25 results on '"Harrison, David James"'
Search Results
2. Interpreting lymphocyte classification from Hoechst stained slides with deep learning
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Cooper, Jessica, Um, In Hwa, Arandelovic, Oggie, Harrison, David James, Innovate UK, University of St Andrews. School of Computer Science, University of St Andrews. School of Medicine, University of St Andrews. Cellular Medicine Division, and University of St Andrews. Sir James Mackenzie Institute for Early Diagnosis
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QA75 ,Image classification ,RC0254 Neoplasms. Tumors. Oncology (including Cancer) ,QA75 Electronic computers. Computer science ,QH301 Biology ,Lymphocyte subsets ,Deep learning ,DAS ,Imaging ,RC0254 ,QH301 ,SDG 3 - Good Health and Well-being ,MCP ,Computer vision - Abstract
Funding: This work is supported by the Industrial Centre for AI Research in Digital Diagnostics (iCAIRD) which is funded by Innovate UK on behalf of UK Research and Innovation (UKRI) [project number: 104690]. Multiplex immunofluorescence and immunohistochemistry benefit patients by allowing cancer pathologists to identify proteins expressed on the surface of cells. This enables cell classification, better understanding of the tumour microenvironment, and more accurate diagnoses, prognoses, and tailored immunotherapy based on the immune status of individual patients. However, these techniques are expensive. They are time consuming processes which require complex staining and imaging techniques by expert technicians. Hoechst staining is far cheaper and easier to perform, but is not typically used as it binds to DNA rather than to the proteins targeted by immunofluorescence techniques. In this work we show that through the use of deep learning it is possible to identify an immune cell subtype without immunofluorescence. We train a deep convolutional neural network to identify cells expressing the T lymphocyte marker CD3 from Hoechst 33342 stained tissue only. CD3 expressing cells are often used in key prognostic metrics such as assessment of immune cell infiltration, and by identifying them without the need for costly immunofluorescence, we present a promising new approach to cheaper prediction and improvement of patient outcomes. We also show that by using deep learning interpretability techniques, we can gain insight into the previously unknown morphological features which make this possible. Publisher PDF
- Published
- 2022
3. Silencing Itch in human PBMCs promotes differentiation of monocytes into osteoclasts
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Read, Oliver, primary and Harrison, David James, additional
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- 2022
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4. Abstract 1655: NUC-3373 induced DAMPs release in CRC cells promotes natural killer cell activation
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Read, Oliver James, primary, Harrison, David James, additional, and Bré, Jennifer, additional
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- 2021
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5. A Comparison of Methods for Studying the Tumor Microenvironment's Spatial Heterogeneity in Digital Pathology Specimens
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Nearchou, Ines Panicou, primary, Soutar, Daniel Alexander, additional, Ueno, Hideki, additional, Harrison, David James, additional, Arandjelovic, Ognjen, additional, and Caie, Peter David, additional
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- 2021
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6. Colorectal cancer outcome prediction from H&E whole slide images using machine learning and automatically inferred phenotype profiles
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Xingzhi, Yue, Dimitriou, Neofytos, Caie, Peter David, Harrison, David James, Arandelovic, Ognjen, University of St Andrews. School of Medicine, University of St Andrews. Sir James Mackenzie Institute for Early Diagnosis, University of St Andrews. Cellular Medicine Division, and University of St Andrews. School of Computer Science
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QA75 ,RC0254 ,SDG 3 - Good Health and Well-being ,RB Pathology ,RC0254 Neoplasms. Tumors. Oncology (including Cancer) ,QA75 Electronic computers. Computer science ,Computer Science - Computer Vision and Pattern Recognition ,Electrical Engineering and Systems Science - Image and Video Processing ,RB ,3rd-NDAS - Abstract
Digital pathology (DP) is a new research area which falls under the broad umbrella of health informatics. Owing to its potential for major public health impact, in recent years DP has been attracting much research attention. Nevertheless, a wide breadth of significant conceptual and technical challenges remain, few of them greater than those encountered in the field of oncology. The automatic analysis of digital pathology slides of cancerous tissues is particularly problematic due to the inherent heterogeneity of the disease, extremely large images, amongst numerous others. In this paper we introduce a novel machine learning based framework for the prediction of colorectal cancer outcome from whole digitized haematoxylin & eosin (H&E) stained histopathology slides. Using a real-world data set we demonstrate the effectiveness of the method and present a detailed analysis of its different elements which corroborate its ability to extract and learn salient, discriminative, and clinically meaningful content., Comment: 2019
- Published
- 2019
7. A Comparison of Methods for Studying the Tumor Microenvironment's Spatial Heterogeneity in Digital Pathology Specimens.
