Multiplex immunoassays of peptide hormones extracted from formalin-fixed, paraffin-embedded tissue accurately subclassify pituitary adenomas

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Figure. 1

Assay linearity assessed by performing reciprocal dilutions on duplicate specimens containing high or low concentrations of each analyte. Slope, intercept, and r² are given in the associated table.

Figure 2

ROC Analysis comparing the ability of the multiplex pituitary hormone quantification to predict IHC diagnoses. Solid line, training set; dashed line, validation set. AUC values are given for each analyte, with the first number the AUC for the training set, and the second number the AUC for the validation set. In each panel, samples with IHC-positive diagnoses for each hormone are counted as true positives, and all other samples (IHC-positive for another hormone or IHC-null) are counted as true negatives.

Figure 3

Performance of the quantitative assay on pituitary adenoma samples with different IHC diagnoses. Each column represents samples with the same IHC diagnosis, and the colored segments of the bar correspond to the number of samples that contained the highest fractional concentration of the indicated hormone.

Figure 4

(A) The first 2 principal components taken from principal component analysis of the training set data. IHC-positive samples are color-coded, according to the legend, and IHC-null samples are shown as open circles. (B) Biplot showing the eigenvectors associated with each hormone indicates the direction in which IHC-positive samples cluster. (C) Relative hormone concentration data from the validation set projected into the principal component space defined by the training set.