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Supplementary Table 4: Differentially expressed gene list contrasting tumour region of origin between Lymph Node and Invasive Front.

Purpose: A number of independent gene expression profiling studies have identified transcriptional subtypes in colorectal cancer with potential diagnostic utility, culminating in publication of a colorectal cancer Consensus Molecular Subtype classification. The worst prognostic subtype has been defined by genes associated with stem-like biology. Recently, it has been shown that the majority of genes associated with this poor prognostic group are stromal derived. We investigated the potential for tumor misclassification into multiple diagnostic subgroups based on tumoral region sampled.Experimental Design: We performed multiregion tissue RNA extraction/transcriptomic analysis using colorectal-specific arrays on invasive front, central tumor, and lymph node regions selected from tissue samples from 25 colorectal cancer patients.Results: We identified a consensus 30-gene list, which represents the intratumoral heterogeneity within a cohort of primary colorectal cancer tumors. Using a series of online datasets, we showed that this gene list displays prognostic potential HR = 2.914 (confidence interval 0.9286–9.162) in stage II/III colorectal cancer patients, but in addition, we demonstrated that these genes are stromal derived, challenging the assumption that poor prognosis tumors with stem-like biology have undergone a widespread epithelial–mesenchymal transition. Most importantly, we showed that patients can be simultaneously classified into multiple diagnostically relevant subgroups based purely on the tumoral region analyzed.Conclusions: Gene expression profiles derived from the nonmalignant stromal region can influence assignment of colorectal cancer transcriptional subtypes, questioning the current molecular classification dogma and highlighting the need to consider pathology sampling region and degree of stromal infiltration when employing transcription-based classifiers to underpin clinical decision making in colorectal cancer. Clin Cancer Res; 22(16); 4095–104. ©2016 AACR.See related commentary by Morris and Kopetz, p. 3989

This Supplementary Table indicates the sample source for the study

This Supplementary Figure indicates the project plan

Supplementary Table 3: Differentially expressed gene list contrasting tumour region of origin between Central Tumor and Lymph Node.

Supplementary Table 2: Differentially expressed gene list contrasting tumour region of origin between Central Tumor and Invasive Front. Supplementary Table 3: Differentially expressed gene list contrasting tumour region of origin between CT-LN. Supplementary Table 4: Differentially expressed gene list contrasting tumour region of origin between LN-IF.

Digital image analysis (DIA) is becoming central to the quantitative evaluation of tissue biomarkers for discovery, diagnosis and therapeutic selection for the delivery of precision medicine. In this study, automated DIA using a new purpose-built software platform (QuPath) is applied to a cohort of 293 breast cancer patients to score five biomarkers in tissue microarrays (TMAs): ER, PR, HER2, Ki67 and p53. This software is able to measure IHC expression following fully automated tumor recognition in the same immunohistochemical (IHC)-stained tissue section, as part of a rapid workflow to ensure objectivity and accelerate biomarker analysis. The digital scores produced by QuPath were compared with manual scores by a pathologist and shown to have a good level of concordance in all cases (Cohen's κ>0.6), and almost perfect agreement for the clinically relevant biomarkers ER, PR and HER2 (κ>0.86). To assess prognostic value, cutoff thresholds could be applied to both manual and automated scores using the QuPath software, and survival analysis performed for 5-year overall survival. DIA was shown to be capable of replicating the statistically significant stratification of patients achieved using manual scoring across all biomarkers (P

Regeneration of CNS myelin involves differentiation of oligodendrocytes from oligodendrocyte progenitor cells. In multiple sclerosis, remyelination can fail despite abundant oligodendrocyte progenitor cells, suggesting impairment of oligodendrocyte differentiation. T cells infiltrate the CNS in multiple sclerosis, yet little is known about T cell functions in remyelination. We report that regulatory T cells (T$_{reg}$) promote oligodendrocyte differentiation and (re)myelination. T$_{reg}$-deficient mice exhibited substantially impaired remyelination and oligodendrocyte differentiation, which was rescued by adoptive transfer of T$_{reg}$. In brain slice cultures, T$_{reg}$ accelerated developmental myelination and remyelination, even in the absence of overt inflammation. T$_{reg}$ directly promoted oligodendrocyte progenitor cell differentiation and myelination in vitro. We identified CCN3 as a T$_{reg}$-derived mediator of oligodendrocyte differentiation and myelination in vitro. These findings reveal a new regenerative function of T$_{reg}$ in the CNS, distinct from immunomodulation. Although the cells were originally named 'T$_{reg}$' to reflect immunoregulatory roles, this also captures emerging, regenerative T$_{reg}$ functions.

Display Omitted We employ machine learning to improve text mining of cancer pathology reports.Machine learning can detect structure in free-text surgical pathology reports.ML algorithms can locate fragments containing cancer staging information.These algorithms are sensitive to the degree of structure in the documents. Background and aimsMachine learning techniques for the text mining of cancer-related clinical documents have not been sufficiently explored. Here some techniques are presented for the pre-processing of free-text breast cancer pathology reports, with the aim of facilitating the extraction of information relevant to cancer staging. Materials and methodsThe first technique was implemented using the freely available software RapidMiner to classify the reports according to their general layout: 'semi-structured' and 'unstructured'. The second technique was developed using the open source language engineering framework GATE and aimed at the prediction of chunks of the report text containing information pertaining to the cancer morphology, the tumour size, its hormone receptor status and the number of positive nodes. The classifiers were trained and tested respectively on sets of 635 and 163 manually classified or annotated reports, from the Northern Ireland Cancer Registry. ResultsThe best result of 99.4% accuracy - which included only one semi-structured report predicted as unstructured - was produced by the layout classifier with the k nearest algorithm, using the binary term occurrence word vector type with stopword filter and pruning. For chunk recognition, the best results were found using the PAUM algorithm with the same parameters for all cases, except for the prediction of chunks containing cancer morphology. For semi-structured reports the performance ranged from 0.97 to 0.94 and from 0.92 to 0.83 in precision and recall, while for unstructured reports performance ranged from 0.91 to 0.64 and from 0.68 to 0.41 in precision and recall. Poor results were found when the classifier was trained on semi-structured reports but tested on unstructured. ConclusionsThese results show that it is possible and beneficial to predict the layout of reports and that the accuracy of prediction of which segments of a report may contain certain information is sensitive to the report layout and the type of information sought.

