Modelling the comet assay

The single-cell gel electrophoresis technique or comet assay is widely regarded as a quick and reliable method of analysing DNA damage in individual cells. It has a proven track record from the fields of biomonitoring to nutritional studies. The assay operates by subjecting cells that are fixed in agarose to high salt and detergent lysis, thus removing all the cellular content except the DNA. By relaxing the DNA in an alkaline buffer, strands containing breaks are released from supercoiling. Upon electrophoresis, these strands are pulled out into the agarose, forming a tail which, when stained with a fluorescent dye, can be analysed by fluorescence microscopy. The intensity of this tail reflects the amount of DNA damage sustained. Despite being such an established and widely used assay, there are still many aspects of the comet assay which are not fully understood. The present review looks at how the comet assay is being used, and highlights some of its limitations. The protocol itself varies among laboratories, so results from similar studies may vary. Given such discrepancies, it would be attractive to break the assay into components to generate a mathematical model to investigate specific parameters.

Comet sensitivity in assessing DNA damage and repair in different cell cycle stages

The comet assay is a sensitive tool for estimation of DNA damage and repair at the cellular level, requiring only a very small number of cells. In comparing the levels of damage or repair in different cell samples, it is possible that small experimental effects could be confounded by different cell cycle states in the samples examined, if sensitivity to DNA damage, and repair capacity, varies with the cell cycle. We assessed this by arresting HeLa cells in various cell cycle stages and then exposing them to ionizing radiation. Unirradiated cells demonstrated significant differences in strand break levels measured by the comet assay (predominantly single-strand breaks) at different cell cycle stages, increasing from G1 into S and falling again in G2. Over and above this variation in endogenous strand break levels, a significant difference in susceptibility to breaks induced by 3.5 Gy ionizing radiation was also evident in different cell cycle phases. Levels of induced DNA damage fluctuate throughout the cycle, with cells in G1 showing slightly lower levels of damage than an asynchronous population. Damage increases as cells progress through S phase before falling again towards the end of S phase and reaching lowest levels in M phase. The results from repair experiments (where cells were allowed to repair for 10 min after exposure to ionizing radiation) also showed differences throughout the cell cycle with G1-phase cells apparently being the most efficient at repair and M-phase cells the least efficient. We suggest, therefore, that in experiments where small differences in DNA damage and repair are to be investigated with the comet assay, it may be desirable to arrest cells in a specific stage of the cell cycle or to allow for differential cycle distribution.

Championing the interface between mental health and child protection: evaluation of a service initiative to improve joint working in Northern Ireland

The importance of establishing effective interagency working between adult mental health services and child care services in order to safeguard children has been repeatedly identified by research, policy, inquiries and inspection reports. This article reports on the evaluation of an initiative in one Health and Social Care Trust in Northern Ireland that aimed to facilitate joint working and so improve service provision and protection for children and families. The Champions Initiative involved identifying a champion in each multi-disciplinary community mental health team and in each family and child care team who would have responsibility for providing information, promoting joint working and identifying any obstacles to better co-operation. The evaluation of this initiative assessed levels of experience, training, confidence, understanding and awareness in the Champions and their team members at baseline. The Champions and their Team Leaders were then followed-up after six months to obtain their qualitative views of the impact of the initiative. The results include comparisons between mental health and child care staff, and crucially, views about whether the initiative has had any impact on working together. This study also generated recommendations for further service development in this complex and important area of practice.

Identification of candidate small-molecule therapeutics to cancer by gene-signature perturbation in connectivity mapping.

Connectivity mapping is a recently developed technique for discovering the underlying connections between different biological states based on gene-expression similarities. The sscMap method has been shown to provide enhanced sensitivity in mapping meaningful connections leading to testable biological hypotheses and in identifying drug candidates with particular pharmacological and/or toxicological properties. Challenges remain, however, as to how to prioritise the large number of discovered connections in an unbiased manner such that the success rate of any following-up investigation can be maximised. We introduce a new concept, gene-signature perturbation, which aims to test whether an identified connection is stable enough against systematic minor changes (perturbation) to the gene-signature. We applied the perturbation method to three independent datasets obtained from the GEO database: acute myeloid leukemia (AML), cervical cancer, and breast cancer treated with letrozole. We demonstrate that the perturbation approach helps to identify meaningful biological connections which suggest the most relevant candidate drugs. In the case of AML, we found that the prevalent compounds were retinoic acids and PPAR activators. For cervical cancer, our results suggested that potential drugs are likely to involve the EGFR pathway; and with the breast cancer dataset, we identified candidates that are involved in prostaglandin inhibition. Thus the gene-signature perturbation approach added real values to the whole connectivity mapping process, allowing for increased specificity in the identification of possible therapeutic candidates.