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Panicou Nearchou, Ines, Alexander Soutar, Daniel, Hideki Ueno, Harrison, David James, Arandjelovic, Ognjen, and Caie, Peter David
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TUMOR microenvironment ,COLORECTAL cancer ,HETEROGENEITY ,TUMOR-infiltrating immune cells ,TUMOR budding ,PROGNOSIS ,CANCER prognosis - Abstract
Background: The tumor microenvironment is highly heterogeneous, and it is understood to affect tumor progression and patient outcome. A number of studies have reported the prognostic significance of tumor-infiltrating lymphocytes and tumor budding in colorectal cancer (CRC). However, the significance of the intratumoral heterogeneity present in the spatial distribution of these features within the tumor immune microenvironment (TIME) has not been previously reported. Evaluating this intratumoral heterogeneity may aid the understanding of the TIME's effect on patient prognosis as well as identify novel aggressive phenotypes which can be further investigated as potential targets for new treatment. Methods: In this study, we propose and apply two spatial statistical methodologies for the evaluation of the intratumor heterogeneity present in the distribution of CD3 + and CD8 + lymphocytes and tumor buds (TB) in 232 Stage II CRC cases. Getis-Ord hotspot analysis was applied to quantify the cold and hotspots, defined as regions with a significantly low or high number of each feature of interest, respectively. A novel spatial heatmap methodology for the quantification of the cold and hotspots of each feature of interest, which took into account both the interpatient heterogeneity and the intratumor heterogeneity, was further developed. Results: Resultant data from each analysis, characterizing the spatial intratumor heterogeneity of lymphocytes and TBs were used for the development of two new highly prognostic risk models. Conclusions: Our results highlight the value of applying spatial statistics for the assessment of the intratumor heterogeneity. Both Getis-Ord hotspot and our proposed spatial heatmap analysis are broadly applicable across other tissue types as well as other features of interest. [ABSTRACT FROM AUTHOR]
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- 2021
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8. Assessing Learning Strategies with an Educational Video
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Harrison, David James
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Even though educational films and videos have been in used for a century, there remains insufficient research into efficacious learning strategies that can be used alongside them. This study sought to investigate active learning strategies as a method to improve learning from video. This true experimental study, supported and informed by qualitative data, examined three active learning strategies utilized within video-based instruction: Guided Notetaking, Personal Notetaking, and Guided Summaries. Outcome measures included three dimensions of learning (factual, conceptual, and procedural) on an immediate posttest, perceptions of extrinsic cognitive load, likelihood that participants would use the strategies again, how often participants paused the video, time-on-task, quality of strategy usage, and commonly shared experiences. While there were no significant differences between groups on general measures of learning, when the scores of only those participants who crafted high quality products (notes or summaries) were compared, the Guided Notetaking group scored significantly higher than the Guided Summaries on factual learning. These results suggest that quality of strategy usage is a factor that should be included in research examining active learning strategies with educational videos. The Guided Notetaking group experienced significantly higher perceived extrinsic cognitive load than the other groups. Participants in the Personal Notetaking group reported significantly higher likelihood that they would use these strategies again compared to the other groups. Participants in the Guided Notetaking strategy paused the video significantly more often than participants in the other groups. Analysis of commonly shared subjective experiences indicated that Guided Notetaking was difficult for several reasons: matching of the video content with the notes, switching back and forth between the video and notes (which some perceived as detracting from their learning), and the constant pausing of the video this strategy required. Personal Notetaking was perceived as the easiest of the three strategies, only slightly easier than the Guided Summaries. Suggestions for implementation of strategies, future research, and production of educational videos are also provided.
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- 2017
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9. Combined DNA-methylation intensity and clinical risk score to stratify patients for high-grade disease.