The last 20 years have seen significant advances in cancer care in Northern Ireland, leading to measureable improvements in patient outcomes. Crucial to this transformation has been an ethos that recognizes the primacy role of research in effecting heath care change. The authors' model of a cross‐sectoral partnership that unites patients, scientists, health care professionals, hospital trusts, bioindustry, and government agencies can be truly transformative, empowering tripartite clinical‐academic‐industry efforts that have already yielded significant benefit and will continue to inform strategy and its implementation going forward.

// Niamh Buckley 1,* , David Boyle 1,* , Darragh McArt 1 , Gareth Irwin 1 , D. Paul Harkin 1 , Tong Lioe 2 , Stephen McQuaid 1 , Jacqueline A. James 1 , Perry Maxwell 1 , Peter Hamilton 1 , Paul B. Mullan 1 and Manuel Salto-Tellez 1 1 Centre for Cancer Research and Cell Biology, Queen’s University Belfast, Belfast, United Kingdom 2 Department of Histopathology, Belfast City Hospital, Belfast, United Kingdom * These authors have contributed equally to this work Correspondence to: Manuel Salto-Tellez, email: // Keywords : pre-invasive breast cancer, DCIS, personalised medicine, biomarker, molecular pathology, Pathology Section Received : November 09, 2015 Accepted : November 27, 2015 Published : December 09, 2015 Abstract Breast cancer screening has led to a dramatic increase in the detection of pre-invasive breast lesions. While mastectomy is almost guaranteed to treat the disease, more conservative approaches could be as effective if patients can be stratified based on risk of co-existing or recurrent invasive disease. Here we use a range of biomarkers to interrogate and classify purely non-invasive lesions (PNL) and those with co-existing invasive breast cancer (CEIN). Apart from Ductal Carcinoma i n situ (DCIS), relative homogeneity is observed. DCIS contained a greater spread of molecular subtypes. Interestingly, high expression of p-mTOR was observed in all PNL with lower expression in DCIS and invasive carcinoma while the opposite expression pattern was observed for TOP2A. Comparing PNL with CEIN, we have identified p53 and Ki67 as predictors of CEIN with a combined PPV and NPV of 90.48% and 43.3% respectively. Furthermore, HER2 expression showed the best concordance between DCIS and its invasive counterpart. We propose that these biomarkers can be used to improve the management of patients with pre-invasive breast lesions following further validation and clinical trials. p53 and Ki67 could be used to stratify patients into low and high-risk groups for co-existing disease. Knowledge of expression of more actionable targets such as HER2 or TOP2A can be used to design chemoprevention or neo-adjuvant strategies. Increased knowledge of the molecular profile of pre-invasive lesions can only serve to enhance our understanding of the disease and, in the era of personalised medicine, bring us closer to improving breast cancer care.

The discovery and clinical application of molecular biomarkers in solid tumors, increasingly relies on nucleic acid extraction from FFPE tissue sections and subsequent molecular profiling. This in turn requires the pathological review of haematoxylin & eosin (H&E) stained slides, to ensure sample quality, tumor DNA sufficiency by visually estimating the percentage tumor nuclei and tumor annotation for manual macrodissection. In this study on NSCLC, we demonstrate considerable variation in tumor nuclei percentage between pathologists, potentially undermining the precision of NSCLC molecular evaluation and emphasising the need for quantitative tumor evaluation. We subsequently describe the development and validation of a system called TissueMark for automated tumor annotation and percentage tumor nuclei measurement in NSCLC using computerized image analysis. Evaluation of 245 NSCLC slides showed precise automated tumor annotation of cases using Tissuemark, strong concordance with manually drawn boundaries and identical EGFR mutational status, following manual macrodissection from the image analysis generated tumor boundaries. Automated analysis of cell counts for % tumor measurements by Tissuemark showed reduced variability and significant correlation (p < 0.001) with benchmark tumor cell counts. This study demonstrates a robust image analysis technology that can facilitate the automated quantitative analysis of tissue samples for molecular profiling in discovery and diagnostics.

Small bowel accounts for only 0.5% of cancer cases in the US but incidence rates have been rising at 2.4% per year over the past decade. One-third of these are adenocarcinomas but little is known about their molecular pathology and no molecular markers are available for clinical use. Using a retrospective 28 patient matched normal-tumor cohort, next-generation sequencing, gene expression arrays and CpG methylation arrays were used for molecular profiling. Next-generation sequencing identified novel mutations in IDH1, CDH1, KIT, FGFR2, FLT3, NPM1, PTEN, MET, AKT1, RET, NOTCH1 and ERBB4. Array data revealed 17% of CpGs and 5% of RNA transcripts assayed to be differentially methylated and expressed respectively (p < 0.01). Merging gene expression and DNA methylation data revealed CHN2 as consistently hypermethylated and downregulated in this disease (Spearman -0.71, p < 0.001). Mutations in TP53 which were found in more than half of the cohort (15/28) and Kazald1 hypomethylation were both were indicative of poor survival (p = 0.03, HR = 3.2 and p = 0.01, HR = 4.9 respectively). By integrating high-throughput mutational, gene expression and DNA methylation data, this study reveals for the first time the distinct molecular profile of small bowel adenocarcinoma and highlights potential clinically exploitable markers.

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.

In this study, we developed an image analysis algorithm for quantification of two potential apoptotic biomarkers in non-small-cell lung cancer (NSCLC): FLIP and procaspase-8. Immunohistochemical expression of FLIP and procaspase-8 in 184 NSCLC tumors were assessed. Individual patient cores were segmented and classified as tumor and stroma using the Definiens Tissue Studio. Subsequently, chromogenic expression of each biomarker was measured separately in the nucleus and cytoplasm and reported as a quantitative histological score. The software package pROC was applied to define biomarker thresholds. Cox proportional hazards analysis was applied to generate hazard ratios (HRs) and associated 95% CI for survival. High cytoplasmic expression of tumoral (but not stromal) FLIP was associated with a 2.5-fold increased risk of death in lung adenocarcinoma patients, even when adjusted for known confounders (HR 2.47, 95% CI 1.14–5.35). Neither nuclear nor cytoplasmic tumoral procaspase-8 expression was associated with overall survival in lung adenocarcinoma patients; however, there was a significant trend (P for trend=0.03) for patients with adenocarcinomas with both high cytoplasmic FLIP and high cytoplasmic procaspase-8 to have a multiplicative increased risk of death. Notably, high stromal nuclear procaspase-8 expression was associated with a reduced risk of death in lung adenocarcinoma patients (adjusted HR 0.31, 95% CI 0.15–0.66). On further examination, the cells with high nuclear procaspase-8 were found to be of lymphoid origin, suggesting that the better prognosis of patients with tumors with high stromal nuclear procaspase-8 is related to immune infiltration, a known favorable prognostic factor. No significant associations were detected in analysis of lung squamous cell carcinoma patients. Our results suggest that cytoplasmic expression of FLIP in the tumor and nuclear expression of procaspase-8 in the stroma are prognostically relevant in non-small-cell adenocarcinomas but not in squamous cell carcinomas of the lung.

