Digital pathology and image analysis in tissue biomarker research

Digital pathology and the adoption of image analysis have grown rapidly in the last few years. This is largely due to the implementation of whole slide scanning, advances in software and computer processing capacity and the increasing importance of tissue-based research for biomarker discovery and stratified medicine. This review sets out the key application areas for digital pathology and image analysis, with a particular focus on research and biomarker discovery. A variety of image analysis applications are reviewed including nuclear morphometry and tissue architecture analysis, but with emphasis on immunohistochemistry and fluorescence analysis of tissue biomarkers. Digital pathology and image analysis have important roles across the drug/companion diagnostic development pipeline including biobanking, molecular pathology, tissue microarray analysis, molecular profiling of tissue and these important developments are reviewed. Underpinning all of these important developments is the need for high quality tissue samples and the impact of pre-analytical variables on tissue research is discussed. This requirement is combined with practical advice on setting up and running a digital pathology laboratory. Finally, we discuss the need to integrate digital image analysis data with epidemiological, clinical and genomic data in order to fully understand the relationship between genotype and phenotype and to drive discovery and the delivery of personalized medicine.

RAS testing of colorectal carcinoma—a guidance document from the Association of Clinical Pathologists Molecular Pathology and Diagnostics Group

Analysis of colorectal carcinoma (CRC) tissue for KRAS codon 12 or 13 mutations to guide use of anti-epidermal growth factor receptor (EGFR) therapy is now considered mandatory in the UK. The scope of this practice has been recently extended because of data indicating that NRAS mutations and additional KRAS mutations also predict for poor response to anti-EGFR therapy. The following document provides guidance on RAS (i.e., KRAS and NRAS) testing of CRC tissue in the setting of personalised medicine within the UK and particularly within the NHS. This guidance covers issues related to case selection, preanalytical aspects, analysis and interpretation of such RAS testing.

Automated tumour annotation and analysis for molecular pathology using TissueMark (R)

Objective: Molecular pathology relies on identifying anomalies using PCR or analysis of DNA/RNA. This is important in solid tumours where molecular stratification of patients define targeted treatment. These molecular biomarkers rely on examination of tumour, annotation for possible macro dissection/tumour cell enrichment and the estimation of % tumour. Manually marking up tumour is error prone. Method: We have developed a method for automated tumour mark-up and % cell calculations using image analysis called TissueMark® based on texture analysis for lung, colorectal and breast (cases=245, 100, 100 respectively). Pathologists marked slides for tumour and reviewed the automated analysis. A subset of slides was manually counted for tumour cells to provide a benchmark for automated image analysis. Results: There was a strong concordance between pathological and automated mark-up (100 % acceptance rate for macro-dissection). We also showed a strong concordance between manually/automatic drawn boundaries (median exclusion/inclusion error of 91.70 %/89 %). EGFR mutation analysis was precisely the same for manual and automated annotation-based macrodissection. The annotation accuracy rates in breast and colorectal cancer were 83 and 80 % respectively. Finally, region-based estimations of tumour percentage using image analysis showed significant correlation with actual cell counts. Conclusion: Image analysis can be used for macro-dissection to (i) annotate tissue for tumour and (ii) estimate the % tumour cells and represents an approach to standardising/improving molecular diagnostics.

Role of the receptor for advanced glycation endproducts (RAGE) in retinal vasodegenerative pathology during diabetes in mice

Aims/hypothesis
The receptor for AGEs (RAGE) is linked to proinflammatory pathology in a range of tissues. The objective of this study was to assess the potential modulatory role of RAGE in diabetic retinopathy.
Methods
Diabetes was induced in wild-type (WT) and Rage −/− mice (also known as Ager −/− mice) using streptozotocin while non-diabetic control mice received saline. For all groups, blood glucose, HbA1c and retinal levels of methylglyoxal (MG) were evaluated up to 24 weeks post diabetes induction. After mice were killed, retinal glia and microglial activation, vasopermeability, leucostasis and degenerative microvasculature changes were determined. 

Results
Retinal expression of RAGE in WT diabetic mice was increased after 12 weeks (p < 0.01) but not after 24 weeks. Rage −/− mice showed comparable diabetes but accumulated less MG and this corresponded to enhanced activity of the MG-detoxifying enzyme glyoxalase I in their retina when compared with WT mice. Diabetic Rage −/− mice showed significantly less vasopermeability, leucostasis and microglial activation (p < 0.05–0.001). Rage −/− mice were also protected against diabetes-related retinal acellular capillary formation (p < 0.001) but not against pericyte loss. 

Conclusions/interpretation Rage −/− in diabetic mice is protective against many retinopathic lesions, especially those related to innate immune responses. Inhibition of RAGE could be a therapeutic option to prevent diabetic retinopathy.