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Van Neste, Leander, primary, Stewart, Grant, additional, Gaston, Sandra Marlene, additional, Grizzle, William E., additional, Adams, George W., additional, Kearney, Gary P, additional, Epstein, Jonathan I, additional, Harrison, David James, additional, Partin, Alan W., additional, and Van Criekinge, Wim, additional
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- 2016
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10. Effect of sunitinib treatment on mutations and methylation in metastatic renal cancer.
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Stewart, Grant, primary, Van Neste, Christophe, additional, Meynert, Alison, additional, Semple, Colin, additional, O'Mahony, Fiach, additional, Laird, Alexander, additional, Mackay, Alan, additional, Trooskens, Geert, additional, Van Criekinge, Wim, additional, De Meyer, Tim, additional, Powles, Thomas, additional, and Harrison, David James, additional
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- 2015
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11. The effect of sunitinib on biomarkers and tumor heterogeneity in metastatic clear cell renal cancer.
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Stewart, Grant, primary, Laird, Alexander, additional, O'Mahony, Fiach, additional, Eory, Lel, additional, Lubbock, Alexander, additional, Nanda, Jyoti, additional, O'Donnell, Marie, additional, Mackay, Alan, additional, Mullen, Peter, additional, McNeill, Alan, additional, Riddick, Antony, additional, Aitchison, Michael, additional, Berney, Daniel, additional, Bex, Axel, additional, Overton, Ian, additional, Harrison, David James, additional, and Powles, Tom, additional
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- 2014
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12. Prediction of risk for prostate cancer in histopathologically negative biopsies by multigene epigenetic assay.
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Van Neste, Leander, primary, Van Criekinge, Wim, additional, Thas, Olivier, additional, Bigley, Joseph, additional, Stewart, Grant Duncan, additional, and Harrison, David James, additional
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- 2013
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13. Mechanisms of action of 3'-deoxyadenosine in treating clear cell renal cell carcinoma
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Kudsy, Mary, Harrison, David James, and Melo Czekster, Clarissa
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Clear cell renal cell carcinoma ,3'-deoxyadenosine ,AMPK ,OXPHOS ,Electron transport chain ,Polyadenylation ,Transcription ,Mitochondria ,RC280.K5K8 ,Renal cell carcinoma - Abstract
Although treatment strategies for advanced and metastatic clear cell renal cell carcinoma (ccRCC) have markedly evolved with the recent use of immune-checkpoint inhibitor (ICI)-based combinations, most patients eventually develop resistance to these therapies. Therefore, there is still an urgent need for the development of effective treatment options. NUC-7738, a novel ProTide transformation of the nucleoside analogue 3ﹶ-deoxyadenosine, releases 3ﹶ-deoxyadenosine monophosphate (3'-dAMP) in cells which is then phosphorylated to the di- (3'-dADP) and tri-phosphate forms (3'-dATP). 3'-dAMP might have the ability to activate AMP-activated protein kinase (AMPK), a key cellular energy sensor, and thus disrupt metabolic homeostasis in cancer cells. Furthermore, 3'-dATP might interfere with RNA synthesis affecting protein expression and survival of cancer cells. The ability of NUC-7738 to activate AMPK through phosphorylation of Th172 was tested in ccRCC cell lines and ex vivo tissue slices of ccRCC from patients. The effect of NUC-7738 on mRNA synthesis and polyadenylation was investigated in two ccRCC cell lines, 786-O and 769-P. AMPK activation by NUC-7738 showed inter-replicate variability and inter-patient variability in ccRCC cell lines and ex vivo tissue slices, respectively, indicating the complexity of the regulation of AMPK phosphorylation. Moreover, mass spectrometry analysis showed that 3'-dATP is the main active metabolite of NUC-7738. Transcriptome data analysis showed mitochondrial gene transcripts of electron transport chain (ETC) complexes were the most significantly altered in both 786-O and 769-P cell lines, with lower expression levels in response to NUC-7738 treatment. This was accompanied by downregulation of the protein expression of ETC complexes subunits. NUC-7738 induced the intrinsic pathway of apoptosis in these cells through the release of cytochrome c from mitochondria and the subsequent activation of caspases -9 and -7. These data suggest that NUC-7738 might inhibit tumour cells growth and proliferation through the inhibition of mitochondrial respiration and the subsequent induction of apoptosis.