BACKGROUND: Statin use after colorectal cancer diagnosis may improve survival but evidence from observational studies is conflicting. The anti-cancer effect of statins may be restricted to certain molecular subgroups. In this population-based cohort study, the interaction between p53 and 3-hydroxy-3-methylglutaryl coenzyme-A reductase (HMGCR) expression, KRAS mutations, and the association between statin use and colon cancer survival was assessed.METHODS: The cohort consisted of 740 stage II and III colon cancer patients diagnosed between 2004 and 2008. Statin use was determined through clinical note review. Tissue blocks were retrieved to determine immunohistochemical expression of p53 and HMGCR in tissue microarrays and the presence of KRAS mutations in extracted DNA. Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for colorectal cancer-specific and overall survival.RESULTS: Statin use was not associated with improved cancer-specific survival in this cohort (HR=0.91, 95% CI 0.64-1.28). Statin use was also not associated with improved survival when the analyses were stratified by tumour p53 (wild-type HR=1.31, 95% CI 0.67-2.56 vs aberrant HR=0.80, 95% CI 0.52-1.24), HMGCR (HMGCR-high HR=0.69, 95% CI 0.40-1.18 vs HMGCR-low HR=1.10, 95% CI 0.66-1.84), and KRAS (wild-type HR=0.73, 95% CI 0.44-1.19 vs mutant HR=1.21, 95% CI 0.70-2.21) status.CONCLUSIONS: Statin use was not associated with improved survival either independently or when stratified by potential mevalonate pathway biomarkers in this population-based cohort of colon cancer patients.

QuPath is new bioimage analysis software designed to meet the growing need for a user-friendly, extensible, open-source solution for digital pathology and whole slide image analysis. In addition to offering a comprehensive panel of tumor identification and high-throughput biomarker evaluation tools, QuPath provides researchers with powerful batch-processing and scripting functionality, and an extensible platform with which to develop and share new algorithms to analyze complex tissue images. Furthermore, QuPath’s flexible design makes it suitable for a wide range of additional image analysis applications across biomedical research.

// Qing Wen 1 , Philip D. Dunne 1 , Paul G. O’Reilly 1 , Gerald Li 1 , Anthony J. Bjourson 2 , Darragh G. McArt 1 , Peter W. Hamilton 1, * , Shu-Dong Zhang 1, 2, * 1 Centre for Cancer Research and Cell Biology, Queen’s University Belfast, UK 2 Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute, Ulster University, C-TRIC, Londonderry, UK * Joint Senior Author Correspondence to: Qing Wen, email: qwen02@qub.ac.uk Peter W. Hamilton, email: P.Hamilton@qub.ac.uk Keywords: connectivity mapping, differentially expressed genes, colorectal cancer, KRAS mutation, FDA approved drugs Received: May 15, 2016 Accepted: November 30, 2016 Published: December 10, 2016 ABSTRACT Colorectal cancer (CRC) is a life-threatening disease with high prevalence and mortality worldwide. The KRAS oncogene is mutated in approximately 40% of CRCs. While antibody based EGFR inhibitors (cetuximab and panitumumab) represent a major treatment strategy for advanced KRAS wild type (KRAS-WT) CRCs, there still remains no effective therapeutic course for advanced KRAS mutant (KRAS-MT) CRC patients. In this study, we employed a novel and comprehensive approach of gene expression connectivity mapping (GECM) to identify candidate compounds to target KRAS-MT tumors. We first created a combined KRAS-MT gene signature with 248 ranked significant genes using 677 CRC clinical samples. A series of 248 sub-signatures was then created containing an increasing number of the top ranked genes. As an input to GECM analysis, each sub-signature was translated into a statistically significant therapeutic drugs list, which was finally combined to obtain a single list of significant drugs. We identify four antihypertensive angiotensin II receptor blockers (ARBs) within the top 30 significant drugs indicating that these drugs have a mechanism of action that can alter the KRAS-MT CRC oncogenic signaling. A hypergeometric test ( p-value = 6.57 × 10 −6 ) confirmed that ARBs are significantly enriched in our results. These findings support the hypothesis that ARB antihypertensive drugs may directly block KRAS signaling resulting in improvement in patient outcome or, through a reversion to a KRAS wild-type phenotype, improve the response to anti-EGFR treatment. Antihypertensive angiotensin II receptor blockers are therefore worth further investigation as potential therapeutic candidates in this difficult category of advanced colorectal cancers.

Molecular Pathology (MP) is at the heart of modern diagnostics and translational research, but the controversy on how MP is best developed has not abated. The lack of a proper model or trained pathologists to support the diagnostic and research missions makes MP a rare commodity overall. Here we analyse the scientific and technology areas, in research and diagnostics, which are encompassed by MP of solid tumours; we highlight the broad overlap of technologies and analytical capabilities in tissue research and diagnostics; and we describe an integrated model that rationalizes technical know-how and pathology talent for both. The model is based on a single, accredited laboratory providing a single standard of high-quality for biomarker discovery, biomarker validation and molecular diagnostics.

