TRARESA: a tissue microarray-based hospital system for biomarker validation and discovery

Formalin fixed and paraffin embedded tissue (FFPE) collections in pathology departments are the largest resource for retrospective biomedical research studies. Based on the literature analysis of FFPE related research, as well as our own technical validation, we present the Translational Research Arrays (TRARESA), a tissue microarray centred, hospital based, translational research conceptual framework for both validation and/or discovery of novel biomarkers. TRARESA incorporates the analysis of protein, DNA and RNA in the same samples, correlating with clinical and pathological parameters from each case, and allowing (a) the confirmation of new biomarkers, disease hypotheses and drug targets, and (b) the postulation of novel hypotheses on disease mechanisms and drug targets based on known biomarkers. While presenting TRARESA, we illustrate the use of such a comprehensive approach. The conceptualisation of the role of FFPE-based studies in translational research allows the utilisation of this commodity, and adds to the hypothesis-generating armamentarium of existing high-throughput technologies.

Tissue microarray study for classification of breast tumors

Clinical and pathological heterogeneity of breast cancer hinders selection of appropriate treatment for individual cases. Molecular profiling at gene or protein levels may elucidate the biological variance of tumors and provide a new classification system that correlates better with biological, clinical and prognostic parameters. We studied the immunohistochemical profile of a panel of seven important biomarkers using tumor tissue arrays. The tumor samples were then classified with a monothetic (binary variables) clustering algorithm. Two distinct groups of tumors are characterized by the estrogen receptor (ER) status and tumor grade (p = 0.0026). Four biomarkers, c-erbB2, Cox-2, p53 and VEGF, were significantly overexpressed in tumors with the ER-negative (ER-) phenotype. Eight subsets of tumors were further identified according to the expression status of VEGF, c-erbB2 and p53. The malignant potential of the ER-/VEGF+ subgroup was associated with the strong correlations of Cox-2 and c-erb132 with VEGF. Our results indicate that this molecular classification system, based on the statistical analysis of immunohistochemical profiling, is a useful approach for tumor grouping. Some of these subgroups have a relative genetic homogeneity that may allow further study of specific genetically-controlled metabolic pathways. This approach may hold great promise in rationalizing the application of different therapeutic strategies for different subgroups of breast tumors. (C) 2003 Elsevier Inc. All rights reserved.

Ultra-fast processing of gigapixel Tissue MicroArray images using high performance computing.

BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.

Tissue microarrays characterise the clinical significance of a VEGF-A protein expression signature in gastrointestinal stromal tumours

A tissue microarray analysis of 22 proteins in gastrointestinal stromal tumours ( GIST), followed by an unsupervised, hierarchical monothetic cluster statistical analysis of the results, allowed us to detect a vascular endothelial growth factor ( VEGF) protein overexpression signature discriminator of prognosis in GIST, and discover novel VEGF-A DNA variants that may have functional significance.

Reliability of tissue microarrays in detecting protein expression and gene amplification in breast cancer

Tissue microarrays allow high throughput molecular profiling of diagnostic or predictive markers in cancer specimens and rapid validation of novel potential candidates identified from genomic and proteomic analyses in a large number of tumor samples. To validate the use of tissue microarray technology for all the main biomarkers routinely used to decide breast cancer prognostication and postsurgical adjuvant therapy, we constructed a tissue microarray from 97 breast tumors, with a single 0.6 mm core per specimen. Inummostaining; of tissue microarray sections and conventional full sections of each tumor were performed using well-characterized prognostic markers (estrogen receptor ER, progesterone receptor PR and c-erbB2). The full section versus tissue microarray concordance for these stains was 97% for ER, 98% for PR, and 97% for c-erbB2, respectively, with a strong statistical association (kappa value more than 0.90). Fluorescence in situ hybridization analysis for HER-2/neu gene amplification from the single-core tissue microarray was technically successful in about 90% (87/97) of the cases, with a concordance of 95% compared with parallel analyses with the full sections. The correlation with other pathological parameters was not significantly different between full-section and array-based results. It is concluded that the constructed tissue microarray with a single core per specimen ensures full biological representativeness to identify the associations between biomarkers and clinicopathological parameters, with no significant associated sampling bias.

