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.

The expression and prognostic impact of CXC-chemokines in stage II and III colorectal cancer epithelial and stromal tissue

BACKGROUND: The CXC-chemokine expression is linked with colorectal cancer (CRC) progression but their significance in resected CRC is unclear. We explored the prognostic impact of such expression in stage II and III CRC.

Preservation methods alter stable isotope values in gelatinous zooplankton: implications for interpreting trophic ecology

Jellyfish are increasingly topical within studies of marine food webs. Stable isotope analysis represents a valuable technique to unravel the complex trophic role of these long-overlooked species. In other taxa, sample preservation has been shown to alter the isotopic values of species under consideration, potentially leading to misinterpretation of trophic ecology. To identify potential preservation effects in jellyfish, we collected Aurelia aurita from Strangford Lough (54(o)22'44.73aEuro(3)N, 5(o)32'53.44aEuro(3)W) during May 2009 and processed them using three different methods prior to isotopic analysis (unpreserved, frozen and preserved in ethanol). A distinct preservation effect was found on delta N-15 values: furthermore, preservation also influenced the positive allometric relationship between individual size and delta N-15 values. Conversely, delta C-13 values remained consistent between the three preservation methods, conflicting with previous findings for other invertebrate, fish and mammalian species. These findings have implications for incorporation of jellyfish into marine food webs and remote sampling regimes where preservation of samples is unavoidable.

Tissue biomarker development in a multicentre trial context: a feasibility study on the PETACC3 stage II and III colon cancer adjuvant treatment trial.

Purpose: We evaluated the feasibility of biomarker development in the context of multicenter clinical trials.

Experimental Design: Formalin-fixed, paraffin-embedded (FFPE) tissue samples were collected from a prospective adjuvant colon cancer trial (PETACC3). DNA was isolated from tumor as well as normal tissue and used for analysis of microsatellite instability, KRAS and BRAF genotyping, UGT1A1 genotyping, and loss of heterozygosity of 18 q loci. Immunohistochemistry was used to test expression of TERT, SMAD4, p53, and TYMS. Messenger RNA was retrieved and tested for use in expression profiling experiments.

Results: Of the 3,278 patients entered in the study, FFPE blocks were obtained from 1,564 patients coming from 368 different centers in 31 countries. In over 95% of the samples, genomic DNA tests yielded a reliable result. Of the immmunohistochemical tests, p53 and SMAD4 staining did best with reliable results in over 85% of the cases. TERT was the most problematic test with 46% of failures, mostly due to insufficient tissue processing quality. Good quality mRNA was obtained, usable in expression profiling experiments.

Conclusions: Prospective clinical trials can be used as framework for biomarker development using routinely processed FFPE tissues. Our results support the notion that as a rule, translational studies based on FFPE should be included in prospective clinical trials.

Connective tissue growth factor antagonizes transforming growth factor-beta 1/Smad signalling in renal mesangial cells

The critical involvement of TGF-beta 1 (transforming growth factor-beta 1) in DN (diabetic nephropathy) is well established. However, the role of CTGF (connective tissue growth factor) in regulating the complex interplay of TGF-beta 1 signalling networks is poorly understood. The purpose of the present study was to investigate co-operative signalling between CTGF and TGF-beta 1 and its physiological significance. CTGF was determined to bind directly to the T beta RIII (TGF-beta type III receptor) and antagonize TGF-beta 1-induced Smad phosphorylation and transcriptional responses via its N-terminal half. Furthermore, TGF-beta 1 binding to its receptor was inhibited by CTGF. A consequent shift towards non-canonical TGF-beta 1 signalling and expression of a unique profile of differentially regulated genes was observed in CTGF/TGF-beta 1-treated mesangial cells. Decreased levels of Smad2/3 phosphorylation were evident in STZ (streptozotocin)-induced diabetic mice, concomitant with increased levels of CTGF Knockdown of T beta RIII restored TGF-beta 1-mediated Smad signalling and cell contractility, suggesting that T beta RIII is key for CTGF-mediated regulation of TGF-beta 1. Comparison of gene expression profiles from CTGF/TGF-beta 1-treated mesangial cells and human renal biopsy material with histological diagnosis of DN revealed significant correlation among gene clusters. In summary, mesangial cell responses to TGF-beta 1 are regulated by cross-talk with CTGF, emphasizing the potential utility of targeting CTGF in DN.