Tissue microarrays (TMAs) represent a powerful method for undertaking large-scale tissue-based biomarker studies. While TMAs offer several advantages, there are a number of issues specific to their use which need to be considered when employing this method. Given the investment in TMA-based research, guidance on design and execution of experiments will be of benefit and should help researchers new to TMA-based studies to avoid known pitfalls. Furthermore, a consensus on quality standards for TMA-based experiments should improve the robustness and reproducibility of studies, thereby increasing the likelihood of identifying clinically useful biomarkers. In order to address these issues, the National Cancer Research Institute Biomarker and Imaging Clinical Studies Group organized a 1-day TMA workshop held in Nottingham in May 2012. The document herein summarizes the conclusions from the workshop. It includes guidance and considerations on all aspects of TMA-based research, including the pre-analytical stages of experimental design, the analytical stages of data acquisition, and the postanalytical stages of data analysis. A checklist is presented which can be used both for planning a TMA experiment and interpreting the results of such an experiment. For studies of cancer biomarkers, this checklist could be used as a supplement to the REMARK guidelines.

Purpose: A number of independent gene expression profiling studies have identified transcriptional subtypes in colorectal cancer with potential diagnostic utility, culminating in publication of a colorectal cancer Consensus Molecular Subtype classification. The worst prognostic subtype has been defined by genes associated with stem-like biology. Recently, it has been shown that the majority of genes associated with this poor prognostic group are stromal derived. We investigated the potential for tumor misclassification into multiple diagnostic subgroups based on tumoral region sampled. Experimental Design: We performed multiregion tissue RNA extraction/transcriptomic analysis using colorectal-specific arrays on invasive front, central tumor, and lymph node regions selected from tissue samples from 25 colorectal cancer patients. Results: We identified a consensus 30-gene list, which represents the intratumoral heterogeneity within a cohort of primary colorectal cancer tumors. Using a series of online datasets, we showed that this gene list displays prognostic potential HR = 2.914 (confidence interval 0.9286–9.162) in stage II/III colorectal cancer patients, but in addition, we demonstrated that these genes are stromal derived, challenging the assumption that poor prognosis tumors with stem-like biology have undergone a widespread epithelial–mesenchymal transition. Most importantly, we showed that patients can be simultaneously classified into multiple diagnostically relevant subgroups based purely on the tumoral region analyzed. Conclusions: Gene expression profiles derived from the nonmalignant stromal region can influence assignment of colorectal cancer transcriptional subtypes, questioning the current molecular classification dogma and highlighting the need to consider pathology sampling region and degree of stromal infiltration when employing transcription-based classifiers to underpin clinical decision making in colorectal cancer. Clin Cancer Res; 22(16); 4095–104. ©2016 AACR. See related commentary by Morris and Kopetz, p. 3989

Repositories containing high quality human biospecimens linked with robust and relevant clinical and pathological information are required for the discovery and validation of biomarkers for disease diagnosis, progression and response to treatment. Current molecular based discovery projects using either low or high throughput technologies rely heavily on ready access to such sample collections. It is imperative that modern biobanks align with molecular diagnostic pathology practices not only to provide the type of samples needed for discovery projects but also to ensure requirements for ongoing sample collections and the future needs of researchers are adequately addressed. Biobanks within comprehensive molecular pathology programmes are perfectly positioned to offer more than just tumour derived biospecimens; for example, they have the ability to facilitate researchers gaining access to sample metadata such as digitised scans of tissue samples annotated prior to macrodissection for molecular diagnostics or pseudoanonymised clinical outcome data or research results retrieved from other users utilising the same or overlapping cohorts of samples. Furthermore, biobanks can work with molecular diagnostic laboratories to develop standardised methodologies for the acquisition and storage of samples required for new approaches to research such as 'liquid biopsies' which will ultimately feed into the test validations required in large prospective clinical studies in order to implement liquid biopsy approaches for routine clinical practice. We draw on our experience in Northern Ireland to discuss how this harmonised approach of biobanks working synergistically with molecular pathology programmes is a key for the future success of precision medicine.

Modern approaches to biomedical research and diagnostics targeted towards precision medicine are generating ‘big data’ across a range of high-throughput experimental and analytical platforms. Integrative analysis of this rich clinical, pathological, molecular and imaging data represents one of the greatest bottlenecks in biomarker discovery research in cancer and other diseases. Following on from the publication of our successful framework for multimodal data amalgamation and integrative analysis, Pathology Integromics in Cancer (PICan), this article will explore the essential elements of assembling an integromics framework from a more detailed perspective. PICan, built around a relational database storing curated multimodal data, is the research tool sitting at the heart of our interdisciplinary efforts to streamline biomarker discovery and validation. While recognizing that every institution has a unique set of priorities and challenges, we will use our experiences with PICan as a case study and starting point, rationalizing the design choices we made within the context of our local infrastructure and specific needs, but also highlighting alternative approaches that may better suit other programmes of research and discovery. Along the way, we stress that integromics is not just a set of tools, but rather a cohesive paradigm for how modern bioinformatics can be enhanced. Successful implementation of an integromics framework is a collaborative team effort that is built with an eye to the future and greatly accelerates the processes of biomarker discovery, validation and translation into clinical practice.

Background Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying potential small molecule compounds, which may be further investigated as candidates for repurposing to treat diseases. The public release of voluminous data from the Library of Integrated Cellular Signatures (LINCS) programme further enhanced the utilities and potentials of gene expression connectivity mapping in biomedicine. Results We describe QUADrATiC (http://go.qub.ac.uk/QUADrATiC), a user-friendly tool for the exploration of gene expression connectivity on the subset of the LINCS data set corresponding to FDA-approved small molecule compounds. It enables the identification of compounds for repurposing therapeutic potentials. The software is designed to cope with the increased volume of data over existing tools, by taking advantage of multicore computing architectures to provide a scalable solution, which may be installed and operated on a range of computers, from laptops to servers. This scalability is provided by the use of the modern concurrent programming paradigm provided by the Akka framework. The QUADrATiC Graphical User Interface (GUI) has been developed using advanced Javascript frameworks, providing novel visualization capabilities for further analysis of connections. There is also a web services interface, allowing integration with other programs or scripts. Conclusions QUADrATiC has been shown to provide an improvement over existing connectivity map software, in terms of scope (based on the LINCS data set), applicability (using FDA-approved compounds), usability and speed. It offers potential to biological researchers to analyze transcriptional data and generate potential therapeutics for focussed study in the lab. QUADrATiC represents a step change in the process of investigating gene expression connectivity and provides more biologically-relevant results than previous alternative solutions. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1062-1) contains supplementary material, which is available to authorized users.

