated state and to determine their differentiation capacity by showing the expression of gene markers representing all germ layers, including ecto-, meso-, and endoderm. To quantify the modulation of gene expression in hESCs during their propagation, expansion, and differentiation via embryoid body (EB) formation, the authors developed a simple, rapid, inexpensive, and definitive multimarker, semiquantitative multiplex RT-PCR (mxPCR) platform technology. Among the 15 gene primers tested, 4 were pluripotent markers comprising set 1, and 3 lineage-specific markers from each ecto-, meso-, and endoderm layers were combined as sets 2 to 4, respectively. The authors found that these 4 sets were not only effective in determining the relative differentiation in hESCs, but were easily reproducible. In this study, they used the HUES-7 cell line to standardize the technique, which was subsequently validated with HUES-9, NTERA-2, and mouse embryonic fibroblast cells. This single-reaction mxPCR assay was flexible and, by selecting appropriate reporter genes, can be designed for characterization of different hESC lines during routine maintenance and directed differentiation.