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- 2023
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14. Biological and clinical implications of the non-small cell lung cancer immune contexture : an investigation of the tumour microenvironment
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Kaghazchi, Boback and Harrison, David James
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- 2023
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15. Targeting mitochondrial metabolism and alternative polyadenylation in acute myeloid leukaemia with 3'-deoxyadenosine
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Shahid, Muhammed Akbar and Harrison, David James
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- 2022
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16. Revealing novel insight in clear cell renal cell carcinoma through high-plex and machine learning tools
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De Filippis, Raffaele and Harrison, David James
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Cancer ,Kidney ,Tumour microenvironment ,Immunofluorescence ,Pathology ,Spatial biology ,Image analysis ,Nanostring - Abstract
Clear Cell Renal Cell Carcinoma (ccRCC) is the most common form of kidney cancer and its incidence is constantly increasing. Although immunotherapy has shown promising results, the only current curative method is ablative surgery, and recurrence is observed in about one third of cases. Moreover, patient prognosis drops significantly with metastatic disease. Current prognostic tools such as Leibovich Score (LS) aim to predict the risk of recurrence by stratifying patients into high, low, and intermediate risk groups. However, this algorithm only takes into account morphological features of the tumour, such as tumour stage and nuclear grade, while it does not consider the vast molecular milieu present in the tumour microenvironment (TME). Furthermore, morphological features are manually assessed by pathologists and are therefore subject to inter- and intra- observer variability. ccRCC TME is complex and heterogeneous, consisting of cell subtypes and molecular mechanisms which may either favour or prevent disease progression and metastatic spread. In this thesis, the author focused on four main molecular mechanisms: immune evasion, T cell exhaustion, epithelial-to-mesenchymal transition (EMT) and cancer stem-like cells (CSCs). Multiplex immunofluorescence (mIF) and GeoMx digital spatial profiling (DSP) by NanoString technology have been used on 150 ccRCC tissue microarrays (TMA) and whole slides (WS) in order to investigate the prognostic role of more than 160 markers. mRNA was also extracted from primary and metastatic tissues from a subset of the cohort to evaluate the expression of 750 genes using the NanoString nCounter technology. Machine learning-based image analysis software were used to detect and quantify these markers, their co-expression at single cell level, and their spatial relationship. Moreover, some markers were chosen to better stratify patients at intermediate LS risk, and increase LS accuracy. To conclude, a semi-automated method was developed in order to investigate the ccRCC TME, reduce observer bias, and increase patients' stratification, facilitating personalised therapy.
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- 2022
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17. A multi-omics approach to investigate the complex interplay between muscle-invasive bladder cancer and the host immune response
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Gavriel, Christos G., Harrison, David James, and Caie, Peter David
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Bladder cancer ,Tumour microenvironment ,Cancer immunology ,Prognostic markers ,Digital pathology ,Extracellular vesicles - Abstract
Muscle-invasive bladder cancer (MIBC) prognosis is mainly assessed by clinical cancer stage which is codified using the Tumour-Node-Metastasis (TNM) staging system. However, recent studies have demonstrated that disease progression and thus prognosis is profoundly influenced by the immune context of the tumour microenvironment. Multiplex immunofluorescence was applied on MIBC tissue sections to capture whole slide images and quantify potential prognostic markers related to lymphocytes, macrophages, PD-L1 and tumour buds. Two independent machine learning-based methodologies were implemented and the resulting prognostic models reported that: (i) tumour budding was the most significant feature (HR=2.59, P=0.0091) for the stratification of non-metastatic patients into high or low risk of disease specific death, and (ii) the combination of image, clinical, and spatial features stratified MIBC patients into two risk groups with high statistical significance (P<1E⁻⁰⁵) and greater accuracy than the current clinical gold standard, the TNM staging system . To provide further insights into the tumour-immune microenvironment, spatially resolved differential expression of immunologically relevant proteins was quantified across entire MIBC tissues using a 31-plex spatial profiling platform. Significant alterations in the expression of proteins were identified within different compartments of the tissue related to tumour core, tumour buds, stroma and tumour infiltrating lymphocytes showing that this technology has the capability to capture immunological signatures if applied in a larger heterogeneous sample population. Lastly, to delve into the molecular causes of immune evasion by cancer cells, extracellular vesicles (EVs) were isolated by differential ultra- centrifugation from conditioned media of PD-L1 and PD-L1 knockout human bladder carcinoma cells. Co-culture assays demonstrated that EVs derived from PD-L1 bladder carcinoma cells can impair immune functions by reducing CD8 T-cell proliferation. In addition, 210 EV proteins were identified by proteomic analysis, including two newly identified proteins which are not present in known exosome databases.