SummaryBackground Acid-sensing ion channels (ASIC) are a family of acid-activated ligand-gated cation channels. As tissue acidosis is a feature of inflammatory conditions, such as allergic rhinitis (AR), we investigated the expression and function of these channels in AR. Objectives The aim of the study was to assess expression and function of ASIC channels in the nasal mucosa of control and AR subjects. Methods Immunohistochemical localization of ASIC receptors and functional responses to lactic acid application were investigated. In vitro studies on cultured epithelial cells were performed to assess underlying mechanisms of ASIC function. Results Lactic acid at pH 7.03 induced a significant rise in nasal fluid secretion that was inhibited by pre-treatment with the ASIC inhibitor amiloride in AR subjects (n = 19). Quantitative PCR on cDNA isolated from nasal biopsies from control and AR subjects demonstrated that ASIC-1 was equally expressed in both populations, but ASIC-3 was significantly more highly expressed in AR (P

Stromal-derived growth factors are required for normal epithelial growth but are also implicated in tumour progression. We have observed inactivation of the retinoblastoma protein (Rb), through phosphorylation, in cancer-associated fibroblasts in oro-pharyngeal cancer specimens. Rb is well known for its cell-autonomous effects on cancer initiation and progression; however, cell non-autonomous functions of Rb are not well described. We have identified a cell non-autonomous role of Rb, using three-dimensional cultures, where depletion of Rb in stromal fibroblasts enhances invasive potential of transformed epithelia. In part, this is mediated by upregulation of keratinocyte growth factor (KGF), which is produced by the depleted fibroblasts. KGF drives invasion of epithelial cells through induction of MMP1 expression in an AKT- and Ets2-dependent manner. Our data identify that stromal fibroblasts can alter the invasive behaviour of the epithelium, and we show that altered expression of KGF can mediate these functions.

Traditionally, education and training in pathology has been delivered using textbooks, glass slides and conventional microscopy. Over the last two decades, the number of web-based pathology resources has expanded dramatically with centralized pathological resources being delivered to many students simultaneously. Recently, whole slide imaging technology allows glass slides to be scanned and viewed on a computer screen via dedicated software. This technology is referred to as virtual microscopy and has created enormous opportunities in pathological training and education. Students are able to learn key histopathological skills, e.g. to identify areas of diagnostic relevance from an entire slide, via a web-based computer environment. Students no longer need to be in the same room as the slides. New human-computer interfaces are also being developed using more natural touch technology to enhance the manipulation of digitized slides. Several major initiatives are also underway introducing online competency and diagnostic decision analysis using virtual microscopy and have important future roles in accreditation and recertification. Finally, researchers are investigating how pathological decision-making is achieved using virtual microscopy and modern eye-tracking devices. Virtual microscopy and digital pathology will continue to improve how pathology training and education is delivered.

BACKGROUND: We appraised 23 biomarkers previously associated with urothelial cancer in a case-control study. Our aim was to determine whether single biomarkers and/or multivariate algorithms significantly improved on the predictive power of an algorithm based on demographics for prediction of urothelial cancer in patients presenting with hematuria. METHODS: Twenty-two biomarkers in urine and carcinoembryonic antigen (CEA) in serum were evaluated using enzyme-linked immunosorbent assays (ELISAs) and biochip array technology in 2 patient cohorts: 80 patients with urothelial cancer, and 77 controls with confounding pathologies. We used Forward Wald binary logistic regression analyses to create algorithms based on demographic variables designated prior predicted probability (PPP) and multivariate algorithms, which included PPP as a single variable. Areas under the curve (AUC) were determined after receiver-operator characteristic (ROC) analysis for single biomarkers and algorithms. RESULTS: After univariate analysis, 9 biomarkers were differentially expressed (t test; P < .05). CEA AUC 0.74; bladder tumor antigen (BTA) AUC 0.74; and nuclear matrix protein (NMP22) 0.79. PPP included age and smoking years; AUC 0.76. An algorithm including PPP, NMP22, and epidermal growth factor (EGF) significantly improved AUC to 0.90 when compared with PPP. The algorithm including PPP, BTA, CEA, and thrombomodulin (TM) increased AUC to 0.86. Sensitivities = 91%, 91%; and specificities = 80%, 71%, respectively, for the algorithms. CONCLUSIONS: Addition of biomarkers representing diverse carcinogenic pathways can significantly impact on the ROC statistic based on demographics. Benign prostate hyperplasia was a significant confounding pathology and identification of nonmuscle invasive urothelial cancer remains a challenge. Cancer 2011. © 2011 American Cancer Society.

Evasion of apoptosis contributes to both tumourigenesis and drug resistance in non-small cell lung carcinoma (NSCLC). The pro-apoptotic BCL-2 family proteins BAX and BAK are critical regulators of mitochondrial apoptosis. New strategies for targeting NSCLC in a mitochondria-independent manner should bypass this common mechanism of apoptosis block. BRCA1 mutation frequency in lung cancer is low; however, decreased BRCA1 mRNA and protein expression levels have been reported in a significant proportion of lung adenocarcinomas. BRCA1 mutation/deficiency confers a defect in homologous recombination DNA repair that has been exploited by synthetic lethality through inhibition of PARP (PARPi) in breast and ovarian cells; however, it is not known whether this same synthetic lethal mechanism exists in NSCLC cells. Additionally, it is unknown whether the mitochondrial apoptotic pathway is required for BRCA1/PARPi-mediated synthetic lethality. Here we demonstrate that silencing of BRCA1 expression by RNA interference sensitizes NSCLC cells to PARP inhibition. Importantly, this sensitivity was not attenuated in cells harbouring mitochondrial apoptosis block induced by co-depletion of BAX and BAK. Furthermore, we demonstrate that BRCA1 inhibition cannot override platinum resistance, which is often mediated by loss of mitochondrial apoptosis signalling, but can still sensitize to PARP inhibition. Finally we demonstrate the existence of a BRCA1-deficient subgroup (11-19%) of NSCLC patients by analysing BRCA1 protein levels using immunohistochemistry in two independent primary NSCLC cohorts. Taken together, the existence of BRCA1-immunodeficient NSCLC suggests that this molecular subgroup could be effectively targeted by PARP inhibitors in the clinic and that PARP inhibitors could be used for the treatment of BRCA1-immunodeficient, platinum-resistant tumours.

