Automated tumor analysis for molecular profiling in lung cancer

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.

Sir Robert Hart Photo Collection on Flickr

The photographs in this album were selected with the assistance of the Sir Robert Hart Research Project, which is a collaboration between Special Collections & Archives in the Library, the School of Modern History & Anthropology, Queen’s University Belfast, and the Institute of Modern History at the Chinese Academy of Social Sciences (CASS) in Beijing. The research project is creating an annotated photobook from the Sir Robert Hart Photo Collection (originally donated in the 1970s) and the Irons Collection. The photographs here reflect those that will be included in the book.

Intravitreal AAV2.COMP-Ang1 prevents neurovascular degeneration in a murine model of diabetic retinopathy

Diabetic retinopathy (DR) is the leading cause of blindness in the working-age population in the United States. The vision-threatening processes of neuroglial and vascular dysfunction in DR occur in concert, driven by hyperglycemia and propelled by a pathway of inflammation, ischemia, vasodegeneration, and breakdown of the blood retinal barrier. Currently, no therapies exist for normalizing the vasculature in DR. Here we show that a single intravitreal dose of adeno-associated virus serotype 2 encoding a more stable, soluble, and potent form of angiopoietin 1 (AAV2.COMP-Ang1) can ameliorate the structural and functional hallmarks of DR in Ins2Akita mice, with sustained effects observed through six months. In early DR, AAV2.COMP-Ang1 restored leukocyte-endothelial interaction, retinal oxygenation, vascular density, vascular marker expression, vessel permeability, retinal thickness, inner retinal cellularity, and retinal neurophysiological response to levels comparable to non-diabetic controls. In late DR, AAV2.COMP-Ang1 enhanced the therapeutic benefit of intravitreally-delivered endothelial colony-forming cells by promoting their integration into the vasculature and thereby stemming further visual decline. AAV2.COMP-Ang1 single-dose gene therapy can prevent neurovascular pathology, support vascular regeneration, and stabilize vision in DR.

Connectivity mapping using a combined gene signature from multiple colorectal cancer datasets identified candidate drugs including existing chemotherapies

BACKGROUND: While the discovery of new drugs is a complex, lengthy and costly process, identifying new uses for existing drugs is a cost-effective approach to therapeutic discovery. Connectivity mapping integrates gene expression profiling with advanced algorithms to connect genes, diseases and small molecule compounds and has been applied in a large number of studies to identify potential drugs, particularly to facilitate drug repurposing. Colorectal cancer (CRC) is a commonly diagnosed cancer with high mortality rates, presenting a worldwide health problem. With the advancement of high throughput omics technologies, a number of large scale gene expression profiling studies have been conducted on CRCs, providing multiple datasets in gene expression data repositories. In this work, we systematically apply gene expression connectivity mapping to multiple CRC datasets to identify candidate therapeutics to this disease.

RESULTS: We developed a robust method to compile a combined gene signature for colorectal cancer across multiple datasets. Connectivity mapping analysis with this signature of 148 genes identified 10 candidate compounds, including irinotecan and etoposide, which are chemotherapy drugs currently used to treat CRCs. These results indicate that we have discovered high quality connections between the CRC disease state and the candidate compounds, and that the gene signature we created may be used as a potential therapeutic target in treating the disease. The method we proposed is highly effective in generating quality gene signature through multiple datasets; the publication of the combined CRC gene signature and the list of candidate compounds from this work will benefit both cancer and systems biology research communities for further development and investigations.

Colocalization of synapsin and actin during synaptic vesicle recycling

It has been hypothesized that in the mature nerve terminal, interactions between synapsin and actin regulate the clustering of synaptic vesicles and the availability of vesicles for release during synaptic activity. Here, we have used immunogold electron microscopy to examine the subcellular localization of actin and synapsin in the giant synapse in lamprey at different states of synaptic activity. In agreement with earlier observations, in synapses at rest, synapsin immunoreactivity was preferentially localized to a portion of the vesicle cluster distal to the active zone. During synaptic activity, however, synapsin was detected in the pool of vesicles proximal to the active zone. In addition, actin and synapsin were found colocalized in a dynamic filamentous cytomatrix at the sites of synaptic vesicle recycling, endocytic zones. Synapsin immunolabeling was not associated with clathrin-coated intermediates but was found on vesicles that appeared to be recycling back to the cluster. Disruption of synapsin function by microinjection of antisynapsin antibodies resulted in a prominent reduction of the cytomatrix at endocytic zones of active synapses. Our data suggest that in addition to its known function in clustering of vesicles in the reserve pool, synapsin migrates from the synaptic vesicle cluster and participates in the organization of the actin-rich cytomatrix in the endocytic zone during synaptic activity.