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- 2021
18. Exploration of the pharmacodynamic profile of Acelarin, a novel ProTide drug, in an in vitro model of ovarian cancer
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Bre´, Jennifer and Harrison, David James
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616.99 ,RM301.57B8 - Published
- 2019
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19. An investigation into the relevance of dual-specificity phosphatase 6 in colorectal cancer
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Williams, Hannah Louise and Harrison, David James
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616.99 ,RC280.C6W5 - Published
- 2019
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20. Exploring the role of Itch in human cancer and bone remodelling
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Read, Oliver James and Harrison, David James
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616.5 ,Itch ,E3 ligase ,Cancer ,Bone remodelling ,siRNA ,CRISPR - Abstract
Tight control of post-translational modifications such as ubiquitination is important for cell homeostasis and dysregulation of this process is a common feature in many diseases. Itch encodes an E3 ubiquitin ligase that conjugates ubiquitin to a variety of substrates such as Jun B, PKC-θ, PLC- γ1, LATS, TXNIP and p73. In this study both transient and stable knockdown techniques (siRNA and CRISPR respectively) were utilised to explore the role of Itch in both cancer progression and bone remodelling. Transient siRNA-mediated knockdown of Itch inhibited cell viability of MiaPaCa-2 and Capan-2 cell lines by ~50% and ~60% respectively compared to both scrambled and untreated controls as determined by SRB. Although siRNA did not increase cell line sensitivity to γ-radiation, doxorubicin, and gemcitabine, it did have an additive effect on resultant survivability. CRISPR-Cas9 mediated stable Itch knockdowns in the same cell lines in contrast showed increased sensitivity to the aforementioned treatment regimens however resultant data obtained from cell survival and clonogenicity assays suggested that the CRISPR⁺ MiaPaCa-2 cells divide faster than both scrambled and parental controls. SWATH-DIA analysis was performed to look for differences in proteome between CRISPR⁺ and parental MiaPaCa-2 cells. Preliminary data based on isogenic clones suggests potential differences, but additional repeats and further validation is required. Transient Itch knockdown in peripheral blood monocytes increased their capacity to differentiate into fully matured osteoclasts ex-vivo: compared to untreated controls, si-Itch treated wells showed higher mean numbers of large TRAP⁺ cells (mean = 63 and 54 for si-Itch and untreated wells respectively) and multinucleate cells (mean = 25 and 17 for si-Itch and untreated wells respectively) in a 96-well format. Meanwhile CRISPR-mediated knockdown induced a large degree of cellular toxicity in PBMCs. This contrast between stable and transient Itch knockdown prompted discussion of the strengths and weaknesses of each technique and their suitability in different experimental contexts.