The ability to take and process digital images is important in histopathology, cytopathology and pathology-centric research. In particular publishers demand that digital images are presented in a certain format. Since recording, processing and preparing digital images are often in the hands of the researcher, we should know how to handle digital images and prepare them for publication. This paper outlines the basic principles of digital imaging, what defines image resolution and how to prepare digital images for publication. Common pitfalls in preparing digital illustrations are reviewed together with the ethical constraints around the processing of scientific images.

Animal models are important for pre-clinical assessment of novel therapies in metastatic bladder cancer. The F344/AY-27 model involves orthotopic colonisation with AY-27 tumour cells which are syngeneic to F344 rats. One disadvantage of the model is the unknown status of colonisation between instillation and sacrifice. Non-invasive optical imaging using red fluorescence reporters could potentially detect tumours in situ and would also reduce the number of animals required for each experiment. AY-27 cells were stably transfected with either pDsRed2-N1 or pcDNA3.1tdTomato. The intensity and stability of fluorescence in the resultant AY-27/DsRed2-N1 and AY-27/tdTomato stable cell lines were compared using Xenogen IVIS®200 and Olympus IX51 systems. AY-27/tdTomato fluorescence intensity was 60-fold brighter than AY­27/DsRed2-N1 and was sustained in AY-27/tdTomato cells following freezing and six subsequent sub-cultures. After sub-cutaneous injection, fluorescence intensity from AY-27/tdTomato cells was threefold stronger than that detected from AY-27/DsRed2-N1 cells. IVIS®200 detected fluorescence from AY-27/tdTomato and AY-27/DsRed2-N1 cells colonising resected and exteriorised bladders, respectively. However, the deep-seated position of the bladder precluded in vivo imaging. Characteristics of AY-27/tdTomato cells in vitro and in tumours colonising F344 rats resembled those of parental AY-27 cells. Tumour transformation was observed in the bladders colonised with AY-27/DsRed2-N1 cells. In vivo whole-body imaging of internal red fluorescent animal tumours should use pcDNA3.1tdTomato rather than pDsRed2-N1. Optical imaging of deep-seated organs in larger animals remains a challenge which may require proteins with brighter red or far-red fluorescence and/or alternative approaches.

Histone acetylation is a fundamental mechanism in the regulation of local chromatin conformation and gene expression. Research has focused on the impact of altered epigenetic environments on the expression of specific genes and their pathways. However, changes in histone acetylation also have a global impact on the cell. In this study we used digital texture analysis to assess global chromatin patterns following treatment with trichostatin A (TSA) and have observed significant alterations in the condensation and distribution of higher-order chromatin, which were associated with altered gene expression profiles in both immortalised normal PNT1A prostate cell line and androgen-dependent prostate cancer cell line LNCaP. Furthermore, the extent of TSA-induced disruption was both cell cycle and cell line dependent. This was illustrated by the identification of sub-populations of prostate cancer cells expressing high levels of H3K9 acetylation in the G2/M phase of the cell cycle that were absent in normal cell populations. In addition, the analysis of enriched populations of G1 cells showed a global decondensation of chromatin exclusively in normal cells.

This paper introduces an automated computer- assisted system for the diagnosis of cervical intraepithelial neoplasia (CIN) using ultra-large cervical histological digital slides. The system contains two parts: the segmentation of squamous epithelium and the diagnosis of CIN. For the segmentation, to reduce processing time, a multiresolution method is developed. The squamous epithelium layer is first segmented at a low (2X) resolution. The boundaries are further fine tuned at a higher (20X) resolution. The block-based segmentation method uses robust texture feature vectors in combination with support vector machines (SVMs) to perform classification. Medical rules are finally applied. In testing, segmentation using 31 digital slides achieves 94.25% accuracy. For the diagnosis of CIN, changes in nuclei structure and morphology along lines perpendicular to the main axis of the squamous epithelium are quantified and classified. Using multi-category SVM, perpendicular lines are classified into Normal, CIN I, CIN II, and CIN III. The robustness of the system in term of regional diagnosis is measured against pathologists' diagnoses and inter-observer variability between two pathologists is considered. Initial results suggest that the system has potential as a tool both to assist in pathologists' diagnoses, and in training.

OBJECTIVE: To examine, for the first time Bcl-2 expression in sequential (autogenous) oral mucosal biopsies taken from the same sites in a gender, risk-factor matched, Caucasoid sample, over a 21-year period. DESIGN: Retrospective immunocytochemical longitudinal study of archival serial biopsies. MATERIALS AND METHODS: Computer records were used to identify biopsy specimens derived from 12 patients. These were divided into four groups: (1) Histologically innocuous lesions which remained histologically innocuous. (2) Dysplastic lesions which remained dysplastic. (3) Histologically innocuous lesions which later progressed to squamous cell carcinoma (SCC). (4) Dysplastic lesions which later progressed to SCC. This represented 65 biopsies in total. Bcl-2 expression was studied using mouse antihuman BCL-2 oncoprotein clone 124 (Dako, Denmark). RESULTS: Generally, there was a lack of Bcl-2 immuno-reactivity in the epithelium, with one exception in dysplastic epithelium from a group (3) patient. CONCLUSION: These findings suggest that in our series, Bcl-2 is not expressed early in oral premalignant lesions and appears to contradict previous reports. Possible explanations for this disparity are considered.

Chromogenic in situ hybridisation (CISH) has become an attractive alternative to fluorescence in situ hybridisation (FISH) due to its permanent stain which is more familiar to pathologists and because it can be viewed using light microscopy. The aim of the present study is to examine reproducibility in the assessment of abnormal chromosome number by CISH in comparison to FISH. Using three prostate cell lines--PNT1A (derived from normal epithelium), LNCAP and DU145 (derived from prostatic carcinoma), chromosomes 7 and 8 were counted in 40 nuclei in FISH preparations (x100 oil immersion) and 100 nuclei in CISH preparations (x40) by two independent observers. The CISH slides were examined using standard light microscopy and virtual microscopy. Reproducibility was examined using paired Student's t-test (P