A comparison of four extraction methods for substance P, neurokinin A and calcitonin gene-related peptide from human dental pulp tissue

Measuring neuropeptides in biological tissues by radioimmunoassay requires efficient extraction that maintains their immunoreactivity. Many different methods for extraction have been described, but there is little information on optimal extraction methods for individual neuropeptides from human dental pulp tissue. The aim was therefore to identify an effective extraction procedure for three pulpal neuropeptides: substance P. neurokinin A and calcitonin gene-related peptide. Tissue was obtained from 20 pulps taken from teeth freshly extracted for orthodontic reasons. The pulp samples were divided into four equal groups and different extraction methods were used for each group. Boiling whole pulp in acetic acid gave the highest overall yield and, in addition, offered an easy and rapid means of pulp tissue processing. The use of protease inhibitors did not increase the recovery of the immunoreactive neuropeptides but did provide the best combination of maximal recoveries and minimal variability. These results should be useful for planning the extraction of these neuropeptides from human pulp tissue in future studies. (C) 1999 Elsevier Science Ltd. All rights reserved.

In Silico Prediction of the Mechanobiological Response of Arterial Tissue: Application to Angioplasty and Stenting

One way to restore physiological blood flow to occluded arteries involves the deformation of plaque using an intravascular balloon and preventing elastic recoil using a stent. Angioplasty and stent implantation cause unphysiological loading of the arterial tissue, which may lead to tissue in-growth and reblockage; termed “restenosis.” In this paper, a computational methodology for predicting the time-course of restenosis is presented. Stress-induced damage, computed using a remaining life approach, stimulates inflammation (production of matrix degrading factors and growth stimuli). This, in turn, induces a change in smooth muscle cell phenotype from contractile (as exists in the quiescent tissue) to synthetic (as exists in the growing tissue). In this paper, smooth muscle cell activity (migration, proliferation, and differentiation) is simulated in a lattice using a stochastic approach to model individual cell activity. The inflammation equations are examined under simplified loading cases. The mechanobiological parameters of the model were estimated by calibrating the model response to the results of a balloon angioplasty study in humans. The simulation method was then used to simulate restenosis in a two dimensional model of a stented artery. Cell activity predictions were similar to those observed during neointimal hyperplasia, culminating in the growth of restenosis. Similar to experiment, the amount of neointima produced increased with the degree of expansion of the stent, and this relationship was found to be highly dependant on the prescribed inflammatory response. It was found that the duration of inflammation affected the amount of restenosis produced, and that this effect was most pronounced with large stent expansions. In conclusion, the paper shows that the arterial tissue response to mechanical stimulation can be predicted using a stochastic cell modeling approach, and that the simulation captures features of restenosis development observed with real stents. The modeling approach is proposed for application in three dimensional models of cardiovascular stenting procedures.

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.

A TMA De-Arraying Method for High Throughput Biomarker Discovery in Tissue Research

Background: Tissue MicroArrays (TMAs) represent a potential high-throughput platform for the analysis and discovery of tissue biomarkers. As TMA slides are produced manually and subject to processing and sectioning artefacts, the layout of TMA cores on the final slide and subsequent digital scan (TMA digital slide) is often disturbed making it difficult to associate cores with their original position in the planned TMA map. Additionally, the individual cores can be greatly altered and contain numerous irregularities such as missing cores, grid rotation and stretching. These factors demand the development of a robust method for de-arraying TMAs which identifies each TMA core, and assigns them to their appropriate coordinates on the constructed TMA slide.

Methodology: This study presents a robust TMA de-arraying method consisting of three functional phases: TMA core segmentation, gridding and mapping. The segmentation of TMA cores uses a set of morphological operations to identify each TMA core. Gridding then utilises a Delaunay Triangulation based method to find the row and column indices of each TMA core. Finally, mapping correlates each TMA core from a high resolution TMA whole slide image with its name within a TMAMap.

Conclusion: This study describes a genuine robust TMA de-arraying algorithm for the rapid identification of TMA cores from digital slides. The result of this de-arraying algorithm allows the easy partition of each TMA core for further processing. Based on a test group of 19 TMA slides (3129 cores), 99.84% of cores were segmented successfully, 99.81% of cores were gridded correctly and 99.96% of cores were mapped with their correct names via TMAMaps. The gridding of TMA cores were also extensively tested using a set of 113 pseudo slide (13,536 cores) with a variety of irregular grid layouts including missing cores, rotation and stretching. 100% of the cores were gridded correctly.