Immunohistochemical (IHC) assays performed on formalin-fixed paraffin-embedded (FFPE) tissue sections traditionally have been semi-quantified by pathologist visual scoring of staining. IHC is useful for validating biomarkers discovered through genomics methods as large clinical repositories of FFPE specimens support the construction of tissue microarrays (TMAs) for high throughput studies. Due to the ubiquitous availability of IHC techniques in clinical laboratories, validated IHC biomarkers may be translated readily into clinical use. However, the method of pathologist semi-quantification is costly, inherently subjective, and produces ordinal rather than continuous variable data. Computer-aided analysis of digitized whole slide images may overcome these limitations. Using TMAs representing 215 ovarian serous carcinoma specimens stained for S100A1, we assessed the degree to which data obtained using computer-aided methods correlated with data obtained by pathologist visual scoring. To evaluate computer-aided image classification, IHC staining within pathologist annotated and software-classified areas of carcinoma were compared for each case. Two metrics for IHC staining were used: the percentage of carcinoma with S100A1 staining (%Pos), and the product of the staining intensity (optical density [OD] of staining) multiplied by the percentage of carcinoma with S100A1 staining (OD*%Pos). A comparison of the IHC staining data obtained from manual annotations and software-derived annotations showed strong agreement, indicating that software efficiently classifies carcinomatous areas within IHC slide images. Comparisons of IHC intensity data derived using pixel analysis software versus pathologist visual scoring demonstrated high Spearman correlations of 0.88 for %Pos (p < 0.0001) and 0.90 for OD*%Pos (p < 0.0001). This study demonstrated that computer-aided methods to classify image areas of interest (e.g., carcinomatous areas of tissue specimens) and quantify IHC staining intensity within those areas can produce highly similar data to visual evaluation by a pathologist.Virtual slidesThe virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1649068103671302

Genetic changes required for the formation and progression of human Schwann cell tumors remain elusive. Using a Sleeping Beauty forward genetic screen, we identified several genes involved in canonical Wnt signaling as potential drivers of benign neurofibromas and malignant peripheral nerve sheath tumors (MPNSTs). In human neurofibromas and MPNSTs, activation of Wnt signaling increased with tumor grade and was associated with down-regulation of β-catenin destruction complex members or overexpression of a ligand that potentiates Wnt signaling, R-spondin 2 (RSPO2). Induction of Wnt signaling was sufficient to induce transformed properties to immortalized human Schwann cells, and down-regulation of this pathway was sufficient to reduce the tumorigenic phenotype of human MPNST cell lines. Small molecule inhibition of Wnt signaling effectively reduced viability of MPNST cell lines, and synergistically induced apoptosis when combined with an mTOR inhibitor, RAD-001, suggesting that Wnt inhibition represents a novel target for therapeutic intervention in Schwann cell tumors.