Background: A preceding exploratory study (J. Clin. Pathol. 57(2004), 1201–1207) had shown that a karyometric assessment of nuclei from papillary urothelial neoplasms of low malignant potential (PUNLMP) revealed subtle differences in phenotype which correlated with recurrence of disease. Aim of the Study: To validate the results from the exploratory study on a larger sample size. Materials: 93 karyometric features were analyzed on haematoxylin and eosin-stained sections from 85 cases of PUNLMP. 45 cases were from patients who had a solitary PUNLMP lesion and were disease-free during a follow-up period of at least 8 years. The other 40 were from patients with a unifocal PUNLMP, with one or more recurrences in the follow-up. A combination of the previously defined classification functions together with a new P-index derived classification method was used in an attempt to classify cases and identify a biomarker of recurrence in PUNLMP lesions. Results: Validation was pursued by a number of separate approaches. First, the exact procedure from the exploratory study was applied to the large validation set. Second, since the discriminant function 2 of the exploratory study had been based on a small sample size, a new discriminant function was derived. The case classification showed a correct classification of 61% for non-recurrent and 74% for recurrent cases, respectively. Greater success was obtained by applying unsupervised learning technologies to take advantage of phenotypical composition (correct classification of 92%). This approach was validated by dividing the data into training and test sets with 2/3 of the cases assigned to the training sets, and 1/3 to the test sets, on a rotating basis, and validation of the classification rate was thus tested on three separate data sets by a leave-k-out process. The average correct classification was 92.8% (training set) and 84.6% (test set). Conclusions: Our validation study detected subvisual differences in chromatin organization state between non-recurrent and recurrent PUNLMP, thus allowing a very stable method of predicting recurrence of papillary urothelial neoplasms of low malignant potential by karyometry.

The treatment of cancer is becoming more precise, targeting specific oncogenic drivers with targeted molecular therapies. The epidermal growth factor receptor has been found to be over-expressed in a multitude of solid tumours. Immunohistochemistry is widely used in the fields of diagnostic and personalised medicine to localise and visualise disease specific proteins. To date the clinical utility of epidermal growth factor receptor immunohistochemistry in determining monoclonal antibody efficacy has remained somewhat inconclusive. The lack of an agreed reproducible scoring criteria for epidermal growth factor receptor immunohistochemistry has, in various clinical trials yielded conflicting results as to the use of epidermal growth factor receptor immunohistochemistry assay as a companion diagnostic. This has resulted in this test being removed from the licence for the drug panitumumab and not performed in clinical practice for cetuximab. In this review we explore the reasons behind this with a particular emphasis on colorectal cancer, and to suggest a way of resolving the situation through improving the precision of epidermal growth factor receptor immunohistochemistry with quantitative image analysis of digitised images complemented with companion molecular morphological techniques such as in situ hybridisation and section based gene mutation analysis.

Barrett’s esophagus (BE) is a precursor of esophageal adenocarcinoma (EAC). Both low-grade dysplasia (LGD) and high-grade dysplasia (HGD) are associated with an increased risk of progression to EAC. However, histological interpretation and grading of dysplasia (particularly LGD) is subjective and poorly reproducible. This study has combined whole slide imaging with DNA image cytometry to provide a novel method for the detection of abnormal DNA content through image analysis of tissue sections. A total of 20 cases were evaluated, including 8 negative for dysplasia (NFD), 6 LGD, and 6 HGD. Feulgen-stained esophageal sections were scanned in their entirety. Barrett’s mucosa was interactively chosen for automatic nuclei segmentation where irrelevant cell types were ignored. The combined DNA content histogram for all nuclei within selected image regions was then obtained. In addition, three histogram measurements were computed, including xER-5C, 2cDI, and DNA-MG. Visual evaluation suggested the shape of DNA content histograms from NFD, LGD, and HGD cases exhibiting identifiable differences. The histogram measurements, xER-5C, 2cDI, and DNA-MG, were shown to be effective in differentiating metaplastic from dysplastic cases with statistical significance. Moreover, they also successfully separated NFD, LGD, and HGD patients with statistical significance. Whole slide image cytometry is a novel and effective method for the detection of abnormal DNA content in BE. Compared with histological review, it is more objective. Compared with flow cytometry and cytology-preparation image cytometry, it is low cost, simple to use, only requires a single 1 μm section, and facilitates selection of tissue and topographical correlation. Whole slide image cytometry can detect differences in DNA content between NFD, LGD, and HGD patients in this cross-sectional study. Abnormal DNA content detection by whole slide image cytometry is a promising biomarker of progression that could affect future diagnostics in BE.

Despite the increasing availability of digital slide viewing, and numerous advantages associated with its application, a lack of quality validation studies is amongst the reasons for poor uptake in routine practice. This study evaluated primary digital pathology reporting in the setting of routine subspecialist gastrointestinal pathology, commonplace in most tissue pathology laboratories and representing one of the highest volume specialties in most laboratories. Individual digital and glass slide diagnoses were compared amongst three pathologists reporting in a gastrointestinal subspecialty team, in a prospective series of 100 consecutive diagnostic cases from routine practice in a large teaching hospital laboratory. The study included a washout period of at least 6 months. Discordant diagnoses were classified, and the study evaluated against recent College of American Pathologists (CAP) recommendations for evaluating digital pathology systems for diagnostic use. The study design met all 12 of the CAP recommendations. The 100 study cases generated 300 pairs of diagnoses, comprising 100 glass slide diagnoses and 100 digital diagnoses from each of the three study pathologists. 286 of 300 pairs of diagnoses were concordant, representing intraobserver concordance of 95.3 %, broadly comparable to rates previously published in this field. In ten of the 14 discordant pairs, the glass slide diagnosis was favoured; in four cases, the digital diagnosis was favoured, but importantly, the 14 discordant intraobserver diagnoses were considered to be of minor clinical significance. Interobserver, or viewing modality independent, concordance was found in 94 of the total of 100 study cases, providing a comparable baseline discordance rate expected in any second viewing of pathology material. These overall results support the safe use of digital pathology in primary diagnostic reporting in this setting.

Modern cancer research on prognostic and predictive biomarkers demands the integration of established and emerging high-throughput technologies. However, these data are meaningless unless carefully integrated with patient clinical outcome and epidemiological information. Integrated datasets hold the key to discovering new biomarkers and therapeutic targets in cancer. We have developed a novel approach and set of methods for integrating and interrogating phenomic, genomic and clinical data sets to facilitate cancer biomarker discovery and patient stratification. Applied to a known paradigm, the biological and clinical relevance of TP53, PICan was able to recapitulate the known biomarker status and prognostic significance at a DNA, RNA and protein levels.