TMAX – a Database System Integrating Tissue Biomarker & Genomic Data

Background: Popular approaches in human tissue-based biomarker discovery include tissue microarrays (TMAs) and DNA Microarrays (DMAs) for protein and gene expression profiling respectively. The data generated by these analytic platforms, together with associated image, clinical and pathological data currently reside on widely different information platforms, making searching and cross-platform analysis difficult. Consequently, there is a strong need to develop a single coherent database capable of correlating all available data types.

Method: This study presents TMAX, a database system to facilitate biomarker discovery tasks. TMAX organises a variety of biomarker discovery-related data into the database. Both TMA and DMA experimental data are integrated in TMAX and connected through common DNA/protein biomarkers. Patient clinical data (including tissue pathological data), computer assisted tissue image and associated analytic data are also included in TMAX to enable the truly high throughput processing of ultra-large digital slides for both TMAs and whole slide tissue digital slides. A comprehensive web front-end was built with embedded XML parser software and predefined SQL queries to enable rapid data exchange in the form of standard XML files.

Results & Conclusion: TMAX represents one of the first attempts to integrate TMA data with public gene expression experiment data. Experiments suggest that TMAX is robust in managing large quantities of data from different sources (clinical, TMA, DMA and image analysis). Its web front-end is user friendly, easy to use, and most importantly allows the rapid and easy data exchange of biomarker discovery related data. In conclusion, TMAX is a robust biomarker discovery data repository and research tool, which opens up the opportunities for biomarker discovery and further integromics research.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. © 2013 McArt et al.

Validation of Next Generation Sequencing Technologies in Comparison to Current Diagnostic Gold Standards for BRAF, EGFR and KRAS Mutational Analysis

Next Generation Sequencing (NGS) has the potential of becoming an important tool in clinical diagnosis and therapeutic decision-making in oncology owing to its enhanced sensitivity in DNA mutation detection, fast-turnaround of samples in comparison to current gold standard methods and the potential to sequence a large number of cancer-driving genes at the one time. We aim to test the diagnostic accuracy of current NGS technology in the analysis of mutations that represent current standard-of-care, and its reliability to generate concomitant information on other key genes in human oncogenesis. Thirteen clinical samples (8 lung adenocarcinomas, 3 colon carcinomas and 2 malignant melanomas) already genotyped for EGFR, KRAS and BRAF mutations by current standard-of-care methods (Sanger Sequencing and q-PCR), were analysed for detection of mutations in the same three genes using two NGS platforms and an additional 43 genes with one of these platforms. The results were analysed using closed platform-specific proprietary bioinformatics software as well as open third party applications. Our results indicate that the existing format of the NGS technology performed well in detecting the clinically relevant mutations stated above but may not be reliable for a broader unsupervised analysis of the wider genome in its current design. Our study represents a diagnostically lead validation of the major strengths and weaknesses of this technology before consideration for diagnostic use.

AXL Is a Key Regulator of Inherent and Chemotherapy-Induced Invasion and Predicts a Poor Clinical Outcome in Early-Stage Colon Cancer

Purpose: Despite the use of 5-fluorouracil (5-FU)–based adjuvant treatments, a large proportion of patients with high-risk stage II/III colorectal cancer will relapse. Thus, novel therapeutic strategies are needed for early-stage colorectal cancer. Residual micrometastatic disease from the primary tumor is a major cause of patient relapse.