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- 2019
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21. Computational image analysis in clear cell renal cell carcinoma
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Um, In Hwa and Harrison, David James
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616.99 - Abstract
Background: In the UK, kidney cancer is the most lethal urologic cancer whose major subtype is renal cell carcinoma (RCC). Surgical resection is the first line of the treatment for renal cell carcinoma (RCC). A number of different integrated staging systems such as UISS, SSIGN and Leibovich score, has been introduced and utilised in clinic as a prognostic tool or as an inclusion criterion of clinical trials. Among them, Leibovich score has been widely utilised in the UK to predict the likelihood of disease free survival for clear cell renal cell carcinoma (ccRCC). However, its prediction rate of disease relapse free for 5 years after surgery varies from 97% (low risk) to 31% (high risk) which might lead to inclusion of some ccRCC patients, who would not recur, into a clinical trial. Therefore, we aim to improve the prediction power of recurrence free (specificity) in localised clear cell renal cell carcinoma (ccRCC) patients, by either modifying Leibovich score with more precise and accurate measurement of ccRCC nuclear morphological features or by improving currently available Leibovich score with the features measured from the chromatin marker colocalisation status, chromatin marker Haralick texture features, and the tumour microenvironment using computational image analysis. Methods: To modify Leibovich score by replacing manual Fuhrman's nuclear grade with the computational image analysis measurement of the nuclear morphological features, digitised images from haematoxylin and eosin stained slides were utilised. For the chromatin marker (H3K9me3, H3K4me3 and HP1α) colocalisation analysis, Haralick texture analysis and tumour microenvironment marker (CD105 and CD3) analysis, the multiplexed immunofluorescence (IF) was performed and IF images were utilised. The image analysis was performed by using Definiens Tissue studio® (Definiens AG, Munich, Germany) and the Developer platform. Moreover, a novel statistical model was developed using AUCp (partial area under the curve) function in R studio, which defines the range of specificity between 1 and 0.8 on the basis of the binomial GLM (Generalised linear model) framework with GAM-SALSA (Generalised Additive Models - Spatially adaptive local smoothing algorithm) as a calibration tool. In order to avoid the overfitting problem, 5-fold cross validation with 100 times repetition was also added in the analysis. Results: Firstly, our statistical model replaced Fuhrman's nuclear grade with 'mean perimeter', which was named 'Modified Leibovich algorithm'. The modified Leibovich algorithm improved its overall specificity 0.86 (80 out of 93 cases) from 0.76 (71 out of 93) from the classic L score in the Scottish training cohort. In particular, the most increase in specificity was seen in Leibovich score 5 and 6, which were 57% and 40%, respectively. The modified Leibovich algorithm also increased overall specificity up to 0.94 (141 out of 150 cases), compared to the classic (original) Leibovich score whose specificity was 0.84 (126 out of 150 cases) in a Singaporean validation cohort. Moreover, specificity was dramatically increased in Leibovich score 5 from 0% to 92%. Secondly, the chromatin marker colocalisation feature significantly improved the specificity of the classic and partial Leibovich score up to 0.98 in overall. In particular, the specificity of the cases in Leibovich score 4, 5 and 6 was improved up to 100%. However, the chromatin marker Haralick texture features did not improve the specificity of the classic and partial Leibovich score as much as the chromatin marker colocalisation features. Thirdly, the tumour microenvironment features such as the density and the spatial distances of CD105 positive blood vessels and CD3 positive mature T lymphocytes augmented the specificity of the classic and partial Leibovich score up to 0.93. In particular, it improved the specificity up to 92% in Leibovich score 5 compared to the classic Leibovich score. Conclusions: Computational image analysis enabled to measure such various ranges of features not only in tumour cells, but also in tumour microenvironment. In this study, ccRCC tumour cell nuclear morphological features, chromatin marker colocalisation feature, chromatin Haralick texture features and tumour microenvironment features were visualised by the multiplexed immunofluorescence and measured by the Tissue studio and developer software: this cannot be done manually. The data from this analysis significantly augmented the specificity of the currently available prognostic tool, Leibovich score, in clinic. In particular, the very last final model developed by combining features of the chromatin marker colocalisation ('Average.HP1a.Intensity..H3K4_HP1a.Overlap.' and 'Manders.Coefficient.Nuclei..H3K4.HP1a..M2') and tumour microenvironment ('Mean.CD3.Area.percentage.of.All.Tissue' and 'Mean.No..of.CD105') selected along with the classic Leibovich score, predicted 100% (93 out of 93 cases) correctly the cases which did not experience the disease recurrence within 5 years after surgery, while the classic Leibovich score predicted 76% (71 out of 93 cases) correctly. This could have prevented 22 ccRCC patients not only to get unpleasant and unnecessary treatment after nephrectomy, but also helped them having been free from the fear of disease recurrence.