Raman spectroscopy is recognized as a tool for chemometric analysis of biological materials due to the high information content relating to specific physical and chemical qualities of the sample. Thirty cells belonging to two different prostatic cell lines, PNT1A (immortalized normal prostate cell line) and LNCaP (malignant cell line derived from prostate metastases), were mapped using Raman microscopy. A range of spectral preprocessing methods (partial least-squares discriminant analyses (PLSDAs), principal component analyses (PCAs), and adjacent band ratios (ABRs)) were compared for input into linear discriminant analysis to model and classify the two cell lines. PLSDA and ABR were able to correctly classify 100% of cells into benign and malignant groups, while PLSDA correctly classified a greater proportion of individual spectra. PCA was used to image the distribution of various biochemicals inside each cell and confirm differences in composition/distribution between benign and malignant cell lines. This study has demonstrated that PLSDAs and ABRs of Raman data can identify subtle differences between benign and malignant prostatic cells in vitro.

Non-invasive real time in vivo molecular imaging in small animal models has become the essential bridge between in vitro data and their translation into clinical applications. The tremendous development and technological progress, such as tumour modelling, monitoring of tumour growth and detection of metastasis, has facilitated translational drug development. This has added to our knowledge on carcinogenesis. The modalities that are commonly used include Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Positron Emission Tomography (PET), bioluminescence imaging, fluorescence imaging and multi-modality imaging systems. The ability to obtain multiple images longitudinally provides reliable information whilst reducing animal numbers. As yet there is no one modality that is ideal for all experimental studies. This review outlines the instrumentation available together with corresponding applications reported in the literature with particular emphasis on cancer research. Advantages and limitations to current imaging technology are discussed and the issues concerning small animal care during imaging are highlighted.

Cysteine proteinases have been implicated in astrocytoma invasion. We recently demonstrated that cathepsin S (CatS) expression is up-regulated in astrocytomas and provided evidence for a potential role in astrocytoma invasion (Flannery et al., Am J Path 2003;163(1):175-82). We aimed to evaluate the significance of CatS in human astrocytoma progression and as a prognostic marker. Frozen tissue homogenates from 71 patients with astrocytomas and 3 normal brain specimens were subjected to ELISA analyses. Immunohistochemical analysis of CatS expression was performed on 126 paraffin-embedded tumour samples. Fifty-one astrocytoma cases were suitable for both frozen tissue and paraffin tissue analysis. ELISA revealed minimal expression of CatS in normal brain homogenates. CatS expression was increased in grade IV tumours whereas astrocytoma grades I-III exhibited lower values. Immunohistochemical analysis revealed a similar pattern of expression. Moreover, high-CatS immunohistochemical scores in glioblastomas were associated with significantly shorter survival (10 vs. 5 months, p = 0.014). With forced inclusion of patient age, radiation dose and Karnofsky score in the Cox multivariate model, CatS score was found to be an independent predictor of survival. CatS expression in astrocytomas is associated with tumour progression and poor outcome in glioblastomas. CatS may serve as a useful prognostic indicator and potential target for anti-invasive therapy.

In this paper, we present a meeting report for the 2nd Summer School in Computational Biology organized by the Queen's University of Belfast. We describe the organization of the summer school, its underlying concept and student feedback we received after the completion of the summer school.

Introduction. Chromatin reorganisation associated withreversible epigenetic modifications is consideredresponsible for changes in gene expression observedduring prostate cancer progression. Histone acetylationis an important epigenetic modification promoting an‘open’ chromatin configuration and transcriptionalactivation. Trichostatin A (TSA), an inhibitor of HDACactivity, has been associated with a globalhyperacetylation that may lead to the disruption ofchromatin phenotype and the transcription of a selectionof genes that inhibit tumour growth. We have alreadyshown that at concentrations of >50ng/ml, TSA inducesapoptosis and G2M cell cycle arrest in these cell lines.However, even at low doses of TSA, which have noobvious impact on the cell cycle or apoptosis (sub-lethaldoses), subtle changes in chromatin phenotype areinduced. The aim of this study was to establish theunderlying alterations in gene expression in normalprostate cell line (PNT1A) and lymph node metastaticcell line (LNCaP) induced by Trichostatin A.Materials and Methods. Following treatment of PNT1Aand LNCaP cell lines with sublethal (12ng/ml) and lethal(100ng/ml) doses of TSA, total cellular RNA wasisolated from cell samples. cDNA was synthesised fromextracted RNA, and control and test samples weredifferentially labelled with fluorescent Cy3 and Cy5 dyesin situ for direct comparison. Dye swaps wereincorporated into the study design to ensure preciseinterpretation of expression profiles. Hybridisation ofappropriately labelled cDNA to MWG Human 30K arrayA containing 9,984 oligonucleotide probes, wasperformed under optimum binding conditions. Scanningand analysis of the microarray slide was completed usingGenePix and Acuity (Axon Instruments) software.Results. Gene expression was clearly disrupted in bothPNT1A and LNCaP in response to TSA inducedhyperacetylation. A significant trend for up-regulation ingene expression was identified in PNT1A following highconcentrations of TSA. This includes the increasedexpression of cell cycle genes such as a 2.27 foldincrease in cyclin g2, as well as a selection of genesrelated to the onset of apoptosis. This is likely to beassociated with increased apoptosis and cell cycle arrestseen at these concentrations. Interestingly, altered geneexpression was also evident in cells treated with sublethaldoses of TSA, where no cytotoxic effects of the treatmentare visible. Several functional gene groups were found tobe down-regulated across both cell lines in response toTSA, including a range of general transcription factors,along with genes involved in the MAP Kinase pathway.A consistent up-regulation can also be reported in both asubset of homeobox genes, and cytochrome c oxidasegenes. Also important is the observation that theKallikrein (prostate specific antigen) gene has beenfound to be down-regulated in both normal prostate andmetastatic cell lines in response to TSA treatment.Conclusions. Histone hyperacetylation and subsequentchromatin redistribution are associated with thedisruption of gene expression profiles in prostate cancer.Disruption in gene expression occurs in the absence ofcytotoxic effects which may be due to subtle chromatinphenotypic changes observed at sublethal doses of TSA,and may therefore be indicative of those genes directly orindirectly regulated by histone acetylation.

Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at x 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 x 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.