Evaluation of HER-2/neu oncogene status in breast tumors on tissue microarrays

The amplification and/or overexpression of the HER-2/neu oncogene and its encoded receptor protein are increasingly used for prognostication and prediction of therapeutic response to Herceptin in breast cancer. However, large-scale examination of archival tumor blocks by immunohistochemistry (IHC) or fluorescence in situ hybridization (FISH) is prohibitively laborious and technically challenging. The tissue microarray (TMA) technique enables hundreds of tumors to be studied simultaneously in a single experiment. To evaluate the HER-2/neu status of a selection of the breast tumors in our tumor bank, we constructed a TMA from 97 breast tumors, with a single 0.6-mm core per specimen. HER-2/neu gene amplification by FISH was found in 20 of the 87 interpretable cases (23%): in 14 of 14 IHC 3+ cases (100%), 5 of 8 IHC 2+ cases (62.5%) and 1 of 65 IHC 0/1+ cases (1.5%). Three of the 67 cases with no evidence of HER-2/neu gene amplification by FISH were moderately positive (2+) by IHC. A close relationship was observed between these 2 assays as applied to the TMA (95.4% concordance: 95% CI, - 2.2% to 6.8%; P

Robust automated tumour segmentation on histological and immunohistochemical tissue images

Tissue microarray (TMA) is a high throughput analysis tool to identify new diagnostic and prognostic markers in human cancers. However, standard automated method in tumour detection on both routine histochemical and immunohistochemistry (IHC) images is under developed. This paper presents a robust automated tumour cell segmentation model which can be applied to both routine histochemical tissue slides and IHC slides and deal with finer pixel-based segmentation in comparison with blob or area based segmentation by existing approaches. The presented technique greatly improves the process of TMA construction and plays an important role in automated IHC quantification in biomarker analysis where excluding stroma areas is critical. With the finest pixel-based evaluation (instead of area-based or object-based), the experimental results show that the proposed method is able to achieve 80% accuracy and 78% accuracy in two different types of pathological virtual slides, i.e., routine histochemical H&E and IHC images, respectively. The presented technique greatly reduces labor-intensive workloads for pathologists and highly speeds up the process of TMA construction and provides a possibility for fully automated IHC quantification.

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.

Absence of aquaporin-4 expression in lesions of neuromyelitis optica but increased expression in multiple sclerosis lesions and normal-appearing white matter.

Aquaporin-4 (AQP4) has recently been implicated in the pathogenesis of neuromyelitis optica(NMO) where it has been identifed as the first defined autoantigen pertinent to an infammatory demyelinating disorder of the human CNS. Furthermore, a recent case report has shown a lack of AQP4 expression in the spinal cord lesions of NMO. However, the pattern of AQP4 expression in multiple sclerosis (MS) tissues has not been well-defned. In the present investigation we have confirmed a lack of expression of AQP4 in optic and spinal cord lesions in NMO which contrasted sharply with the increased levels of AQP4 expression seen in MS lesions. Furthermore a detailed immunohistochemical and semi-quantitative analysis is used to describe the expression pattern of AQP4 on well-characterized tissue microarray samples of MS and control white matter. Anatomically AQP4 was more highly expressed in all categories of MS tissue compared to normal control tissues with the most abundant expression in active lesions. Within active lesions AQP4 expression was significantly correlated with expression of the pro-infammatory cytokine osteopontin. At the cellular level dual-labelling immunofluoresence demonstrated that increased expression of AQP4 was most pronounced at the astrocytic endfeet but was also associated with the cell bodies of astrocytes in the tissue parenchyma. The finding of increased AQP4 expression in MS lesions in contrast to the lack of expression in NMO lesions may suggest different mechanisms of initiation and progression between the two disease states.