Experimental Design: To model colorectal cancer tumor cell invasion/metastasis, we have generated invasive (KRASMT/KRASWT/+chr3/p53-null) colorectal cancer cell subpopulations. Receptor tyrosine kinase (RTK) screens were used to identify novel proteins that underpin the migratory/invasive phenotype. Migration/invasion was assessed using the XCELLigence system. Tumors from patients with early-stage colorectal cancer (N = 336) were examined for AXL expression.

Results: Invasive colorectal cancer cell subpopulations showed a transition from an epithelial-to-mesenchymal like phenotype with significant increases in migration, invasion, colony-forming ability, and an attenuation of EGF receptor (EGFR)/HER2 autocrine signaling. RTK arrays showed significant increases in AXL levels in all invasive sublines. Importantly, 5-FU treatment resulted in significantly increased migration and invasion, and targeting AXL using pharmacologic inhibition or RNA interference (RNAi) approaches suppressed basal and 5-FU–induced migration and invasion. Significantly, high AXL mRNA and protein expression were found to be associated with poor overall survival in early-stage colorectal cancer tissues.

Conclusions: We have identified AXL as a poor prognostic marker and important mediator of cell migration/invasiveness in colorectal cancer. These findings provide support for the further investigation of AXL as a novel prognostic biomarker and therapeutic target in colorectal cancer, in particular in the adjuvant disease in which EGFR/VEGF–targeted therapies have failed.

cudaMap: a GPU accelerated program for gene expression connectivity mapping

Background: Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take >2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping.

Results: cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance.

Conclusion: Emerging 'omics' technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.

The opportunities and limitations of using CFD in the development of wave energy converters

Most Wave Energy Converters (WECs) being developed are fundamentally different from known marine structures. Limited experience is a fundamental challenge for the design, especially issues concerning load assumptions and power estimates. Reynolds-Averaged Navier-Stokes (RANS) CFD methods are being used successfully in many areas of marine engineering. They have been shown to accurately simulate many hydrodynamic effects and are a helpful tool for investigating complex flows. The major drawback is the significant computational power required and the associated overhead with pre and post-processing. This paper presents the challenges and advantages in the application of RANS CFD methods in the design process of a wave energy converter and compares the time, labour and ultimately financial requirements for obtaining practical results.

The effect of the spectral distribution of wave energy on the performance of a bottom hinged flap type wave energy converter

The power output from a wave energy converter is typically predicted using experimental and/or numerical modelling techniques. In order to yield meaningful results the relevant characteristics of the device, together with those of the wave climate must be modelled with sufficient accuracy.

The wave climate is commonly described using a scatter table of sea states defined according to parameters related to wave height and period. These sea states are traditionally modelled with the spectral distribution of energy defined according to some empirical formulation. Since the response of most wave energy converters vary at different frequencies of excitation, their performance in a particular sea state may be expected to depend on the choice of spectral shape employed rather than simply the spectral parameters. Estimates of energy production may therefore be affected if the spectral distribution of wave energy at the deployment site is not well modelled. Furthermore, validation of the model may be affected by differences between the observed full scale spectral energy distribution and the spectrum used to model it.

This paper investigates the sensitivity of the performance of a bottom hinged flap type wave energy converter to the spectral energy distribution of the incident waves. This is investigated experimentally using a 1:20 scale model of Aquamarine Power’s Oyster wave energy converter, a bottom hinged flap type device situated at the European Marine Energy Centre (EMEC) in approximately 13m water depth. The performance of the model is tested in sea states defined according to the same wave height and period parameters but adhering to different spectral energy distributions.

The results of these tests show that power capture is reduced with increasing spectral bandwidth. This result is explored with consideration of the spectral response of the device in irregular wave conditions. The implications of this result are discussed in the context of validation of the model against particular prototype data sets and estimation of annual energy production.

TBX2 represses CST6 resulting in uncontrolled legumain activity to sustain breast cancer proliferation: a novel cancer-selective target pathway with therapeutic opportunities.