The Middle Stone Age of Eastern Africa

The Middle Stone Age (MSA) covers the evolution, emergence, and dispersal of Homo sapiens. This article focuses on archaeological data and on published material from key stratified sites with some form of geochronological control from across eastern Africa. The MSA is often characterised by a shift from handaxe production towards discoidal and Levallois techniques. Although evidence for the controlled use of fire remains minimal, it seems likely that MSA hominins used it, as well as being highly skilled in working stone and probably bone and wood. MSA hominins appear to have exploited a range of different ecozones and many MSA sites are focused on ecotones, maximising access to resources. Over time, use of rockshelters and caves also seems to have increased. Although much work remains, the MSA is presently one of the most exciting and dynamic periods in the study of human evolution.

Delivering a Research-Enabled Multistakeholder Partnership for Enhanced Patient Care at a Population Level: The Northern Ireland Comprehensive Cancer Program

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.

Molecular classification of non-invasive breast lesions for personalised therapy and chemoprevention

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 In 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.

Comprehensive molecular pathology analysis of small bowel adenocarcinoma reveals novel targets with potential for clinical utility

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.

Calmodulin disruption impacts growth and motility in juvenile liver fluke

Background: Deficiencies in effective flukicide options and growing issues with drug resistance make current strategies for liver fluke control unsustainable, thereby promoting the need to identify and validate new control targets in Fasciola spp. parasites. Calmodulins (CaMs) are small calcium-sensing proteins with ubiquitous expression in all eukaryotic organisms and generally use fluctuations in intracellular calcium levels to modulate cell signalling events. CaMs are essential for fundamental processes including the phosphorylation of protein kinases, gene transcription, calcium transport and smooth muscle contraction. In the blood fluke Schistosoma mansoni, calmodulins have been implicated in egg hatching, miracidial transformation and larval development. Previously, CaMs have been identified amongst liver fluke excretory-secretory products and three CaM-like proteins have been characterised biochemically from adult Fasciola hepatica, although their functions remain unknown.

Methods: In this study, we set out to investigate the biological function and control target potential of F. hepatica CaMs (FhCaMs) using RNAi methodology alongside novel in vitro bioassays.

Results: Our results reveal that: (i) FhCaMs are widely expressed in parenchymal cells throughout the forebody region of juvenile fluke; (ii) significant transcriptional knockdown of FhCaM1-3 was inducible by exposure to either long (~200 nt) double stranded (ds) RNAs or 27 nt short interfering (si) RNAs, although siRNAs were less effective than long dsRNAs; (iii) transient long dsRNA exposure-induced RNA interference (RNAi) of FhCaMs triggered transcript knockdown that persisted for ≥ 21 days, and led to detectable suppression of FhCaM proteins; (iv) FhCaM RNAi significantly reduced the growth of juvenile flukes maintained in vitro; (v) FhCaM RNAi juveniles also displayed hyperactivity encompassing significantly increased migration; (vi) both the reduced growth and increased motility phenotypes were recapitulated in juvenile fluke using the CaM inhibitor trifluoperazine hydrochloride, supporting phenotype specificity.

Conclusions: These data indicate that the Ca(2+)-modulating functions of FhCaMs are important for juvenile fluke growth and movement and provide the first functional genomics-based example of a growth-defect resulting from gene silencing in liver fluke. Whilst the phenotypic impacts of FhCaM silencing on fluke behaviour do not strongly support their candidature as new flukicide targets, the growth impacts encourage further consideration, especially in light of the speed of juvenile fluke growth in vivo.

QUADrATiC: scalable gene expression connectivity mapping for repurposing FDA-approved therapeutics

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.

Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned

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.

Challenging the cancer molecular stratification dogma: Intratumoral heterogeneity undermines consensus molecular subtypes and potential diagnostic value in colorectal cancer

Purpose:
A number of independent gene expression profiling studies have identified transcriptional subtypes in colorectal cancer (CRC) with potential diagnostic utility, culminating in publication of a CRC 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 multi-region tissue RNA extraction/transcriptomic analysis using Colorectal Specific Arrays on invasive front, central tumor and lymph node regions selected from tissue samples from 25 CRC patients.

Results:
We identified a consensus 30 gene list which represents the intratumoral heterogeneity within a cohort of primary CRC tumors. Using a series of online datasets, we showed that this gene list displays prognostic potential (HR=2.914 (CI 0.9286-9.162) in stage II/III CRC 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 (EMT). Most importantly, we showed that patients can be simultaneously classified into multiple diagnostically relevant subgroups based purely on the tumoral region analysed.

Conclusions:
Gene expression profiles derived from the non-malignant stromal region can influence assignment of CRC 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 CRC.