Activated oncogenic pathways and therapeutic targets in extranodal nasal-type NK/T cell lymphoma revealed by gene expression profiling

We performed comprehensive genome-wide gene expression profiling (GEP) of extranodal nasal-type natural killer/T-cell lymphoma (NKTL) using formalin-fixed, paraffin-embedded tissue (n = 9) and NK cell lines (n = 5) in comparison with normal NK cells, with the objective of understanding the oncogenic pathways involved in the pathogenesis of NKTL and to identify potential therapeutic targets. Pathway and network analysis of genes differentially expressed between NKTL and normal NK cells revealed significant enrichment for cell cycle-related genes and pathways, such as PLK1, CDK1, and Aurora-A. Furthermore, our results demonstrated a pro-proliferative and anti-apoptotic phenotype in NKTL characterized by activation of Myc and nuclear factor kappa B (NF-kappa B), and deregulation of p53. In corroboration with GEP findings, a significant percentage of NKTLs (n = 33) overexpressed c-Myc (45.4%), p53 (87.9%), and NF-kappa B p50 (67.7%) on immunohistochemistry using a tissue microarray containing 33 NKTL samples. Notably, overexpression of survivin was observed in 97% of cases. Based on our findings, we propose a model of NKTL pathogenesis where deregulation of p53 together with activation of Myc and NF-kappa B, possibly driven by EBV LMP-1, results in the cumulative up-regulation of survivin. Down-regulation of survivin with Terameprocol (EM-1421, a survivin inhibitor) results in reduced cell viability and increased apoptosis in tumour cells, suggesting that targeting survivin may be a potential novel therapeutic strategy in NKTL. Copyright (C) 2011 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Cofilin immunolabelling correlates with depth of invasion in gastrointestinal endocrine cell tumors

Gastrointestinal endocrine cell tumors are a heterogeneous population of lesions believed to arise from neuroendocrine cells of the gastrointestinal mucosa. The current classification of these tumors is based on tumor size, microscopic features and clinical evidence of metastasis. Although diagnostic categories generally correlate with prognosis, molecular prognostic markers will be clinically useful adjuncts. Cofilin has been implicated in tumor invasion, and its immunolocalisation was studied in gastrointestinal endocrine cell tumors. The immunolocalisation of cofilin was studied by immunohistochemistry in 34 formalin-fixed, paraffin wax-embedded gastrointestinal endocrine cell tumors using a tissue microarray platform. A significant correlation was found between high cofilin immunolabelling and the depth of invasion (p

PIM-1 kinase expression in adipocytic neoplasms: diagnostic and biological implications

The differential diagnosis of soft tissue tumours poses a considerable challenge for pathologists, especially adipocytic tumours, as these may show considerable overlap in clinical presentation and morphological features with many other mesenchymal neoplasms. Hence, a specific and reliable marker that identifies adipocytic differentiation is much sought. We investigated the immunohistochemical expression of PIM-1 kinase in 35 samples of soft tissue tumours using tissue microarray technology and 49 full sections of adipocytic (n = 26) and non-adipocytic tumours (n = 23). Benign and malignant adipocytic tumours showed strong expression of PIM-1 while the non-adipocytic tumours were either negative or showed only weak staining for the protein. In myxoid liposarcomas, PIM-1 showed a distinct, unique vacuolar staining pattern, clearly outlining fine cytoplasmic lipid vacuoles. By contrast, non-adipocytic myxoid tumours (myxoma, chordoma and myxoid chondrosarcoma) did not show this vacuolar pattern of PIM-1 staining, although vacuolated cells were present on H&E. This differential expression was confirmed at a gene expression level in selected cases. Our results indicate that the expression of PIM-1 in adipose tissue may be a useful marker of adipocytic differentiation, in particular if the staining is both of high intensity and present in a unique, vacuolar pattern.