TBX2 is an oncogenic transcription factor known to drive breast cancer proliferation. We have identified the cysteine protease inhibitor Cystatin 6 (CST6) as a consistently repressed TBX2 target gene, co-repressed through a mechanism involving Early Growth Response 1 (EGR1). Exogenous expression of CST6 in TBX2-expressing breast cancer cells resulted in significant apoptosis whilst non-tumorigenic breast cells remained unaffected. CST6 is an important tumor suppressor in multiple tissues, acting as a dual protease inhibitor of both papain-like cathepsins and asparaginyl endopeptidases (AEPs) such as Legumain (LGMN). Mutation of the CST6 LGMN-inhibitory domain completely abrogated its ability to induce apoptosis in TBX2-expressing breast cancer cells, whilst mutation of the cathepsin-inhibitory domain or treatment with a pan-cathepsin inhibitor had no effect, suggesting that LGMN is the key oncogenic driver enzyme. LGMN activity assays confirmed the observed growth inhibitory effects were consistent with CST6 inhibition of LGMN. Knockdown of LGMN and the only other known AEP enzyme (GPI8) by siRNA confirmed that LGMN was the enzyme responsible for maintaining breast cancer proliferation. CST6 did not require secretion or glycosylation to elicit its cell killing effects, suggesting an intracellular mode of action. Finally, we show that TBX2 and CST6 displayed reciprocal expression in a cohort of primary breast cancers with increased TBX2 expression associating with increased metastases. We have also noted that tumors with altered TBX2/CST6 expression show poor overall survival. This novel TBX2-CST6-LGMN signaling pathway, therefore, represents an exciting opportunity for the development of novel therapies to target TBX2 driven breast cancers.

The prognostic significance of the aberrant extremes of p53 immunophenotypes in breast cancer

Aims: The utility of p53 as a prognostic assay has been elusive. The aims of this study were to describe a novel, reproducible scoring system and assess the relationship between differential p53 immunohistochemistry (IHC) expression patterns, TP53 mutation status and patient outcomes in breast cancer.

Methods and Results: Tissue microarrays were used to study p53 IHC expression patterns: expression was defined as extreme positive (EP), extreme negative (EN), and non-extreme (NE; intermediate patterns). Overall survival (OS) was used to define patient outcome. A representative subgroup (n = 30) showing the various p53 immunophenotypes was analysed for TP53 hotspot mutation status (exons 4-9). Extreme expression of any type occurred in 176 of 288 (61%) cases. As compared with NE expression, EP expression was significantly associated (P = 0.039) with poorer OS. In addition, as compared with NE expression, EN expression was associated (P = 0.059) with poorer OS. Combining cases showing either EP or EN expression better predicted OS than either pattern alone (P = 0.028). This combination immunophenotype was significant in univariate but not multivariate analysis. In subgroup analysis, six substitution exon mutations were detected, all corresponding to extreme IHC phenotypes. Five missense mutations corresponded to EP staining, and the nonsense mutation corresponded to EN staining. No mutations were detected in the NE group.

Conclusions: Patients with extreme p53 IHC expression have a worse OS than those with NE expression. Accounting for EN as well as EP expression improves the prognostic impact. Extreme expression positively correlates with nodal stage and histological grade, and negatively with hormone receptor status. Extreme expression may relate to specific mutational status.

Analysis of wntless (WLS) expression in gastric, ovarian, and breast cancers reveals a strong association with HER2 overexpression

The oncogenic role of WNT is well characterized. Wntless (WLS) (also known as GPR177, or Evi), a key modulator of WNT protein secretion, was recently found to be highly overexpressed in malignant astrocytomas. We hypothesized that this molecule may be aberrantly expressed in other cancers known to possess aberrant WNT signaling such as ovarian, gastric, and breast cancers. Immunohistochemical analysis using a TMA platform revealed WLS overexpression in a subset of ovarian, gastric, and breast tumors; this overexpression was associated with poorer clinical outcomes in gastric cancer (P=0.025). In addition, a strong correlation was observed between WLS expression and human epidermal growth factor receptor 2 (HER2) overexpression. Indeed, 100% of HER2-positive intestinal gastric carcinomas, 100% of HER2-positive serous ovarian carcinomas, and 64% of HER2-positive breast carcinomas coexpressed WLS protein. Although HER2 protein expression or gene amplification is an established predictive biomarker for trastuzumab response in breast and gastric cancers, a significant proportion of HER2-positive tumors display resistance to trastuzumab, which may be in part explainable by a possible mechanistic link between WLS and HER2.