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- 2019
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22. Identification of novel podocyte stress-response mechanisms in vitro
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Haley, Kathryn, Reynolds, Paul Andrew, and Harrison, David James
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612.4 ,RG133.5H26 - Published
- 2018
23. War surgical experience reduces operation times and saves lives : a comprehensive analysis of all trauma sustained in the Afghanistan conflict 2009-2014 prioritises the surgical procedures to improve training and readiness for future armed conflicts, terror attacks, and civilian damage control surgery
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Maitland, Laura Mary Rose and Harrison, David James
- Subjects
617.9 ,RD750.M2 - Abstract
Background: Between 2009 and the end of UK combat operations in Helmand, Afghanistan (2014), each consecutive surgical procedure carried out by the multinational, military surgical team at the Medical Treatment Facility, Camp Bastion was collated. Through analysis I aim to develop the template for prioritising surgical procedures to improve surgical training and readiness for future armed conflicts and terror attacks. Methods: All surgical teams operating in Camp Bastion filled out detailed, handwritten theatre logbooks for each surgical case. I transcribed all 10,891 consecutive surgical cases, and 20,266 surgical procedures, into an electronic format. I provide for the first time the distinct, original and stand-alone surgical database for this thesis: the "Maitland Module", the largest of its kind. Results: I present a new analysis and classification of surgery by anatomical region which accounts for the impact of the multiplicity of wounding caused by explosion on surgical workload. I present the first evidenced-based skill set requirement for war, including the most frequently performed humanitarian surgical procedures and their impact on the skill set required of a surgeon in armed conflict. I show that surgical experience predicted shorter operation times for blast trauma. I found that surgical experience of >50 blast trauma cases predicted lower fatality rates. Skill atrophy in surgical competence between conflicts exists, with an associated rise in preventable loss of life at the start of conflict. Discussion: I propose that the Complex Attack Surgical Team (CAST) of surgeons, with >50 blast trauma case experience, be on standby in the event of a terrorist attack in the UK to support the currently blast-naive civilian surgeons. I hope that the template for surgical procedures may lead to standardisation and prioritisation of the skill set requirement for: trauma surgical training; NATO curriculum development; and intelligent, risk-assessed, deployment of surgeons to conflict zones.
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- 2018
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24. Was King John of England bipolar? : a medical history using mathematical modelling
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Gillespie, Janet Patricia and Harrison, David James
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942.03 ,King John of England ,Magna Carta ,Bipolar disorder ,Activity ,Change point analysis ,Bollinger Bands™ ,Mania ,Depression - Abstract
BACKGROUND - Bipolar disorder has been postulated as an explanation for King John's inconsistencies of leadership and vagaries of character. Changes in activity, matching those in mood, are core features of the condition. METHOD - A measure of King John's activity was derived from his travelling itinerary. Change Point Analysis (CPA) was used to detect significant changes in that travelling activity and from them, to identify clinically compliant, high and low, activity time periods. The results were tested against an alternative mathematical model (Bollinger Bands™), three alternative parameters and two comparator itineraries (familial & non-familial). Using primary historical sources and published analyses, bipolar symptoms were identified and their temporal relationship to the ICD-10 compliant CPA periods evaluated. The influence of circumstances was also evaluated using primary sources and a representative sequential sample (1200-1204). RESULTS - CPA identified 83 periods of changed travelling activity. These changes were mathematically independent of the availability of the historical sources that underpin the itinerary. From these, 37 high and 22 low periods complied with current diagnostic guidelines and demonstrated descriptive and statistical similarities to those found in the bipolar literature. Analyses using alternative mathematical modelling and different parameters showed similar changes; analyses of comparator itineraries showed a possible familial trait. Of the 17 bipolar symptoms identified, all were found in CPA periods of appropriate polarity. Of the 23 sequential periods, 10 showed evidence of behaviour that was difficult to attribute to circumstances. CONCLUSIONS & OUTCOMES - The pattern of changes in King John's activity are highly suggestive of bipolar disorder with primary historical sources describing synchronous bipolar behaviour. This may alter our understanding both of King John and of Magna Carta. Change Point Analysis merits greater consideration when analysing time based data, as does the use of activity as an objective marker of human behaviour.
- Published
- 2017
25. Exploration of the pharmacodynamic profile of Acelarin, a novel ProTide drug, in an in vitro model of ovarian cancer
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Bré, Jennifer, Harrison, David James, NHS Lothian, and NuCana PLC
- Subjects
RM301.57B8 - Published
- 2019
- Full Text
- View/download PDF
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